import logging import os logger = logging.getLogger(__name__) def check_framework(framework="tf"): """ Checks, whether the given framework is "valid", meaning, whether all necessary dependencies are installed. Errors otherwise. Args: framework (str): Once of "tf", "torch", or None. Returns: str: The input framework string. """ if framework == "tf": try_import_tf(error=True) elif framework == "torch": try_import_torch(error=True) else: assert framework is None return framework def try_import_tf(error=False): """ Args: error (bool): Whether to raise an error if tf cannot be imported. Returns: The tf module (either from tf2.0.compat.v1 OR as tf1.x. """ if "RLLIB_TEST_NO_TF_IMPORT" in os.environ: logger.warning("Not importing TensorFlow for test purposes") return None try: if "TF_CPP_MIN_LOG_LEVEL" not in os.environ: os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" import tensorflow.compat.v1 as tf tf.logging.set_verbosity(tf.logging.ERROR) tf.disable_v2_behavior() return tf except ImportError: try: import tensorflow as tf return tf except ImportError as e: if error: raise e return None def try_import_tfp(error=False): """ Args: error (bool): Whether to raise an error if tfp cannot be imported. Returns: The tfp module. """ if "RLLIB_TEST_NO_TF_IMPORT" in os.environ: logger.warning("Not importing TensorFlow Probability for test " "purposes.") return None try: import tensorflow_probability as tfp return tfp except ImportError as e: if error: raise e return None def try_import_torch(error=False): """ Args: error (bool): Whether to raise an error if torch cannot be imported. Returns: tuple: torch AND torch.nn modules. """ if "RLLIB_TEST_NO_TORCH_IMPORT" in os.environ: logger.warning("Not importing Torch for test purposes.") return None, None try: import torch import torch.nn as nn return torch, nn except ImportError as e: if error: raise e return None, None