[refactor] Add --tensorflow, enable Torch as default setting

com.unity.ml-agents/CHANGELOG.md

@@ -12,6 +12,11 @@ and this project adheres to
 ### Major Changes
 #### com.unity.ml-agents (C#)
 #### ml-agents / ml-agents-envs / gym-unity (Python)
+ - PyTorch trainers are now the default. See the
+ [installation docs](https://github.com/Unity-Technologies/ml-agents/blob/mastere/docs/Installation.md) for
+ more information on installing PyTorch. For the time being, TensorFlow is still available;
+ you can use the TensorFlow backend by adding `--tensorflow` to the CLI, or
+ adding `framework: tensorflow` in the configuration YAML. (#4517)
 
 ### Minor Changes
 #### com.unity.ml-agents (C#)

ml-agents/mlagents/trainers/cli_utils.py

@@ -172,8 +172,15 @@ def _create_parser() -> argparse.ArgumentParser:
         "--torch",
         default=False,
         action=DetectDefaultStoreTrue,
-        help="(Experimental) Use the PyTorch framework instead of TensorFlow. Install PyTorch "
-        "before using this option",
+        help="Use the PyTorch framework. Note that this option is not required anymore as PyTorch is the"
+        "default framework, and will be removed in the next release.",
+    )
+    argparser.add_argument(
+        "--tensorflow",
+        default=False,
+        action=DetectDefaultStoreTrue,
+        help="(Deprecated) Use the TensorFlow framework instead of PyTorch. Install TensorFlow "
+        "before using this option.",
     )
 
     eng_conf = argparser.add_argument_group(title="Engine Configuration")

ml-agents/mlagents/trainers/learn.py

@@ -136,6 +136,7 @@ def run_training(run_seed: int, options: RunOptions) -> None:
             init_path=maybe_init_path,
             multi_gpu=False,
             force_torch="torch" in DetectDefault.non_default_args,
+            force_tensorflow="tensorflow" in DetectDefault.non_default_args,
         )
         # Create controller and begin training.
         tc = TrainerController(

ml-agents/mlagents/trainers/settings.py

@@ -620,7 +620,7 @@ def _set_default_hyperparameters(self):
     threaded: bool = True
     self_play: Optional[SelfPlaySettings] = None
     behavioral_cloning: Optional[BehavioralCloningSettings] = None
-    framework: FrameworkType = FrameworkType.TENSORFLOW
+    framework: FrameworkType = FrameworkType.PYTORCH
 
     cattr.register_structure_hook(
         Dict[RewardSignalType, RewardSignalSettings], RewardSignalSettings.structure

ml-agents/mlagents/trainers/trainer/trainer_factory.py

@@ -27,6 +27,7 @@ def __init__(
         init_path: str = None,
         multi_gpu: bool = False,
         force_torch: bool = False,
+        force_tensorflow: bool = False,
     ):
         """
         The TrainerFactory generates the Trainers based on the configuration passed as
@@ -45,7 +46,9 @@ def __init__(
         :param init_path: Path from which to load model.
         :param multi_gpu: If True, multi-gpu will be used. (currently not available)
         :param force_torch: If True, the Trainers will all use the PyTorch framework
-        instead of the TensorFlow framework.
+        instead of what is specified in the config YAML.
+        :param force_tensorflow: If True, thee Trainers will all use the TensorFlow
+        framework.
         """
         self.trainer_config = trainer_config
         self.output_path = output_path
@@ -57,6 +60,7 @@ def __init__(
         self.multi_gpu = multi_gpu
         self.ghost_controller = GhostController()
         self._force_torch = force_torch
+        self._force_tf = force_tensorflow
 
     def generate(self, behavior_name: str) -> Trainer:
         if behavior_name not in self.trainer_config.keys():
@@ -67,6 +71,18 @@ def generate(self, behavior_name: str) -> Trainer:
         trainer_settings = self.trainer_config[behavior_name]
         if self._force_torch:
             trainer_settings.framework = FrameworkType.PYTORCH
+            logger.warning(
+                "Note that specifying --torch is not required anymore as PyTorch is the default framework."
+            )
+        if self._force_tf:
+            trainer_settings.framework = FrameworkType.TENSORFLOW
+            logger.warning(
+                "Setting the framework to TensorFlow. TensorFlow trainers will be deprecated in the future."
+            )
+            if self._force_torch:
+                logger.warning(
+                    "Both --torch and --tensorflow CLI options were specified. Using TensorFlow."
+                )
         return TrainerFactory._initialize_trainer(
             trainer_settings,
             behavior_name,