Merge branch 'securefederatedai:develop' into serialization_removal

securefederatedai · Sep 27, 2023 · 41589c2 · 41589c2
2 parents b6fdfaa + 62b5b0c
commit 41589c2
Show file tree

Hide file tree

Showing 9 changed files with 38 additions and 48 deletions.
diff --git a/openfl-docker/Dockerfile.base b/openfl-docker/Dockerfile.base
@@ -3,7 +3,7 @@
 
 # If your machine is behind a proxy, make sure you set it up in ~/.docker/config.json
 
-FROM ubuntu:22.10
+FROM ubuntu:22.04
 
 SHELL ["/bin/bash", "-o", "pipefail", "-c"]
 ARG INSTALL_SOURCES="yes"

diff --git a/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_1.py b/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_1.py
@@ -451,22 +451,21 @@ def train(self):
                 last_iter=(batch_idx == (len(self.train_loader) - 1)),
             )
 
-            if self.dp_params is not None:
-                if batch_idx % self.dp_params["clip_frequency"] == 0 or (
-                    batch_idx == (len(self.train_loader) - 1)
-                ):
-                    if self.clip_test:
-                        optimizer_after_step_params = [
-                            param.data
-                            for param in self.optimizer.param_groups()[0]["params"]
-                        ]
-                        clip_testing_on_optimizer_parameters(
-                            optimizer_before_step_params,
-                            optimizer_after_step_params,
-                            self.collaborator_name,
-                            self.round,
-                            self.device,
-                        )
+            if batch_idx % self.dp_params["clip_frequency"] == 0 or (
+                batch_idx == (len(self.train_loader) - 1)
+            ):
+                if self.clip_test:
+                    optimizer_after_step_params = [
+                        param.data
+                        for param in self.optimizer.param_groups()[0]["params"]
+                    ]
+                    clip_testing_on_optimizer_parameters(
+                        optimizer_before_step_params,
+                        optimizer_after_step_params,
+                        self.collaborator_name,
+                        self.round,
+                        self.device,
+                    )
 
             train_losses.append(loss.item())
 

diff --git a/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_2.py b/openfl-tutorials/experimental/Global_DP/Workflow_Interface_Mnist_Implementation_2.py
@@ -454,22 +454,21 @@ def train(self):
                 last_iter=(batch_idx == (len(self.train_loader) - 1)),
             )
 
-            if self.dp_params is not None:
-                if batch_idx % self.dp_params["clip_frequency"] == 0 or (
-                    batch_idx == (len(self.train_loader) - 1)
-                ):
-                    if self.clip_test:
-                        optimizer_after_step_params = [
-                            param.data
-                            for param in self.optimizer.param_groups()[0]["params"]
-                        ]
-                        clip_testing_on_optimizer_parameters(
-                            optimizer_before_step_params,
-                            optimizer_after_step_params,
-                            self.collaborator_name,
-                            self.round,
-                            self.device,
-                        )
+            if batch_idx % self.dp_params["clip_frequency"] == 0 or (
+                batch_idx == (len(self.train_loader) - 1)
+            ):
+                if self.clip_test:
+                    optimizer_after_step_params = [
+                        param.data
+                        for param in self.optimizer.param_groups()[0]["params"]
+                    ]
+                    clip_testing_on_optimizer_parameters(
+                        optimizer_before_step_params,
+                        optimizer_after_step_params,
+                        self.collaborator_name,
+                        self.round,
+                        self.device,
+                    )
 
             train_losses.append(loss.item())
 

diff --git a/openfl-workspace/keras_cnn_mnist/src/keras_cnn.py b/openfl-workspace/keras_cnn_mnist/src/keras_cnn.py
@@ -30,9 +30,8 @@ def __init__(self, **kwargs):
 
         self.model.summary(print_fn=self.logger.info)
 
-        if self.data_loader is not None:
-            self.logger.info(f'Train Set Size : {self.get_train_data_size()}')
-            self.logger.info(f'Valid Set Size : {self.get_valid_data_size()}')
+        self.logger.info(f'Train Set Size : {self.get_train_data_size()}')
+        self.logger.info(f'Valid Set Size : {self.get_valid_data_size()}')
 
     def build_model(self,
                     input_shape,

diff --git a/openfl-workspace/keras_cnn_with_compression/src/keras_cnn.py b/openfl-workspace/keras_cnn_with_compression/src/keras_cnn.py
@@ -30,9 +30,8 @@ def __init__(self, **kwargs):
 
         self.model.summary(print_fn=self.logger.info)
 
-        if self.data_loader is not None:
-            self.logger.info(f'Train Set Size : {self.get_train_data_size()}')
-            self.logger.info(f'Valid Set Size : {self.get_valid_data_size()}')
+        self.logger.info(f'Train Set Size : {self.get_train_data_size()}')
+        self.logger.info(f'Valid Set Size : {self.get_valid_data_size()}')
 
     def build_model(self,
                     input_shape,

diff --git a/openfl-workspace/keras_nlp/src/nlp_taskrunner.py b/openfl-workspace/keras_nlp/src/nlp_taskrunner.py
@@ -70,5 +70,4 @@ def __init__(self, latent_dim, **kwargs):
 
         self.model.summary(print_fn=self.logger.info)
 
-        if self.data_loader is not None:
-            self.logger.info(f'Train Set Size : {self.get_train_data_size()}')
+        self.logger.info(f'Train Set Size : {self.get_train_data_size()}')
diff --git a/openfl-workspace/keras_nlp_gramine_ready/src/nlp_taskrunner.py b/openfl-workspace/keras_nlp_gramine_ready/src/nlp_taskrunner.py
@@ -70,5 +70,4 @@ def __init__(self, latent_dim, **kwargs):
 
         self.model.summary(print_fn=self.logger.info)
 
-        if self.data_loader is not None:
-            self.logger.info(f'Train Set Size : {self.get_train_data_size()}')
+        self.logger.info(f'Train Set Size : {self.get_train_data_size()}')
diff --git a/openfl/component/aggregator/aggregator.py b/openfl/component/aggregator/aggregator.py
@@ -834,10 +834,6 @@ def _compute_validation_related_task_metrics(self, task_name):
                     'metric_value': agg_results.item(),
                     'round': round_number}
 
-                if agg_results is None:
-                    self.logger.warning(
-                        f'Aggregated metric {agg_tensor_name} could not be collected '
-                        f'for round {self.round_number}. Skipping reporting for this round')
                 if agg_function:
                     self.logger.metric(f'Round {round_number}, aggregator: {task_name} '
                                        f'{agg_function} {agg_tensor_name}:\t{agg_results:f}')

diff --git a/openfl/databases/utilities/dataframe.py b/openfl/databases/utilities/dataframe.py
@@ -34,7 +34,7 @@ def _search(self, tensor_name: str = None, origin: str = None,
             pd.DataFrame : New dataframe that matches the search query from
                            the tensor_db dataframe
     """
-    df = None
+    df = pd.DataFrame()
     query_string = []
     if tensor_name is not None:
         query_string.append(f"(tensor_name == '{tensor_name}')")