From 2e9306680fb85866433fa7fb3b0bf7055c7b8c0c Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Wed, 7 Oct 2020 17:24:30 -0400
Subject: [PATCH 01/48] allow default environments

---
 envs/__init__.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/envs/__init__.py b/envs/__init__.py
index ec2a070..70580b3 100644
--- a/envs/__init__.py
+++ b/envs/__init__.py
@@ -1,7 +1,8 @@
 import copy
 import os
 
-import minerl
+from minerl.herobraine.env_spec import MISSIONS_DIR
+from minerl.herobraine.envs import ENVS
 from ray.tune.registry import register_env
 
 from envs.env import LazyMineRLEnv, MineRLRandomDebugEnv
@@ -13,12 +14,12 @@ def register():
     Must be called to register the MineRL environments for RLlib
     """
 
-    for env_spec in minerl.herobraine.envs.obfuscated_envs:
+    for env_spec in ENVS:
         env_kwargs = copy.deepcopy(dict(
             observation_space=env_spec.observation_space,
             action_space=env_spec.action_space,
             docstr=env_spec.get_docstring(),
-            xml=os.path.join(minerl.herobraine.env_spec.MISSIONS_DIR, env_spec.xml),
+            xml=os.path.join(MISSIONS_DIR, env_spec.xml),
             env_spec=env_spec,
         ))
 

From 39a4106c3015773fdc7ce58c6b54c3e04050fe05 Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Tue, 20 Jul 2021 21:36:23 -0400
Subject: [PATCH 02/48] update input api and use minerl-wrappers package

---
 envs/__init__.py |  32 ++----------
 envs/env.py      |  37 +++++++++----
 envs/input.py    | 132 +++++++++++++++++++++++++++++++++++++++++++++++
 3 files changed, 164 insertions(+), 37 deletions(-)
 create mode 100644 envs/input.py

diff --git a/envs/__init__.py b/envs/__init__.py
index 70580b3..31a65a4 100644
--- a/envs/__init__.py
+++ b/envs/__init__.py
@@ -1,34 +1,10 @@
-import copy
-import os
-
-from minerl.herobraine.env_spec import MISSIONS_DIR
-from minerl.herobraine.envs import ENVS
-from ray.tune.registry import register_env
-
-from envs.env import LazyMineRLEnv, MineRLRandomDebugEnv
-from envs.wrappers import wrap
+from envs.env import register_minerl_envs
+from envs.input import register_minerl_input
 
 
 def register():
     """
     Must be called to register the MineRL environments for RLlib
     """
-
-    for env_spec in ENVS:
-        env_kwargs = copy.deepcopy(dict(
-            observation_space=env_spec.observation_space,
-            action_space=env_spec.action_space,
-            docstr=env_spec.get_docstring(),
-            xml=os.path.join(MISSIONS_DIR, env_spec.xml),
-            env_spec=env_spec,
-        ))
-
-        def env_creator(env_config):
-            return wrap(LazyMineRLEnv(**env_kwargs), **env_config)
-
-        register_env(env_spec.name, env_creator)
-
-    def env_creator(env_config):
-        return wrap(MineRLRandomDebugEnv(), **env_config)
-
-    register_env('MineRLRandomDebug-v0', env_creator)
+    register_minerl_envs()
+    register_minerl_input()
diff --git a/envs/env.py b/envs/env.py
index a66127c..9c3289a 100644
--- a/envs/env.py
+++ b/envs/env.py
@@ -1,23 +1,27 @@
 import filelock
 import gym
 import gym.wrappers
-import minerl
+from minerl.herobraine.env_spec import EnvSpec
+from minerl.herobraine.envs import BASIC_ENV_SPECS, COMPETITION_ENV_SPECS, BASALT_COMPETITION_ENV_SPECS
+from minerl.herobraine.envs import MINERL_OBTAIN_DIAMOND_OBF_V0 as DEBUG_ENV_SPEC
+from minerl_wrappers import wrap
+from ray.tune.registry import register_env
 
 
 class LazyMineRLEnv(gym.Env):
-    def __init__(self, *args, **kwargs):
-        self._args = args
+    def __init__(self, env_spec, **kwargs):
         self._kwargs = kwargs
+        self.env_spec: EnvSpec = env_spec
         self._env = None
-        self.observation_space = kwargs.get('observation_space')
-        self.action_space = kwargs.get('action_space')
-        self.env_spec = kwargs.get('env_spec')
         super().__init__()
 
+    def init_env(self):
+        with filelock.FileLock('minerl_env.lock'):
+            self._env = self.env_spec.make(**self._kwargs)
+
     def reset(self, **kwargs):
         if self._env is None:
-            with filelock.FileLock('minerl_env.lock'):
-                self._env = minerl.env.MineRLEnv(*self._args, **self._kwargs)
+            self.init_env()
         return self._env.reset()
 
     def step(self, action):
@@ -29,6 +33,8 @@ def render(self, mode='human'):
     def __getattr__(self, name):
         if name.startswith('_'):
             raise AttributeError("attempted to get missing private attribute '{}'".format(name))
+        if self._env is None:
+            self.init_env()
         return getattr(self._env, name)
 
 
@@ -42,7 +48,7 @@ def __init__(self):
         self.action_space = gym.spaces.Dict(dict(vector=action_space))
         self.done = False
         self.t = 0
-        self.env_spec = minerl.herobraine.envs.MINERL_OBTAIN_DIAMOND_OBF_V0
+        self.env_spec = DEBUG_ENV_SPEC
 
     def _obs(self):
         return self.observation_space.sample()
@@ -65,3 +71,16 @@ def reset(self):
 
     def render(self, mode='human'):
         pass
+
+
+def register_minerl_envs():
+    for env_spec in (BASIC_ENV_SPECS + COMPETITION_ENV_SPECS + BASALT_COMPETITION_ENV_SPECS):
+        def env_creator(env_config):
+            return wrap(LazyMineRLEnv(env_spec), **env_config)
+
+        register_env(env_spec.name, env_creator)
+
+    def env_creator(env_config):
+        return wrap(MineRLRandomDebugEnv(), **env_config)
+
+    register_env('MineRLRandomDebug-v0', env_creator)
diff --git a/envs/input.py b/envs/input.py
new file mode 100644
index 0000000..74bce95
--- /dev/null
+++ b/envs/input.py
@@ -0,0 +1,132 @@
+import os
+
+import gym
+import numpy as np
+from ray.rllib.models.preprocessors import get_preprocessor
+
+from ray.rllib.offline import IOContext
+from ray.rllib.offline.input_reader import InputReader
+from ray.rllib.policy.sample_batch import SampleBatch
+from ray.rllib.utils.typing import SampleBatchType
+from ray.tune.registry import register_input
+
+from envs.data import MinerRLDataEnv, wrap_env
+
+
+class MineRLInputReader(InputReader):
+    def __init__(self, ioctx: IOContext = None):
+        super().__init__()
+        print('Input reader initialization success!')
+        import minerl
+        input_config = ioctx.input_config
+        env_name = ioctx.config.get('env')
+        env_config = ioctx.config.get('env_config', {})
+        self.data = minerl.data.make(env_name,
+                                     data_dir=os.getenv('MINERL_DATA_ROOT', input_config.get('data_dir', 'data')),
+                                     num_workers=input_config.get('num_workers', 4),
+                                     worker_batch_size=input_config.get('worker_batch_size', 32),
+                                     minimum_size_to_dequeue=input_config.get('minimum_size_to_dequeue', 32),
+                                     force_download=input_config.get('force_download', False))
+        batch_size = input_config.get('batch_size', 1)
+        seq_len = input_config.get('seq_len', 32)
+        num_epochs = input_config.get('num_epochs', -1)
+        preload_buffer_size = input_config.get('preload_buffer_size', 2)
+        seed = input_config.get('seed', None)
+        include_metadata = input_config.get('include_metadata', False)
+        self.generator = self.data.batch_iter(batch_size, seq_len, num_epochs=num_epochs,
+                                              preload_buffer_size=preload_buffer_size, seed=seed,
+                                              include_metadata=include_metadata)
+        env = MinerRLDataEnv(self.data)
+        env = wrap_env(env, env_config)
+        print(env.observation_space)
+        self.prep = get_preprocessor(env.observation_space)(env.observation_space)
+
+        env_ptr = env
+        self.obs_fns = []
+        self.action_fns = []
+        self.reverse_action_fns = []
+        self.reward_fns = []
+        while hasattr(env_ptr, 'env'):
+            if isinstance(env_ptr, gym.ObservationWrapper):
+                self.obs_fns.append(env_ptr.observation)
+            if isinstance(env_ptr, gym.ActionWrapper):
+                self.action_fns.append(env_ptr.action)
+                self.reverse_action_fns.append(env_ptr.reverse_action)
+            if isinstance(env_ptr, gym.RewardWrapper):
+                self.reward_fns.append(env_ptr.reward)
+            env_ptr = env_ptr.env
+
+    def process_obs(self, obs):
+        for i in range(len(self.obs_fns) - 1, -1, -1):
+            f = self.obs_fns[i]
+            obs = f(obs)
+        return self.prep.transform(obs)
+
+    def process_action(self, action):
+        for i in range(len(self.action_fns) - 1, -1, -1):
+            f = self.action_fns[i]
+            action = f(action)
+        return action
+
+    def process_reverse_action(self, action):
+        for i in range(len(self.reverse_action_fns)):
+            f = self.reverse_action_fns[i]
+            action = f(action)
+        return action
+
+    def process_reward(self, reward):
+        for i in range(len(self.reward_fns) - 1, -1, -1):
+            f = self.reward_fns[i]
+            reward = f(reward)
+        return reward
+
+    def next(self) -> SampleBatchType:
+        obs, action, reward, next_obs, done = self.process_batch(next(self.generator))
+        d = {
+            SampleBatch.OBS: obs,
+            SampleBatch.ACTIONS: action,
+            SampleBatch.NEXT_OBS: next_obs,
+            SampleBatch.REWARDS: reward,
+            SampleBatch.DONES: done
+        }
+        # recursive_print(d)
+        return SampleBatch(d)
+
+    def process_batch(self, batch):
+        obs, action, reward, next_obs, done = batch
+        batch_n, batch_t = obs['vector'].shape[0], obs['vector'].shape[1]
+        action = [[self.process_reverse_action({'vector': action['vector'][i][t]}) for i in range(batch_n)] for t in
+                  range(batch_t)]
+        reward = [[self.process_reward(reward[i][t]) for i in range(batch_n)] for t in range(batch_t)]
+        obs = [[self.process_obs({'pov': obs['pov'][i][t], 'vector': obs['vector'][i][t]}) for i in range(batch_n)] for
+               t in range(batch_t)]
+        next_obs = [[self.process_obs({'pov': next_obs['pov'][i][t], 'vector': next_obs['vector'][i][t]}) for i in
+                     range(batch_n)] for t in range(batch_t)]
+        # print(len(obs), len(obs[0]), obs[0][0].shape)
+        return np.array(obs).squeeze(1), np.array(action).squeeze(1), np.array(reward).squeeze(1), np.array(
+            next_obs).squeeze(1), np.transpose(done).squeeze(1)
+
+
+def minerl_input_creator(ioctx: IOContext = None):
+    return MineRLInputReader(ioctx=ioctx)
+
+
+def recursive_print(d):
+    if isinstance(d, dict):
+        print('{')
+        for k, v in d.items():
+            print(f'key={k}')
+            recursive_print(v)
+        print('}')
+    elif isinstance(d, list) or isinstance(d, tuple):
+        print('[')
+        for v in d:
+            recursive_print(v)
+        print(']')
+    elif isinstance(d, np.ndarray):
+        print(d.shape)
+    else:
+        print(d)
+
+def register_minerl_input():
+    register_input('minerl', minerl_input_creator)
\ No newline at end of file

From 147c10f1d7df180e0f874fda0e38482f5568a75b Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Tue, 20 Jul 2021 21:39:41 -0400
Subject: [PATCH 03/48] black format

---
 envs/data.py  |  58 ++++++++++++++++++--------
 envs/env.py   |  39 ++++++++++++------
 envs/input.py | 110 +++++++++++++++++++++++++++++++++-----------------
 3 files changed, 143 insertions(+), 64 deletions(-)

diff --git a/envs/data.py b/envs/data.py
index 81ccfaf..597d162 100644
--- a/envs/data.py
+++ b/envs/data.py
@@ -28,25 +28,27 @@ def __init__(self, data_pipeline: minerl.data.DataPipeline):
     def step(self, action):
         prev_obs, action, reward, obs, done = self.trajectory[self.step_index]
         info = {
-            'prev_obs': prev_obs,
-            'action': action,
+            "prev_obs": prev_obs,
+            "action": action,
         }
         self.step_index += 1
         if self.step_index >= len(self.trajectory):
             if not done:
-                print('Encountered end of trajectory when done returned False!')
+                print("Encountered end of trajectory when done returned False!")
             done = True
         return obs, reward, done, info
 
     def reset(self):
-        self.trajectory = list(self.data_pipeline.load_data(self.trajectory_names[self.index]))
+        self.trajectory = list(
+            self.data_pipeline.load_data(self.trajectory_names[self.index])
+        )
         self.index += 1
         self.index %= len(self.trajectory_names)
         self.step_index = 0
         obs, _, _, _, _ = self.trajectory[self.step_index]
         return obs
 
-    def render(self, mode='human'):
+    def render(self, mode="human"):
         pass
 
 
@@ -54,7 +56,15 @@ def wrap_env(env: MinerRLDataEnv, env_config):
     return wrap(env, **env_config)
 
 
-def write_jsons(environment, data_dir, env_config, save_path, overwrite=False, fail_safe=True, **kwargs):
+def write_jsons(
+    environment,
+    data_dir,
+    env_config,
+    save_path,
+    overwrite=False,
+    fail_safe=True,
+    **kwargs,
+):
     data_pipeline = minerl.data.make(environment, data_dir, **kwargs)
     env = MinerRLDataEnv(data_pipeline)
     env = wrap_env(env, env_config)
@@ -64,15 +74,17 @@ def write_jsons(environment, data_dir, env_config, save_path, overwrite=False, f
     if len(os.listdir(save_path)) != 0:
         abs_save_path = os.path.abspath(save_path)
         if overwrite:
-            print(f'Overwriting! {abs_save_path}')
+            print(f"Overwriting! {abs_save_path}")
             shutil.rmtree(abs_save_path)
         else:
             if fail_safe:
-                print(f'Json data already exists at {abs_save_path}')
+                print(f"Json data already exists at {abs_save_path}")
                 return
             else:
-                raise ValueError(f'Directory {abs_save_path} not empty!'
-                                 f'Cannot overwrite existing data automatically, please delete old data if unused.')
+                raise ValueError(
+                    f"Directory {abs_save_path} not empty!"
+                    f"Cannot overwrite existing data automatically, please delete old data if unused."
+                )
 
     batch_builder = SampleBatchBuilder()
     writer = JsonWriter(save_path)
@@ -89,7 +101,7 @@ def write_jsons(environment, data_dir, env_config, save_path, overwrite=False, f
             continue
         while not done:
             new_obs, reward, done, info = env.step(env.action_space.sample())
-            action = info['action']
+            action = info["action"]
             action = env.reverse_action(action)
             if prev_action is None:
                 prev_action = np.zeros_like(action)
@@ -105,7 +117,7 @@ def write_jsons(environment, data_dir, env_config, save_path, overwrite=False, f
                 prev_actions=prev_action,
                 prev_rewards=prev_reward,
                 dones=done,
-                infos={'trajectory_name': trajectory_name},
+                infos={"trajectory_name": trajectory_name},
                 new_obs=prep.transform(new_obs),
             )
             obs = new_obs
@@ -116,12 +128,26 @@ def write_jsons(environment, data_dir, env_config, save_path, overwrite=False, f
 
 
 class MineRLReader(InputReader):
-    def __init__(self, env_config, environment, data_dir, num_workers, worker_batch_size=4, minimum_size_to_dequeue=32):
+    def __init__(
+        self,
+        env_config,
+        environment,
+        data_dir,
+        num_workers,
+        worker_batch_size=4,
+        minimum_size_to_dequeue=32,
+    ):
         super().__init__()
-        self.data_pipeline = minerl.data.make(environment, data_dir, num_workers, worker_batch_size,
-                                              minimum_size_to_dequeue, force_download=False)
+        self.data_pipeline = minerl.data.make(
+            environment,
+            data_dir,
+            num_workers,
+            worker_batch_size,
+            minimum_size_to_dequeue,
+            force_download=False,
+        )
         self.env_config = env_config
-        self.env_config.update({'data_dir': data_dir})
+        self.env_config.update({"data_dir": data_dir})
 
     def get_env(self, env):
         return wrap(env, **self.env_config)
diff --git a/envs/env.py b/envs/env.py
index 9c3289a..5233a68 100644
--- a/envs/env.py
+++ b/envs/env.py
@@ -2,7 +2,11 @@
 import gym
 import gym.wrappers
 from minerl.herobraine.env_spec import EnvSpec
-from minerl.herobraine.envs import BASIC_ENV_SPECS, COMPETITION_ENV_SPECS, BASALT_COMPETITION_ENV_SPECS
+from minerl.herobraine.envs import (
+    BASIC_ENV_SPECS,
+    COMPETITION_ENV_SPECS,
+    BASALT_COMPETITION_ENV_SPECS,
+)
 from minerl.herobraine.envs import MINERL_OBTAIN_DIAMOND_OBF_V0 as DEBUG_ENV_SPEC
 from minerl_wrappers import wrap
 from ray.tune.registry import register_env
@@ -16,7 +20,7 @@ def __init__(self, env_spec, **kwargs):
         super().__init__()
 
     def init_env(self):
-        with filelock.FileLock('minerl_env.lock'):
+        with filelock.FileLock("minerl_env.lock"):
             self._env = self.env_spec.make(**self._kwargs)
 
     def reset(self, **kwargs):
@@ -27,12 +31,14 @@ def reset(self, **kwargs):
     def step(self, action):
         return self._env.step(action)
 
-    def render(self, mode='human'):
+    def render(self, mode="human"):
         return self._env.render(mode)
 
     def __getattr__(self, name):
-        if name.startswith('_'):
-            raise AttributeError("attempted to get missing private attribute '{}'".format(name))
+        if name.startswith("_"):
+            raise AttributeError(
+                "attempted to get missing private attribute '{}'".format(name)
+            )
         if self._env is None:
             self.init_env()
         return getattr(self._env, name)
@@ -42,9 +48,15 @@ class MineRLRandomDebugEnv(gym.Env):
     def __init__(self):
         super(MineRLRandomDebugEnv, self).__init__()
         pov_space = gym.spaces.Box(low=0, high=255, shape=(64, 64, 3))
-        vector_space = gym.spaces.Box(low=-1.2000000476837158, high=1.2000000476837158, shape=(64,))
-        self.observation_space = gym.spaces.Dict(dict(pov=pov_space, vector=vector_space))
-        action_space = gym.spaces.Box(low=-1.0499999523162842, high=1.0499999523162842, shape=(64,))
+        vector_space = gym.spaces.Box(
+            low=-1.2000000476837158, high=1.2000000476837158, shape=(64,)
+        )
+        self.observation_space = gym.spaces.Dict(
+            dict(pov=pov_space, vector=vector_space)
+        )
+        action_space = gym.spaces.Box(
+            low=-1.0499999523162842, high=1.0499999523162842, shape=(64,)
+        )
         self.action_space = gym.spaces.Dict(dict(vector=action_space))
         self.done = False
         self.t = 0
@@ -55,7 +67,7 @@ def _obs(self):
 
     def step(self, action):
         obs = self._obs()
-        reward = 0.
+        reward = 0.0
         if self.t < 100:
             self.done = False
         else:
@@ -69,12 +81,15 @@ def reset(self):
         self.t = 0
         return self._obs()
 
-    def render(self, mode='human'):
+    def render(self, mode="human"):
         pass
 
 
 def register_minerl_envs():
-    for env_spec in (BASIC_ENV_SPECS + COMPETITION_ENV_SPECS + BASALT_COMPETITION_ENV_SPECS):
+    for env_spec in (
+        BASIC_ENV_SPECS + COMPETITION_ENV_SPECS + BASALT_COMPETITION_ENV_SPECS
+    ):
+
         def env_creator(env_config):
             return wrap(LazyMineRLEnv(env_spec), **env_config)
 
@@ -83,4 +98,4 @@ def env_creator(env_config):
     def env_creator(env_config):
         return wrap(MineRLRandomDebugEnv(), **env_config)
 
-    register_env('MineRLRandomDebug-v0', env_creator)
+    register_env("MineRLRandomDebug-v0", env_creator)
diff --git a/envs/input.py b/envs/input.py
index 74bce95..dbdc620 100644
--- a/envs/input.py
+++ b/envs/input.py
@@ -16,26 +16,36 @@
 class MineRLInputReader(InputReader):
     def __init__(self, ioctx: IOContext = None):
         super().__init__()
-        print('Input reader initialization success!')
+        print("Input reader initialization success!")
         import minerl
+
         input_config = ioctx.input_config
-        env_name = ioctx.config.get('env')
-        env_config = ioctx.config.get('env_config', {})
-        self.data = minerl.data.make(env_name,
-                                     data_dir=os.getenv('MINERL_DATA_ROOT', input_config.get('data_dir', 'data')),
-                                     num_workers=input_config.get('num_workers', 4),
-                                     worker_batch_size=input_config.get('worker_batch_size', 32),
-                                     minimum_size_to_dequeue=input_config.get('minimum_size_to_dequeue', 32),
-                                     force_download=input_config.get('force_download', False))
-        batch_size = input_config.get('batch_size', 1)
-        seq_len = input_config.get('seq_len', 32)
-        num_epochs = input_config.get('num_epochs', -1)
-        preload_buffer_size = input_config.get('preload_buffer_size', 2)
-        seed = input_config.get('seed', None)
-        include_metadata = input_config.get('include_metadata', False)
-        self.generator = self.data.batch_iter(batch_size, seq_len, num_epochs=num_epochs,
-                                              preload_buffer_size=preload_buffer_size, seed=seed,
-                                              include_metadata=include_metadata)
+        env_name = ioctx.config.get("env")
+        env_config = ioctx.config.get("env_config", {})
+        self.data = minerl.data.make(
+            env_name,
+            data_dir=os.getenv(
+                "MINERL_DATA_ROOT", input_config.get("data_dir", "data")
+            ),
+            num_workers=input_config.get("num_workers", 4),
+            worker_batch_size=input_config.get("worker_batch_size", 32),
+            minimum_size_to_dequeue=input_config.get("minimum_size_to_dequeue", 32),
+            force_download=input_config.get("force_download", False),
+        )
+        batch_size = input_config.get("batch_size", 1)
+        seq_len = input_config.get("seq_len", 32)
+        num_epochs = input_config.get("num_epochs", -1)
+        preload_buffer_size = input_config.get("preload_buffer_size", 2)
+        seed = input_config.get("seed", None)
+        include_metadata = input_config.get("include_metadata", False)
+        self.generator = self.data.batch_iter(
+            batch_size,
+            seq_len,
+            num_epochs=num_epochs,
+            preload_buffer_size=preload_buffer_size,
+            seed=seed,
+            include_metadata=include_metadata,
+        )
         env = MinerRLDataEnv(self.data)
         env = wrap_env(env, env_config)
         print(env.observation_space)
@@ -46,7 +56,7 @@ def __init__(self, ioctx: IOContext = None):
         self.action_fns = []
         self.reverse_action_fns = []
         self.reward_fns = []
-        while hasattr(env_ptr, 'env'):
+        while hasattr(env_ptr, "env"):
             if isinstance(env_ptr, gym.ObservationWrapper):
                 self.obs_fns.append(env_ptr.observation)
             if isinstance(env_ptr, gym.ActionWrapper):
@@ -87,24 +97,51 @@ def next(self) -> SampleBatchType:
             SampleBatch.ACTIONS: action,
             SampleBatch.NEXT_OBS: next_obs,
             SampleBatch.REWARDS: reward,
-            SampleBatch.DONES: done
+            SampleBatch.DONES: done,
         }
         # recursive_print(d)
         return SampleBatch(d)
 
     def process_batch(self, batch):
         obs, action, reward, next_obs, done = batch
-        batch_n, batch_t = obs['vector'].shape[0], obs['vector'].shape[1]
-        action = [[self.process_reverse_action({'vector': action['vector'][i][t]}) for i in range(batch_n)] for t in
-                  range(batch_t)]
-        reward = [[self.process_reward(reward[i][t]) for i in range(batch_n)] for t in range(batch_t)]
-        obs = [[self.process_obs({'pov': obs['pov'][i][t], 'vector': obs['vector'][i][t]}) for i in range(batch_n)] for
-               t in range(batch_t)]
-        next_obs = [[self.process_obs({'pov': next_obs['pov'][i][t], 'vector': next_obs['vector'][i][t]}) for i in
-                     range(batch_n)] for t in range(batch_t)]
+        batch_n, batch_t = obs["vector"].shape[0], obs["vector"].shape[1]
+        action = [
+            [
+                self.process_reverse_action({"vector": action["vector"][i][t]})
+                for i in range(batch_n)
+            ]
+            for t in range(batch_t)
+        ]
+        reward = [
+            [self.process_reward(reward[i][t]) for i in range(batch_n)]
+            for t in range(batch_t)
+        ]
+        obs = [
+            [
+                self.process_obs(
+                    {"pov": obs["pov"][i][t], "vector": obs["vector"][i][t]}
+                )
+                for i in range(batch_n)
+            ]
+            for t in range(batch_t)
+        ]
+        next_obs = [
+            [
+                self.process_obs(
+                    {"pov": next_obs["pov"][i][t], "vector": next_obs["vector"][i][t]}
+                )
+                for i in range(batch_n)
+            ]
+            for t in range(batch_t)
+        ]
         # print(len(obs), len(obs[0]), obs[0][0].shape)
-        return np.array(obs).squeeze(1), np.array(action).squeeze(1), np.array(reward).squeeze(1), np.array(
-            next_obs).squeeze(1), np.transpose(done).squeeze(1)
+        return (
+            np.array(obs).squeeze(1),
+            np.array(action).squeeze(1),
+            np.array(reward).squeeze(1),
+            np.array(next_obs).squeeze(1),
+            np.transpose(done).squeeze(1),
+        )
 
 
 def minerl_input_creator(ioctx: IOContext = None):
@@ -113,20 +150,21 @@ def minerl_input_creator(ioctx: IOContext = None):
 
 def recursive_print(d):
     if isinstance(d, dict):
-        print('{')
+        print("{")
         for k, v in d.items():
-            print(f'key={k}')
+            print(f"key={k}")
             recursive_print(v)
-        print('}')
+        print("}")
     elif isinstance(d, list) or isinstance(d, tuple):
-        print('[')
+        print("[")
         for v in d:
             recursive_print(v)
-        print(']')
+        print("]")
     elif isinstance(d, np.ndarray):
         print(d.shape)
     else:
         print(d)
 
+
 def register_minerl_input():
-    register_input('minerl', minerl_input_creator)
\ No newline at end of file
+    register_input("minerl", minerl_input_creator)

From 1ddf869c70c41b84158ddae1f6b90033f61f59fa Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Tue, 20 Jul 2021 21:44:14 -0400
Subject: [PATCH 04/48] update url

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index f08e8bd..3e09c18 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
 
 Here we benchmark various reinforcement learning algorithms available in [RLlib](https://docs.ray.io/en/releases-0.8.6/rllib.html) on the [MineRL](https://minerl.io/docs/) environment.
 
-[RLlib](https://docs.ray.io/en/releases-0.8.6/rllib.html) is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications. 
+[RLlib](https://docs.ray.io/en/master/rllib.html) is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications. 
 RLlib natively supports TensorFlow, TensorFlow Eager, and PyTorch, but most of its internals are framework agnostic.
 
 ## Installation

From af271031c68b7450b8b21be5b665a21ed477c4c2 Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Tue, 20 Jul 2021 21:46:17 -0400
Subject: [PATCH 05/48] remove old data pipeline

---
 rllib_train.py | 32 --------------------------------
 1 file changed, 32 deletions(-)

diff --git a/rllib_train.py b/rllib_train.py
index f43b858..ddf5b5a 100644
--- a/rllib_train.py
+++ b/rllib_train.py
@@ -3,9 +3,7 @@
 See help with:
 $ python rllib_train.py --help
 """
-import subprocess
 
-import yaml
 from ray.rllib.train import create_parser, run
 
 import envs
@@ -15,39 +13,9 @@
 models.register()
 
 
-def generate_kmeans(env):
-    command = f'python generate_kmeans.py --env {env}'
-    print('running:', command)
-    subprocess.run(command.split())
-
-
-def convert_data(args):
-    command = f'python convert_data.py -f {args.config_file}'
-    print('running:', command)
-    subprocess.run(command.split())
-
-
-def check_data(args):
-    if args.config_file is not None:
-        config = yaml.safe_load(open(args.config_file))
-        settings = list(config.values())[0]
-        if 'env' in settings:
-            env = settings['env']
-        if 'config' in settings:
-            if 'env' in settings['config']:
-                env = settings['config']['env']
-            if 'env_config' in settings['config']:
-                env_config = settings['config']['env_config']
-                if env_config.get('discrete', False):
-                    generate_kmeans(env)
-            if 'input' in settings['config']:
-                convert_data(args)
-
-
 def main():
     parser = create_parser()
     args = parser.parse_args()
-    check_data(args)
     run(args, parser)
 
 

From b47d314c3ebf5f6f5dc2f0f0322428d1b6c1b891 Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Tue, 20 Jul 2021 21:50:16 -0400
Subject: [PATCH 06/48] refactor into minerl_rllib package

---
 {models/tf => minerl_rllib}/__init__.py       |  0
 .../convert_data.py                           |  2 +-
 {envs => minerl_rllib/envs}/__init__.py       |  4 +-
 {envs => minerl_rllib/envs}/data.py           |  2 +-
 {envs => minerl_rllib/envs}/env.py            |  0
 {envs => minerl_rllib/envs}/input.py          |  2 +-
 .../envs}/wrappers/__init__.py                | 18 ++---
 .../envs}/wrappers/action_repeat_wrapper.py   |  0
 .../envs}/wrappers/action_wrapper.py          |  0
 .../envs}/wrappers/deterministic_wrapper.py   |  0
 .../envs}/wrappers/discrete_action_wrapper.py |  0
 .../envs}/wrappers/gray_scale_wrapper.py      |  0
 .../envs}/wrappers/normalize.py               |  0
 .../wrappers/observation_stack_wrapper.py     |  0
 .../envs}/wrappers/observation_wrapper.py     |  0
 .../envs}/wrappers/reward_penalty_wrapper.py  |  0
 .../envs}/wrappers/time_limit_wrapper.py      |  0
 .../generate_kmeans.py                        |  0
 {models => minerl_rllib/models}/__init__.py   |  5 +-
 minerl_rllib/models/tf/__init__.py            |  0
 minerl_rllib/models/torch/__init__.py         |  1 +
 .../models}/torch/action.py                   |  0
 .../models}/torch/baseline.py                 | 76 ++++++++++++++-----
 minerl_rllib/models/torch/cql.py              | 10 +++
 {models => minerl_rllib/models}/torch/pov.py  |  0
 .../models}/torch/reward.py                   |  0
 {models => minerl_rllib/models}/torch/rnn.py  |  0
 .../models}/torch/vector.py                   |  0
 rllib_train.py => minerl_rllib/rllib_train.py |  3 +-
 models/torch/__init__.py                      |  6 --
 rllib_test.py                                 | 38 ----------
 tests/discrete.py                             |  2 +-
 train.py                                      |  2 +-
 33 files changed, 88 insertions(+), 83 deletions(-)
 rename {models/tf => minerl_rllib}/__init__.py (100%)
 rename convert_data.py => minerl_rllib/convert_data.py (98%)
 rename {envs => minerl_rllib/envs}/__init__.py (57%)
 rename {envs => minerl_rllib/envs}/data.py (99%)
 rename {envs => minerl_rllib/envs}/env.py (100%)
 rename {envs => minerl_rllib/envs}/input.py (98%)
 rename {envs => minerl_rllib/envs}/wrappers/__init__.py (64%)
 rename {envs => minerl_rllib/envs}/wrappers/action_repeat_wrapper.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/action_wrapper.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/deterministic_wrapper.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/discrete_action_wrapper.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/gray_scale_wrapper.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/normalize.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/observation_stack_wrapper.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/observation_wrapper.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/reward_penalty_wrapper.py (100%)
 rename {envs => minerl_rllib/envs}/wrappers/time_limit_wrapper.py (100%)
 rename generate_kmeans.py => minerl_rllib/generate_kmeans.py (100%)
 rename {models => minerl_rllib/models}/__init__.py (57%)
 create mode 100644 minerl_rllib/models/tf/__init__.py
 create mode 100644 minerl_rllib/models/torch/__init__.py
 rename {models => minerl_rllib/models}/torch/action.py (100%)
 rename {models => minerl_rllib/models}/torch/baseline.py (73%)
 create mode 100644 minerl_rllib/models/torch/cql.py
 rename {models => minerl_rllib/models}/torch/pov.py (100%)
 rename {models => minerl_rllib/models}/torch/reward.py (100%)
 rename {models => minerl_rllib/models}/torch/rnn.py (100%)
 rename {models => minerl_rllib/models}/torch/vector.py (100%)
 rename rllib_train.py => minerl_rllib/rllib_train.py (89%)
 delete mode 100644 models/torch/__init__.py
 delete mode 100644 rllib_test.py

diff --git a/models/tf/__init__.py b/minerl_rllib/__init__.py
similarity index 100%
rename from models/tf/__init__.py
rename to minerl_rllib/__init__.py
diff --git a/convert_data.py b/minerl_rllib/convert_data.py
similarity index 98%
rename from convert_data.py
rename to minerl_rllib/convert_data.py
index 736dca4..d189e13 100644
--- a/convert_data.py
+++ b/minerl_rllib/convert_data.py
@@ -6,7 +6,7 @@
 from minerl.herobraine.envs import obfuscated_envs
 from ray.tune.utils import merge_dicts
 
-from envs.data import write_jsons
+from minerl_rllib.envs.data import write_jsons
 
 parser = argparse.ArgumentParser()
 parser.add_argument('--data-dir', type=str, default=os.getenv('MINERL_DATA_ROOT', 'data'),
diff --git a/envs/__init__.py b/minerl_rllib/envs/__init__.py
similarity index 57%
rename from envs/__init__.py
rename to minerl_rllib/envs/__init__.py
index 31a65a4..afc6cdd 100644
--- a/envs/__init__.py
+++ b/minerl_rllib/envs/__init__.py
@@ -1,5 +1,5 @@
-from envs.env import register_minerl_envs
-from envs.input import register_minerl_input
+from minerl_rllib.envs.env import register_minerl_envs
+from minerl_rllib.envs.input import register_minerl_input
 
 
 def register():
diff --git a/envs/data.py b/minerl_rllib/envs/data.py
similarity index 99%
rename from envs/data.py
rename to minerl_rllib/envs/data.py
index 597d162..9a41126 100644
--- a/envs/data.py
+++ b/minerl_rllib/envs/data.py
@@ -9,7 +9,7 @@
 from ray.rllib.offline import InputReader
 from ray.rllib.offline.json_writer import JsonWriter
 
-from envs.wrappers import wrap
+from minerl_rllib.envs.wrappers import wrap
 
 
 class MinerRLDataEnv(gym.Env):
diff --git a/envs/env.py b/minerl_rllib/envs/env.py
similarity index 100%
rename from envs/env.py
rename to minerl_rllib/envs/env.py
diff --git a/envs/input.py b/minerl_rllib/envs/input.py
similarity index 98%
rename from envs/input.py
rename to minerl_rllib/envs/input.py
index dbdc620..04e82f8 100644
--- a/envs/input.py
+++ b/minerl_rllib/envs/input.py
@@ -10,7 +10,7 @@
 from ray.rllib.utils.typing import SampleBatchType
 from ray.tune.registry import register_input
 
-from envs.data import MinerRLDataEnv, wrap_env
+from minerl_rllib.envs.data import MinerRLDataEnv, wrap_env
 
 
 class MineRLInputReader(InputReader):
diff --git a/envs/wrappers/__init__.py b/minerl_rllib/envs/wrappers/__init__.py
similarity index 64%
rename from envs/wrappers/__init__.py
rename to minerl_rllib/envs/wrappers/__init__.py
index 0ddb3a5..8f09484 100644
--- a/envs/wrappers/__init__.py
+++ b/minerl_rllib/envs/wrappers/__init__.py
@@ -1,13 +1,13 @@
-from envs.wrappers.action_repeat_wrapper import MineRLActionRepeat
-from envs.wrappers.action_wrapper import MineRLActionWrapper
-from envs.wrappers.deterministic_wrapper import MineRLDeterministic
-from envs.wrappers.discrete_action_wrapper import MineRLDiscreteActionWrapper
-from envs.wrappers.gray_scale_wrapper import MineRLGrayScale
-from envs.wrappers.normalize import MineRLNormalizeObservationWrapper, MineRLNormalizeActionWrapper, \
+from minerl_rllib.envs.wrappers.action_repeat_wrapper import MineRLActionRepeat
+from minerl_rllib.envs.wrappers.action_wrapper import MineRLActionWrapper
+from minerl_rllib.envs.wrappers.deterministic_wrapper import MineRLDeterministic
+from minerl_rllib.envs.wrappers.discrete_action_wrapper import MineRLDiscreteActionWrapper
+from minerl_rllib.envs.wrappers.gray_scale_wrapper import MineRLGrayScale
+from minerl_rllib.envs.wrappers.normalize import MineRLNormalizeObservationWrapper, MineRLNormalizeActionWrapper, \
     MineRLRewardScaleWrapper
-from envs.wrappers.observation_stack_wrapper import MineRLObservationStack
-from envs.wrappers.observation_wrapper import MineRLObservationWrapper
-from envs.wrappers.time_limit_wrapper import MineRLTimeLimitWrapper
+from minerl_rllib.envs.wrappers.observation_stack_wrapper import MineRLObservationStack
+from minerl_rllib.envs.wrappers.observation_wrapper import MineRLObservationWrapper
+from minerl_rllib.envs.wrappers.time_limit_wrapper import MineRLTimeLimitWrapper
 
 
 def wrap(env, discrete=False, num_actions=32, data_dir=None, num_stack=1, action_repeat=1,
diff --git a/envs/wrappers/action_repeat_wrapper.py b/minerl_rllib/envs/wrappers/action_repeat_wrapper.py
similarity index 100%
rename from envs/wrappers/action_repeat_wrapper.py
rename to minerl_rllib/envs/wrappers/action_repeat_wrapper.py
diff --git a/envs/wrappers/action_wrapper.py b/minerl_rllib/envs/wrappers/action_wrapper.py
similarity index 100%
rename from envs/wrappers/action_wrapper.py
rename to minerl_rllib/envs/wrappers/action_wrapper.py
diff --git a/envs/wrappers/deterministic_wrapper.py b/minerl_rllib/envs/wrappers/deterministic_wrapper.py
similarity index 100%
rename from envs/wrappers/deterministic_wrapper.py
rename to minerl_rllib/envs/wrappers/deterministic_wrapper.py
diff --git a/envs/wrappers/discrete_action_wrapper.py b/minerl_rllib/envs/wrappers/discrete_action_wrapper.py
similarity index 100%
rename from envs/wrappers/discrete_action_wrapper.py
rename to minerl_rllib/envs/wrappers/discrete_action_wrapper.py
diff --git a/envs/wrappers/gray_scale_wrapper.py b/minerl_rllib/envs/wrappers/gray_scale_wrapper.py
similarity index 100%
rename from envs/wrappers/gray_scale_wrapper.py
rename to minerl_rllib/envs/wrappers/gray_scale_wrapper.py
diff --git a/envs/wrappers/normalize.py b/minerl_rllib/envs/wrappers/normalize.py
similarity index 100%
rename from envs/wrappers/normalize.py
rename to minerl_rllib/envs/wrappers/normalize.py
diff --git a/envs/wrappers/observation_stack_wrapper.py b/minerl_rllib/envs/wrappers/observation_stack_wrapper.py
similarity index 100%
rename from envs/wrappers/observation_stack_wrapper.py
rename to minerl_rllib/envs/wrappers/observation_stack_wrapper.py
diff --git a/envs/wrappers/observation_wrapper.py b/minerl_rllib/envs/wrappers/observation_wrapper.py
similarity index 100%
rename from envs/wrappers/observation_wrapper.py
rename to minerl_rllib/envs/wrappers/observation_wrapper.py
diff --git a/envs/wrappers/reward_penalty_wrapper.py b/minerl_rllib/envs/wrappers/reward_penalty_wrapper.py
similarity index 100%
rename from envs/wrappers/reward_penalty_wrapper.py
rename to minerl_rllib/envs/wrappers/reward_penalty_wrapper.py
diff --git a/envs/wrappers/time_limit_wrapper.py b/minerl_rllib/envs/wrappers/time_limit_wrapper.py
similarity index 100%
rename from envs/wrappers/time_limit_wrapper.py
rename to minerl_rllib/envs/wrappers/time_limit_wrapper.py
diff --git a/generate_kmeans.py b/minerl_rllib/generate_kmeans.py
similarity index 100%
rename from generate_kmeans.py
rename to minerl_rllib/generate_kmeans.py
diff --git a/models/__init__.py b/minerl_rllib/models/__init__.py
similarity index 57%
rename from models/__init__.py
rename to minerl_rllib/models/__init__.py
index a30bf48..78da858 100644
--- a/models/__init__.py
+++ b/minerl_rllib/models/__init__.py
@@ -1,8 +1,5 @@
-import models.torch
-
-
 def register():
     """
     Registers all models as available for RLlib
     """
-    models.torch.baseline.register()
+    minerl_rllib.models.torch.baseline.register()
diff --git a/minerl_rllib/models/tf/__init__.py b/minerl_rllib/models/tf/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/minerl_rllib/models/torch/__init__.py b/minerl_rllib/models/torch/__init__.py
new file mode 100644
index 0000000..b3836d0
--- /dev/null
+++ b/minerl_rllib/models/torch/__init__.py
@@ -0,0 +1 @@
+import minerl_rllib.models.torch.action
diff --git a/models/torch/action.py b/minerl_rllib/models/torch/action.py
similarity index 100%
rename from models/torch/action.py
rename to minerl_rllib/models/torch/action.py
diff --git a/models/torch/baseline.py b/minerl_rllib/models/torch/baseline.py
similarity index 73%
rename from models/torch/baseline.py
rename to minerl_rllib/models/torch/baseline.py
index d3da1d1..e9b5633 100644
--- a/models/torch/baseline.py
+++ b/minerl_rllib/models/torch/baseline.py
@@ -1,13 +1,12 @@
+import gym
 import numpy as np
 import torch
 import torch.nn as nn
-import gym
-
 from ray.rllib.models import ModelCatalog
 from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
 from ray.tune.utils import merge_dicts
 
-import models
+from minerl_rllib import models
 
 BASELINE_CONFIG = {
     # specifies the size of the state embedding
@@ -19,7 +18,7 @@
     # implemented: [gru, lstm]
     'rnn_type': 'gru',
     # specifies whether to include the previous action and reward as part of the observation
-    'use_prev_action_reward': True,
+    'use_prev_action_reward': False,
     # specifies extra key word arguments for the RNN class
     'rnn_config': {
         # specifies the rnn hidden layer size
@@ -104,9 +103,9 @@ def get_factory(network_name):
         if self.use_rnn:
             state_embed_size = rnn_config['hidden_size']
             if rnn_type == 'lstm':
-                self._rnn = models.torch.rnn.LSTMBaseline(state_input_size, **rnn_config)
+                self._rnn = minerl_rllib.models.torch.rnn.LSTMBaseline(state_input_size, **rnn_config)
             elif rnn_type == 'gru':
-                self._rnn = models.torch.rnn.GRUBaseline(state_input_size, **rnn_config)
+                self._rnn = minerl_rllib.models.torch.rnn.GRUBaseline(state_input_size, **rnn_config)
             else:
                 raise NotImplementedError
         else:
@@ -127,8 +126,33 @@ def get_initial_state(self):
         return []
 
     def forward(self, input_dict, state, seq_lens):
+        recursive_print(dict(input_dict=input_dict, state=state, seq_lens=seq_lens))
+        includes_time_dim = False if seq_lens is None else len(seq_lens) > 0
+
+        flat_shape = input_dict['obs_flat'].shape
+        if len(flat_shape) == 3:
+            batch_t = flat_shape[0]
+            batch_n = flat_shape[1]
+            raise ValueError(f"obs_flat shape = {flat_shape}")
+        elif len(flat_shape) == 2:
+            if includes_time_dim:
+                batch_n = len(seq_lens)
+                batch_t = flat_shape[0] // batch_n
+            else:
+                batch_t = 1
+                batch_n = flat_shape[0]
+        else:
+            batch_t = 1
+            batch_n = 1
+
         device = next(self.parameters()).device
         pov = input_dict['obs'][0].permute(0, 3, 1, 2)  # n,c,h,w
+        # if len(input_dict['obs'][0].shape) == 4:
+        #     pov = input_dict['obs'][0].permute(0, 3, 1, 2)  # n,c,h,w
+        # elif len(input_dict['obs'][0].shape) == 5:
+        #     pov = input_dict['obs'][0].permute(0, 1, 4, 2, 3)  # t,n,c,h,w
+        # else:
+        #     raise ValueError('expected different shape for pov input')
         vector = input_dict['obs'][1]
         pov_embed = self._pov_network(pov.to(device))
         pov_embed = torch.reshape(pov_embed, pov_embed.shape[:2])
@@ -139,7 +163,6 @@ def forward(self, input_dict, state, seq_lens):
             if self.discrete:
                 prev_actions = prev_actions.long()
             prev_rewards = input_dict['prev_rewards']
-            prev_rewards = torch.reshape(prev_rewards, (-1, 1))
 
             action_embed = self._action_network(prev_actions.to(device))
             reward_embed = self._reward_network(prev_rewards.to(device))
@@ -149,16 +172,17 @@ def forward(self, input_dict, state, seq_lens):
             state_inputs = torch.cat((pov_embed, vector_embed), dim=-1)
 
         if self.use_rnn:
-            batch_t, batch_n, state_size = 1, state_inputs.size(0), state_inputs.size(1)
-            if isinstance(seq_lens, np.ndarray):
-                batch_t, batch_n = state_inputs.size(0) // len(seq_lens), len(seq_lens)
-                state_inputs = torch.reshape(state_inputs, (batch_t, batch_n, state_size))
-                state_inputs = torch.nn.utils.rnn.pack_padded_sequence(state_inputs, seq_lens, enforce_sorted=False)
-            else:
-                state_inputs = torch.reshape(state_inputs, (batch_t, batch_n, state_size))
+            state_size = state_inputs.shape[-1]
+            state_inputs = torch.reshape(state_inputs, (batch_t, batch_n, state_size))
+            # if includes_time_dim:
+            #     state_inputs = torch.reshape(state_inputs, (batch_t, batch_n, state_size))
+            #     print(state_inputs, state_inputs.shape, seq_lens)
+            #     state_inputs = torch.nn.utils.rnn.pack_padded_sequence(state_inputs, seq_lens, enforce_sorted=False)
+            # else:
+            #     state_inputs = torch.reshape(state_inputs, (batch_t, batch_n, state_size))
             rnn_output, rnn_state = self._rnn(state_inputs, state)
-            if isinstance(seq_lens, np.ndarray):
-                rnn_output, _ = torch.nn.utils.rnn.pad_packed_sequence(rnn_output)
+            # if includes_time_dim:
+            #     rnn_output, _ = torch.nn.utils.rnn.pad_packed_sequence(rnn_output)
             self._logits = torch.reshape(rnn_output, (batch_t * batch_n, self._rnn.hidden_size))
         else:
             self._logits = self._state_network(state_inputs)
@@ -168,7 +192,7 @@ def forward(self, input_dict, state, seq_lens):
         return outputs, rnn_state
 
     def value_function(self):
-        values = self._value_head(self._logits).squeeze()
+        values = self._value_head(self._logits)
         return values
 
     def import_from_h5(self, h5_file):
@@ -182,3 +206,21 @@ def custom_loss(self, policy_loss, loss_inputs):
 
 def register():
     ModelCatalog.register_custom_model('minerl_torch_model', MineRLTorchModel)
+
+
+def recursive_print(d):
+    if isinstance(d, dict):
+        print('{')
+        for k, v in d.items():
+            print(f'key={k}')
+            recursive_print(v)
+        print('}')
+    elif isinstance(d, list) or isinstance(d, tuple):
+        print('[')
+        for v in d:
+            recursive_print(v)
+        print(']')
+    elif isinstance(d, np.ndarray) or isinstance(d, torch.Tensor):
+        print(d.shape)
+    else:
+        print(d)
diff --git a/minerl_rllib/models/torch/cql.py b/minerl_rllib/models/torch/cql.py
new file mode 100644
index 0000000..2260419
--- /dev/null
+++ b/minerl_rllib/models/torch/cql.py
@@ -0,0 +1,10 @@
+from ray.rllib.agents.sac.sac_torch_model import SACTorchModel
+from ray.rllib.utils.framework import TensorType
+
+
+class CQLModel(SACTorchModel):
+    def value_function(self) -> TensorType:
+        pass
+
+    def import_from_h5(self, h5_file: str) -> None:
+        pass
diff --git a/models/torch/pov.py b/minerl_rllib/models/torch/pov.py
similarity index 100%
rename from models/torch/pov.py
rename to minerl_rllib/models/torch/pov.py
diff --git a/models/torch/reward.py b/minerl_rllib/models/torch/reward.py
similarity index 100%
rename from models/torch/reward.py
rename to minerl_rllib/models/torch/reward.py
diff --git a/models/torch/rnn.py b/minerl_rllib/models/torch/rnn.py
similarity index 100%
rename from models/torch/rnn.py
rename to minerl_rllib/models/torch/rnn.py
diff --git a/models/torch/vector.py b/minerl_rllib/models/torch/vector.py
similarity index 100%
rename from models/torch/vector.py
rename to minerl_rllib/models/torch/vector.py
diff --git a/rllib_train.py b/minerl_rllib/rllib_train.py
similarity index 89%
rename from rllib_train.py
rename to minerl_rllib/rllib_train.py
index ddf5b5a..527ac42 100644
--- a/rllib_train.py
+++ b/minerl_rllib/rllib_train.py
@@ -6,8 +6,7 @@
 
 from ray.rllib.train import create_parser, run
 
-import envs
-import models
+from minerl_rllib import models, envs
 
 envs.register()
 models.register()
diff --git a/models/torch/__init__.py b/models/torch/__init__.py
deleted file mode 100644
index a724dc5..0000000
--- a/models/torch/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-import models.torch.action
-import models.torch.baseline
-import models.torch.pov
-import models.torch.reward
-import models.torch.rnn
-import models.torch.vector
diff --git a/rllib_test.py b/rllib_test.py
deleted file mode 100644
index 70af870..0000000
--- a/rllib_test.py
+++ /dev/null
@@ -1,38 +0,0 @@
-from ray.rllib.rollout import create_parser, deprecation_warning, run
-
-import envs
-import models
-
-envs.register()
-models.register()
-
-
-def main():
-    parser = create_parser()
-    args = parser.parse_args()
-
-    # Old option: monitor, use video-dir instead.
-    if args.monitor:
-        deprecation_warning("--monitor", "--video-dir=[some dir]")
-    # User tries to record videos, but no-render is set: Error.
-    if (args.monitor or args.video_dir) and args.no_render:
-        raise ValueError(
-            "You have --no-render set, but are trying to record rollout videos"
-            " (via options --video-dir/--monitor)! "
-            "Either unset --no-render or do not use --video-dir/--monitor.")
-    # --use_shelve w/o --out option.
-    if args.use_shelve and not args.out:
-        raise ValueError(
-            "If you set --use-shelve, you must provide an output file via "
-            "--out as well!")
-    # --track-progress w/o --out option.
-    if args.track_progress and not args.out:
-        raise ValueError(
-            "If you set --track-progress, you must provide an output file via "
-            "--out as well!")
-
-    run(args, parser)
-
-
-if __name__ == '__main__':
-    main()
diff --git a/tests/discrete.py b/tests/discrete.py
index 9ad81af..d8bd28d 100644
--- a/tests/discrete.py
+++ b/tests/discrete.py
@@ -2,7 +2,7 @@
 import numpy as np
 import gym
 from tqdm import tqdm
-from envs import wrap
+from minerl_rllib.envs import wrap
 
 
 def test_discrete():
diff --git a/train.py b/train.py
index 416716e..5c081bd 100644
--- a/train.py
+++ b/train.py
@@ -1,4 +1,4 @@
-import rllib_train
+from minerl_rllib import rllib_train
 
 if __name__ == '__main__':
     rllib_train.main()

From 5d1cbb1626300bc671a4e82cc05c153be09360bd Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Tue, 20 Jul 2021 21:52:56 -0400
Subject: [PATCH 07/48] black format

---
 minerl_rllib/convert_data.py                  |  72 ++++++----
 minerl_rllib/envs/wrappers/__init__.py        |  48 +++++--
 minerl_rllib/envs/wrappers/action_wrapper.py  |   4 +-
 .../envs/wrappers/discrete_action_wrapper.py  |   6 +-
 minerl_rllib/envs/wrappers/normalize.py       |  54 ++++++--
 .../wrappers/observation_stack_wrapper.py     |  16 ++-
 .../envs/wrappers/observation_wrapper.py      |   6 +-
 .../envs/wrappers/reward_penalty_wrapper.py   |   2 +-
 minerl_rllib/generate_kmeans.py               |  28 ++--
 minerl_rllib/models/torch/baseline.py         | 128 ++++++++++--------
 minerl_rllib/models/torch/rnn.py              |   8 +-
 minerl_rllib/rllib_train.py                   |   2 +-
 tests/discrete.py                             |   6 +-
 train.py                                      |   2 +-
 14 files changed, 244 insertions(+), 138 deletions(-)

diff --git a/minerl_rllib/convert_data.py b/minerl_rllib/convert_data.py
index d189e13..86bdfa4 100644
--- a/minerl_rllib/convert_data.py
+++ b/minerl_rllib/convert_data.py
@@ -9,22 +9,46 @@
 from minerl_rllib.envs.data import write_jsons
 
 parser = argparse.ArgumentParser()
-parser.add_argument('--data-dir', type=str, default=os.getenv('MINERL_DATA_ROOT', 'data'),
-                    help='path to the data directory of the MineRL data')
-parser.add_argument('--save-path', default=None, type=str,
-                    help='directory to write jsons. defaults to the rllib subdirectory of the MineRL data path')
-parser.add_argument('--env', type=str, default=None, help='Environment name to write jsons')
-parser.add_argument('-f', '--config-file', default=None, type=str, help='config file to load environment config')
-parser.add_argument('--env-config', default='{}', type=json.loads,
-                    help='specifies environment configuration options. overrides config file specifications')
-parser.add_argument('--overwrite', action='store_true', help='overwrite existing data if directory not empty')
+parser.add_argument(
+    "--data-dir",
+    type=str,
+    default=os.getenv("MINERL_DATA_ROOT", "data"),
+    help="path to the data directory of the MineRL data",
+)
+parser.add_argument(
+    "--save-path",
+    default=None,
+    type=str,
+    help="directory to write jsons. defaults to the rllib subdirectory of the MineRL data path",
+)
+parser.add_argument(
+    "--env", type=str, default=None, help="Environment name to write jsons"
+)
+parser.add_argument(
+    "-f",
+    "--config-file",
+    default=None,
+    type=str,
+    help="config file to load environment config",
+)
+parser.add_argument(
+    "--env-config",
+    default="{}",
+    type=json.loads,
+    help="specifies environment configuration options. overrides config file specifications",
+)
+parser.add_argument(
+    "--overwrite",
+    action="store_true",
+    help="overwrite existing data if directory not empty",
+)
 
 
 def get_save_path(data_dir, env_config, env_name=None):
-    save_dir = 'env-config'
+    save_dir = "env-config"
     for key, value in env_config.items():
-        save_dir += f'--{key}-{value}'
-    save_path = os.path.join(data_dir, 'rllib', save_dir)
+        save_dir += f"--{key}-{value}"
+    save_path = os.path.join(data_dir, "rllib", save_dir)
     if env_name is not None:
         save_path = os.path.join(save_path, env_name)
     return save_path
@@ -39,13 +63,13 @@ def main():
     if args.config_file is not None:
         config = yaml.safe_load(open(args.config_file))
         settings = list(config.values())[0]
-        if 'config' in settings:
-            if 'env_config' in settings['config']:
-                env_config = settings['config']['env_config']
-            if 'env' in settings['config']:
-                env_list.append(settings['config']['env'])
-        if 'env' in settings:
-            env_list.append(settings['env'])
+        if "config" in settings:
+            if "env_config" in settings["config"]:
+                env_config = settings["config"]["env_config"]
+            if "env" in settings["config"]:
+                env_list.append(settings["config"]["env"])
+        if "env" in settings:
+            env_list.append(settings["env"])
     else:
         if args.env is None:
             for env_spec in obfuscated_envs:
@@ -58,13 +82,15 @@ def main():
         save_path = get_save_path(args.data_dir, env_config)
     else:
         save_path = args.save_path
-    print(f'saving jsons to {save_path}')
+    print(f"saving jsons to {save_path}")
 
     for env_name in env_list:
-        print(f'Writing data to json files for environment {env_name}')
+        print(f"Writing data to json files for environment {env_name}")
         env_save_path = os.path.join(save_path, env_name)
-        write_jsons(env_name, args.data_dir, env_config, env_save_path, overwrite=args.overwrite)
+        write_jsons(
+            env_name, args.data_dir, env_config, env_save_path, overwrite=args.overwrite
+        )
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()
diff --git a/minerl_rllib/envs/wrappers/__init__.py b/minerl_rllib/envs/wrappers/__init__.py
index 8f09484..f4596e3 100644
--- a/minerl_rllib/envs/wrappers/__init__.py
+++ b/minerl_rllib/envs/wrappers/__init__.py
@@ -1,17 +1,34 @@
 from minerl_rllib.envs.wrappers.action_repeat_wrapper import MineRLActionRepeat
 from minerl_rllib.envs.wrappers.action_wrapper import MineRLActionWrapper
 from minerl_rllib.envs.wrappers.deterministic_wrapper import MineRLDeterministic
-from minerl_rllib.envs.wrappers.discrete_action_wrapper import MineRLDiscreteActionWrapper
+from minerl_rllib.envs.wrappers.discrete_action_wrapper import (
+    MineRLDiscreteActionWrapper,
+)
 from minerl_rllib.envs.wrappers.gray_scale_wrapper import MineRLGrayScale
-from minerl_rllib.envs.wrappers.normalize import MineRLNormalizeObservationWrapper, MineRLNormalizeActionWrapper, \
-    MineRLRewardScaleWrapper
+from minerl_rllib.envs.wrappers.normalize import (
+    MineRLNormalizeObservationWrapper,
+    MineRLNormalizeActionWrapper,
+    MineRLRewardScaleWrapper,
+)
 from minerl_rllib.envs.wrappers.observation_stack_wrapper import MineRLObservationStack
 from minerl_rllib.envs.wrappers.observation_wrapper import MineRLObservationWrapper
 from minerl_rllib.envs.wrappers.time_limit_wrapper import MineRLTimeLimitWrapper
 
 
-def wrap(env, discrete=False, num_actions=32, data_dir=None, num_stack=1, action_repeat=1,
-         gray_scale=False, seed=None, normalize_observation=False, normalize_action=False, reward_scale=1., **kwargs):
+def wrap(
+    env,
+    discrete=False,
+    num_actions=32,
+    data_dir=None,
+    num_stack=1,
+    action_repeat=1,
+    gray_scale=False,
+    seed=None,
+    normalize_observation=False,
+    normalize_action=False,
+    reward_scale=1.0,
+    **kwargs
+):
     env = MineRLTimeLimitWrapper(env)
     env = MineRLObservationWrapper(env)
     env = MineRLActionWrapper(env)
@@ -20,15 +37,24 @@ def wrap(env, discrete=False, num_actions=32, data_dir=None, num_stack=1, action
     if gray_scale:
         env = MineRLGrayScale(env)
     if normalize_observation:
-        env = MineRLNormalizeObservationWrapper(env, kwargs.get('norm_pov_low', 0.), kwargs.get('norm_pov_high', 1.),
-                                                kwargs.get('norm_vec_low', -1.), kwargs.get('norm_vec_high', 1.))
+        env = MineRLNormalizeObservationWrapper(
+            env,
+            kwargs.get("norm_pov_low", 0.0),
+            kwargs.get("norm_pov_high", 1.0),
+            kwargs.get("norm_vec_low", -1.0),
+            kwargs.get("norm_vec_high", 1.0),
+        )
     if normalize_action:
         if discrete:
-            print('Tried to normalize discrete actions which is not possible! '
-                  'Skipping the normalizing action wrapper.')
+            print(
+                "Tried to normalize discrete actions which is not possible! "
+                "Skipping the normalizing action wrapper."
+            )
         else:
-            env = MineRLNormalizeActionWrapper(env, kwargs.get('norm_act_low', -1.), kwargs.get('norm_act_high', 1.))
-    if reward_scale != 1.:
+            env = MineRLNormalizeActionWrapper(
+                env, kwargs.get("norm_act_low", -1.0), kwargs.get("norm_act_high", 1.0)
+            )
+    if reward_scale != 1.0:
         env = MineRLRewardScaleWrapper(env, reward_scale)
     if num_stack > 1:
         env = MineRLObservationStack(env, num_stack)
diff --git a/minerl_rllib/envs/wrappers/action_wrapper.py b/minerl_rllib/envs/wrappers/action_wrapper.py
index 80b708c..d664a52 100644
--- a/minerl_rllib/envs/wrappers/action_wrapper.py
+++ b/minerl_rllib/envs/wrappers/action_wrapper.py
@@ -4,10 +4,10 @@
 class MineRLActionWrapper(gym.ActionWrapper):
     def __init__(self, env):
         super().__init__(env)
-        self.action_space = self.action_space['vector']
+        self.action_space = self.action_space["vector"]
 
     def action(self, action):
         return dict(vector=action)
 
     def reverse_action(self, action):
-        return action['vector']
+        return action["vector"]
diff --git a/minerl_rllib/envs/wrappers/discrete_action_wrapper.py b/minerl_rllib/envs/wrappers/discrete_action_wrapper.py
index 9bc60be..b9ad262 100644
--- a/minerl_rllib/envs/wrappers/discrete_action_wrapper.py
+++ b/minerl_rllib/envs/wrappers/discrete_action_wrapper.py
@@ -10,8 +10,10 @@ def __init__(self, env, num_actions=32, data_dir=None):
         super().__init__(env)
         self.num_actions = num_actions
         if data_dir is None:
-            data_dir = os.environ.get('MINERL_DATA_ROOT', 'data')
-        kmeans_file = os.path.join(data_dir, f'{num_actions}-means', f'{env.env_spec.name}.npy')
+            data_dir = os.environ.get("MINERL_DATA_ROOT", "data")
+        kmeans_file = os.path.join(
+            data_dir, f"{num_actions}-means", f"{env.env_spec.name}.npy"
+        )
         self.kmeans = np.load(kmeans_file)
         self.action_space = gym.spaces.Discrete(num_actions)
         self.nearest_neighbors = NearestNeighbors(n_neighbors=1).fit(self.kmeans)
diff --git a/minerl_rllib/envs/wrappers/normalize.py b/minerl_rllib/envs/wrappers/normalize.py
index c86cb7e..c7c5005 100644
--- a/minerl_rllib/envs/wrappers/normalize.py
+++ b/minerl_rllib/envs/wrappers/normalize.py
@@ -8,42 +8,68 @@ def normalize(a, prev_low, prev_high, new_low, new_high):
 
 
 class MineRLNormalizeObservationWrapper(gym.ObservationWrapper):
-    def __init__(self, env, pov_low=0., pov_high=1., vec_low=-1., vec_high=1.):
+    def __init__(self, env, pov_low=0.0, pov_high=1.0, vec_low=-1.0, vec_high=1.0):
         super().__init__(env)
         self._old_pov_space: gym.spaces.Box = self.env.observation_space.spaces[0]
         self._old_vec_space: gym.spaces.Box = self.env.observation_space.spaces[1]
-        self._pov_space = gym.spaces.Box(pov_low, pov_high, self._old_pov_space.low.shape, np.float32)
-        self._vec_space = gym.spaces.Box(vec_low, vec_high, self._old_vec_space.low.shape, np.float32)
+        self._pov_space = gym.spaces.Box(
+            pov_low, pov_high, self._old_pov_space.low.shape, np.float32
+        )
+        self._vec_space = gym.spaces.Box(
+            vec_low, vec_high, self._old_vec_space.low.shape, np.float32
+        )
         self.observation_space = gym.spaces.Tuple((self._pov_space, self._vec_space))
 
     def observation(self, observation):
         pov, vec = observation
-        pov = normalize(pov, self._old_pov_space.low, self._old_pov_space.high, self._pov_space.low,
-                        self._pov_space.high)
-        vec = normalize(vec, self._old_vec_space.low, self._old_vec_space.high, self._vec_space.low,
-                        self._vec_space.high)
+        pov = normalize(
+            pov,
+            self._old_pov_space.low,
+            self._old_pov_space.high,
+            self._pov_space.low,
+            self._pov_space.high,
+        )
+        vec = normalize(
+            vec,
+            self._old_vec_space.low,
+            self._old_vec_space.high,
+            self._vec_space.low,
+            self._vec_space.high,
+        )
         return pov, vec
 
 
 class MineRLNormalizeActionWrapper(gym.ActionWrapper):
-    def __init__(self, env, low=-1., high=1.):
+    def __init__(self, env, low=-1.0, high=1.0):
         super().__init__(env)
         self._old_vec_space: gym.spaces.Box = self.env.action_space
-        self._vec_space = gym.spaces.Box(low, high, self._old_vec_space.low.shape, np.float32)
+        self._vec_space = gym.spaces.Box(
+            low, high, self._old_vec_space.low.shape, np.float32
+        )
         self.action_space = self._vec_space
 
     def action(self, action):
-        return normalize(action, self._old_vec_space.low, self._old_vec_space.high, self._vec_space.low,
-                         self._vec_space.high)
+        return normalize(
+            action,
+            self._old_vec_space.low,
+            self._old_vec_space.high,
+            self._vec_space.low,
+            self._vec_space.high,
+        )
 
     def reverse_action(self, action):
         action = self.env.reverse_action(action)
-        return normalize(action, self._vec_space.low, self._vec_space.high, self._old_vec_space.low,
-                         self._old_vec_space.high)
+        return normalize(
+            action,
+            self._vec_space.low,
+            self._vec_space.high,
+            self._old_vec_space.low,
+            self._old_vec_space.high,
+        )
 
 
 class MineRLRewardScaleWrapper(TransformReward):
-    def __init__(self, env, reward_scale=1.):
+    def __init__(self, env, reward_scale=1.0):
         def f(reward):
             return reward * reward_scale
 
diff --git a/minerl_rllib/envs/wrappers/observation_stack_wrapper.py b/minerl_rllib/envs/wrappers/observation_stack_wrapper.py
index 3b3d8f9..b390ac6 100644
--- a/minerl_rllib/envs/wrappers/observation_stack_wrapper.py
+++ b/minerl_rllib/envs/wrappers/observation_stack_wrapper.py
@@ -28,16 +28,24 @@ def __init__(self, env, num_stack, lz4_compress=False):
                 self.tuple_len += 1
             self.observation_space = gym.spaces.Tuple(new_spaces)
         elif isinstance(self.observation_space, gym.spaces.Box):
-            low = np.repeat(self.observation_space.low[np.newaxis, ...], num_stack, axis=0)
-            high = np.repeat(self.observation_space.high[np.newaxis, ...], num_stack, axis=0)
-            self.observation_space = gym.spaces.Box(low=low, high=high, dtype=self.observation_space.dtype)
+            low = np.repeat(
+                self.observation_space.low[np.newaxis, ...], num_stack, axis=0
+            )
+            high = np.repeat(
+                self.observation_space.high[np.newaxis, ...], num_stack, axis=0
+            )
+            self.observation_space = gym.spaces.Box(
+                low=low, high=high, dtype=self.observation_space.dtype
+            )
         else:
             raise NotImplementedError
 
     def _get_observation(self):
         assert len(self.frames) == self.num_stack, (len(self.frames), self.num_stack)
         if not self.tuple:
-            return gym.wrappers.frame_stack.LazyFrames(list(self.frames), self.lz4_compress)
+            return gym.wrappers.frame_stack.LazyFrames(
+                list(self.frames), self.lz4_compress
+            )
         obs = []
         for i in range(self.tuple_len):
             frames = [f[i] for f in self.frames]
diff --git a/minerl_rllib/envs/wrappers/observation_wrapper.py b/minerl_rllib/envs/wrappers/observation_wrapper.py
index 20d7c11..5ae01b2 100644
--- a/minerl_rllib/envs/wrappers/observation_wrapper.py
+++ b/minerl_rllib/envs/wrappers/observation_wrapper.py
@@ -4,7 +4,9 @@
 class MineRLObservationWrapper(gym.ObservationWrapper):
     def __init__(self, env):
         super().__init__(env)
-        self.observation_space = gym.spaces.Tuple((self.observation_space['pov'], self.observation_space['vector']))
+        self.observation_space = gym.spaces.Tuple(
+            (self.observation_space["pov"], self.observation_space["vector"])
+        )
 
     def observation(self, observation):
-        return observation['pov'], observation['vector']
+        return observation["pov"], observation["vector"]
diff --git a/minerl_rllib/envs/wrappers/reward_penalty_wrapper.py b/minerl_rllib/envs/wrappers/reward_penalty_wrapper.py
index c034819..5d39fff 100644
--- a/minerl_rllib/envs/wrappers/reward_penalty_wrapper.py
+++ b/minerl_rllib/envs/wrappers/reward_penalty_wrapper.py
@@ -3,4 +3,4 @@
 
 class MineRLRewardPenaltyWrapper(gym.wrappers.TransformReward):
     def __init__(self, env, reward_penalty=0.001):
-        super().__init__(env, lambda r: r - reward_penalty)
\ No newline at end of file
+        super().__init__(env, lambda r: r - reward_penalty)
diff --git a/minerl_rllib/generate_kmeans.py b/minerl_rllib/generate_kmeans.py
index 25552d8..16d0ac0 100644
--- a/minerl_rllib/generate_kmeans.py
+++ b/minerl_rllib/generate_kmeans.py
@@ -8,10 +8,10 @@
 
 parser = argparse.ArgumentParser()
 
-parser.add_argument('--env', default=None)
-parser.add_argument('--num-actions', type=int, default=32)
-parser.add_argument('--data-dir', default=os.getenv('MINERL_DATA_ROOT', 'data'))
-parser.add_argument('--overwrite', action='store_true')
+parser.add_argument("--env", default=None)
+parser.add_argument("--num-actions", type=int, default=32)
+parser.add_argument("--data-dir", default=os.getenv("MINERL_DATA_ROOT", "data"))
+parser.add_argument("--overwrite", action="store_true")
 
 
 def main():
@@ -19,18 +19,18 @@ def main():
     if args.env is None:
         env_list = []
         for env_name in os.listdir(args.data_dir):
-            if 'VectorObf' in env_name:
+            if "VectorObf" in env_name:
                 env_list.append(env_name)
     else:
         env_list = [args.env]
 
     for env_name in env_list:
-        print(f'Generating {args.num_actions}-means for {env_name}')
+        print(f"Generating {args.num_actions}-means for {env_name}")
 
-        file_dir = os.path.join(args.data_dir, f'{args.num_actions}-means')
-        file = os.path.join(file_dir, env_name + '.npy')
+        file_dir = os.path.join(args.data_dir, f"{args.num_actions}-means")
+        file = os.path.join(file_dir, env_name + ".npy")
         if os.path.exists(file) and not args.overwrite:
-            print(f'k-means file already exists at {file}')
+            print(f"k-means file already exists at {file}")
             continue
         if not os.path.exists(file_dir):
             os.mkdir(file_dir)
@@ -40,15 +40,17 @@ def main():
         for trajectory_name in tqdm(list(data.get_trajectory_names())):
             try:
                 for _, action, _, _, _ in data.load_data(trajectory_name):
-                    actions.append(action['vector'])
+                    actions.append(action["vector"])
             except TypeError:
                 pass
         actions = np.stack(actions)
-        print('computing k-means...')
-        kmeans = KMeans(n_clusters=args.num_actions, verbose=1, random_state=0).fit(actions)
+        print("computing k-means...")
+        kmeans = KMeans(n_clusters=args.num_actions, verbose=1, random_state=0).fit(
+            actions
+        )
         print(kmeans)
         np.save(file, kmeans.cluster_centers_)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()
diff --git a/minerl_rllib/models/torch/baseline.py b/minerl_rllib/models/torch/baseline.py
index e9b5633..f79f8e9 100644
--- a/minerl_rllib/models/torch/baseline.py
+++ b/minerl_rllib/models/torch/baseline.py
@@ -11,55 +11,45 @@
 BASELINE_CONFIG = {
     # specifies the size of the state embedding
     # this is the rnn hidden size if use_rnn = True
-    'state_embed_size': 512,
+    "state_embed_size": 512,
     # specifies whether to use a recurrent neural network for the state embedding
-    'use_rnn': True,
+    "use_rnn": True,
     # specifies the type of rnn layer
     # implemented: [gru, lstm]
-    'rnn_type': 'gru',
+    "rnn_type": "gru",
     # specifies whether to include the previous action and reward as part of the observation
-    'use_prev_action_reward': False,
+    "use_prev_action_reward": False,
     # specifies extra key word arguments for the RNN class
-    'rnn_config': {
+    "rnn_config": {
         # specifies the rnn hidden layer size
-        'hidden_size': 512,
+        "hidden_size": 512,
         # specifies the number of rnn layers
-        'num_layers': 1,
+        "num_layers": 1,
     },
-
     # specifies the network architecture for pov image observations
     # gets the pov network factory method from pov.py
     # takes in pov_net_kwargs as input and produces pov_network and pov_embed_size
-    'pov_net': 'baseline',
+    "pov_net": "baseline",
     # specifies the network architecture for vector observations
     # gets the vector network factory method from vector.py
     # takes in vector_net_kwargs as input and produces vector_network and vector_embed_size
-    'vector_net': 'baseline',
+    "vector_net": "baseline",
     # specifies the network architecture for action observations (discrete or continuous)
     # gets the action network factory method from action.py
     # takes in action_net_kwargs as input and produces action_network and action_embed_size
-    'action_net': 'baseline',
+    "action_net": "baseline",
     # specifies the network architecture for reward observations
     # gets the reward network factory method from reward.py
     # takes in reward_net_kwargs as input and produces reward_network and reward_embed_size
-    'reward_net': 'baseline',
-
+    "reward_net": "baseline",
     # key word arguments for the pov network factory method
-    'pov_net_kwargs': {
-        'pov_embed_size': 256
-    },
+    "pov_net_kwargs": {"pov_embed_size": 256},
     # key word arguments for the vector network factory method
-    'vector_net_kwargs': {
-        'vector_embed_size': 512
-    },
+    "vector_net_kwargs": {"vector_embed_size": 512},
     # key word arguments for the action network factory method
-    'action_net_kwargs': {
-        'action_embed_size': 128
-    },
+    "action_net_kwargs": {"action_embed_size": 128},
     # key word arguments for the reward network factory method
-    'reward_net_kwargs': {
-        'reward_embed_size': 128
-    },
+    "reward_net_kwargs": {"reward_embed_size": 128},
 }
 
 
@@ -69,43 +59,61 @@ class MineRLTorchModel(TorchModelV2, nn.Module):
     See rllib documentation on custom models: https://docs.ray.io/en/master/rllib-models.html#pytorch-models
     """
 
-    def __init__(self, obs_space, action_space, num_outputs, model_config, name, **kwargs):
-        TorchModelV2.__init__(self, obs_space, action_space, num_outputs, model_config, name)
+    def __init__(
+        self, obs_space, action_space, num_outputs, model_config, name, **kwargs
+    ):
+        TorchModelV2.__init__(
+            self, obs_space, action_space, num_outputs, model_config, name
+        )
         nn.Module.__init__(self)
-        model_config = merge_dicts(BASELINE_CONFIG, model_config['custom_model_config'])
+        model_config = merge_dicts(BASELINE_CONFIG, model_config["custom_model_config"])
         # new way to get model config directly from keyword arguments
         model_config = merge_dicts(model_config, kwargs)
 
-        state_embed_size = model_config['state_embed_size']
-        self.use_rnn = model_config['use_rnn']
-        rnn_type = model_config['rnn_type']
-        self.use_prev_action_reward = model_config['use_prev_action_reward']
+        state_embed_size = model_config["state_embed_size"]
+        self.use_rnn = model_config["use_rnn"]
+        rnn_type = model_config["rnn_type"]
+        self.use_prev_action_reward = model_config["use_prev_action_reward"]
 
-        action_net_kwargs = model_config['action_net_kwargs']
+        action_net_kwargs = model_config["action_net_kwargs"]
         if isinstance(action_space, gym.spaces.Discrete):
-            action_net_kwargs.update({'discrete': True, 'n': action_space.n})
+            action_net_kwargs.update({"discrete": True, "n": action_space.n})
             self.discrete = True
         else:
             self.discrete = False
 
         def get_factory(network_name):
-            return getattr(getattr(models.torch, network_name), model_config[f'{network_name}_net'])
+            return getattr(
+                getattr(models.torch, network_name), model_config[f"{network_name}_net"]
+            )
 
-        self._pov_network, pov_embed_size = get_factory('pov')(**model_config['pov_net_kwargs'])
-        self._vector_network, vector_embed_size = get_factory('vector')(**model_config['vector_net_kwargs'])
+        self._pov_network, pov_embed_size = get_factory("pov")(
+            **model_config["pov_net_kwargs"]
+        )
+        self._vector_network, vector_embed_size = get_factory("vector")(
+            **model_config["vector_net_kwargs"]
+        )
         state_input_size = pov_embed_size + vector_embed_size
         if self.use_prev_action_reward:
-            self._action_network, action_embed_size = get_factory('action')(**action_net_kwargs)
-            self._reward_network, reward_embed_size = get_factory('reward')(**model_config['reward_net_kwargs'])
+            self._action_network, action_embed_size = get_factory("action")(
+                **action_net_kwargs
+            )
+            self._reward_network, reward_embed_size = get_factory("reward")(
+                **model_config["reward_net_kwargs"]
+            )
             state_input_size += action_embed_size + reward_embed_size
 
-        rnn_config = model_config.get('rnn_config')
+        rnn_config = model_config.get("rnn_config")
         if self.use_rnn:
-            state_embed_size = rnn_config['hidden_size']
-            if rnn_type == 'lstm':
-                self._rnn = minerl_rllib.models.torch.rnn.LSTMBaseline(state_input_size, **rnn_config)
-            elif rnn_type == 'gru':
-                self._rnn = minerl_rllib.models.torch.rnn.GRUBaseline(state_input_size, **rnn_config)
+            state_embed_size = rnn_config["hidden_size"]
+            if rnn_type == "lstm":
+                self._rnn = minerl_rllib.models.torch.rnn.LSTMBaseline(
+                    state_input_size, **rnn_config
+                )
+            elif rnn_type == "gru":
+                self._rnn = minerl_rllib.models.torch.rnn.GRUBaseline(
+                    state_input_size, **rnn_config
+                )
             else:
                 raise NotImplementedError
         else:
@@ -129,7 +137,7 @@ def forward(self, input_dict, state, seq_lens):
         recursive_print(dict(input_dict=input_dict, state=state, seq_lens=seq_lens))
         includes_time_dim = False if seq_lens is None else len(seq_lens) > 0
 
-        flat_shape = input_dict['obs_flat'].shape
+        flat_shape = input_dict["obs_flat"].shape
         if len(flat_shape) == 3:
             batch_t = flat_shape[0]
             batch_n = flat_shape[1]
@@ -146,28 +154,30 @@ def forward(self, input_dict, state, seq_lens):
             batch_n = 1
 
         device = next(self.parameters()).device
-        pov = input_dict['obs'][0].permute(0, 3, 1, 2)  # n,c,h,w
+        pov = input_dict["obs"][0].permute(0, 3, 1, 2)  # n,c,h,w
         # if len(input_dict['obs'][0].shape) == 4:
         #     pov = input_dict['obs'][0].permute(0, 3, 1, 2)  # n,c,h,w
         # elif len(input_dict['obs'][0].shape) == 5:
         #     pov = input_dict['obs'][0].permute(0, 1, 4, 2, 3)  # t,n,c,h,w
         # else:
         #     raise ValueError('expected different shape for pov input')
-        vector = input_dict['obs'][1]
+        vector = input_dict["obs"][1]
         pov_embed = self._pov_network(pov.to(device))
         pov_embed = torch.reshape(pov_embed, pov_embed.shape[:2])
         vector_embed = self._vector_network(vector.to(device))
 
         if self.use_prev_action_reward:
-            prev_actions = input_dict['prev_actions']
+            prev_actions = input_dict["prev_actions"]
             if self.discrete:
                 prev_actions = prev_actions.long()
-            prev_rewards = input_dict['prev_rewards']
+            prev_rewards = input_dict["prev_rewards"]
 
             action_embed = self._action_network(prev_actions.to(device))
             reward_embed = self._reward_network(prev_rewards.to(device))
 
-            state_inputs = torch.cat((pov_embed, vector_embed, action_embed, reward_embed), dim=-1)
+            state_inputs = torch.cat(
+                (pov_embed, vector_embed, action_embed, reward_embed), dim=-1
+            )
         else:
             state_inputs = torch.cat((pov_embed, vector_embed), dim=-1)
 
@@ -183,7 +193,9 @@ def forward(self, input_dict, state, seq_lens):
             rnn_output, rnn_state = self._rnn(state_inputs, state)
             # if includes_time_dim:
             #     rnn_output, _ = torch.nn.utils.rnn.pad_packed_sequence(rnn_output)
-            self._logits = torch.reshape(rnn_output, (batch_t * batch_n, self._rnn.hidden_size))
+            self._logits = torch.reshape(
+                rnn_output, (batch_t * batch_n, self._rnn.hidden_size)
+            )
         else:
             self._logits = self._state_network(state_inputs)
             rnn_state = []
@@ -205,21 +217,21 @@ def custom_loss(self, policy_loss, loss_inputs):
 
 
 def register():
-    ModelCatalog.register_custom_model('minerl_torch_model', MineRLTorchModel)
+    ModelCatalog.register_custom_model("minerl_torch_model", MineRLTorchModel)
 
 
 def recursive_print(d):
     if isinstance(d, dict):
-        print('{')
+        print("{")
         for k, v in d.items():
-            print(f'key={k}')
+            print(f"key={k}")
             recursive_print(v)
-        print('}')
+        print("}")
     elif isinstance(d, list) or isinstance(d, tuple):
-        print('[')
+        print("[")
         for v in d:
             recursive_print(v)
-        print(']')
+        print("]")
     elif isinstance(d, np.ndarray) or isinstance(d, torch.Tensor):
         print(d.shape)
     else:
diff --git a/minerl_rllib/models/torch/rnn.py b/minerl_rllib/models/torch/rnn.py
index 8af0788..2d05004 100644
--- a/minerl_rllib/models/torch/rnn.py
+++ b/minerl_rllib/models/torch/rnn.py
@@ -14,7 +14,9 @@ def __init__(self, input_size: int, hidden_size: int, num_layers: int, name: str
         self.num_layers = num_layers
         self.name = name
 
-    def forward(self, x: Union[Tensor, PackedSequence], state: List[Tensor]) -> Tuple[Union[Tensor, PackedSequence]]:
+    def forward(
+        self, x: Union[Tensor, PackedSequence], state: List[Tensor]
+    ) -> Tuple[Union[Tensor, PackedSequence]]:
         """
         Forward pass through the recurrent network
         :param x: input tensor for the RNN with shape (seq, batch, feature) which can be a packed sequence
@@ -44,7 +46,7 @@ def custom_loss(self):
 
 class GRUBaseline(RecurrentBaseline):
     def __init__(self, input_size, hidden_size, num_layers=1, **kwargs):
-        super().__init__(input_size, hidden_size, num_layers, 'gru')
+        super().__init__(input_size, hidden_size, num_layers, "gru")
         self.rnn = nn.GRU(input_size, hidden_size, num_layers, **kwargs)
 
     def initial_state(self):
@@ -75,7 +77,7 @@ def forward(self, x, state):
 
 class LSTMBaseline(RecurrentBaseline):
     def __init__(self, input_size, hidden_size, num_layers=1, **kwargs):
-        super().__init__(input_size, hidden_size, num_layers, 'lstm')
+        super().__init__(input_size, hidden_size, num_layers, "lstm")
         self.rnn = nn.LSTM(input_size, hidden_size, num_layers, **kwargs)
 
     def initial_state(self):
diff --git a/minerl_rllib/rllib_train.py b/minerl_rllib/rllib_train.py
index 527ac42..474272f 100644
--- a/minerl_rllib/rllib_train.py
+++ b/minerl_rllib/rllib_train.py
@@ -18,5 +18,5 @@ def main():
     run(args, parser)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()
diff --git a/tests/discrete.py b/tests/discrete.py
index d8bd28d..ddedc37 100644
--- a/tests/discrete.py
+++ b/tests/discrete.py
@@ -6,8 +6,8 @@
 
 
 def test_discrete():
-    os.chdir('..')
-    env = gym.make('MineRLTreechopVectorObf-v0')
+    os.chdir("..")
+    env = gym.make("MineRLTreechopVectorObf-v0")
     env = wrap(env, discrete=True, num_actions=32)
 
     for _ in tqdm(range(100)):
@@ -22,5 +22,5 @@ def test_discrete():
         obs, reward, done, info = env.step(action)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     test_discrete()
diff --git a/train.py b/train.py
index 5c081bd..9e9f57d 100644
--- a/train.py
+++ b/train.py
@@ -1,4 +1,4 @@
 from minerl_rllib import rllib_train
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     rllib_train.main()

From f23c075d92684f7272091db982ec0a90cacd8755 Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Thu, 22 Jul 2021 02:11:23 -0400
Subject: [PATCH 08/48] updated requirements

---
 README.md        |  7 ++++---
 requirements.txt | 11 +++--------
 2 files changed, 7 insertions(+), 11 deletions(-)

diff --git a/README.md b/README.md
index 3e09c18..37eb403 100644
--- a/README.md
+++ b/README.md
@@ -7,15 +7,16 @@ RLlib natively supports TensorFlow, TensorFlow Eager, and PyTorch, but most of i
 
 ## Installation
 
+Requires Python 3.7 or 3.8.
+
 1. Make sure you have JDK 1.8 on your system for [MineRL](https://minerl.io/docs/tutorials/index.html#installation).
-2. Install [PyTorch](https://pytorch.org/get-started/locally/) and [TensorFlow](https://www.tensorflow.org/install) with correct cuda version
-3. Install [Ray Latest Snapshots (Nightlies)](https://docs.ray.io/en/master/installation.html#latest-snapshots-nightlies) 
-4. Finally, 
 ```
 git clone https://github.com/juliusfrost/minerl-rllib.git
 cd minerl-rllib
 pip install -r requirements.txt
 ```
+2. Install [Ray Latest Snapshots (Nightlies)](https://docs.ray.io/en/master/installation.html#latest-snapshots-nightlies)
+3. Install [PyTorch](https://pytorch.org/get-started/locally/) and [TensorFlow](https://www.tensorflow.org/install) with correct cuda version.
 
 ## Implementation Details
 See [Implementation Details](Implementation.md)
diff --git a/requirements.txt b/requirements.txt
index 421fc62..a90d487 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,8 +1,3 @@
-tqdm
-numpy
-sklearn
-gym
-minerl
-pyyaml
-filelock
-ray[rllib]
\ No newline at end of file
+ray[default,tune,rllib]>=1.4.1
+git+https://github.com/minerl-wrappers/minerl-wrappers.git
+scikit-learn>=0.24.2
\ No newline at end of file

From de41be2bbae9194802f245c54d8c0127b8d38cdb Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Thu, 22 Jul 2021 02:11:34 -0400
Subject: [PATCH 09/48] fix import error

---
 minerl_rllib/models/__init__.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/minerl_rllib/models/__init__.py b/minerl_rllib/models/__init__.py
index 78da858..e3a0fb8 100644
--- a/minerl_rllib/models/__init__.py
+++ b/minerl_rllib/models/__init__.py
@@ -1,3 +1,6 @@
+import minerl_rllib.models.torch.baseline
+
+
 def register():
     """
     Registers all models as available for RLlib

From f7f54d1af94fd5c0ee438756527d8141c84cde00 Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Sun, 25 Jul 2021 20:23:11 -0400
Subject: [PATCH 10/48] don't use lazy environment

---
 minerl_rllib/envs/env.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/minerl_rllib/envs/env.py b/minerl_rllib/envs/env.py
index 5233a68..0ba49c2 100644
--- a/minerl_rllib/envs/env.py
+++ b/minerl_rllib/envs/env.py
@@ -91,7 +91,9 @@ def register_minerl_envs():
     ):
 
         def env_creator(env_config):
-            return wrap(LazyMineRLEnv(env_spec), **env_config)
+            with filelock.FileLock("minerl_env.lock"):
+                env = wrap(env_spec.make(), **env_config)
+            return env
 
         register_env(env_spec.name, env_creator)
 

From 9e434acefa17e940521d0a3fdc34d8ae13f07f40 Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Sun, 25 Jul 2021 20:30:10 -0400
Subject: [PATCH 11/48] fix imports

---
 minerl_rllib/models/torch/baseline.py | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/minerl_rllib/models/torch/baseline.py b/minerl_rllib/models/torch/baseline.py
index f79f8e9..415cede 100644
--- a/minerl_rllib/models/torch/baseline.py
+++ b/minerl_rllib/models/torch/baseline.py
@@ -1,3 +1,5 @@
+import importlib
+
 import gym
 import numpy as np
 import torch
@@ -6,7 +8,7 @@
 from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
 from ray.tune.utils import merge_dicts
 
-from minerl_rllib import models
+from minerl_rllib.models.torch.rnn import GRUBaseline, LSTMBaseline
 
 BASELINE_CONFIG = {
     # specifies the size of the state embedding
@@ -83,9 +85,8 @@ def __init__(
             self.discrete = False
 
         def get_factory(network_name):
-            return getattr(
-                getattr(models.torch, network_name), model_config[f"{network_name}_net"]
-            )
+            base_module = importlib.import_module(f"minerl_rllib.models.torch.{network_name}")
+            return getattr(base_module, model_config[f"{network_name}_net"])
 
         self._pov_network, pov_embed_size = get_factory("pov")(
             **model_config["pov_net_kwargs"]
@@ -107,11 +108,11 @@ def get_factory(network_name):
         if self.use_rnn:
             state_embed_size = rnn_config["hidden_size"]
             if rnn_type == "lstm":
-                self._rnn = minerl_rllib.models.torch.rnn.LSTMBaseline(
+                self._rnn = LSTMBaseline(
                     state_input_size, **rnn_config
                 )
             elif rnn_type == "gru":
-                self._rnn = minerl_rllib.models.torch.rnn.GRUBaseline(
+                self._rnn = GRUBaseline(
                     state_input_size, **rnn_config
                 )
             else:

From d55c97ef23b635b88d94fe9224d06c2bae7e5c4a Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Mon, 26 Jul 2021 23:28:59 -0400
Subject: [PATCH 12/48] remove old config files

---
 config/custom_model/impala.yaml  | 16 -----------
 config/custom_model/marwil.yaml  | 16 -----------
 config/custom_model/sac.yaml     | 43 -----------------------------
 config/untuned/a2c.yaml          | 11 --------
 config/untuned/apex.yaml         | 32 ----------------------
 config/untuned/dist-dqn.yaml     | 31 ---------------------
 config/untuned/dqn.yaml          | 29 --------------------
 config/untuned/dueling-ddqn.yaml | 29 --------------------
 config/untuned/impala.yaml       | 12 ---------
 config/untuned/ppo.yaml          | 21 ---------------
 config/untuned/rainbow.yaml      | 46 --------------------------------
 config/untuned/sac.yaml          | 36 -------------------------
 12 files changed, 322 deletions(-)
 delete mode 100644 config/custom_model/impala.yaml
 delete mode 100644 config/custom_model/marwil.yaml
 delete mode 100644 config/custom_model/sac.yaml
 delete mode 100644 config/untuned/a2c.yaml
 delete mode 100644 config/untuned/apex.yaml
 delete mode 100644 config/untuned/dist-dqn.yaml
 delete mode 100644 config/untuned/dqn.yaml
 delete mode 100644 config/untuned/dueling-ddqn.yaml
 delete mode 100644 config/untuned/impala.yaml
 delete mode 100644 config/untuned/ppo.yaml
 delete mode 100644 config/untuned/rainbow.yaml
 delete mode 100644 config/untuned/sac.yaml

diff --git a/config/custom_model/impala.yaml b/config/custom_model/impala.yaml
deleted file mode 100644
index 126be13..0000000
--- a/config/custom_model/impala.yaml
+++ /dev/null
@@ -1,16 +0,0 @@
-minerl-impala:
-    run: IMPALA
-    config:
-        rollout_fragment_length: 50
-        train_batch_size: 500
-        num_workers: 2
-        num_envs_per_worker: 1
-        clip_rewards: True
-        lr_schedule: [
-            [0, 0.0001],
-            [20000000, 0.000000000001],
-        ]
-
-        framework: torch
-        model:
-            custom_model: minerl_torch_model
diff --git a/config/custom_model/marwil.yaml b/config/custom_model/marwil.yaml
deleted file mode 100644
index de571d6..0000000
--- a/config/custom_model/marwil.yaml
+++ /dev/null
@@ -1,16 +0,0 @@
-minerl-marwil:
-    run: MARWIL
-    config:
-        framework: torch
-        model:
-            custom_model: minerl_torch_model
-
-        # In order to evaluate on an actual environment, use these following
-        # settings:
-#        evaluation_num_workers: 1
-#        evaluation_interval: 1
-#        evaluation_config:
-#            input: sampler
-        # Compare IL (beta=0) vs MARWIL.
-#        beta:
-#            grid_search: [0, 1]
\ No newline at end of file
diff --git a/config/custom_model/sac.yaml b/config/custom_model/sac.yaml
deleted file mode 100644
index 9e84762..0000000
--- a/config/custom_model/sac.yaml
+++ /dev/null
@@ -1,43 +0,0 @@
-atari-sac:
-    run: SAC
-    config:
-        gamma: 0.99
-        # state-preprocessor=Our default Atari Conv2D-net.
-        use_state_preprocessor: true
-        Q_model:
-            fcnet_activation: relu
-            fcnet_hiddens: [512]
-        policy_model:
-            fcnet_activation: relu
-            fcnet_hiddens: [512]
-        # Do hard syncs.
-        # Soft-syncs seem to work less reliably for discrete action spaces.
-        tau: 1.0
-        target_network_update_freq: 8000
-        # auto = 0.98 * -log(1/|A|)
-        target_entropy: auto
-        clip_rewards: 1.0
-        no_done_at_end: False
-        n_step: 1
-        rollout_fragment_length: 1
-        prioritized_replay: true
-        train_batch_size: 64
-        timesteps_per_iteration: 4
-        # Paper uses 20k random timesteps, which is not exactly the same, but
-        # seems to work nevertheless. We use 100k here for the longer Atari
-        # runs (DQN style: filling up the buffer a bit before learning).
-        learning_starts: 20000
-        optimization:
-            actor_learning_rate: 0.0003
-            critic_learning_rate: 0.0003
-            entropy_learning_rate: 0.0003
-        num_workers: 0
-        num_gpus: 1
-        metrics_smoothing_episodes: 5
-
-        framework: torch
-        model:
-            custom_model: minerl_torch_model
-            custom_model_config:
-                use_rnn: false
-                use_prev_action_reward: false
diff --git a/config/untuned/a2c.yaml b/config/untuned/a2c.yaml
deleted file mode 100644
index 49e5eb6..0000000
--- a/config/untuned/a2c.yaml
+++ /dev/null
@@ -1,11 +0,0 @@
-atari-a2c:
-    run: A2C
-    config:
-        rollout_fragment_length: 20
-        num_workers: 5
-        num_envs_per_worker: 5
-        num_gpus: 1
-        lr_schedule: [
-            [0, 0.0007],
-            [20000000, 0.000000000001],
-        ]
diff --git a/config/untuned/apex.yaml b/config/untuned/apex.yaml
deleted file mode 100644
index 90bce81..0000000
--- a/config/untuned/apex.yaml
+++ /dev/null
@@ -1,32 +0,0 @@
-atari-apex:
-    run: APEX
-    config:
-        double_q: false
-        dueling: false
-        num_atoms: 1
-        noisy: false
-        n_step: 3
-        lr: .0001
-        adam_epsilon: .00015
-        hiddens: [512]
-        buffer_size: 1000000
-        exploration_config:
-          final_epsilon: 0.01
-          epsilon_timesteps: 200000
-        prioritized_replay_alpha: 0.5
-        final_prioritized_replay_beta: 1.0
-        prioritized_replay_beta_annealing_timesteps: 2000000
-
-        num_gpus: 1
-
-        # APEX
-        num_workers: 8
-        num_envs_per_worker: 8
-        rollout_fragment_length: 20
-        train_batch_size: 512
-        target_network_update_freq: 50000
-        timesteps_per_iteration: 25000
-
-        # MineRL
-        env_config:
-            discrete: true
diff --git a/config/untuned/dist-dqn.yaml b/config/untuned/dist-dqn.yaml
deleted file mode 100644
index 281ddcb..0000000
--- a/config/untuned/dist-dqn.yaml
+++ /dev/null
@@ -1,31 +0,0 @@
-atari-dist-dqn:
-    run: DQN
-    config:
-        # only works on tf for now
-        framework: tf
-        double_q: false
-        dueling: false
-        num_atoms: 51
-        noisy: false
-        prioritized_replay: false
-        n_step: 1
-        target_network_update_freq: 8000
-        lr: .0000625
-        adam_epsilon: .00015
-        hiddens: [512]
-        learning_starts: 20000
-        buffer_size: 1000000
-        rollout_fragment_length: 4
-        train_batch_size: 32
-        exploration_config:
-          epsilon_timesteps: 200000
-          final_epsilon: 0.01
-        prioritized_replay_alpha: 0.5
-        final_prioritized_replay_beta: 1.0
-        prioritized_replay_beta_annealing_timesteps: 2000000
-        num_gpus: 0.2
-        timesteps_per_iteration: 10000
-
-        # MineRL
-        env_config:
-            discrete: true
diff --git a/config/untuned/dqn.yaml b/config/untuned/dqn.yaml
deleted file mode 100644
index 7d3a0c5..0000000
--- a/config/untuned/dqn.yaml
+++ /dev/null
@@ -1,29 +0,0 @@
-atari-basic-dqn:
-    run: DQN
-    config:
-        double_q: false
-        dueling: false
-        num_atoms: 1
-        noisy: false
-        prioritized_replay: false
-        n_step: 1
-        target_network_update_freq: 8000
-        lr: .0000625
-        adam_epsilon: .00015
-        hiddens: [512]
-        learning_starts: 20000
-        buffer_size: 1000000
-        rollout_fragment_length: 4
-        train_batch_size: 32
-        exploration_config:
-          epsilon_timesteps: 200000
-          final_epsilon: 0.01
-        prioritized_replay_alpha: 0.5
-        final_prioritized_replay_beta: 1.0
-        prioritized_replay_beta_annealing_timesteps: 2000000
-        num_gpus: 0.2
-        timesteps_per_iteration: 10000
-
-        # MineRL
-        env_config:
-            discrete: true
diff --git a/config/untuned/dueling-ddqn.yaml b/config/untuned/dueling-ddqn.yaml
deleted file mode 100644
index c2242c9..0000000
--- a/config/untuned/dueling-ddqn.yaml
+++ /dev/null
@@ -1,29 +0,0 @@
-atari-dueling-ddqn:
-    run: DQN
-    config:
-        double_q: true
-        dueling: true
-        num_atoms: 1
-        noisy: false
-        prioritized_replay: false
-        n_step: 1
-        target_network_update_freq: 8000
-        lr: .0000625
-        adam_epsilon: .00015
-        hiddens: [512]
-        learning_starts: 20000
-        buffer_size: 1000000
-        rollout_fragment_length: 4
-        train_batch_size: 32
-        exploration_config:
-          epsilon_timesteps: 200000
-          final_epsilon: 0.01
-        prioritized_replay_alpha: 0.5
-        final_prioritized_replay_beta: 1.0
-        prioritized_replay_beta_annealing_timesteps: 2000000
-        num_gpus: 0.2
-        timesteps_per_iteration: 10000
-
-        # MineRL
-        env_config:
-            discrete: true
diff --git a/config/untuned/impala.yaml b/config/untuned/impala.yaml
deleted file mode 100644
index 43e8ad1..0000000
--- a/config/untuned/impala.yaml
+++ /dev/null
@@ -1,12 +0,0 @@
-atari-impala:
-    run: IMPALA
-    config:
-        rollout_fragment_length: 50
-        train_batch_size: 500
-        num_workers: 32
-        num_envs_per_worker: 5
-        clip_rewards: True
-        lr_schedule: [
-            [0, 0.0005],
-            [20000000, 0.000000000001],
-        ]
diff --git a/config/untuned/ppo.yaml b/config/untuned/ppo.yaml
deleted file mode 100644
index 9d72fab..0000000
--- a/config/untuned/ppo.yaml
+++ /dev/null
@@ -1,21 +0,0 @@
-atari-ppo:
-    run: PPO
-    config:
-        lambda: 0.95
-        kl_coeff: 0.5
-        clip_rewards: True
-        clip_param: 0.1
-        vf_clip_param: 10.0
-        entropy_coeff: 0.01
-        train_batch_size: 5000
-        rollout_fragment_length: 100
-        sgd_minibatch_size: 500
-        num_sgd_iter: 10
-        num_workers: 10
-        num_envs_per_worker: 5
-        batch_mode: truncate_episodes
-        observation_filter: NoFilter
-        vf_share_layers: true
-        num_gpus: 1
-        model:
-            use_lstm: true
diff --git a/config/untuned/rainbow.yaml b/config/untuned/rainbow.yaml
deleted file mode 100644
index 433c03f..0000000
--- a/config/untuned/rainbow.yaml
+++ /dev/null
@@ -1,46 +0,0 @@
-# base hyperparameters used from sample efficient rainbow: https://arxiv.org/abs/1906.05243
-atari-rainbow:
-    run: DQN
-    config:
-        double_q: true
-        dueling: true
-        num_atoms: 51
-        noisy: True
-        sigma0: 0.1 # noisy nets parameter
-        gamma: 0.99
-        lr: .0001
-        adam_epsilon: .00015
-        grad_clip: 10
-        hiddens: [512]
-        learning_starts: 1600  # 20000 -> 1600
-        buffer_size: 100000
-        rollout_fragment_length: 1  # 4 -> 1
-        train_batch_size: 32
-        exploration_config:
-            epsilon_timesteps: 2
-            final_epsilon: 0.0
-        target_network_update_freq: 2000
-        prioritized_replay: True
-        prioritized_replay_alpha: 0.5
-        prioritized_replay_beta: 0.4
-        final_prioritized_replay_beta: 1.0
-        prioritized_replay_beta_annealing_timesteps: 8000000 # set to the expected maximum number of time steps
-        n_step: 20  # 3 -> 20
-        num_gpus: 1
-
-        model:
-            # Filter config. List of [out_channels, kernel, stride] for each filter
-            conv_filters: [
-                [32, [5, 5], 5],
-                [64, [5, 5], 5],
-            ]
-            fcnet_hiddens: [256]
-            framestack: false
-            dim: 64  # this shouldn't do anything in the preprocessor but MineRL pov observations are 64x64
-
-        # MineRL
-        env_config:
-            discrete: true
-            action_repeat: 4
-            num_stack: 4
-            gray_scale: true
diff --git a/config/untuned/sac.yaml b/config/untuned/sac.yaml
deleted file mode 100644
index 5460a0d..0000000
--- a/config/untuned/sac.yaml
+++ /dev/null
@@ -1,36 +0,0 @@
-atari-sac:
-    run: SAC
-    config:
-        gamma: 0.99
-        # state-preprocessor=Our default Atari Conv2D-net.
-        use_state_preprocessor: true
-        Q_model:
-            fcnet_activation: relu
-            fcnet_hiddens: [512]
-        policy_model:
-            fcnet_activation: relu
-            fcnet_hiddens: [512]
-        # Do hard syncs.
-        # Soft-syncs seem to work less reliably for discrete action spaces.
-        tau: 1.0
-        target_network_update_freq: 8000
-        # auto = 0.98 * -log(1/|A|)
-        target_entropy: auto
-        clip_rewards: 1.0
-        no_done_at_end: False
-        n_step: 1
-        rollout_fragment_length: 1
-        prioritized_replay: true
-        train_batch_size: 64
-        timesteps_per_iteration: 4
-        # Paper uses 20k random timesteps, which is not exactly the same, but
-        # seems to work nevertheless. We use 100k here for the longer Atari
-        # runs (DQN style: filling up the buffer a bit before learning).
-        learning_starts: 20000
-        optimization:
-            actor_learning_rate: 0.0003
-            critic_learning_rate: 0.0003
-            entropy_learning_rate: 0.0003
-        num_workers: 0
-        num_gpus: 1
-        metrics_smoothing_episodes: 5

From 35bf4f3ffaf82dbc110434f2371c05531202ff4a Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Mon, 26 Jul 2021 23:50:19 -0400
Subject: [PATCH 13/48] remove invalid argument

---
 minerl_rllib/envs/input.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/minerl_rllib/envs/input.py b/minerl_rllib/envs/input.py
index 04e82f8..2868f4f 100644
--- a/minerl_rllib/envs/input.py
+++ b/minerl_rllib/envs/input.py
@@ -37,14 +37,12 @@ def __init__(self, ioctx: IOContext = None):
         num_epochs = input_config.get("num_epochs", -1)
         preload_buffer_size = input_config.get("preload_buffer_size", 2)
         seed = input_config.get("seed", None)
-        include_metadata = input_config.get("include_metadata", False)
         self.generator = self.data.batch_iter(
             batch_size,
             seq_len,
             num_epochs=num_epochs,
             preload_buffer_size=preload_buffer_size,
             seed=seed,
-            include_metadata=include_metadata,
         )
         env = MinerRLDataEnv(self.data)
         env = wrap_env(env, env_config)

From 69ee229e8fea2968e0199c55bc7f12376d9c9f71 Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Sat, 31 Jul 2021 02:00:14 -0400
Subject: [PATCH 14/48] format

---
 minerl_rllib/models/torch/baseline.py | 12 +++++-------
 1 file changed, 5 insertions(+), 7 deletions(-)

diff --git a/minerl_rllib/models/torch/baseline.py b/minerl_rllib/models/torch/baseline.py
index 415cede..23934bc 100644
--- a/minerl_rllib/models/torch/baseline.py
+++ b/minerl_rllib/models/torch/baseline.py
@@ -85,7 +85,9 @@ def __init__(
             self.discrete = False
 
         def get_factory(network_name):
-            base_module = importlib.import_module(f"minerl_rllib.models.torch.{network_name}")
+            base_module = importlib.import_module(
+                f"minerl_rllib.models.torch.{network_name}"
+            )
             return getattr(base_module, model_config[f"{network_name}_net"])
 
         self._pov_network, pov_embed_size = get_factory("pov")(
@@ -108,13 +110,9 @@ def get_factory(network_name):
         if self.use_rnn:
             state_embed_size = rnn_config["hidden_size"]
             if rnn_type == "lstm":
-                self._rnn = LSTMBaseline(
-                    state_input_size, **rnn_config
-                )
+                self._rnn = LSTMBaseline(state_input_size, **rnn_config)
             elif rnn_type == "gru":
-                self._rnn = GRUBaseline(
-                    state_input_size, **rnn_config
-                )
+                self._rnn = GRUBaseline(state_input_size, **rnn_config)
             else:
                 raise NotImplementedError
         else:

From 364d8f20690dc8f7b8d016e4042a031d21b24968 Mon Sep 17 00:00:00 2001
From: Julius <juliustfrost@gmail.com>
Date: Sat, 31 Jul 2021 02:01:17 -0400
Subject: [PATCH 15/48] add episode based data loader

---
 minerl_rllib/envs/env.py   |  6 +++-
 minerl_rllib/envs/input.py | 71 ++++++++++++++++++++++++++++++++++----
 2 files changed, 70 insertions(+), 7 deletions(-)

diff --git a/minerl_rllib/envs/env.py b/minerl_rllib/envs/env.py
index 0ba49c2..3c25229 100644
--- a/minerl_rllib/envs/env.py
+++ b/minerl_rllib/envs/env.py
@@ -85,6 +85,10 @@ def render(self, mode="human"):
         pass
 
 
+def wrap_env(env, **kwargs):
+    return wrap(env, **kwargs)
+
+
 def register_minerl_envs():
     for env_spec in (
         BASIC_ENV_SPECS + COMPETITION_ENV_SPECS + BASALT_COMPETITION_ENV_SPECS
@@ -92,7 +96,7 @@ def register_minerl_envs():
 
         def env_creator(env_config):
             with filelock.FileLock("minerl_env.lock"):
-                env = wrap(env_spec.make(), **env_config)
+                env = wrap_env(env_spec.make(), **env_config)
             return env
 
         register_env(env_spec.name, env_creator)
diff --git a/minerl_rllib/envs/input.py b/minerl_rllib/envs/input.py
index 2868f4f..415e45c 100644
--- a/minerl_rllib/envs/input.py
+++ b/minerl_rllib/envs/input.py
@@ -2,15 +2,62 @@
 
 import gym
 import numpy as np
+from ray.rllib.evaluation import SampleBatchBuilder
 from ray.rllib.models.preprocessors import get_preprocessor
-
 from ray.rllib.offline import IOContext
 from ray.rllib.offline.input_reader import InputReader
 from ray.rllib.policy.sample_batch import SampleBatch
 from ray.rllib.utils.typing import SampleBatchType
 from ray.tune.registry import register_input
 
-from minerl_rllib.envs.data import MinerRLDataEnv, wrap_env
+from minerl_rllib.envs.data import MinerRLDataEnv
+from minerl_rllib.envs.env import wrap_env
+from minerl_rllib.envs.utils import patch_data_pipeline
+
+
+def simulate_env_interaction(env, restart=True) -> SampleBatch:
+    prep = get_preprocessor(env.observation_space)(env.observation_space)
+    batch_builder = SampleBatchBuilder()
+    while restart:
+        for eps_id, trajectory_name in enumerate(env.trajectory_names):
+            t = 0
+            prev_action = None
+            prev_reward = 0
+            done = False
+            try:
+                obs = env.reset()
+            except TypeError:
+                continue
+            while not done:
+                new_obs, reward, done, info = env.step(env.action_space.sample())
+                action = info["action"]
+                action = env.reverse_action(action)
+                if prev_action is None:
+                    prev_action = np.zeros_like(action)
+
+                batch = {
+                    "t": t,
+                    SampleBatch.EPS_ID: eps_id,
+                    SampleBatch.AGENT_INDEX: eps_id,
+                    SampleBatch.OBS: prep.transform(obs),
+                    SampleBatch.ACTIONS: action,
+                    SampleBatch.ACTION_PROB: 1.0,
+                    SampleBatch.ACTION_LOGP: 0,
+                    SampleBatch.ACTION_DIST_INPUTS: 0,
+                    SampleBatch.REWARDS: reward,
+                    SampleBatch.PREV_ACTIONS: prev_action,
+                    SampleBatch.PREV_REWARDS: prev_reward,
+                    SampleBatch.DONES: done,
+                    SampleBatch.INFOS: {"trajectory_name": trajectory_name},
+                    SampleBatch.NEXT_OBS: prep.transform(new_obs),
+                }
+
+                batch_builder.add_values(**batch)
+                obs = new_obs
+                prev_action = action
+                prev_reward = reward
+                t += 1
+            yield batch_builder.build_and_reset()
 
 
 class MineRLInputReader(InputReader):
@@ -19,6 +66,8 @@ def __init__(self, ioctx: IOContext = None):
         print("Input reader initialization success!")
         import minerl
 
+        patch_data_pipeline()
+
         input_config = ioctx.input_config
         env_name = ioctx.config.get("env")
         env_config = ioctx.config.get("env_config", {})
@@ -37,6 +86,7 @@ def __init__(self, ioctx: IOContext = None):
         num_epochs = input_config.get("num_epochs", -1)
         preload_buffer_size = input_config.get("preload_buffer_size", 2)
         seed = input_config.get("seed", None)
+        self.load_complete_episodes = input_config.get("load_complete_episodes", True)
         self.generator = self.data.batch_iter(
             batch_size,
             seq_len,
@@ -45,8 +95,8 @@ def __init__(self, ioctx: IOContext = None):
             seed=seed,
         )
         env = MinerRLDataEnv(self.data)
-        env = wrap_env(env, env_config)
-        print(env.observation_space)
+        env = wrap_env(env, **env_config)
+        self.episode_generator = simulate_env_interaction(env)
         self.prep = get_preprocessor(env.observation_space)(env.observation_space)
 
         env_ptr = env
@@ -89,7 +139,17 @@ def process_reward(self, reward):
         return reward
 
     def next(self) -> SampleBatchType:
-        obs, action, reward, next_obs, done = self.process_batch(next(self.generator))
+        if self.load_complete_episodes:
+            return self.next_episode_batch()
+        else:
+            return self.next_trajectory_batch()
+
+    def next_episode_batch(self) -> SampleBatch:
+        return next(self.episode_generator)
+
+    def next_trajectory_batch(self) -> SampleBatch:
+        data = self.process_batch(next(self.generator))
+        obs, action, reward, next_obs, done = data[:5]
         d = {
             SampleBatch.OBS: obs,
             SampleBatch.ACTIONS: action,
@@ -97,7 +157,6 @@ def next(self) -> SampleBatchType:
             SampleBatch.REWARDS: reward,
             SampleBatch.DONES: done,
         }
-        # recursive_print(d)
         return SampleBatch(d)
 
     def process_batch(self, batch):

From 78ea58cfbc3528227988216e26a31f6598319fe1 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Sun, 5 Sep 2021 19:46:09 -0400
Subject: [PATCH 16/48] update requirements

---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index a90d487..bc53cb7 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,3 @@
 ray[default,tune,rllib]>=1.4.1
-git+https://github.com/minerl-wrappers/minerl-wrappers.git
+minerl-wrappers>=0.1.3
 scikit-learn>=0.24.2
\ No newline at end of file

From 88e5d51619841d9e50319b197df598b627c825a1 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 9 Sep 2021 00:51:51 -0400
Subject: [PATCH 17/48] add LICENSE.md

---
 LICENSE.md | 674 +++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 674 insertions(+)
 create mode 100644 LICENSE.md

diff --git a/LICENSE.md b/LICENSE.md
new file mode 100644
index 0000000..e72bfdd
--- /dev/null
+++ b/LICENSE.md
@@ -0,0 +1,674 @@
+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
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+ Everyone is permitted to copy and distribute verbatim copies
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+contain the covered work, unless you entered into that arrangement,
+or that patent license was granted, prior to 28 March 2007.
+
+  Nothing in this License shall be construed as excluding or limiting
+any implied license or other defenses to infringement that may
+otherwise be available to you under applicable patent law.
+
+  12. No Surrender of Others' Freedom.
+
+  If conditions are imposed on you (whether by court order, agreement or
+otherwise) that contradict the conditions of this License, they do not
+excuse you from the conditions of this License.  If you cannot convey a
+covered work so as to satisfy simultaneously your obligations under this
+License and any other pertinent obligations, then as a consequence you may
+not convey it at all.  For example, if you agree to terms that obligate you
+to collect a royalty for further conveying from those to whom you convey
+the Program, the only way you could satisfy both those terms and this
+License would be to refrain entirely from conveying the Program.
+
+  13. Use with the GNU Affero General Public License.
+
+  Notwithstanding any other provision of this License, you have
+permission to link or combine any covered work with a work licensed
+under version 3 of the GNU Affero General Public License into a single
+combined work, and to convey the resulting work.  The terms of this
+License will continue to apply to the part which is the covered work,
+but the special requirements of the GNU Affero General Public License,
+section 13, concerning interaction through a network will apply to the
+combination as such.
+
+  14. Revised Versions of this License.
+
+  The Free Software Foundation may publish revised and/or new versions of
+the GNU General Public License from time to time.  Such new versions will
+be similar in spirit to the present version, but may differ in detail to
+address new problems or concerns.
+
+  Each version is given a distinguishing version number.  If the
+Program specifies that a certain numbered version of the GNU General
+Public License "or any later version" applies to it, you have the
+option of following the terms and conditions either of that numbered
+version or of any later version published by the Free Software
+Foundation.  If the Program does not specify a version number of the
+GNU General Public License, you may choose any version ever published
+by the Free Software Foundation.
+
+  If the Program specifies that a proxy can decide which future
+versions of the GNU General Public License can be used, that proxy's
+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+  Later license versions may give you additional or different
+permissions.  However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
+
+  15. Disclaimer of Warranty.
+
+  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
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+  16. Limitation of Liability.
+
+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+    <program>  Copyright (C) <year>  <name of author>
+    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+    This is free software, and you are welcome to redistribute it
+    under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License.  Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+<https://www.gnu.org/licenses/>.
+
+  The GNU General Public License does not permit incorporating your program
+into proprietary programs.  If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library.  If this is what you want to do, use the GNU Lesser General
+Public License instead of this License.  But first, please read
+<https://www.gnu.org/licenses/why-not-lgpl.html>.
\ No newline at end of file

From bd962e6b0025276c23512e2b009f736b1d229212 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 9 Sep 2021 00:52:12 -0400
Subject: [PATCH 18/48] add poetry as dependency manager

---
 poetry.lock    | 2672 ++++++++++++++++++++++++++++++++++++++++++++++++
 pyproject.toml |   30 +
 2 files changed, 2702 insertions(+)
 create mode 100644 poetry.lock
 create mode 100644 pyproject.toml

diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..75926aa
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,2672 @@
+[[package]]
+name = "aiohttp"
+version = "3.7.4.post0"
+description = "Async http client/server framework (asyncio)"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+async-timeout = ">=3.0,<4.0"
+attrs = ">=17.3.0"
+chardet = ">=2.0,<5.0"
+multidict = ">=4.5,<7.0"
+typing-extensions = ">=3.6.5"
+yarl = ">=1.0,<2.0"
+
+[package.extras]
+speedups = ["aiodns", "brotlipy", "cchardet"]
+
+[[package]]
+name = "aiohttp-cors"
+version = "0.7.0"
+description = "CORS support for aiohttp"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+aiohttp = ">=1.1"
+
+[[package]]
+name = "aioredis"
+version = "1.3.1"
+description = "asyncio (PEP 3156) Redis support"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+async-timeout = "*"
+hiredis = "*"
+
+[[package]]
+name = "appnope"
+version = "0.1.2"
+description = "Disable App Nap on macOS >= 10.9"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "async-timeout"
+version = "3.0.1"
+description = "Timeout context manager for asyncio programs"
+category = "main"
+optional = false
+python-versions = ">=3.5.3"
+
+[[package]]
+name = "atomicwrites"
+version = "1.4.0"
+description = "Atomic file writes."
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[[package]]
+name = "attrs"
+version = "21.2.0"
+description = "Classes Without Boilerplate"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[package.extras]
+dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit"]
+docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"]
+tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface"]
+tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins"]
+
+[[package]]
+name = "backcall"
+version = "0.2.0"
+description = "Specifications for callback functions passed in to an API"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "black"
+version = "21.8b0"
+description = "The uncompromising code formatter."
+category = "dev"
+optional = false
+python-versions = ">=3.6.2"
+
+[package.dependencies]
+click = ">=7.1.2"
+mypy-extensions = ">=0.4.3"
+pathspec = ">=0.9.0,<1"
+platformdirs = ">=2"
+regex = ">=2020.1.8"
+tomli = ">=0.2.6,<2.0.0"
+typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\""}
+typing-extensions = [
+    {version = ">=3.10.0.0", markers = "python_version < \"3.10\""},
+    {version = "!=3.10.0.1", markers = "python_version >= \"3.10\""},
+]
+
+[package.extras]
+colorama = ["colorama (>=0.4.3)"]
+d = ["aiohttp (>=3.6.0)", "aiohttp-cors (>=0.4.0)"]
+jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
+python2 = ["typed-ast (>=1.4.2)"]
+uvloop = ["uvloop (>=0.15.2)"]
+
+[[package]]
+name = "blessings"
+version = "1.7"
+description = "A thin, practical wrapper around terminal coloring, styling, and positioning"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[package.dependencies]
+six = "*"
+
+[[package]]
+name = "bullet"
+version = "2.2.0"
+description = "Beautiful Python prompts made simple."
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "cachetools"
+version = "4.2.2"
+description = "Extensible memoizing collections and decorators"
+category = "main"
+optional = false
+python-versions = "~=3.5"
+
+[[package]]
+name = "certifi"
+version = "2021.5.30"
+description = "Python package for providing Mozilla's CA Bundle."
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "chardet"
+version = "4.0.0"
+description = "Universal encoding detector for Python 2 and 3"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[[package]]
+name = "charset-normalizer"
+version = "2.0.4"
+description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+category = "main"
+optional = false
+python-versions = ">=3.5.0"
+
+[package.extras]
+unicode_backport = ["unicodedata2"]
+
+[[package]]
+name = "click"
+version = "8.0.1"
+description = "Composable command line interface toolkit"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
+
+[[package]]
+name = "cloudpickle"
+version = "1.6.0"
+description = "Extended pickling support for Python objects"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[[package]]
+name = "colorama"
+version = "0.4.4"
+description = "Cross-platform colored terminal text."
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[[package]]
+name = "coloredlogs"
+version = "15.0.1"
+description = "Colored terminal output for Python's logging module"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[package.dependencies]
+humanfriendly = ">=9.1"
+
+[package.extras]
+cron = ["capturer (>=2.4)"]
+
+[[package]]
+name = "colorful"
+version = "0.5.4"
+description = "Terminal string styling done right, in Python."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[[package]]
+name = "cycler"
+version = "0.10.0"
+description = "Composable style cycles"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+six = "*"
+
+[[package]]
+name = "daemoniker"
+version = "0.2.3"
+description = "Cross-platform daemonization tools."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.extras]
+test = ["psutil"]
+
+[[package]]
+name = "decorator"
+version = "5.0.9"
+description = "Decorators for Humans"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[[package]]
+name = "dill"
+version = "0.3.4"
+description = "serialize all of python"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*"
+
+[package.extras]
+graph = ["objgraph (>=1.7.2)"]
+
+[[package]]
+name = "dm-tree"
+version = "0.1.6"
+description = "Tree is a library for working with nested data structures."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+six = ">=1.12.0"
+
+[[package]]
+name = "filelock"
+version = "3.0.12"
+description = "A platform independent file lock."
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "getch"
+version = "1.0"
+description = "Does single char input, like C getch/getche"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "google-api-core"
+version = "1.31.2"
+description = "Google API client core library"
+category = "main"
+optional = false
+python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
+
+[package.dependencies]
+google-auth = ">=1.25.0,<2.0dev"
+googleapis-common-protos = ">=1.6.0,<2.0dev"
+packaging = ">=14.3"
+protobuf = ">=3.12.0"
+pytz = "*"
+requests = ">=2.18.0,<3.0.0dev"
+six = ">=1.13.0"
+
+[package.extras]
+grpc = ["grpcio (>=1.29.0,<2.0dev)"]
+grpcgcp = ["grpcio-gcp (>=0.2.2)"]
+grpcio-gcp = ["grpcio-gcp (>=0.2.2)"]
+
+[[package]]
+name = "google-auth"
+version = "1.35.0"
+description = "Google Authentication Library"
+category = "main"
+optional = false
+python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
+
+[package.dependencies]
+cachetools = ">=2.0.0,<5.0"
+pyasn1-modules = ">=0.2.1"
+rsa = {version = ">=3.1.4,<5", markers = "python_version >= \"3.6\""}
+six = ">=1.9.0"
+
+[package.extras]
+aiohttp = ["requests (>=2.20.0,<3.0.0dev)", "aiohttp (>=3.6.2,<4.0.0dev)"]
+pyopenssl = ["pyopenssl (>=20.0.0)"]
+reauth = ["pyu2f (>=0.1.5)"]
+
+[[package]]
+name = "googleapis-common-protos"
+version = "1.53.0"
+description = "Common protobufs used in Google APIs"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+protobuf = ">=3.12.0"
+
+[package.extras]
+grpc = ["grpcio (>=1.0.0)"]
+
+[[package]]
+name = "gpustat"
+version = "0.6.0"
+description = "An utility to monitor NVIDIA GPU status and usage"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+blessings = ">=1.6"
+nvidia-ml-py3 = ">=7.352.0"
+psutil = "*"
+six = ">=1.7"
+
+[package.extras]
+test = ["mock (>=2.0.0)", "pytest (<5.0)"]
+
+[[package]]
+name = "grpcio"
+version = "1.40.0"
+description = "HTTP/2-based RPC framework"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+six = ">=1.5.2"
+
+[package.extras]
+protobuf = ["grpcio-tools (>=1.40.0)"]
+
+[[package]]
+name = "gym"
+version = "0.19.0"
+description = "The OpenAI Gym: A toolkit for developing and comparing your reinforcement learning agents."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+cloudpickle = ">=1.2.0,<1.7.0"
+numpy = ">=1.18.0"
+
+[package.extras]
+all = ["atari-py (==0.2.6)", "box2d-py (>=2.3.5,<2.4.0)", "opencv-python (>=3)", "mujoco_py (>=1.50,<2.0)", "scipy", "imageio", "pyglet (>=1.4.0)"]
+atari = ["atari-py (==0.2.6)", "opencv-python (>=3)"]
+box2d = ["box2d-py (>=2.3.5,<2.4.0)", "pyglet (>=1.4.0)"]
+classic_control = ["pyglet (>=1.4.0)"]
+mujoco = ["mujoco_py (>=1.50,<2.0)", "imageio"]
+nomujoco = ["atari-py (==0.2.6)", "box2d-py (>=2.3.5,<2.4.0)", "opencv-python (>=3)", "scipy", "pyglet (>=1.4.0)"]
+robotics = ["mujoco_py (>=1.50,<2.0)", "imageio"]
+toy_text = ["scipy"]
+
+[[package]]
+name = "hiredis"
+version = "2.0.0"
+description = "Python wrapper for hiredis"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "humanfriendly"
+version = "9.2"
+description = "Human friendly output for text interfaces using Python"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[package.dependencies]
+pyreadline = {version = "*", markers = "sys_platform == \"win32\""}
+
+[[package]]
+name = "idna"
+version = "3.2"
+description = "Internationalized Domain Names in Applications (IDNA)"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[[package]]
+name = "imageio"
+version = "2.9.0"
+description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats."
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[package.dependencies]
+numpy = "*"
+pillow = "*"
+
+[package.extras]
+ffmpeg = ["imageio-ffmpeg"]
+fits = ["astropy"]
+full = ["astropy", "gdal", "imageio-ffmpeg", "itk"]
+gdal = ["gdal"]
+itk = ["itk"]
+
+[[package]]
+name = "importlib-metadata"
+version = "4.8.1"
+description = "Read metadata from Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
+zipp = ">=0.5"
+
+[package.extras]
+docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
+perf = ["ipython"]
+testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pep517", "pyfakefs", "flufl.flake8", "pytest-perf (>=0.9.2)", "pytest-black (>=0.3.7)", "pytest-mypy", "importlib-resources (>=1.3)"]
+
+[[package]]
+name = "inflection"
+version = "0.5.1"
+description = "A port of Ruby on Rails inflector to Python"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[[package]]
+name = "iniconfig"
+version = "1.1.1"
+description = "iniconfig: brain-dead simple config-ini parsing"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "ipython"
+version = "7.27.0"
+description = "IPython: Productive Interactive Computing"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+appnope = {version = "*", markers = "sys_platform == \"darwin\""}
+backcall = "*"
+colorama = {version = "*", markers = "sys_platform == \"win32\""}
+decorator = "*"
+jedi = ">=0.16"
+matplotlib-inline = "*"
+pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
+pickleshare = "*"
+prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0"
+pygments = "*"
+traitlets = ">=4.2"
+
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diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..4498847
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,30 @@
+[tool.poetry]
+name = "minerl-rllib"
+version = "0.1.0"
+description = "minerl-rllib is a reinforcement learning suite that benchmarks algorithms in RLLib on the MineRL environment."
+license = "GPL-3.0-only"
+authors = ["Julius Frost"]
+readme = "README.md"
+homepage = "https://github.com/juliusfrost/minerl-rllib/"
+repository = "https://github.com/juliusfrost/minerl-rllib/"
+
+[tool.poetry.dependencies]
+python = "^3.7.1"
+scikit-learn = "^0.24.2"
+ray = [
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.9' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl"},
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.8' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"},
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+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.8' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp38-cp38-win_amd64.whl"},
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.7' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp37-cp37m-win_amd64.whl"}
+]
+minerl-wrappers = "^0.1.4"
+
+[tool.poetry.dev-dependencies]
+pytest = "^6.2.4"
+black = "^21.7b0"
+
+[build-system]
+requires = ["poetry-core=1.1.8"]
+build-backend = "poetry.core.masonry.api"

From c49e2231ab55cc9542fed876675f98fe55ea6f15 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 9 Sep 2021 00:57:33 -0400
Subject: [PATCH 19/48] update .gitignore

---
 .gitignore | 238 +++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 238 insertions(+)

diff --git a/.gitignore b/.gitignore
index 8b63158..5762a63 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,241 @@
+# Project Specific
 data/
 logs/
 results/
+
+# Created by https://www.toptal.com/developers/gitignore/api/pycharm+all,python
+# Edit at https://www.toptal.com/developers/gitignore?templates=pycharm+all,python
+
+### PyCharm+all ###
+# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider
+# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
+
+# User-specific stuff
+.idea/**/workspace.xml
+.idea/**/tasks.xml
+.idea/**/usage.statistics.xml
+.idea/**/dictionaries
+.idea/**/shelf
+
+# AWS User-specific
+.idea/**/aws.xml
+
+# Generated files
+.idea/**/contentModel.xml
+
+# Sensitive or high-churn files
+.idea/**/dataSources/
+.idea/**/dataSources.ids
+.idea/**/dataSources.local.xml
+.idea/**/sqlDataSources.xml
+.idea/**/dynamic.xml
+.idea/**/uiDesigner.xml
+.idea/**/dbnavigator.xml
+
+# Gradle
+.idea/**/gradle.xml
+.idea/**/libraries
+
+# Gradle and Maven with auto-import
+# When using Gradle or Maven with auto-import, you should exclude module files,
+# since they will be recreated, and may cause churn.  Uncomment if using
+# auto-import.
+# .idea/artifacts
+# .idea/compiler.xml
+# .idea/jarRepositories.xml
+# .idea/modules.xml
+# .idea/*.iml
+# .idea/modules
+# *.iml
+# *.ipr
+
+# CMake
+cmake-build-*/
+
+# Mongo Explorer plugin
+.idea/**/mongoSettings.xml
+
+# File-based project format
+*.iws
+
+# IntelliJ
+out/
+
+# mpeltonen/sbt-idea plugin
+.idea_modules/
+
+# JIRA plugin
+atlassian-ide-plugin.xml
+
+# Cursive Clojure plugin
+.idea/replstate.xml
+
+# Crashlytics plugin (for Android Studio and IntelliJ)
+com_crashlytics_export_strings.xml
+crashlytics.properties
+crashlytics-build.properties
+fabric.properties
+
+# Editor-based Rest Client
+.idea/httpRequests
+
+# Android studio 3.1+ serialized cache file
+.idea/caches/build_file_checksums.ser
+
+### PyCharm+all Patch ###
+# Ignores the whole .idea folder and all .iml files
+# See https://github.com/joeblau/gitignore.io/issues/186 and https://github.com/joeblau/gitignore.io/issues/360
+
+.idea/
+
+# Reason: https://github.com/joeblau/gitignore.io/issues/186#issuecomment-249601023
+
+*.iml
+modules.xml
+.idea/misc.xml
+*.ipr
+
+# Sonarlint plugin
+.idea/sonarlint
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# End of https://www.toptal.com/developers/gitignore/api/pycharm+all,python

From 88be6074ac65709bfbb750ab89d893946e9dcf19 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 9 Sep 2021 19:18:25 -0400
Subject: [PATCH 20/48] update

---
 poetry.lock | 24 ++++++++++++------------
 1 file changed, 12 insertions(+), 12 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 75926aa..741f19d 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -710,7 +710,7 @@ python-versions = "*"
 
 [[package]]
 name = "networkx"
-version = "2.6.2"
+version = "2.6.3"
 description = "Python package for creating and manipulating graphs and networks"
 category = "main"
 optional = false
@@ -933,7 +933,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 
 [[package]]
 name = "py-spy"
-version = "0.3.8"
+version = "0.3.9"
 description = "Sampling profiler for Python programs"
 category = "main"
 optional = false
@@ -1993,8 +1993,8 @@ mypy-extensions = [
     {file = "mypy_extensions-0.4.3.tar.gz", hash = "sha256:2d82818f5bb3e369420cb3c4060a7970edba416647068eb4c5343488a6c604a8"},
 ]
 networkx = [
-    {file = "networkx-2.6.2-py3-none-any.whl", hash = "sha256:5fcb7004be69e8fbdf07dcb502efa5c77cadcaad6982164134eeb9721f826c2e"},
-    {file = "networkx-2.6.2.tar.gz", hash = "sha256:2306f1950ce772c5a59a57f5486d59bb9cab98497c45fc49cbc45ac0dec119bb"},
+    {file = "networkx-2.6.3-py3-none-any.whl", hash = "sha256:80b6b89c77d1dfb64a4c7854981b60aeea6360ac02c6d4e4913319e0a313abef"},
+    {file = "networkx-2.6.3.tar.gz", hash = "sha256:c0946ed31d71f1b732b5aaa6da5a0388a345019af232ce2f49c766e2d6795c51"},
 ]
 numpy = [
     {file = "numpy-1.21.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:38e8648f9449a549a7dfe8d8755a5979b45b3538520d1e735637ef28e8c2dc50"},
@@ -2243,14 +2243,14 @@ py = [
     {file = "py-1.10.0.tar.gz", hash = "sha256:21b81bda15b66ef5e1a777a21c4dcd9c20ad3efd0b3f817e7a809035269e1bd3"},
 ]
 py-spy = [
-    {file = "py_spy-0.3.8-py2.py3-none-macosx_10_7_x86_64.whl", hash = "sha256:f13a61fc643fb99bfb3e133d6d92534121ce21a9e5a237da919bd635ad438e5e"},
-    {file = "py_spy-0.3.8-py2.py3-none-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:ee84219d9187f8e6693ff02f3cea975f7edf75440fef3fa060bac4338615e1ed"},
-    {file = "py_spy-0.3.8-py2.py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b085fb41994006c4e29be6605bda5275e23c7cf78993f1fe64203d6811dad77"},
-    {file = "py_spy-0.3.8-py2.py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0503a0189b2030f7bb794e72f4b08b30d99efb5fc42d3d6ed901a21118280c60"},
-    {file = "py_spy-0.3.8-py2.py3-none-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:5ef21e03dfc8d6ae55d3da450daeb8495f96e47ca150a535a7c98de85bfbe290"},
-    {file = "py_spy-0.3.8-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:281afa786bd3a70a8375029f47f34b23aec02d9b06ed9b7cab8741c4e8cb8e32"},
-    {file = "py_spy-0.3.8-py2.py3-none-win_amd64.whl", hash = "sha256:3f55b6ef89b069166b6bd8927cccf0f960d6233875110f1de92159498c7a38c5"},
-    {file = "py_spy-0.3.8.tar.gz", hash = "sha256:eeb8961605e9071a8d501e43f9cd4896bc50efd58a891aa435735fb8d2ba21dd"},
+    {file = "py_spy-0.3.9-py2.py3-none-macosx_10_7_x86_64.whl", hash = "sha256:3c80c50a5b6b25a761c3688f9205330d20e4862152ef65a821349d5993ffe4a0"},
+    {file = "py_spy-0.3.9-py2.py3-none-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:c39178711e83e921aa15c61ebd37fbcd205cce8250c6844bfa3ce493ec09ff49"},
+    {file = "py_spy-0.3.9-py2.py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a43be414930cae73672d89d2c57c45fffa0d68a2c259047c50eab174f635528f"},
+    {file = "py_spy-0.3.9-py2.py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1f76f97029f8839306d8a38e10319b8695d1ed4fa693396341b3ba9a9b4c8ff6"},
+    {file = "py_spy-0.3.9-py2.py3-none-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3df9b490c40882ce9291037997496c281b3f0c6f50c5f0b9b0a159ba0f5ad43c"},
+    {file = "py_spy-0.3.9-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:8105e691eca41849e7940db49b340697a117f4b7a091fc248cf7d13be2bbc7d2"},
+    {file = "py_spy-0.3.9-py2.py3-none-win_amd64.whl", hash = "sha256:31e556317501dbf70ef14cb180f652905e7776228b79ba2c642f5deb5e826cf5"},
+    {file = "py_spy-0.3.9.tar.gz", hash = "sha256:127148a0de9264c9e036509c1596ca7402438bf7906c16a082e335af7a0d4261"},
 ]
 pyasn1 = [
     {file = "pyasn1-0.4.8-py2.4.egg", hash = "sha256:fec3e9d8e36808a28efb59b489e4528c10ad0f480e57dcc32b4de5c9d8c9fdf3"},

From 39448055bb9d188046c837d771d8869f92d5c283 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 9 Sep 2021 19:18:51 -0400
Subject: [PATCH 21/48] outdated requirements.txt

---
 requirements.txt | 3 ---
 1 file changed, 3 deletions(-)
 delete mode 100644 requirements.txt

diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index bc53cb7..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,3 +0,0 @@
-ray[default,tune,rllib]>=1.4.1
-minerl-wrappers>=0.1.3
-scikit-learn>=0.24.2
\ No newline at end of file

From f3509b7e8b589756b6d0c0d3a762cd3e7cac2153 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 9 Sep 2021 20:05:21 -0400
Subject: [PATCH 22/48] fix build system

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 4498847..9bd62e9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -26,5 +26,5 @@ pytest = "^6.2.4"
 black = "^21.7b0"
 
 [build-system]
-requires = ["poetry-core=1.1.8"]
+requires = ["poetry-core>=1.0.0"]
 build-backend = "poetry.core.masonry.api"

From c6a4d77eed98e23aebc1590ed69704b7ea2b2300 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Sat, 11 Sep 2021 23:02:21 -0400
Subject: [PATCH 23/48] update dependencies

---
 poetry.lock    | 25 ++++++++++++-------------
 pyproject.toml | 20 +++++++++++++-------
 2 files changed, 25 insertions(+), 20 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 741f19d..fe84076 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -245,7 +245,7 @@ test = ["psutil"]
 
 [[package]]
 name = "decorator"
-version = "5.0.9"
+version = "5.1.0"
 description = "Decorators for Humans"
 category = "main"
 optional = false
@@ -635,7 +635,7 @@ traitlets = "*"
 
 [[package]]
 name = "minerl"
-version = "0.4.1a2"
+version = "0.4.2"
 description = "MineRL environment and data loader for reinforcement learning from human demonstration in Minecraft"
 category = "main"
 optional = false
@@ -671,7 +671,7 @@ docs = ["sphinx-rtd-theme", "sphinxcontrib-napoleon"]
 
 [[package]]
 name = "minerl-wrappers"
-version = "0.1.4"
+version = "0.1.5"
 description = "minerl-wrappers compiles common wrappers and standardizes code for reproducibility in the MineRL environment!"
 category = "main"
 optional = false
@@ -679,7 +679,7 @@ python-versions = ">=3.7,<4.0"
 
 [package.dependencies]
 gym = ">=0.19.0,<0.20.0"
-minerl = "0.4.1a2"
+minerl = "0.4.2"
 numpy = ">=1.21.0,<2.0.0"
 opencv-python = ">=4.5.3,<5.0.0"
 PyYAML = ">=5.4.1,<6.0.0"
@@ -1103,8 +1103,7 @@ tabulate = {version = "*", optional = true, markers = "extra == \"rllib\""}
 tensorboardX = {version = ">=1.9", optional = true, markers = "extra == \"rllib\""}
 
 [package.extras]
-all = ["opentelemetry-exporter-otlp (==1.1.0)", "kubernetes", "lz4", "scikit-image", "aioredis (<2)", "prometheus-client (>=0.7.1)", "aiohttp-cors", "opentelemetry-api (==1.1.0)", "uvicorn", "tabulate", "pandas", "py-spy (>=0.2.0)", "starlette", "fastapi", "opencensus", "dm-tree", "scipy", "urllib3", "tensorboardX (>=1.9)", "colorful", "ray-cpp (==2.0.0.dev0)", "kopf", "aiohttp", "pyyaml", "jsonschema", "matplotlib (!=3.4.3)", "gym", "requests", "gpustat", "opentelemetry-sdk (==1.1.0)"]
-cpp = ["ray-cpp (==2.0.0.dev0)"]
+all = ["aioredis (<2)", "starlette", "opencensus", "scikit-image", "prometheus-client (>=0.7.1)", "aiohttp-cors", "tabulate", "tensorboardX (>=1.9)", "jsonschema", "scipy", "uvicorn", "kubernetes", "requests", "gym", "gpustat", "aiohttp", "urllib3", "dm-tree", "py-spy (>=0.2.0)", "pandas", "opentelemetry-api (==1.1.0)", "kopf", "matplotlib (!=3.4.3)", "opentelemetry-sdk (==1.1.0)", "fastapi", "colorful", "pyyaml", "opentelemetry-exporter-otlp (==1.1.0)", "lz4"]
 default = ["aiohttp", "aiohttp-cors", "aioredis (<2)", "colorful", "py-spy (>=0.2.0)", "jsonschema", "requests", "gpustat", "opencensus", "prometheus-client (>=0.7.1)"]
 k8s = ["kubernetes", "urllib3", "kopf"]
 observability = ["opentelemetry-api (==1.1.0)", "opentelemetry-sdk (==1.1.0)", "opentelemetry-exporter-otlp (==1.1.0)"]
@@ -1114,7 +1113,7 @@ tune = ["pandas", "tabulate", "tensorboardX (>=1.9)", "requests"]
 
 [package.source]
 type = "url"
-url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl"
+url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl"
 [[package]]
 name = "redis"
 version = "3.5.3"
@@ -1411,7 +1410,7 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytes
 [metadata]
 lock-version = "1.1"
 python-versions = "^3.7.1"
-content-hash = "77e59ba63c88b601e79bddfd9d9675b77367f6acbff2db6e199ab2815dbd6065"
+content-hash = "8496b7df4a4b60a43fe04bd4f68ea41be7abdb16c4cf05c9766acafc37e5ff31"
 
 [metadata.files]
 aiohttp = [
@@ -1539,8 +1538,8 @@ daemoniker = [
     {file = "daemoniker-0.2.3.tar.gz", hash = "sha256:d9b62c8d75227b3da88c0ca22b82e19d88d32dade4ffa838427235e0cdd5e578"},
 ]
 decorator = [
-    {file = "decorator-5.0.9-py3-none-any.whl", hash = "sha256:6e5c199c16f7a9f0e3a61a4a54b3d27e7dad0dbdde92b944426cb20914376323"},
-    {file = "decorator-5.0.9.tar.gz", hash = "sha256:72ecfba4320a893c53f9706bebb2d55c270c1e51a28789361aa93e4a21319ed5"},
+    {file = "decorator-5.1.0-py3-none-any.whl", hash = "sha256:7b12e7c3c6ab203a29e157335e9122cb03de9ab7264b137594103fd4a683b374"},
+    {file = "decorator-5.1.0.tar.gz", hash = "sha256:e59913af105b9860aa2c8d3272d9de5a56a4e608db9a2f167a8480b323d529a7"},
 ]
 dill = [
     {file = "dill-0.3.4-py2.py3-none-any.whl", hash = "sha256:7e40e4a70304fd9ceab3535d36e58791d9c4a776b38ec7f7ec9afc8d3dca4d4f"},
@@ -1913,11 +1912,11 @@ matplotlib-inline = [
     {file = "matplotlib_inline-0.1.3-py3-none-any.whl", hash = "sha256:aed605ba3b72462d64d475a21a9296f400a19c4f74a31b59103d2a99ffd5aa5c"},
 ]
 minerl = [
-    {file = "minerl-0.4.1a2.tar.gz", hash = "sha256:ddeff068c75d586d9b36cd839a611feabff594d9549d93c8bbdfad3bb5d1dd53"},
+    {file = "minerl-0.4.2.tar.gz", hash = "sha256:653d2fe1079e003736dccee09fd957570e238dce1ac411ffa3e2d342bafa4006"},
 ]
 minerl-wrappers = [
-    {file = "minerl-wrappers-0.1.4.tar.gz", hash = "sha256:e005ce75fcfe5fd345384635e692050848ffafe5a6b7e10e43073238c6522060"},
-    {file = "minerl_wrappers-0.1.4-py3-none-any.whl", hash = "sha256:7675201bb81347c94b67659dbd05f496b167a15ed6e7035953bbd5f641fcd7cf"},
+    {file = "minerl-wrappers-0.1.5.tar.gz", hash = "sha256:1ce39c8849061a244d98815fe6c4ff36d13cfa1782344d78601bb75d3ea23cec"},
+    {file = "minerl_wrappers-0.1.5-py3-none-any.whl", hash = "sha256:15246bbf96ba0f37188dd8c83c2810141ee5b178637b6b3716efc72c61d74598"},
 ]
 msgpack = [
     {file = "msgpack-1.0.2-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:b6d9e2dae081aa35c44af9c4298de4ee72991305503442a5c74656d82b581fe9"},
diff --git a/pyproject.toml b/pyproject.toml
index 9bd62e9..3352bbb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -12,14 +12,14 @@ repository = "https://github.com/juliusfrost/minerl-rllib/"
 python = "^3.7.1"
 scikit-learn = "^0.24.2"
 ray = [
-    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.9' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl"},
-    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.8' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"},
-    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.7' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"},
-    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.9' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp39-cp39-win_amd64.whl"},
-    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.8' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp38-cp38-win_amd64.whl"},
-    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.7' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/cd22a7d1bbf38f66aa8b735459319ff24f102a20/ray-2.0.0.dev0-cp37-cp37m-win_amd64.whl"}
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.9' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl"},
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.8' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"},
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.7' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"},
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.9' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp39-cp39-win_amd64.whl"},
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.8' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp38-cp38-win_amd64.whl"},
+    {extras = ["default", "tune", "rllib"], markers = "python_version == '3.7' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp37-cp37m-win_amd64.whl"}
 ]
-minerl-wrappers = "^0.1.4"
+minerl-wrappers = "^0.1.5"
 
 [tool.poetry.dev-dependencies]
 pytest = "^6.2.4"
@@ -28,3 +28,9 @@ black = "^21.7b0"
 [build-system]
 requires = ["poetry-core>=1.0.0"]
 build-backend = "poetry.core.masonry.api"
+
+[tool.pytest.ini_options]
+log_cli = true
+log_cli_level = "DEBUG"
+log_cli_format = "%(asctime)s [%(levelname)8s] %(message)s (%(filename)s:%(lineno)s)"
+log_cli_date_format = "%Y-%m-%d %H:%M:%S"

From 67f1f22c36ca50d5b7f8ae7055cd35f9e3db4f99 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Mon, 13 Sep 2021 01:46:49 -0400
Subject: [PATCH 24/48] test behavioral cloning

---
 config/bc.yaml | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)
 create mode 100644 config/bc.yaml

diff --git a/config/bc.yaml b/config/bc.yaml
new file mode 100644
index 0000000..15e3d3a
--- /dev/null
+++ b/config/bc.yaml
@@ -0,0 +1,31 @@
+minerl-marwil:
+  run: MARWIL
+  # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
+#  checkpoint_freq: 1
+  checkpoint_at_end: true
+#  keep_checkpoints_num: 1 # keep the best checkpoint around
+#  checkpoint_score_attr: episode_reward_mean
+#  restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
+  local_dir: results # specifies the results folder
+  num_samples: 1 # number of random seeds to try
+  log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
+  config:
+    # minerl-rllib config changes
+    env: MineRLObtainDiamondVectorObf-v0
+    env_config:
+      diamond: true
+    input: minerl
+    input_evaluation: [ ]
+    model:
+      conv_filters: [ [ 64, 4, 4 ], [ 128, 4, 4 ], [ 256, 4, 4 ] ]
+    framework: torch
+    num_gpus: 1
+    log_level: DEBUG
+    # marwil config
+    # In order to evaluate on an actual environment, use these following
+    # settings:
+#    evaluation_num_workers: 1
+#    evaluation_interval: 1
+#    evaluation_config:
+#      input: sampler
+    beta: 0
\ No newline at end of file

From adcec2f8a2bceacac00f31ae622039a96ba8250a Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Mon, 13 Sep 2021 01:47:04 -0400
Subject: [PATCH 25/48] build minerl script

---
 tests/build_minerl.py | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 tests/build_minerl.py

diff --git a/tests/build_minerl.py b/tests/build_minerl.py
new file mode 100644
index 0000000..3b1779f
--- /dev/null
+++ b/tests/build_minerl.py
@@ -0,0 +1,15 @@
+import logging
+
+import gym
+import minerl
+
+
+def main():
+    logging.basicConfig(level=logging.DEBUG)
+    env = gym.make("MineRLNavigateDense-v0")
+    env.reset()
+    env.close()
+
+
+if __name__ == "__main__":
+    main()

From 06d2ba7ffa68b5c597008d872dbd473faf1ec4f7 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Mon, 13 Sep 2021 21:39:45 -0400
Subject: [PATCH 26/48] docker

---
 .dockerignore | 241 ++++++++++++++++++++++++++++++++++++++++++++++++++
 Dockerfile    |  34 +++++++
 2 files changed, 275 insertions(+)
 create mode 100644 .dockerignore
 create mode 100644 Dockerfile

diff --git a/.dockerignore b/.dockerignore
new file mode 100644
index 0000000..5762a63
--- /dev/null
+++ b/.dockerignore
@@ -0,0 +1,241 @@
+# Project Specific
+data/
+logs/
+results/
+
+# Created by https://www.toptal.com/developers/gitignore/api/pycharm+all,python
+# Edit at https://www.toptal.com/developers/gitignore?templates=pycharm+all,python
+
+### PyCharm+all ###
+# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider
+# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
+
+# User-specific stuff
+.idea/**/workspace.xml
+.idea/**/tasks.xml
+.idea/**/usage.statistics.xml
+.idea/**/dictionaries
+.idea/**/shelf
+
+# AWS User-specific
+.idea/**/aws.xml
+
+# Generated files
+.idea/**/contentModel.xml
+
+# Sensitive or high-churn files
+.idea/**/dataSources/
+.idea/**/dataSources.ids
+.idea/**/dataSources.local.xml
+.idea/**/sqlDataSources.xml
+.idea/**/dynamic.xml
+.idea/**/uiDesigner.xml
+.idea/**/dbnavigator.xml
+
+# Gradle
+.idea/**/gradle.xml
+.idea/**/libraries
+
+# Gradle and Maven with auto-import
+# When using Gradle or Maven with auto-import, you should exclude module files,
+# since they will be recreated, and may cause churn.  Uncomment if using
+# auto-import.
+# .idea/artifacts
+# .idea/compiler.xml
+# .idea/jarRepositories.xml
+# .idea/modules.xml
+# .idea/*.iml
+# .idea/modules
+# *.iml
+# *.ipr
+
+# CMake
+cmake-build-*/
+
+# Mongo Explorer plugin
+.idea/**/mongoSettings.xml
+
+# File-based project format
+*.iws
+
+# IntelliJ
+out/
+
+# mpeltonen/sbt-idea plugin
+.idea_modules/
+
+# JIRA plugin
+atlassian-ide-plugin.xml
+
+# Cursive Clojure plugin
+.idea/replstate.xml
+
+# Crashlytics plugin (for Android Studio and IntelliJ)
+com_crashlytics_export_strings.xml
+crashlytics.properties
+crashlytics-build.properties
+fabric.properties
+
+# Editor-based Rest Client
+.idea/httpRequests
+
+# Android studio 3.1+ serialized cache file
+.idea/caches/build_file_checksums.ser
+
+### PyCharm+all Patch ###
+# Ignores the whole .idea folder and all .iml files
+# See https://github.com/joeblau/gitignore.io/issues/186 and https://github.com/joeblau/gitignore.io/issues/360
+
+.idea/
+
+# Reason: https://github.com/joeblau/gitignore.io/issues/186#issuecomment-249601023
+
+*.iml
+modules.xml
+.idea/misc.xml
+*.ipr
+
+# Sonarlint plugin
+.idea/sonarlint
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# End of https://www.toptal.com/developers/gitignore/api/pycharm+all,python
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..a672385
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,34 @@
+FROM pytorch/pytorch:1.9.0-cuda10.2-cudnn7-runtime AS dependencies
+
+ENV POETRY_VERSION=1.1.8 \
+    PYTHONFAULTHANDLER=1 \
+    PYTHONUNBUFFERED=1 \
+    PYTHONHASHSEED=random \
+    PIP_NO_CACHE_DIR=off \
+    PIP_DISABLE_PIP_VERSION_CHECK=on \
+    PIP_DEFAULT_TIMEOUT=100 \
+    MINERL_HEADLESS=1
+
+RUN apt-get update \
+    && apt-get install -y \
+    build-essential \
+    xvfb \
+    x11-xserver-utils \
+    openjdk-8-jdk \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /minerl-rllib
+COPY poetry.lock pyproject.toml /minerl-rllib/
+
+RUN pip install poetry==$POETRY_VERSION
+RUN poetry config virtualenvs.create false \
+  && poetry install --no-interaction --no-ansi
+
+COPY tests/build_minerl.py /minerl-rllib/tests/build_minerl.py
+RUN python /minerl-rllib/tests/build_minerl.py
+
+COPY . /minerl-rllib
+
+FROM dependencies AS train
+#ENTRYPOINT ["python", "minerl_rllib/rllib_train.py"]
+#CMD ["-f bc.yaml"]
\ No newline at end of file

From f5da450508e89c76eeeea939c220c42f90defbec Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Mon, 13 Sep 2021 21:56:58 -0400
Subject: [PATCH 27/48] install development package for training

---
 Dockerfile | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/Dockerfile b/Dockerfile
index a672385..0028d2f 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -30,5 +30,7 @@ RUN python /minerl-rllib/tests/build_minerl.py
 COPY . /minerl-rllib
 
 FROM dependencies AS train
+# Installs the minerl-rllib package
+RUN poetry install --no-interaction --no-ansi
 #ENTRYPOINT ["python", "minerl_rllib/rllib_train.py"]
 #CMD ["-f bc.yaml"]
\ No newline at end of file

From d56ef7d6b879d6d097de74d4d97e357226dd1843 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Mon, 13 Sep 2021 21:59:45 -0400
Subject: [PATCH 28/48] forgot to commit this for input.py

---
 minerl_rllib/envs/utils.py | 84 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 84 insertions(+)
 create mode 100644 minerl_rllib/envs/utils.py

diff --git a/minerl_rllib/envs/utils.py b/minerl_rllib/envs/utils.py
new file mode 100644
index 0000000..a5b2357
--- /dev/null
+++ b/minerl_rllib/envs/utils.py
@@ -0,0 +1,84 @@
+import collections
+import copy
+import os
+
+import gym
+from minerl.data.data_pipeline import DataPipeline, tree_slice
+
+
+def patch_data_pipeline():
+    # copied from the DataPipeline class and removed tqdm
+    def load_data(
+        self,
+        stream_name: str,
+        skip_interval=0,
+        include_metadata=False,
+        include_monitor_data=False,
+    ):
+        """Iterates over an individual trajectory named stream_name.
+
+        Args:
+            stream_name (str): The stream name desired to be iterated through.
+            skip_interval (int, optional): How many sices should be skipped.. Defaults to 0.
+            include_metadata (bool, optional): Whether or not meta data about the loaded trajectory should be included.. Defaults to False.
+            include_monitor_data (bool, optional): Whether to include all of the monitor data from the environment. Defaults to False.
+        Yields:
+            A tuple of (state, player_action, reward_from_action, next_state, is_next_state_terminal).
+            These are tuples are yielded in order of the episode.
+        """
+        if "/" in stream_name:
+            file_dir = stream_name
+        else:
+            file_dir = os.path.join(self.data_dir, stream_name)
+
+        if DataPipeline._is_blacklisted(stream_name):
+            raise RuntimeError(
+                "This stream is corrupted (and will be removed in the next version of the data!)"
+            )
+
+        seq = DataPipeline._load_data_pyfunc(
+            file_dir,
+            -1,
+            None,
+            self.environment,
+            skip_interval=skip_interval,
+            include_metadata=include_metadata,
+        )
+
+        observation_seq, action_seq, reward_seq, next_observation_seq, done_seq = seq[
+            :5
+        ]
+        remainder = iter(seq[5:])
+
+        monitor_seq = next(remainder) if include_monitor_data else None
+        meta = next(remainder) if include_monitor_data else None
+
+        # make a copty
+        gym_spec = gym.envs.registration.spec(self.environment)
+        target_space = copy.deepcopy(self.observation_space)
+
+        x = list(target_space.spaces.items())
+        target_space.spaces = collections.OrderedDict(
+            sorted(x, key=lambda x: x[0] if x[0] != "pov" else "z")
+        )
+
+        # Now we just need to slice the dict.
+        for idx in range(len(reward_seq)):
+            # Wrap in dict
+            action_dict = tree_slice(action_seq, idx)
+            observation_dict = tree_slice(observation_seq, idx)
+            next_observation_dict = tree_slice(next_observation_seq, idx)
+
+            yield_list = [
+                observation_dict,
+                action_dict,
+                reward_seq[idx],
+                next_observation_dict,
+                done_seq[idx],
+            ]
+            yield yield_list + (
+                ([tree_slice(monitor_seq, idx)] if include_monitor_data else [])
+                + ([meta] if include_metadata else [])
+            )
+
+    DataPipeline.load_data = load_data

From f35027a9bf50a86be1c761a1ecaa25f80c6b8728 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Tue, 14 Sep 2021 00:17:53 -0400
Subject: [PATCH 29/48] add sac-offline.yaml

---
 config/sac-offline.yaml | 56 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 56 insertions(+)
 create mode 100644 config/sac-offline.yaml

diff --git a/config/sac-offline.yaml b/config/sac-offline.yaml
new file mode 100644
index 0000000..82140fd
--- /dev/null
+++ b/config/sac-offline.yaml
@@ -0,0 +1,56 @@
+minerl-sac:
+    run: SAC
+    stop:
+      time_total_s: 345600 # 4 days in seconds
+      info/num_steps_sampled: 8000000 # competition sample limit
+    # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
+#    checkpoint_freq: 1
+    checkpoint_at_end: true
+#    keep_checkpoints_num: 1 # keep the best checkpoint around
+#    checkpoint_score_attr: episode_reward_mean
+    # restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
+    local_dir: results # specifies the results folder
+    num_samples: 1 # number of random seeds to try
+    log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
+    config:
+        env: MineRLObtainDiamondVectorObf-v0
+        env_config:
+          diamond: true
+        input: minerl
+        input_evaluation: []
+        evaluation_interval: 10
+        evaluation_config:
+          input: sampler
+#        train_batch_size: 1
+        buffer_size: 50000
+        # SAC Configs
+        framework: torch
+        soft_horizon: False
+        horizon: 1000
+        Q_model:
+          conv_filters: [[64, 4, 4], [128, 4, 4], [256, 4, 4]]
+          fcnet_activation: relu
+          fcnet_hiddens: [ 256, 256, 256 ]
+        policy_model:
+          conv_filters: [[64, 4, 4], [128, 4, 4], [256, 4, 4]]
+          fcnet_activation: relu
+          fcnet_hiddens: [ 256, 256, 256 ]
+        tau: 0.005
+        target_entropy: auto
+        no_done_at_end: false
+        n_step: 1
+        rollout_fragment_length: 1
+        prioritized_replay: false
+        train_batch_size: 256
+        target_network_update_freq: 0
+        timesteps_per_iteration: 1000
+        learning_starts: 10
+        optimization:
+          actor_learning_rate: 0.0001
+          critic_learning_rate: 0.0003
+          entropy_learning_rate: 0.0001
+        num_workers: 0
+        num_gpus: 1
+        clip_actions: false
+        normalize_actions: true
+        metrics_smoothing_episodes: 5
\ No newline at end of file

From 6334bd85bf8363a805050fc517ff303f5d3ce4c0 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Tue, 14 Sep 2021 00:18:49 -0400
Subject: [PATCH 30/48] remove unused

---
 config/minerl-impala-debug.yaml | 39 ---------------------------------
 config/minerl-marwil.yaml       | 39 ---------------------------------
 2 files changed, 78 deletions(-)
 delete mode 100644 config/minerl-impala-debug.yaml
 delete mode 100644 config/minerl-marwil.yaml

diff --git a/config/minerl-impala-debug.yaml b/config/minerl-impala-debug.yaml
deleted file mode 100644
index 65fa622..0000000
--- a/config/minerl-impala-debug.yaml
+++ /dev/null
@@ -1,39 +0,0 @@
-# use this config with $ python rllib_train.py -f config/minerl-impala-debug.yaml
-# see Experiment.spec for valid config options:
-# https://docs.ray.io/en/master/_modules/ray/tune/experiment.html#Experiment
-minerl-impala-debug: # name of the experiment - name of the folder in results
-    run: IMPALA # RL Algorithm
-    env: MineRLRandomDebug-v0 # MineRL Environment
-    stop:
-        time_total_s: 169200 # two days minus one hour in seconds
-        info/num_steps_sampled: 8000000 # competition sample limit
-
-    # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
-    checkpoint_freq: 1
-    checkpoint_at_end: true
-    keep_checkpoints_num: 1 # keep the best checkpoint around
-    checkpoint_score_attr: episode_reward_mean
-    # restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
-
-    local_dir: results # specifies the results folder
-    num_samples: 1 # number of random seeds to try
-    log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
-
-    # config specific to algorithm
-    # see rllib documentation: https://docs.ray.io/en/master/rllib-training.html#common-parameters
-    config:
-        rollout_fragment_length: 50
-        train_batch_size: 500
-        num_workers: 2
-        num_envs_per_worker: 1
-        num_gpus: 0 # set to 0 if cpu
-        clip_rewards: True
-        lr_schedule: [
-            [0, 0.0001],
-            [20000000, 0.000000000001],
-        ]
-
-        framework: torch
-        model:
-            custom_model: minerl_torch_model
-            # custom_model_config: # use this to add any custom model configuration
diff --git a/config/minerl-marwil.yaml b/config/minerl-marwil.yaml
deleted file mode 100644
index 40671d9..0000000
--- a/config/minerl-marwil.yaml
+++ /dev/null
@@ -1,39 +0,0 @@
-# use this config with $ python rllib_train.py -f config/minerl-impala-debug.yaml
-# see Experiment.spec for valid config options:
-# https://docs.ray.io/en/master/_modules/ray/tune/experiment.html#Experiment
-minerl-marwil: # name of the experiment - name of the folder in results
-    run: MARWIL # RL Algorithm
-    env: MineRLObtainDiamondVectorObf-v0 # MineRL Environment
-    stop:
-        time_total_s: 169200 # two days minus one hour in seconds
-        info/num_steps_sampled: 8000000 # competition sample limit
-
-    # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
-    checkpoint_freq: 1
-    checkpoint_at_end: true
-    keep_checkpoints_num: 1 # keep the best checkpoint around
-    checkpoint_score_attr: episode_reward_mean
-    # restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
-
-    local_dir: results # specifies the results folder
-    num_samples: 1 # number of random seeds to try
-    log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
-
-    # config specific to algorithm
-    # see rllib documentation: https://docs.ray.io/en/master/rllib-training.html#common-parameters
-    config:
-        framework: torch
-        model:
-            custom_model: minerl_torch_model
-            # custom_model_config: # use this to add any custom model configuration
-        # input data must be absolute path
-        # input: path_to_json_files
-        # In order to evaluate on an actual environment, use these following
-        # settings:
-#        evaluation_num_workers: 1
-#        evaluation_interval: 1
-#        evaluation_config:
-#            input: sampler
-        # Compare IL (beta=0) vs MARWIL.
-#        beta:
-#            grid_search: [0, 1]
\ No newline at end of file

From 433eb710eb42de38b7c63100f4b415510b85fec2 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Tue, 14 Sep 2021 00:24:00 -0400
Subject: [PATCH 31/48] fix configs

---
 config/bc.yaml          | 19 +++++++++----------
 config/sac-offline.yaml |  5 +++--
 2 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/config/bc.yaml b/config/bc.yaml
index 15e3d3a..6860226 100644
--- a/config/bc.yaml
+++ b/config/bc.yaml
@@ -1,5 +1,9 @@
-minerl-marwil:
-  run: MARWIL
+minerl-bc:
+  run: BC
+  stop:
+    time_total_s: 345600 # 4 days in seconds
+    # no sample limit since using offline rl
+    # info/num_steps_sampled: 8000000 # competition sample limit
   # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
 #  checkpoint_freq: 1
   checkpoint_at_end: true
@@ -16,16 +20,11 @@ minerl-marwil:
       diamond: true
     input: minerl
     input_evaluation: [ ]
+    evaluation_interval: 10
+    evaluation_config:
+      input: sampler
     model:
       conv_filters: [ [ 64, 4, 4 ], [ 128, 4, 4 ], [ 256, 4, 4 ] ]
     framework: torch
     num_gpus: 1
     log_level: DEBUG
-    # marwil config
-    # In order to evaluate on an actual environment, use these following
-    # settings:
-#    evaluation_num_workers: 1
-#    evaluation_interval: 1
-#    evaluation_config:
-#      input: sampler
-    beta: 0
\ No newline at end of file
diff --git a/config/sac-offline.yaml b/config/sac-offline.yaml
index 82140fd..e3c2292 100644
--- a/config/sac-offline.yaml
+++ b/config/sac-offline.yaml
@@ -1,8 +1,9 @@
-minerl-sac:
+minerl-sac-offline:
     run: SAC
     stop:
       time_total_s: 345600 # 4 days in seconds
-      info/num_steps_sampled: 8000000 # competition sample limit
+      # no sample limit since using offline rl
+      # info/num_steps_sampled: 8000000 # competition sample limit
     # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
 #    checkpoint_freq: 1
     checkpoint_at_end: true

From 2132cbce29656a443869b4e214725a62bc0a3afe Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Tue, 14 Sep 2021 21:58:44 -0400
Subject: [PATCH 32/48] add tensorflow

---
 poetry.lock    | 765 +++++++++++++++++++++++++++++++------------------
 pyproject.toml |   6 +-
 2 files changed, 495 insertions(+), 276 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index fe84076..b026df4 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,3 +1,14 @@
+[[package]]
+name = "absl-py"
+version = "0.13.0"
+description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+six = "*"
+
 [[package]]
 name = "aiohttp"
 version = "3.7.4.post0"
@@ -48,6 +59,17 @@ category = "main"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "astunparse"
+version = "1.6.3"
+description = "An AST unparser for Python"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+six = ">=1.6.1,<2.0"
+
 [[package]]
 name = "async-timeout"
 version = "3.0.1"
@@ -86,34 +108,6 @@ category = "main"
 optional = false
 python-versions = "*"
 
-[[package]]
-name = "black"
-version = "21.8b0"
-description = "The uncompromising code formatter."
-category = "dev"
-optional = false
-python-versions = ">=3.6.2"
-
-[package.dependencies]
-click = ">=7.1.2"
-mypy-extensions = ">=0.4.3"
-pathspec = ">=0.9.0,<1"
-platformdirs = ">=2"
-regex = ">=2020.1.8"
-tomli = ">=0.2.6,<2.0.0"
-typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\""}
-typing-extensions = [
-    {version = ">=3.10.0.0", markers = "python_version < \"3.10\""},
-    {version = "!=3.10.0.1", markers = "python_version >= \"3.10\""},
-]
-
-[package.extras]
-colorama = ["colorama (>=0.4.3)"]
-d = ["aiohttp (>=3.6.0)", "aiohttp-cors (>=0.4.0)"]
-jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
-python2 = ["typed-ast (>=1.4.2)"]
-uvloop = ["uvloop (>=0.15.2)"]
-
 [[package]]
 name = "blessings"
 version = "1.7"
@@ -133,6 +127,14 @@ category = "main"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "cached-property"
+version = "1.5.2"
+description = "A decorator for caching properties in classes."
+category = "main"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "cachetools"
 version = "4.2.2"
@@ -159,7 +161,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 
 [[package]]
 name = "charset-normalizer"
-version = "2.0.4"
+version = "2.0.5"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 category = "main"
 optional = false
@@ -168,6 +170,14 @@ python-versions = ">=3.5.0"
 [package.extras]
 unicode_backport = ["unicodedata2"]
 
+[[package]]
+name = "clang"
+version = "5.0"
+description = "libclang python bindings"
+category = "main"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "click"
 version = "8.0.1"
@@ -281,6 +291,22 @@ category = "main"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "flatbuffers"
+version = "1.12"
+description = "The FlatBuffers serialization format for Python"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "gast"
+version = "0.4.0"
+description = "Python AST that abstracts the underlying Python version"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
 [[package]]
 name = "getch"
 version = "1.0"
@@ -330,6 +356,32 @@ aiohttp = ["requests (>=2.20.0,<3.0.0dev)", "aiohttp (>=3.6.2,<4.0.0dev)"]
 pyopenssl = ["pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 
+[[package]]
+name = "google-auth-oauthlib"
+version = "0.4.6"
+description = "Google Authentication Library"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+google-auth = ">=1.0.0"
+requests-oauthlib = ">=0.7.0"
+
+[package.extras]
+tool = ["click (>=6.0.0)"]
+
+[[package]]
+name = "google-pasta"
+version = "0.2.0"
+description = "pasta is an AST-based Python refactoring library"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+six = "*"
+
 [[package]]
 name = "googleapis-common-protos"
 version = "1.53.0"
@@ -397,6 +449,22 @@ nomujoco = ["atari-py (==0.2.6)", "box2d-py (>=2.3.5,<2.4.0)", "opencv-python (>
 robotics = ["mujoco_py (>=1.50,<2.0)", "imageio"]
 toy_text = ["scipy"]
 
+[[package]]
+name = "h5py"
+version = "3.1.0"
+description = "Read and write HDF5 files from Python"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+cached-property = {version = "*", markers = "python_version < \"3.8\""}
+numpy = [
+    {version = ">=1.14.5", markers = "python_version == \"3.7\""},
+    {version = ">=1.17.5", markers = "python_version == \"3.8\""},
+    {version = ">=1.19.3", markers = "python_version >= \"3.9\""},
+]
+
 [[package]]
 name = "hiredis"
 version = "2.0.0"
@@ -563,6 +631,31 @@ six = ">=1.11.0"
 format = ["idna", "jsonpointer (>1.13)", "rfc3987", "strict-rfc3339", "webcolors"]
 format_nongpl = ["idna", "jsonpointer (>1.13)", "webcolors", "rfc3986-validator (>0.1.0)", "rfc3339-validator"]
 
+[[package]]
+name = "keras"
+version = "2.6.0"
+description = "TensorFlow Keras."
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "keras-preprocessing"
+version = "1.1.2"
+description = "Easy data preprocessing and data augmentation for deep learning models"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+numpy = ">=1.9.1"
+six = ">=1.9.0"
+
+[package.extras]
+image = ["scipy (>=0.14)", "Pillow (>=5.2.0)"]
+pep8 = ["flake8"]
+tests = ["pandas", "pillow", "tensorflow", "keras", "pytest", "pytest-xdist", "pytest-cov"]
+
 [[package]]
 name = "kiwisolver"
 version = "1.3.2"
@@ -598,6 +691,20 @@ docs = ["sphinx (>=1.6.0)", "sphinx-bootstrap-theme"]
 flake8 = ["flake8"]
 tests = ["pytest (!=3.3.0)", "psutil", "pytest-cov"]
 
+[[package]]
+name = "markdown"
+version = "3.3.4"
+description = "Python implementation of Markdown."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
+
+[package.extras]
+testing = ["coverage", "pyyaml"]
+
 [[package]]
 name = "markupsafe"
 version = "2.0.1"
@@ -671,18 +778,18 @@ docs = ["sphinx-rtd-theme", "sphinxcontrib-napoleon"]
 
 [[package]]
 name = "minerl-wrappers"
-version = "0.1.5"
+version = "0.1.6"
 description = "minerl-wrappers compiles common wrappers and standardizes code for reproducibility in the MineRL environment!"
 category = "main"
 optional = false
 python-versions = ">=3.7,<4.0"
 
 [package.dependencies]
-gym = ">=0.19.0,<0.20.0"
-minerl = "0.4.2"
-numpy = ">=1.21.0,<2.0.0"
-opencv-python = ">=4.5.3,<5.0.0"
-PyYAML = ">=5.4.1,<6.0.0"
+gym = "*"
+minerl = ">=0.4.0,<0.5.0"
+numpy = "*"
+opencv-python = "*"
+PyYAML = "*"
 
 [[package]]
 name = "msgpack"
@@ -700,14 +807,6 @@ category = "main"
 optional = false
 python-versions = ">=3.6"
 
-[[package]]
-name = "mypy-extensions"
-version = "0.4.3"
-description = "Experimental type system extensions for programs checked with the mypy typechecker."
-category = "dev"
-optional = false
-python-versions = "*"
-
 [[package]]
 name = "networkx"
 version = "2.6.3"
@@ -725,11 +824,11 @@ test = ["pytest (>=6.2)", "pytest-cov (>=2.12)", "codecov (>=2.1)"]
 
 [[package]]
 name = "numpy"
-version = "1.21.1"
+version = "1.19.5"
 description = "NumPy is the fundamental package for array computing with Python."
 category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.6"
 
 [[package]]
 name = "nvidia-ml-py3"
@@ -739,6 +838,19 @@ category = "main"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "oauthlib"
+version = "3.1.1"
+description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.extras]
+rsa = ["cryptography (>=3.0.0,<4)"]
+signals = ["blinker (>=1.4.0)"]
+signedtoken = ["cryptography (>=3.0.0,<4)", "pyjwt (>=2.0.0,<3)"]
+
 [[package]]
 name = "opencensus"
 version = "0.7.13"
@@ -761,14 +873,29 @@ python-versions = "*"
 
 [[package]]
 name = "opencv-python"
-version = "4.5.3.56"
+version = "4.5.2.54"
 description = "Wrapper package for OpenCV python bindings."
 category = "main"
 optional = false
 python-versions = ">=3.6"
 
 [package.dependencies]
-numpy = ">=1.21.0"
+numpy = ">=1.13.3"
+
+[[package]]
+name = "opt-einsum"
+version = "3.3.0"
+description = "Optimizing numpys einsum function"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[package.dependencies]
+numpy = ">=1.7"
+
+[package.extras]
+docs = ["sphinx (==1.2.3)", "sphinxcontrib-napoleon", "sphinx-rtd-theme", "numpydoc"]
+tests = ["pytest", "pytest-cov", "pytest-pep8"]
 
 [[package]]
 name = "packaging"
@@ -783,7 +910,7 @@ pyparsing = ">=2.0.2"
 
 [[package]]
 name = "pandas"
-version = "1.3.2"
+version = "1.3.3"
 description = "Powerful data structures for data analysis, time series, and statistics"
 category = "main"
 optional = false
@@ -809,14 +936,6 @@ python-versions = ">=3.6"
 qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
 testing = ["docopt", "pytest (<6.0.0)"]
 
-[[package]]
-name = "pathspec"
-version = "0.9.0"
-description = "Utility library for gitignore style pattern matching of file paths."
-category = "dev"
-optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
-
 [[package]]
 name = "pexpect"
 version = "4.8.0"
@@ -844,18 +963,6 @@ category = "main"
 optional = false
 python-versions = ">=3.6"
 
-[[package]]
-name = "platformdirs"
-version = "2.3.0"
-description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
-category = "dev"
-optional = false
-python-versions = ">=3.6"
-
-[package.extras]
-docs = ["Sphinx (>=4)", "furo (>=2021.7.5b38)", "proselint (>=0.10.2)", "sphinx-autodoc-typehints (>=1.12)"]
-test = ["appdirs (==1.4.4)", "pytest (>=6)", "pytest-cov (>=2.7)", "pytest-mock (>=3.6)"]
-
 [[package]]
 name = "pluggy"
 version = "1.0.0"
@@ -984,7 +1091,7 @@ python-versions = "*"
 
 [[package]]
 name = "pyro4"
-version = "4.80"
+version = "4.81"
 description = "distributed object middleware for Python (RPC)"
 category = "main"
 optional = false
@@ -1114,6 +1221,7 @@ tune = ["pandas", "tabulate", "tensorboardX (>=1.9)", "requests"]
 [package.source]
 type = "url"
 url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl"
+
 [[package]]
 name = "redis"
 version = "3.5.3"
@@ -1125,14 +1233,6 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 [package.extras]
 hiredis = ["hiredis (>=0.1.3)"]
 
-[[package]]
-name = "regex"
-version = "2021.8.28"
-description = "Alternative regular expression module, to replace re."
-category = "dev"
-optional = false
-python-versions = "*"
-
 [[package]]
 name = "requests"
 version = "2.26.0"
@@ -1151,6 +1251,21 @@ urllib3 = ">=1.21.1,<1.27"
 socks = ["PySocks (>=1.5.6,!=1.5.7)", "win-inet-pton"]
 use_chardet_on_py3 = ["chardet (>=3.0.2,<5)"]
 
+[[package]]
+name = "requests-oauthlib"
+version = "1.3.0"
+description = "OAuthlib authentication support for Requests."
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[package.dependencies]
+oauthlib = ">=3.0.0"
+requests = ">=2.0.0"
+
+[package.extras]
+rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
+
 [[package]]
 name = "rsa"
 version = "4.7.2"
@@ -1235,7 +1350,7 @@ python-versions = "~=3.5"
 
 [[package]]
 name = "six"
-version = "1.16.0"
+version = "1.15.0"
 description = "Python 2 and 3 compatibility utilities"
 category = "main"
 optional = false
@@ -1252,6 +1367,43 @@ python-versions = "*"
 [package.extras]
 widechars = ["wcwidth"]
 
+[[package]]
+name = "tensorboard"
+version = "2.6.0"
+description = "TensorBoard lets you watch Tensors Flow"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+absl-py = ">=0.4"
+google-auth = ">=1.6.3,<2"
+google-auth-oauthlib = ">=0.4.1,<0.5"
+grpcio = ">=1.24.3"
+markdown = ">=2.6.8"
+numpy = ">=1.12.0"
+protobuf = ">=3.6.0"
+requests = ">=2.21.0,<3"
+tensorboard-data-server = ">=0.6.0,<0.7.0"
+tensorboard-plugin-wit = ">=1.6.0"
+werkzeug = ">=0.11.15"
+
+[[package]]
+name = "tensorboard-data-server"
+version = "0.6.1"
+description = "Fast data loading for TensorBoard"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "tensorboard-plugin-wit"
+version = "1.8.0"
+description = "What-If Tool TensorBoard plugin."
+category = "main"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "tensorboardx"
 version = "2.4"
@@ -1264,6 +1416,51 @@ python-versions = "*"
 numpy = "*"
 protobuf = ">=3.8.0"
 
+[[package]]
+name = "tensorflow"
+version = "2.6.0"
+description = "TensorFlow is an open source machine learning framework for everyone."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+absl-py = ">=0.10,<1.0"
+astunparse = ">=1.6.3,<1.7.0"
+clang = ">=5.0,<6.0"
+flatbuffers = ">=1.12.0,<1.13.0"
+gast = "0.4.0"
+google-pasta = ">=0.2,<1.0"
+grpcio = ">=1.37.0,<2.0"
+h5py = ">=3.1.0,<3.2.0"
+keras = ">=2.6,<3.0"
+keras-preprocessing = ">=1.1.2,<1.2.0"
+numpy = ">=1.19.2,<1.20.0"
+opt-einsum = ">=3.3.0,<3.4.0"
+protobuf = ">=3.9.2"
+six = ">=1.15.0,<1.16.0"
+tensorboard = ">=2.6,<3.0"
+tensorflow-estimator = ">=2.6,<3.0"
+termcolor = ">=1.1.0,<1.2.0"
+typing-extensions = ">=3.7.4,<3.8.0"
+wrapt = ">=1.12.1,<1.13.0"
+
+[[package]]
+name = "tensorflow-estimator"
+version = "2.6.0"
+description = "TensorFlow Estimator."
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "termcolor"
+version = "1.1.0"
+description = "ANSII Color formatting for output in terminal."
+category = "main"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "threadpoolctl"
 version = "2.2.0"
@@ -1294,14 +1491,6 @@ category = "main"
 optional = false
 python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 
-[[package]]
-name = "tomli"
-version = "1.2.1"
-description = "A lil' TOML parser"
-category = "dev"
-optional = false
-python-versions = ">=3.6"
-
 [[package]]
 name = "tqdm"
 version = "4.62.2"
@@ -1329,14 +1518,6 @@ python-versions = ">=3.7"
 [package.extras]
 test = ["pytest"]
 
-[[package]]
-name = "typed-ast"
-version = "1.4.3"
-description = "a fork of Python 2 and 3 ast modules with type comment support"
-category = "dev"
-optional = false
-python-versions = "*"
-
 [[package]]
 name = "typing"
 version = "3.7.4.3"
@@ -1347,7 +1528,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 
 [[package]]
 name = "typing-extensions"
-version = "3.10.0.2"
+version = "3.7.4.3"
 description = "Backported and Experimental Type Hints for Python 3.5+"
 category = "main"
 optional = false
@@ -1374,6 +1555,25 @@ category = "main"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "werkzeug"
+version = "2.0.1"
+description = "The comprehensive WSGI web application library."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.extras]
+watchdog = ["watchdog"]
+
+[[package]]
+name = "wrapt"
+version = "1.12.1"
+description = "Module for decorators, wrappers and monkey patching."
+category = "main"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "xmltodict"
 version = "0.12.0"
@@ -1410,9 +1610,13 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytes
 [metadata]
 lock-version = "1.1"
 python-versions = "^3.7.1"
-content-hash = "8496b7df4a4b60a43fe04bd4f68ea41be7abdb16c4cf05c9766acafc37e5ff31"
+content-hash = "b4bfc03df2ceba2e70e0cdbefd9255fd28a85e8c2a630936c92f49f178e2805c"
 
 [metadata.files]
+absl-py = [
+    {file = "absl-py-0.13.0.tar.gz", hash = "sha256:6953272383486044699fd0e9f00aad167a27e08ce19aae66c6c4b10e7e767793"},
+    {file = "absl_py-0.13.0-py3-none-any.whl", hash = "sha256:62bd4e248ddb19d81aec8f9446b407ff37c8175c2ba88266a7afa9b4ce4a333b"},
+]
 aiohttp = [
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@@ -1464,6 +1668,10 @@ appnope = [
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     {file = "appnope-0.1.2.tar.gz", hash = "sha256:dd83cd4b5b460958838f6eb3000c660b1f9caf2a5b1de4264e941512f603258a"},
 ]
+astunparse = [
+    {file = "astunparse-1.6.3-py2.py3-none-any.whl", hash = "sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8"},
+    {file = "astunparse-1.6.3.tar.gz", hash = "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872"},
+]
 async-timeout = [
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@@ -1480,10 +1688,6 @@ backcall = [
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 ]
-black = [
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-    {file = "black-21.8b0.tar.gz", hash = "sha256:570608d28aa3af1792b98c4a337dbac6367877b47b12b88ab42095cfc1a627c2"},
-]
 blessings = [
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@@ -1493,6 +1697,10 @@ bullet = [
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     {file = "bullet-2.2.0.tar.gz", hash = "sha256:dfa0fa81810ad1a9e688815ca04f24af87ff5cdbe803b42fa634b1f50fc9d887"},
 ]
+cached-property = [
+    {file = "cached-property-1.5.2.tar.gz", hash = "sha256:9fa5755838eecbb2d234c3aa390bd80fbd3ac6b6869109bfc1b499f7bd89a130"},
+    {file = "cached_property-1.5.2-py2.py3-none-any.whl", hash = "sha256:df4f613cf7ad9a588cc381aaf4a512d26265ecebd5eb9e1ba12f1319eb85a6a0"},
+]
 cachetools = [
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@@ -1506,8 +1714,12 @@ chardet = [
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 ]
 charset-normalizer = [
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-    {file = "charset_normalizer-2.0.4-py3-none-any.whl", hash = "sha256:0c8911edd15d19223366a194a513099a302055a962bca2cec0f54b8b63175d8b"},
+    {file = "charset-normalizer-2.0.5.tar.gz", hash = "sha256:7098e7e862f6370a2a8d1a6398cd359815c45d12626267652c3f13dec58e2367"},
+    {file = "charset_normalizer-2.0.5-py3-none-any.whl", hash = "sha256:fa471a601dfea0f492e4f4fca035cd82155e65dc45c9b83bf4322dfab63755dd"},
+]
+clang = [
+    {file = "clang-5.0-py2-none-any.whl", hash = "sha256:b9301dff507041b5019b30ae710b78b0552c1ca1d4441b8dfa93c2e85078a5f8"},
+    {file = "clang-5.0.tar.gz", hash = "sha256:ceccae97eda0225a5b44d42ffd61102e248325c2865ca53e4407746464a5333a"},
 ]
 click = [
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@@ -1568,6 +1780,14 @@ filelock = [
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     {file = "filelock-3.0.12.tar.gz", hash = "sha256:18d82244ee114f543149c66a6e0c14e9c4f8a1044b5cdaadd0f82159d6a6ff59"},
 ]
+flatbuffers = [
+    {file = "flatbuffers-1.12-py2.py3-none-any.whl", hash = "sha256:9e9ef47fa92625c4721036e7c4124182668dc6021d9e7c73704edd395648deb9"},
+    {file = "flatbuffers-1.12.tar.gz", hash = "sha256:63bb9a722d5e373701913e226135b28a6f6ac200d5cc7b4d919fa38d73b44610"},
+]
+gast = [
+    {file = "gast-0.4.0-py3-none-any.whl", hash = "sha256:b7adcdd5adbebf1adf17378da5ba3f543684dbec47b1cda1f3997e573cd542c4"},
+    {file = "gast-0.4.0.tar.gz", hash = "sha256:40feb7b8b8434785585ab224d1568b857edb18297e5a3047f1ba012bc83b42c1"},
+]
 getch = [
     {file = "getch-1.0-python2.tar.gz", hash = "sha256:be451438f7a2b389f96753aea39b6ed2540a390f1b9a12badcbc110cf9a5ce7f"},
     {file = "getch-1.0.tar.gz", hash = "sha256:a6c22717c10051ce65b8fb7bddb171af705b1175e694a73be956990f6089d8b1"},
@@ -1580,6 +1800,15 @@ google-auth = [
     {file = "google-auth-1.35.0.tar.gz", hash = "sha256:b7033be9028c188ee30200b204ea00ed82ea1162e8ac1df4aa6ded19a191d88e"},
     {file = "google_auth-1.35.0-py2.py3-none-any.whl", hash = "sha256:997516b42ecb5b63e8d80f5632c1a61dddf41d2a4c2748057837e06e00014258"},
 ]
+google-auth-oauthlib = [
+    {file = "google-auth-oauthlib-0.4.6.tar.gz", hash = "sha256:a90a072f6993f2c327067bf65270046384cda5a8ecb20b94ea9a687f1f233a7a"},
+    {file = "google_auth_oauthlib-0.4.6-py2.py3-none-any.whl", hash = "sha256:3f2a6e802eebbb6fb736a370fbf3b055edcb6b52878bf2f26330b5e041316c73"},
+]
+google-pasta = [
+    {file = "google-pasta-0.2.0.tar.gz", hash = "sha256:c9f2c8dfc8f96d0d5808299920721be30c9eec37f2389f28904f454565c8a16e"},
+    {file = "google_pasta-0.2.0-py2-none-any.whl", hash = "sha256:4612951da876b1a10fe3960d7226f0c7682cf901e16ac06e473b267a5afa8954"},
+    {file = "google_pasta-0.2.0-py3-none-any.whl", hash = "sha256:b32482794a366b5366a32c92a9a9201b107821889935a02b3e51f6b432ea84ed"},
+]
 googleapis-common-protos = [
     {file = "googleapis-common-protos-1.53.0.tar.gz", hash = "sha256:a88ee8903aa0a81f6c3cec2d5cf62d3c8aa67c06439b0496b49048fb1854ebf4"},
     {file = "googleapis_common_protos-1.53.0-py2.py3-none-any.whl", hash = "sha256:f6d561ab8fb16b30020b940e2dd01cd80082f4762fa9f3ee670f4419b4b8dbd0"},
@@ -1636,6 +1865,21 @@ grpcio = [
 gym = [
     {file = "gym-0.19.0.tar.gz", hash = "sha256:940069b983806e1ccc400fa6d47b4e34e462accf6a4fb0acb0a5e509ad0f502d"},
 ]
+h5py = [
+    {file = "h5py-3.1.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:1cd367f89a5441236bdbb795e9fb9a9e3424929c00b4a54254ca760437f83d69"},
+    {file = "h5py-3.1.0-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:fea05349f63625a8fb808e57e42bb4c76930cf5d50ac58b678c52f913a48a89b"},
+    {file = "h5py-3.1.0-cp36-cp36m-win_amd64.whl", hash = "sha256:2e37352ddfcf9d77a2a47f7c8f7e125c6d20cc06c2995edeb7be222d4e152636"},
+    {file = "h5py-3.1.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:e33f61d3eb862614c0f273a1f993a64dc2f093e1a3094932c50ada9d2db2170f"},
+    {file = "h5py-3.1.0-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:236ac8d943be30b617ab615c3d4a4bf4a438add2be87e54af3687ab721a18fac"},
+    {file = "h5py-3.1.0-cp37-cp37m-win_amd64.whl", hash = "sha256:02c391fdb980762a1cc03a4bcaecd03dc463994a9a63a02264830114a96e111f"},
+    {file = "h5py-3.1.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:f89a3dae38843ffa49d17a31a3509a8129e9b46ece602a0138e1ed79e685c361"},
+    {file = "h5py-3.1.0-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:ba71f6229d2013fbb606476ecc29c6223fc16b244d35fcd8566ad9dbaf910857"},
+    {file = "h5py-3.1.0-cp38-cp38-win_amd64.whl", hash = "sha256:dccb89358bc84abcd711363c3e138f9f4eccfdf866f2139a8e72308328765b2c"},
+    {file = "h5py-3.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:cb74df83709d6d03d11e60b9480812f58da34f194beafa8c8314dbbeeedfe0a6"},
+    {file = "h5py-3.1.0-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:80c623be10479e81b64fa713b7ed4c0bbe9f02e8e7d2a2e5382336087b615ce4"},
+    {file = "h5py-3.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:1cdfd1c5449ca1329d152f0b66830e93226ebce4f5e07dd8dc16bfc2b1a49d7b"},
+    {file = "h5py-3.1.0.tar.gz", hash = "sha256:1e2516f190652beedcb8c7acfa1c6fa92d99b42331cbef5e5c7ec2d65b0fc3c2"},
+]
 hiredis = [
     {file = "hiredis-2.0.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:b4c8b0bc5841e578d5fb32a16e0c305359b987b850a06964bd5a62739d688048"},
     {file = "hiredis-2.0.0-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:0adea425b764a08270820531ec2218d0508f8ae15a448568109ffcae050fee26"},
@@ -1723,6 +1967,13 @@ jsonschema = [
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     {file = "jsonschema-3.2.0.tar.gz", hash = "sha256:c8a85b28d377cc7737e46e2d9f2b4f44ee3c0e1deac6bf46ddefc7187d30797a"},
 ]
+keras = [
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+]
+keras-preprocessing = [
+    {file = "Keras_Preprocessing-1.1.2-py2.py3-none-any.whl", hash = "sha256:7b82029b130ff61cc99b55f3bd27427df4838576838c5b2f65940e4fcec99a7b"},
+    {file = "Keras_Preprocessing-1.1.2.tar.gz", hash = "sha256:add82567c50c8bc648c14195bf544a5ce7c1f76761536956c3d2978970179ef3"},
+]
 kiwisolver = [
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@@ -1850,6 +2101,10 @@ lz4 = [
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     {file = "lz4-3.1.3.tar.gz", hash = "sha256:081ef0a3b5941cb03127f314229a1c78bd70c9c220bb3f4dd80033e707feaa18"},
 ]
+markdown = [
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+    {file = "Markdown-3.3.4.tar.gz", hash = "sha256:31b5b491868dcc87d6c24b7e3d19a0d730d59d3e46f4eea6430a321bed387a49"},
+]
 markupsafe = [
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@@ -1915,8 +2170,8 @@ minerl = [
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 ]
 minerl-wrappers = [
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+    {file = "minerl-wrappers-0.1.6.tar.gz", hash = "sha256:87fba6e3c0a3e83851e66f953c9c11a0d4796fbd3e0e9379fdb064f98299b84a"},
+    {file = "minerl_wrappers-0.1.6-py3-none-any.whl", hash = "sha256:4c17bda1c43a375e4208ea81e645e15dad3c2d4266db25e044e89523268a387d"},
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 msgpack = [
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@@ -1987,47 +2242,53 @@ multidict = [
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 ]
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 ]
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-    {file = "typed_ast-1.4.3-cp38-cp38-win32.whl", hash = "sha256:f2362f3cb0f3172c42938946dbc5b7843c2a28aec307c49100c8b38764eb6927"},
-    {file = "typed_ast-1.4.3-cp38-cp38-win_amd64.whl", hash = "sha256:dd4a21253f42b8d2b48410cb31fe501d32f8b9fbeb1f55063ad102fe9c425e40"},
-    {file = "typed_ast-1.4.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f328adcfebed9f11301eaedfa48e15bdece9b519fb27e6a8c01aa52a17ec31b3"},
-    {file = "typed_ast-1.4.3-cp39-cp39-manylinux1_i686.whl", hash = "sha256:2c726c276d09fc5c414693a2de063f521052d9ea7c240ce553316f70656c84d4"},
-    {file = "typed_ast-1.4.3-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:cae53c389825d3b46fb37538441f75d6aecc4174f615d048321b716df2757fb0"},
-    {file = "typed_ast-1.4.3-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:b9574c6f03f685070d859e75c7f9eeca02d6933273b5e69572e5ff9d5e3931c3"},
-    {file = "typed_ast-1.4.3-cp39-cp39-win32.whl", hash = "sha256:209596a4ec71d990d71d5e0d312ac935d86930e6eecff6ccc7007fe54d703808"},
-    {file = "typed_ast-1.4.3-cp39-cp39-win_amd64.whl", hash = "sha256:9c6d1a54552b5330bc657b7ef0eae25d00ba7ffe85d9ea8ae6540d2197a3788c"},
-    {file = "typed_ast-1.4.3.tar.gz", hash = "sha256:fb1bbeac803adea29cedd70781399c99138358c26d05fcbd23c13016b7f5ec65"},
-]
 typing = [
     {file = "typing-3.7.4.3-py2-none-any.whl", hash = "sha256:283d868f5071ab9ad873e5e52268d611e851c870a2ba354193026f2dfb29d8b5"},
     {file = "typing-3.7.4.3.tar.gz", hash = "sha256:1187fb9c82fd670d10aa07bbb6cfcfe4bdda42d6fab8d5134f04e8c4d0b71cc9"},
 ]
 typing-extensions = [
-    {file = "typing_extensions-3.10.0.2-py2-none-any.whl", hash = "sha256:d8226d10bc02a29bcc81df19a26e56a9647f8b0a6d4a83924139f4a8b01f17b7"},
-    {file = "typing_extensions-3.10.0.2-py3-none-any.whl", hash = "sha256:f1d25edafde516b146ecd0613dabcc61409817af4766fbbcfb8d1ad4ec441a34"},
-    {file = "typing_extensions-3.10.0.2.tar.gz", hash = "sha256:49f75d16ff11f1cd258e1b988ccff82a3ca5570217d7ad8c5f48205dd99a677e"},
+    {file = "typing_extensions-3.7.4.3-py2-none-any.whl", hash = "sha256:dafc7639cde7f1b6e1acc0f457842a83e722ccca8eef5270af2d74792619a89f"},
+    {file = "typing_extensions-3.7.4.3-py3-none-any.whl", hash = "sha256:7cb407020f00f7bfc3cb3e7881628838e69d8f3fcab2f64742a5e76b2f841918"},
+    {file = "typing_extensions-3.7.4.3.tar.gz", hash = "sha256:99d4073b617d30288f569d3f13d2bd7548c3a7e4c8de87db09a9d29bb3a4a60c"},
 ]
 urllib3 = [
     {file = "urllib3-1.26.6-py2.py3-none-any.whl", hash = "sha256:39fb8672126159acb139a7718dd10806104dec1e2f0f6c88aab05d17df10c8d4"},
@@ -2622,6 +2834,13 @@ wcwidth = [
     {file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
     {file = "wcwidth-0.2.5.tar.gz", hash = "sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"},
 ]
+werkzeug = [
+    {file = "Werkzeug-2.0.1-py3-none-any.whl", hash = "sha256:6c1ec500dcdba0baa27600f6a22f6333d8b662d22027ff9f6202e3367413caa8"},
+    {file = "Werkzeug-2.0.1.tar.gz", hash = "sha256:1de1db30d010ff1af14a009224ec49ab2329ad2cde454c8a708130642d579c42"},
+]
+wrapt = [
+    {file = "wrapt-1.12.1.tar.gz", hash = "sha256:b62ffa81fb85f4332a4f609cab4ac40709470da05643a082ec1eb88e6d9b97d7"},
+]
 xmltodict = [
     {file = "xmltodict-0.12.0-py2.py3-none-any.whl", hash = "sha256:8bbcb45cc982f48b2ca8fe7e7827c5d792f217ecf1792626f808bf41c3b86051"},
     {file = "xmltodict-0.12.0.tar.gz", hash = "sha256:50d8c638ed7ecb88d90561beedbf720c9b4e851a9fa6c47ebd64e99d166d8a21"},
diff --git a/pyproject.toml b/pyproject.toml
index 3352bbb..127805b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,7 +10,7 @@ repository = "https://github.com/juliusfrost/minerl-rllib/"
 
 [tool.poetry.dependencies]
 python = "^3.7.1"
-scikit-learn = "^0.24.2"
+scikit-learn = "*"
 ray = [
     {extras = ["default", "tune", "rllib"], markers = "python_version == '3.9' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl"},
     {extras = ["default", "tune", "rllib"], markers = "python_version == '3.8' and sys_platform == 'linux'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"},
@@ -19,11 +19,11 @@ ray = [
     {extras = ["default", "tune", "rllib"], markers = "python_version == '3.8' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp38-cp38-win_amd64.whl"},
     {extras = ["default", "tune", "rllib"], markers = "python_version == '3.7' and sys_platform == 'win32'", url = "https://s3-us-west-2.amazonaws.com/ray-wheels/master/ea4a22249c7029fef1d7686e94ddde28c67ee5c8/ray-2.0.0.dev0-cp37-cp37m-win_amd64.whl"}
 ]
-minerl-wrappers = "^0.1.5"
+minerl-wrappers = "^0.1.6"
+tensorflow = "^2.6.0"
 
 [tool.poetry.dev-dependencies]
 pytest = "^6.2.4"
-black = "^21.7b0"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

From 2ec2b26c0cd0605dfb98ed0ac199e9276198e488 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 16 Sep 2021 23:35:20 -0400
Subject: [PATCH 33/48] lazy minerl env

---
 minerl_rllib/envs/env.py | 6 +-----
 1 file changed, 1 insertion(+), 5 deletions(-)

diff --git a/minerl_rllib/envs/env.py b/minerl_rllib/envs/env.py
index 3c25229..3c56295 100644
--- a/minerl_rllib/envs/env.py
+++ b/minerl_rllib/envs/env.py
@@ -85,10 +85,6 @@ def render(self, mode="human"):
         pass
 
 
-def wrap_env(env, **kwargs):
-    return wrap(env, **kwargs)
-
-
 def register_minerl_envs():
     for env_spec in (
         BASIC_ENV_SPECS + COMPETITION_ENV_SPECS + BASALT_COMPETITION_ENV_SPECS
@@ -96,7 +92,7 @@ def register_minerl_envs():
 
         def env_creator(env_config):
             with filelock.FileLock("minerl_env.lock"):
-                env = wrap_env(env_spec.make(), **env_config)
+                env = wrap(LazyMineRLEnv(env_spec), **env_config)
             return env
 
         register_env(env_spec.name, env_creator)

From 9910ddcbc02c74a19ec1a2b81c125b1db55b9042 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 16 Sep 2021 23:37:38 -0400
Subject: [PATCH 34/48] fix input.py

---
 minerl_rllib/envs/input.py | 22 ++--------------------
 1 file changed, 2 insertions(+), 20 deletions(-)

diff --git a/minerl_rllib/envs/input.py b/minerl_rllib/envs/input.py
index 415e45c..ca8c3e1 100644
--- a/minerl_rllib/envs/input.py
+++ b/minerl_rllib/envs/input.py
@@ -11,7 +11,7 @@
 from ray.tune.registry import register_input
 
 from minerl_rllib.envs.data import MinerRLDataEnv
-from minerl_rllib.envs.env import wrap_env
+from minerl_rllib.envs.env import wrap
 from minerl_rllib.envs.utils import patch_data_pipeline
 
 
@@ -95,7 +95,7 @@ def __init__(self, ioctx: IOContext = None):
             seed=seed,
         )
         env = MinerRLDataEnv(self.data)
-        env = wrap_env(env, **env_config)
+        env = wrap(env, **env_config)
         self.episode_generator = simulate_env_interaction(env)
         self.prep = get_preprocessor(env.observation_space)(env.observation_space)
 
@@ -205,23 +205,5 @@ def minerl_input_creator(ioctx: IOContext = None):
     return MineRLInputReader(ioctx=ioctx)
 
 
-def recursive_print(d):
-    if isinstance(d, dict):
-        print("{")
-        for k, v in d.items():
-            print(f"key={k}")
-            recursive_print(v)
-        print("}")
-    elif isinstance(d, list) or isinstance(d, tuple):
-        print("[")
-        for v in d:
-            recursive_print(v)
-        print("]")
-    elif isinstance(d, np.ndarray):
-        print(d.shape)
-    else:
-        print(d)
-
-
 def register_minerl_input():
     register_input("minerl", minerl_input_creator)

From 2308013bd0fc24a8995c6515507c3c867eddd8ce Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 16 Sep 2021 23:39:12 -0400
Subject: [PATCH 35/48] outdated test

---
 tests/discrete.py | 26 --------------------------
 1 file changed, 26 deletions(-)
 delete mode 100644 tests/discrete.py

diff --git a/tests/discrete.py b/tests/discrete.py
deleted file mode 100644
index ddedc37..0000000
--- a/tests/discrete.py
+++ /dev/null
@@ -1,26 +0,0 @@
-import os
-import numpy as np
-import gym
-from tqdm import tqdm
-from minerl_rllib.envs import wrap
-
-
-def test_discrete():
-    os.chdir("..")
-    env = gym.make("MineRLTreechopVectorObf-v0")
-    env = wrap(env, discrete=True, num_actions=32)
-
-    for _ in tqdm(range(100)):
-        print(env.reverse_action(np.random.randn(1, 64)))
-
-    done = False
-    obs = env.reset()
-    for _ in tqdm(range(100)):
-        if done:
-            break
-        action = env.action_space.sample()
-        obs, reward, done, info = env.step(action)
-
-
-if __name__ == "__main__":
-    test_discrete()

From 59121cffb3fd1b257639b1be37102eb3bef78f13 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Fri, 17 Sep 2021 00:02:00 -0400
Subject: [PATCH 36/48] update README.md

---
 README.md | 72 ++++++++++++++++++-------------------------------------
 1 file changed, 23 insertions(+), 49 deletions(-)

diff --git a/README.md b/README.md
index 37eb403..43fe104 100644
--- a/README.md
+++ b/README.md
@@ -7,66 +7,40 @@ RLlib natively supports TensorFlow, TensorFlow Eager, and PyTorch, but most of i
 
 ## Installation
 
+Make sure you have JDK 1.8 on your system for [MineRL](https://minerl.io/docs/tutorials/index.html#installation)
+
 Requires Python 3.7 or 3.8.
 
-1. Make sure you have JDK 1.8 on your system for [MineRL](https://minerl.io/docs/tutorials/index.html#installation).
-```
-git clone https://github.com/juliusfrost/minerl-rllib.git
-cd minerl-rllib
-pip install -r requirements.txt
+#### Use a conda virtual environment
+```bash
+conda create --name minerl-rllib python=3.8
+conda activate minerl-rllib
 ```
-2. Install [Ray Latest Snapshots (Nightlies)](https://docs.ray.io/en/master/installation.html#latest-snapshots-nightlies)
-3. Install [PyTorch](https://pytorch.org/get-started/locally/) and [TensorFlow](https://www.tensorflow.org/install) with correct cuda version.
-
-## Implementation Details
-See [Implementation Details](Implementation.md)
-
-For discrete action spaces, make sure you have the environment variable `MINERL_DATA_ROOT` set, 
-otherwise it defaults to the `data` folder. 
-Then, run `python generate_kmeans.py`
-
-### Configuration
 
-This repository comes with a modular configuration system.
-We specify configuration `yaml` files according to the rllib specification.
-You can see an example config at `config/minerl-impala-debug.yaml`
+#### Install dependencies
+```bash
+pip install poetry
+poetry install
+```
+Install [PyTorch](https://pytorch.org/get-started/locally/) with correct cuda version.
 
+## How to Use
 ### Data
+Make sure you have the environment variable `MINERL_DATA_ROOT` set, 
+otherwise it defaults to the `data` folder.
+
 #### Downloading the MineRL dataset
 Follow the official instructions: https://minerl.io/dataset/  
 If you download the data to `./data` then you don't need to set `MINERL_DATA_ROOT` in your environment variables.
 
-#### Discrete Action Space with K-means clustering
-You can use a discrete action space by running the `generate_kmeans.py` script. For example,
-```
-python generate_kmeans.py --num-actions 32 --env MineRLObtainDiamondVectorObf-v0
-```
-Then to use discrete actions with your agent, set `discrete: true` in the `env_config` of your config file.
-
-#### Input data to your RLLib algorithm
-To feed data to your rllib algorithm, you must first convert the minerl dataset into the json format 
-that is specified by the [RLLib Input API](https://docs.ray.io/en/master/rllib-offline.html#input-api).
-Use the `convert_data.py` script to convert the data into the correct format. 
-You can specify the environment configuration `env_config` 
-with either the `-f` / `--config-file` or `--env-config` flag.
-Example:
-```
-# if you use an env_config different from the default settings, you must specify it 
-python convert_data.py --env MineRLObtainDiamondVectorObf-v0 -f example_config.yaml
-```
-
 ### Training
-We use `rllib_train.py` to train our RL algorithm on MineRL.
-The easiest way to get started is to specify all of your configurations first as stated in the previous section.
-See help with `python rllib_train.py --help`
-
-Here is an example command:
+Do `train.py --help` to see all options.
+See the following command trains the SAC algorithm on offline data in the `MineRLObtainDiamondVectorObf-v0` environment.
 ```
-python rllib_train.py -f config/minerl-impala-debug.yaml
+python train.py -f config/sac-offline.yaml
 ```
-This will run the IMPALA RL algorithm on the MineRL Debug Environment,
-which has the same observation space and action space as the competition environments 
-but doesn't run Minecraft explicitly.
 
-### Testing
-See help with `python rllib_test.py --help`
+#### Configuration
+
+This repository comes with a modular configuration system.
+We specify configuration `yaml` files according to the rllib specification.

From 4fc336a9c537e696c15c1e69b71ea4a97a5cab23 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Sat, 18 Sep 2021 22:02:59 -0400
Subject: [PATCH 37/48] automate kmeans generation

---
 minerl_rllib/convert_data.py    | 10 ++++++++-
 minerl_rllib/envs/env.py        | 37 +++++++++++++++++++++++++++++++--
 minerl_rllib/envs/input.py      |  4 ++--
 minerl_rllib/generate_kmeans.py |  9 ++++++--
 4 files changed, 53 insertions(+), 7 deletions(-)

diff --git a/minerl_rllib/convert_data.py b/minerl_rllib/convert_data.py
index 86bdfa4..6cf58c7 100644
--- a/minerl_rllib/convert_data.py
+++ b/minerl_rllib/convert_data.py
@@ -8,7 +8,10 @@
 
 from minerl_rllib.envs.data import write_jsons
 
-parser = argparse.ArgumentParser()
+parser = argparse.ArgumentParser(
+    "This script is outdated. "
+    "Use the 'input: minerl' option to load the correct data automatically."
+)
 parser.add_argument(
     "--data-dir",
     type=str,
@@ -57,6 +60,11 @@ def get_save_path(data_dir, env_config, env_name=None):
 def main():
     args = parser.parse_args()
 
+    print(
+        "This script is outdated. "
+        "Use the 'input: minerl' option to load the correct data automatically."
+    )
+
     env_list = []
 
     env_config = {}
diff --git a/minerl_rllib/envs/env.py b/minerl_rllib/envs/env.py
index 3c56295..2e1035b 100644
--- a/minerl_rllib/envs/env.py
+++ b/minerl_rllib/envs/env.py
@@ -1,3 +1,5 @@
+import os
+
 import filelock
 import gym
 import gym.wrappers
@@ -11,6 +13,8 @@
 from minerl_wrappers import wrap
 from ray.tune.registry import register_env
 
+from minerl_rllib.generate_kmeans import main as generate_kmeans
+
 
 class LazyMineRLEnv(gym.Env):
     def __init__(self, env_spec, **kwargs):
@@ -85,14 +89,43 @@ def render(self, mode="human"):
         pass
 
 
+def wrap_env(env, env_config, env_name):
+    if env_config.get("kmeans", False):
+        # generate kmeans actions or load from data path if exists
+        # sets the minerl-wrappers config to use these action means
+        kmeans_config = env_config.get("kmeans_config", {})
+        args = [
+            "--env",
+            env_name,
+            "--num-actions",
+            str(kmeans_config.get("num_actions", 32)),
+            "--data-dir",
+            kmeans_config.get("data_dir", os.getenv("MINERL_DATA_ROOT", "data"))
+        ]
+        with filelock.FileLock("minerl_env.lock"):
+            means = generate_kmeans(args)
+        if env_config.get("diamond", False):
+            if "diamond_config" in env_config:
+                env_config["diamond_config"]["action_choices"] = means
+            else:
+                env_config["diamond_config"] = {"action_choices": means}
+        if env_config.get("pfrl_2020", False):
+            if "pfrl_2020_config" in env_config:
+                env_config["pfrl_2020_config"]["action_choices"] = means
+            else:
+                env_config["pfrl_2020_config"] = {"action_choices": means}
+    env = wrap(env, **env_config)
+    return env
+
+
 def register_minerl_envs():
     for env_spec in (
         BASIC_ENV_SPECS + COMPETITION_ENV_SPECS + BASALT_COMPETITION_ENV_SPECS
     ):
 
         def env_creator(env_config):
-            with filelock.FileLock("minerl_env.lock"):
-                env = wrap(LazyMineRLEnv(env_spec), **env_config)
+            env = LazyMineRLEnv(env_spec)
+            env = wrap_env(env, env_config, env_spec.name)
             return env
 
         register_env(env_spec.name, env_creator)
diff --git a/minerl_rllib/envs/input.py b/minerl_rllib/envs/input.py
index ca8c3e1..7f065b5 100644
--- a/minerl_rllib/envs/input.py
+++ b/minerl_rllib/envs/input.py
@@ -11,7 +11,7 @@
 from ray.tune.registry import register_input
 
 from minerl_rllib.envs.data import MinerRLDataEnv
-from minerl_rllib.envs.env import wrap
+from minerl_rllib.envs.env import wrap_env
 from minerl_rllib.envs.utils import patch_data_pipeline
 
 
@@ -95,7 +95,7 @@ def __init__(self, ioctx: IOContext = None):
             seed=seed,
         )
         env = MinerRLDataEnv(self.data)
-        env = wrap(env, **env_config)
+        env = wrap_env(env, env_config, env_name)
         self.episode_generator = simulate_env_interaction(env)
         self.prep = get_preprocessor(env.observation_space)(env.observation_space)
 
diff --git a/minerl_rllib/generate_kmeans.py b/minerl_rllib/generate_kmeans.py
index 16d0ac0..58dfd02 100644
--- a/minerl_rllib/generate_kmeans.py
+++ b/minerl_rllib/generate_kmeans.py
@@ -14,8 +14,8 @@
 parser.add_argument("--overwrite", action="store_true")
 
 
-def main():
-    args = parser.parse_args()
+def main(args=None):
+    args = parser.parse_args(args=args)
     if args.env is None:
         env_list = []
         for env_name in os.listdir(args.data_dir):
@@ -24,11 +24,13 @@ def main():
     else:
         env_list = [args.env]
 
+    return_path = None
     for env_name in env_list:
         print(f"Generating {args.num_actions}-means for {env_name}")
 
         file_dir = os.path.join(args.data_dir, f"{args.num_actions}-means")
         file = os.path.join(file_dir, env_name + ".npy")
+        return_path = file
         if os.path.exists(file) and not args.overwrite:
             print(f"k-means file already exists at {file}")
             continue
@@ -51,6 +53,9 @@ def main():
         print(kmeans)
         np.save(file, kmeans.cluster_centers_)
 
+    if len(env_list) == 1:
+        return return_path
+
 
 if __name__ == "__main__":
     main()

From 24b18dab526aec8929d7ae09ab22eb1da9369bd5 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Sun, 19 Sep 2021 01:58:21 -0400
Subject: [PATCH 38/48] fix tqdm

---
 minerl_rllib/envs/env.py        |  6 ++++--
 minerl_rllib/generate_kmeans.py | 12 ++++++++++--
 2 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/minerl_rllib/envs/env.py b/minerl_rllib/envs/env.py
index 2e1035b..4540f2b 100644
--- a/minerl_rllib/envs/env.py
+++ b/minerl_rllib/envs/env.py
@@ -16,11 +16,13 @@
 from minerl_rllib.generate_kmeans import main as generate_kmeans
 
 
-class LazyMineRLEnv(gym.Env):
+class LazyMineRLEnv:
     def __init__(self, env_spec, **kwargs):
         self._kwargs = kwargs
         self.env_spec: EnvSpec = env_spec
         self._env = None
+        self.observation_space = self.env_spec.observation_space
+        self.action_space = self.env_spec.action_space
         super().__init__()
 
     def init_env(self):
@@ -30,7 +32,7 @@ def init_env(self):
     def reset(self, **kwargs):
         if self._env is None:
             self.init_env()
-        return self._env.reset()
+        return self._env.reset(**kwargs)
 
     def step(self, action):
         return self._env.step(action)
diff --git a/minerl_rllib/generate_kmeans.py b/minerl_rllib/generate_kmeans.py
index 58dfd02..9011fae 100644
--- a/minerl_rllib/generate_kmeans.py
+++ b/minerl_rllib/generate_kmeans.py
@@ -6,16 +6,20 @@
 from sklearn.cluster import KMeans
 from tqdm import tqdm
 
+from minerl_rllib.envs.utils import patch_data_pipeline
+
 parser = argparse.ArgumentParser()
 
 parser.add_argument("--env", default=None)
 parser.add_argument("--num-actions", type=int, default=32)
 parser.add_argument("--data-dir", default=os.getenv("MINERL_DATA_ROOT", "data"))
 parser.add_argument("--overwrite", action="store_true")
+parser.add_argument("--use-tqdm", action="store_true")
 
 
 def main(args=None):
     args = parser.parse_args(args=args)
+    patch_data_pipeline()
     if args.env is None:
         env_list = []
         for env_name in os.listdir(args.data_dir):
@@ -39,7 +43,10 @@ def main(args=None):
 
         data = minerl.data.make(env_name)
         actions = []
-        for trajectory_name in tqdm(list(data.get_trajectory_names())):
+        iter = list(data.get_trajectory_names())
+        if args.use_tqdm:
+            iter = tqdm(iter)
+        for trajectory_name in iter:
             try:
                 for _, action, _, _, _ in data.load_data(trajectory_name):
                     actions.append(action["vector"])
@@ -53,7 +60,8 @@ def main(args=None):
         print(kmeans)
         np.save(file, kmeans.cluster_centers_)
 
-    if len(env_list) == 1:
+    if args.env is not None:
+        assert isinstance(return_path, str)
         return return_path
 
 

From 6ce37f3d17083d4667cb4a8ba93dc72a65d0b0b3 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Sun, 19 Sep 2021 01:59:00 -0400
Subject: [PATCH 39/48] add sac-discrete.yaml

---
 config/sac-discrete.yaml | 59 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 59 insertions(+)
 create mode 100644 config/sac-discrete.yaml

diff --git a/config/sac-discrete.yaml b/config/sac-discrete.yaml
new file mode 100644
index 0000000..bf10774
--- /dev/null
+++ b/config/sac-discrete.yaml
@@ -0,0 +1,59 @@
+minerl-sac-discrete:
+    run: SAC
+    stop:
+      time_total_s: 345600 # 4 days in seconds
+      info/num_steps_sampled: 8000000 # competition sample limit
+    # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
+#    checkpoint_freq: 1
+    checkpoint_at_end: true
+#    keep_checkpoints_num: 1 # keep the best checkpoint around
+#    checkpoint_score_attr: episode_reward_mean
+    # restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
+    local_dir: results # specifies the results folder
+    num_samples: 1 # number of random seeds to try
+    log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
+    config:
+        env: MineRLObtainDiamondVectorObf-v0
+        env_config:
+          diamond: true
+          kmeans: true # setting this automatically generates, saves, and uses kmeans actions to discretize the action space.
+          kmeans_config:
+            num_actions: 30
+        input: sampler
+        input_evaluation: []
+        evaluation_interval: 10
+        evaluation_config:
+          input: sampler
+#        train_batch_size: 1
+        buffer_size: 50000
+        # SAC Configs
+        framework: torch
+        soft_horizon: False
+        horizon: 1000
+        Q_model:
+          conv_filters: [[64, 4, 4], [128, 4, 4], [256, 4, 4]]
+          fcnet_activation: relu
+          fcnet_hiddens: [ 256, 256, 256 ]
+        policy_model:
+          conv_filters: [[64, 4, 4], [128, 4, 4], [256, 4, 4]]
+          fcnet_activation: relu
+          fcnet_hiddens: [ 256, 256, 256 ]
+        tau: 0.005
+        target_entropy: auto
+        no_done_at_end: false
+        n_step: 1
+        rollout_fragment_length: 1
+        prioritized_replay: false
+        train_batch_size: 256
+        target_network_update_freq: 0
+        timesteps_per_iteration: 1000
+        learning_starts: 10
+        optimization:
+          actor_learning_rate: 0.0001
+          critic_learning_rate: 0.0003
+          entropy_learning_rate: 0.0001
+        num_workers: 0
+        num_gpus: 1
+        clip_actions: false
+        normalize_actions: true
+        metrics_smoothing_episodes: 5
\ No newline at end of file

From 62530eada1472196e3102135ca7e90a660b3618c Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Sun, 19 Sep 2021 15:11:58 -0400
Subject: [PATCH 40/48] fix reverse actions

---
 minerl_rllib/envs/input.py | 16 +++++++++++++++-
 1 file changed, 15 insertions(+), 1 deletion(-)

diff --git a/minerl_rllib/envs/input.py b/minerl_rllib/envs/input.py
index 7f065b5..16a3627 100644
--- a/minerl_rllib/envs/input.py
+++ b/minerl_rllib/envs/input.py
@@ -18,6 +18,20 @@
 def simulate_env_interaction(env, restart=True) -> SampleBatch:
     prep = get_preprocessor(env.observation_space)(env.observation_space)
     batch_builder = SampleBatchBuilder()
+
+    # get reverse action functions
+    env_ptr = env
+    reverse_action_fns = []
+    while hasattr(env_ptr, "env"):
+        if isinstance(env_ptr, gym.ActionWrapper):
+            reverse_action_fns.append(env_ptr.reverse_action)
+        env_ptr = env_ptr.env
+
+    def reverse_action(action):
+        for f in reversed(reverse_action_fns):
+            action = f(action)
+        return action
+
     while restart:
         for eps_id, trajectory_name in enumerate(env.trajectory_names):
             t = 0
@@ -31,7 +45,7 @@ def simulate_env_interaction(env, restart=True) -> SampleBatch:
             while not done:
                 new_obs, reward, done, info = env.step(env.action_space.sample())
                 action = info["action"]
-                action = env.reverse_action(action)
+                action = reverse_action(action)
                 if prev_action is None:
                     prev_action = np.zeros_like(action)
 

From cb8ec26cccf3b6b50757f71a47ea3782202615a4 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 23 Sep 2021 00:14:52 -0400
Subject: [PATCH 41/48] rainbow

---
 config/rainbow.yaml | 74 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 74 insertions(+)
 create mode 100644 config/rainbow.yaml

diff --git a/config/rainbow.yaml b/config/rainbow.yaml
new file mode 100644
index 0000000..2d67677
--- /dev/null
+++ b/config/rainbow.yaml
@@ -0,0 +1,74 @@
+# base hyperparameters used from sample efficient rainbow (Appendix F)
+# https://arxiv.org/abs/1906.05243
+minerl-rainbow:
+  run: DQN
+  stop:
+    time_total_s: 345600 # 4 days in seconds
+    info/num_steps_sampled: 8000000 # competition sample limit
+  local_dir: results # specifies the results folder
+  num_samples: 1 # number of random seeds to try
+  log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
+  checkpoint_freq: 1000
+  checkpoint_at_end: true
+  keep_checkpoints_num: 1 # keep the best checkpoint around
+  checkpoint_score_attr: eval/episode_reward_mean
+  config:
+    log_level: INFO
+    # MineRL config
+    env: MineRLObtainDiamondVectorObf-v0
+    env_config:
+      diamond: true
+#      diamond_config:
+#        gray_scale: true # (rainbow setting)
+#        frame_skip: 4 # (rainbow setting)
+#        frame_stack: 4 # (rainbow setting)
+      kmeans: true
+      kmeans_config:
+        num_actions: 30
+    framework: torch
+    # evaluation
+    evaluation_interval: 1000
+    evaluation_num_workers: 1
+    evaluation_parallel_to_training: true
+    evaluation_config:
+      input: sampler
+      explore: false
+    # Rainbow config
+    gamma: 0.99 # (rainbow setting)
+    num_atoms: 51  # (rainbow setting)
+    noisy: True  # (rainbow setting)
+    sigma0: 0.1 # (rainbow setting)
+    dueling: true # (rainbow setting)
+    hiddens: [ 256 ] # (sample-efficient rainbow setting)
+    double_q: true # (rainbow setting)
+    n_step: 20 # (sample-efficient rainbow setting)
+    model:
+      # Filter config. List of [out_channels, kernel, stride] for each filter
+      conv_filters: [ [ 64, 4, 4 ], [ 128, 4, 4 ], [ 256, 4, 4 ] ]
+      fcnet_hiddens: [ 256 ]
+      framestack: false
+    # exploration settings
+    exploration_config: # (default setting)
+      initial_epsilon: 1.0
+      final_epsilon: 0.02
+      epsilon_timesteps: 10000
+    # do a train op every step
+    timesteps_per_iteration: 1 # (sample-efficient rainbow setting)
+    target_network_update_freq: 2000 # (rainbow setting)
+    # optimization settings
+    lr: .0001 # (sample-efficient rainbow setting)
+    adam_epsilon: .00015 # (rainbow setting)
+    grad_clip: 10 # (rainbow setting)
+    learning_starts: 1600 # (sample-efficient rainbow setting)
+    rollout_fragment_length: 1 # (sample-efficient rainbow setting)
+    train_batch_size: 32 # (rainbow setting)
+    # replay buffer settings
+    # tweak this according to how much memory you have
+    buffer_size: 500000 # (rainbow setting)
+    replay_sequence_length: 1 # (sample-efficient rainbow setting)
+    prioritized_replay: True # (rainbow setting)
+    prioritized_replay_alpha: 0.5 # (rainbow setting)
+    prioritized_replay_beta: 0.4 # (rainbow setting)
+    final_prioritized_replay_beta: 1.0 # (rainbow setting)
+    prioritized_replay_beta_annealing_timesteps: 8000000 # set to the expected maximum number of time steps
+    num_gpus: 1
\ No newline at end of file

From 33272359703b3131773141d08b4e5bfc498b024e Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 23 Sep 2021 00:34:17 -0400
Subject: [PATCH 42/48] update config

---
 config/sac-offline.yaml | 114 ++++++++++++++++++++--------------------
 1 file changed, 58 insertions(+), 56 deletions(-)

diff --git a/config/sac-offline.yaml b/config/sac-offline.yaml
index e3c2292..a962776 100644
--- a/config/sac-offline.yaml
+++ b/config/sac-offline.yaml
@@ -1,57 +1,59 @@
 minerl-sac-offline:
-    run: SAC
-    stop:
-      time_total_s: 345600 # 4 days in seconds
-      # no sample limit since using offline rl
-      # info/num_steps_sampled: 8000000 # competition sample limit
-    # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
-#    checkpoint_freq: 1
-    checkpoint_at_end: true
-#    keep_checkpoints_num: 1 # keep the best checkpoint around
-#    checkpoint_score_attr: episode_reward_mean
-    # restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
-    local_dir: results # specifies the results folder
-    num_samples: 1 # number of random seeds to try
-    log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
-    config:
-        env: MineRLObtainDiamondVectorObf-v0
-        env_config:
-          diamond: true
-        input: minerl
-        input_evaluation: []
-        evaluation_interval: 10
-        evaluation_config:
-          input: sampler
-#        train_batch_size: 1
-        buffer_size: 50000
-        # SAC Configs
-        framework: torch
-        soft_horizon: False
-        horizon: 1000
-        Q_model:
-          conv_filters: [[64, 4, 4], [128, 4, 4], [256, 4, 4]]
-          fcnet_activation: relu
-          fcnet_hiddens: [ 256, 256, 256 ]
-        policy_model:
-          conv_filters: [[64, 4, 4], [128, 4, 4], [256, 4, 4]]
-          fcnet_activation: relu
-          fcnet_hiddens: [ 256, 256, 256 ]
-        tau: 0.005
-        target_entropy: auto
-        no_done_at_end: false
-        n_step: 1
-        rollout_fragment_length: 1
-        prioritized_replay: false
-        train_batch_size: 256
-        target_network_update_freq: 0
-        timesteps_per_iteration: 1000
-        learning_starts: 10
-        optimization:
-          actor_learning_rate: 0.0001
-          critic_learning_rate: 0.0003
-          entropy_learning_rate: 0.0001
-        num_workers: 0
-        num_gpus: 1
-        clip_actions: false
-        normalize_actions: true
-        metrics_smoothing_episodes: 5
\ No newline at end of file
+  run: SAC
+  stop:
+    time_total_s: 345600 # 4 days in seconds
+    # no sample limit since using offline rl
+    # info/num_steps_sampled: 8000000 # competition sample limit
+  # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
+  checkpoint_freq: 1000
+  checkpoint_at_end: true
+  keep_checkpoints_num: 1 # keep the best checkpoint around
+  checkpoint_score_attr: eval/episode_reward_mean
+  # restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
+  local_dir: results # specifies the results folder
+  num_samples: 1 # number of random seeds to try
+  log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
+  config:
+    log_level: INFO
+    env: MineRLObtainDiamondVectorObf-v0
+    env_config:
+      diamond: true
+    input: minerl
+    input_evaluation: [ ]
+    evaluation_interval: 1000
+    evaluation_num_workers: 1
+    evaluation_parallel_to_training: true
+    evaluation_config:
+      input: sampler
+    buffer_size: 500000 # runs on 128 GB memory system
+    # SAC Configs
+    framework: torch
+    soft_horizon: False
+    horizon: 1000
+    Q_model:
+      conv_filters: [ [ 64, 4, 4 ], [ 128, 4, 4 ], [ 256, 4, 4 ] ]
+      fcnet_activation: relu
+      fcnet_hiddens: [ 256, 256, 256 ]
+    policy_model:
+      conv_filters: [ [ 64, 4, 4 ], [ 128, 4, 4 ], [ 256, 4, 4 ] ]
+      fcnet_activation: relu
+      fcnet_hiddens: [ 256, 256, 256 ]
+    tau: 0.005
+    target_entropy: auto
+    no_done_at_end: false
+    n_step: 1
+    rollout_fragment_length: 1
+    prioritized_replay: false
+    train_batch_size: 256
+    target_network_update_freq: 0
+    timesteps_per_iteration: 1000
+    learning_starts: 10
+    optimization:
+      actor_learning_rate: 0.0001
+      critic_learning_rate: 0.0003
+      entropy_learning_rate: 0.0001
+    num_workers: 0
+    num_gpus: 1
+    clip_actions: false
+    normalize_actions: true
+    metrics_smoothing_episodes: 5
\ No newline at end of file

From 31f4272b8dc2dfe42c2380c03592af676760ace5 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 23 Sep 2021 00:42:36 -0400
Subject: [PATCH 43/48] update config

---
 config/sac-discrete.yaml | 118 ++++++++++++++++++++-------------------
 1 file changed, 60 insertions(+), 58 deletions(-)

diff --git a/config/sac-discrete.yaml b/config/sac-discrete.yaml
index bf10774..e3e2c8c 100644
--- a/config/sac-discrete.yaml
+++ b/config/sac-discrete.yaml
@@ -1,59 +1,61 @@
 minerl-sac-discrete:
-    run: SAC
-    stop:
-      time_total_s: 345600 # 4 days in seconds
-      info/num_steps_sampled: 8000000 # competition sample limit
-    # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
-#    checkpoint_freq: 1
-    checkpoint_at_end: true
-#    keep_checkpoints_num: 1 # keep the best checkpoint around
-#    checkpoint_score_attr: episode_reward_mean
-    # restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
-    local_dir: results # specifies the results folder
-    num_samples: 1 # number of random seeds to try
-    log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
-    config:
-        env: MineRLObtainDiamondVectorObf-v0
-        env_config:
-          diamond: true
-          kmeans: true # setting this automatically generates, saves, and uses kmeans actions to discretize the action space.
-          kmeans_config:
-            num_actions: 30
-        input: sampler
-        input_evaluation: []
-        evaluation_interval: 10
-        evaluation_config:
-          input: sampler
-#        train_batch_size: 1
-        buffer_size: 50000
-        # SAC Configs
-        framework: torch
-        soft_horizon: False
-        horizon: 1000
-        Q_model:
-          conv_filters: [[64, 4, 4], [128, 4, 4], [256, 4, 4]]
-          fcnet_activation: relu
-          fcnet_hiddens: [ 256, 256, 256 ]
-        policy_model:
-          conv_filters: [[64, 4, 4], [128, 4, 4], [256, 4, 4]]
-          fcnet_activation: relu
-          fcnet_hiddens: [ 256, 256, 256 ]
-        tau: 0.005
-        target_entropy: auto
-        no_done_at_end: false
-        n_step: 1
-        rollout_fragment_length: 1
-        prioritized_replay: false
-        train_batch_size: 256
-        target_network_update_freq: 0
-        timesteps_per_iteration: 1000
-        learning_starts: 10
-        optimization:
-          actor_learning_rate: 0.0001
-          critic_learning_rate: 0.0003
-          entropy_learning_rate: 0.0001
-        num_workers: 0
-        num_gpus: 1
-        clip_actions: false
-        normalize_actions: true
-        metrics_smoothing_episodes: 5
\ No newline at end of file
+  run: SAC
+  stop:
+    time_total_s: 345600 # 4 days in seconds
+    info/num_steps_sampled: 8000000 # competition sample limit
+  # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
+  checkpoint_freq: 100
+  checkpoint_at_end: true
+  keep_checkpoints_num: 1 # keep the best checkpoint around
+  checkpoint_score_attr: eval/episode_reward_mean
+  # restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
+  local_dir: results # specifies the results folder
+  num_samples: 1 # number of random seeds to try
+  log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
+  config:
+    log_level: INFO
+    env: MineRLObtainDiamondVectorObf-v0
+    env_config:
+      diamond: true
+      kmeans: true # setting this automatically generates, saves, and uses kmeans actions to discretize the action space.
+      kmeans_config:
+        num_actions: 30
+    input: sampler
+    input_evaluation: [ ]
+    evaluation_interval: 100
+    evaluation_num_workers: 1
+    evaluation_parallel_to_training: true
+    evaluation_config:
+      input: sampler
+    buffer_size: 500000 # runs on 128 GB memory system
+    # SAC Configs
+    framework: torch
+    soft_horizon: False
+    horizon: 1000
+    Q_model:
+      conv_filters: [ [ 64, 4, 4 ], [ 128, 4, 4 ], [ 256, 4, 4 ] ]
+      fcnet_activation: relu
+      fcnet_hiddens: [ 256, 256, 256 ]
+    policy_model:
+      conv_filters: [ [ 64, 4, 4 ], [ 128, 4, 4 ], [ 256, 4, 4 ] ]
+      fcnet_activation: relu
+      fcnet_hiddens: [ 256, 256, 256 ]
+    tau: 0.005
+    target_entropy: auto
+    no_done_at_end: false
+    n_step: 1
+    rollout_fragment_length: 1
+    prioritized_replay: false
+    train_batch_size: 256
+    target_network_update_freq: 0
+    timesteps_per_iteration: 1000
+    learning_starts: 10
+    optimization:
+      actor_learning_rate: 0.0001
+      critic_learning_rate: 0.0003
+      entropy_learning_rate: 0.0001
+    num_workers: 0
+    num_gpus: 1
+    clip_actions: false
+    normalize_actions: true
+    metrics_smoothing_episodes: 5
\ No newline at end of file

From 216c60f408124588ae2780d318db73844bda814a Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 23 Sep 2021 00:44:49 -0400
Subject: [PATCH 44/48] update config

---
 config/bc.yaml | 12 +++++++-----
 1 file changed, 7 insertions(+), 5 deletions(-)

diff --git a/config/bc.yaml b/config/bc.yaml
index 6860226..16539ab 100644
--- a/config/bc.yaml
+++ b/config/bc.yaml
@@ -5,26 +5,28 @@ minerl-bc:
     # no sample limit since using offline rl
     # info/num_steps_sampled: 8000000 # competition sample limit
   # check point file located results/experiment-name/unique-name/checkpoint_X/checkpoint-X
-#  checkpoint_freq: 1
+  checkpoint_freq: 1000
   checkpoint_at_end: true
-#  keep_checkpoints_num: 1 # keep the best checkpoint around
-#  checkpoint_score_attr: episode_reward_mean
+  keep_checkpoints_num: 1 # keep the best checkpoint around
+  checkpoint_score_attr: eval/episode_reward_mean
 #  restore: path_to_checkpoint_file # does not restore the replay buffer so use with caution
   local_dir: results # specifies the results folder
   num_samples: 1 # number of random seeds to try
   log_to_file: log.txt # useful for debugging with print statements, errors are logged to error.txt
   config:
+    log_level: INFO
     # minerl-rllib config changes
     env: MineRLObtainDiamondVectorObf-v0
     env_config:
       diamond: true
     input: minerl
     input_evaluation: [ ]
-    evaluation_interval: 10
+    evaluation_interval: 1000
+    evaluation_num_workers: 1
+    evaluation_parallel_to_training: true
     evaluation_config:
       input: sampler
     model:
       conv_filters: [ [ 64, 4, 4 ], [ 128, 4, 4 ], [ 256, 4, 4 ] ]
     framework: torch
     num_gpus: 1
-    log_level: DEBUG

From 37a94c985313d0627f0897801adc00d0e724a57c Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 23 Sep 2021 00:47:00 -0400
Subject: [PATCH 45/48] add README.md

---
 config/README.md | 11 +++++++++++
 1 file changed, 11 insertions(+)
 create mode 100644 config/README.md

diff --git a/config/README.md b/config/README.md
new file mode 100644
index 0000000..64266b9
--- /dev/null
+++ b/config/README.md
@@ -0,0 +1,11 @@
+# Algorithms
+
+All algorithm configs here are an MVP and not tuned. All of them do not obtain good reward.
+
+`bc.yaml`: currently bugged because rllib
+
+`rainbow.yaml`: sometimes discovers rewarding episodes but data is too sparse to learn
+
+`sac-discrete.yaml`: extremely slow to train
+
+`sac-offline.yaml`: Q function drastically overestimates values highlighted due to OOD actions

From 1a3bc52ee478bb46a78d20f6ef49444ba109e300 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 23 Sep 2021 00:49:00 -0400
Subject: [PATCH 46/48] typo

---
 config/README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/config/README.md b/config/README.md
index 64266b9..82c4e07 100644
--- a/config/README.md
+++ b/config/README.md
@@ -4,8 +4,8 @@ All algorithm configs here are an MVP and not tuned. All of them do not obtain g
 
 `bc.yaml`: currently bugged because rllib
 
-`rainbow.yaml`: sometimes discovers rewarding episodes but data is too sparse to learn
+`rainbow.yaml`: sometimes discovers rewarding episodes but rewards are too sparse to learn
 
 `sac-discrete.yaml`: extremely slow to train
 
-`sac-offline.yaml`: Q function drastically overestimates values highlighted due to OOD actions
+`sac-offline.yaml`: Q function drastically overestimates values due to OOD actions

From 41ec1477240019b1de6a62df8d9a4a9b3ed5a92c Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 23 Sep 2021 01:14:07 -0400
Subject: [PATCH 47/48] more documentation

---
 README.md           | 36 ++++++++++++++++++++++++++++++++++--
 config/rainbow.yaml |  2 ++
 2 files changed, 36 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 43fe104..b4a7938 100644
--- a/README.md
+++ b/README.md
@@ -34,9 +34,13 @@ Follow the official instructions: https://minerl.io/dataset/
 If you download the data to `./data` then you don't need to set `MINERL_DATA_ROOT` in your environment variables.
 
 ### Training
-Do `train.py --help` to see all options.
-See the following command trains the SAC algorithm on offline data in the `MineRLObtainDiamondVectorObf-v0` environment.
+Training is simple with just one command. Do `python train.py --help` to see all options.
+```bash
+python train.py -f path/to/config.yaml
 ```
+
+For example, see the following command trains the SAC algorithm on offline data in the `MineRLObtainDiamondVectorObf-v0` environment.
+```bash
 python train.py -f config/sac-offline.yaml
 ```
 
@@ -44,3 +48,31 @@ python train.py -f config/sac-offline.yaml
 
 This repository comes with a modular configuration system.
 We specify configuration `yaml` files according to the rllib specification.
+Read more about rllib config specification [here](https://docs.ray.io/en/master/rllib-training.html#common-parameters). 
+Check out the [`config/`](https://github.com/juliusfrost/minerl-rllib/tree/master/config)
+directory for more example configs.
+
+You can specify the [`minerl-wrappers`](https://github.com/minerl-wrappers/minerl-wrappers)
+configuration arguments with the `env_config` setting.
+Check [here](https://github.com/minerl-wrappers/minerl-wrappers/blob/main/minerl_wrappers/config.py)
+for other config options for different wrappers.
+```yaml
+training-run-name:
+  ...
+  config:
+    ...
+    env: MineRLObtainDiamondVectorObf-v0
+    env_config:
+      # use diamond wrappers from minerl-wrappers
+      diamond: true
+      diamond_config:
+        gray_scale: true
+        frame_skip: 4
+        frame_stack: 4
+      # This repo-exclusive API discretizes the action space by calculating the kmeans actions
+      # from the minerl dataset for the chosen env. Kmeans results are cached to data location.
+      kmeans: true
+      kmeans_config:
+        num_actions: 30
+```
+
diff --git a/config/rainbow.yaml b/config/rainbow.yaml
index 2d67677..6b8b32e 100644
--- a/config/rainbow.yaml
+++ b/config/rainbow.yaml
@@ -22,6 +22,8 @@ minerl-rainbow:
 #        gray_scale: true # (rainbow setting)
 #        frame_skip: 4 # (rainbow setting)
 #        frame_stack: 4 # (rainbow setting)
+      # This repo-exclusive API discretizes the action space by calculating the kmeans actions
+      # from the minerl dataset for the chosen env. Kmeans results are cached to data location.
       kmeans: true
       kmeans_config:
         num_actions: 30

From 463757f5a43d98f58e5aaa10c771a29de0d6ae50 Mon Sep 17 00:00:00 2001
From: Julius Frost <33183774+juliusfrost@users.noreply.github.com>
Date: Thu, 23 Sep 2021 01:16:29 -0400
Subject: [PATCH 48/48] add CITATION.cff

---
 CITATION.cff | 14 ++++++++++++++
 1 file changed, 14 insertions(+)
 create mode 100644 CITATION.cff

diff --git a/CITATION.cff b/CITATION.cff
new file mode 100644
index 0000000..b0b426d
--- /dev/null
+++ b/CITATION.cff
@@ -0,0 +1,14 @@
+# YAML 1.2
+---
+authors: 
+  -
+    family-names: Frost
+    given-names: Julius
+    orcid: "https://orcid.org/0000-0002-8401-8122"
+cff-version: "1.1.0"
+date-released: 2020-06-24
+license: "GPL-3.0-only"
+message: "If you use this software, please cite it using these metadata."
+repository-code: "https://github.com/juliusfrost/minerl-rllib"
+title: "minerl-wrappers"
+...
\ No newline at end of file