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Adding step dependent dynamics #1

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Adding step dependent dynamics #1

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bc53b37
adding option for step-dependent dynamics
mr-mikmik Apr 5, 2024
aa66be6
adding option for displaying optimization progress as a progress bar …
mr-mikmik Apr 5, 2024
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18 changes: 13 additions & 5 deletions src/pytorch_icem/icem.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
import torch
import colorednoise
from arm_pytorch_utilities import handle_batch_input
from tqdm import tqdm

import logging

Expand All @@ -26,6 +27,7 @@ def __init__(self, dynamics, trajectory_cost, nx, nu, sigma=None, num_samples=10
warmup_iters=100, online_iters=100,
includes_x0=False,
fixed_H=True,
step_dependent_dynamics=False,
device="cpu"):

self.dynamics = dynamics
Expand All @@ -47,6 +49,7 @@ def __init__(self, dynamics, trajectory_cost, nx, nu, sigma=None, num_samples=10
self.sigma = sigma
self.dtype = self.sigma.dtype

self.step_dependency = step_dependent_dynamics
self.warmup_iters = warmup_iters
self.online_iters = online_iters
self.includes_x0 = includes_x0
Expand Down Expand Up @@ -104,8 +107,8 @@ def _cost(self, x, u):
# return self.problem.objective(xu)

@handle_batch_input(n=2)
def _dynamics(self, x, u):
return self.dynamics(x, u)
def _dynamics(self, x, u, t):
return self.dynamics(x, u, t) if self.step_dependency else self.dynamics(x, u)

def _rollout_dynamics(self, x0, u):
N, H, du = u.shape
Expand All @@ -114,13 +117,13 @@ def _rollout_dynamics(self, x0, u):

x = [x0.reshape(1, self.nx).repeat(N, 1)]
for t in range(self.H):
x.append(self._dynamics(x[-1], u[:, t]))
x.append(self._dynamics(x[-1], u[:, t], t))

if self.includes_x0:
return torch.stack(x[:-1], dim=1)
return torch.stack(x[1:], dim=1)

def command(self, state, shift_nominal_trajectory=True, return_full_trajectories=False, **kwargs):
def command(self, state, shift_nominal_trajectory=True, return_full_trajectories=False, progress_bar=False, **kwargs):
if not torch.is_tensor(state):
state = torch.tensor(state, device=self.device, dtype=self.dtype)
x = state
Expand All @@ -142,7 +145,12 @@ def command(self, state, shift_nominal_trajectory=True, return_full_trajectories

# Shift the keep elites

for i in range(iterations):
if progress_bar:
its = tqdm(range(iterations))
else:
its = range(iterations)

for i in its:
if self.kept_elites is None:
# Sample actions
U = self.sample_action_sequences(x, self.N)
Expand Down