optimum/commands/env.py (39 lines of code) (raw):

# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import platform import huggingface_hub from transformers import __version__ as transformers_version from transformers.utils import is_tf_available, is_torch_available from ..version import __version__ as version from . import BaseOptimumCLICommand, CommandInfo class EnvironmentCommand(BaseOptimumCLICommand): COMMAND = CommandInfo(name="env", help="Get information about the environment used.") @staticmethod def format_dict(d): return "\n".join([f"- {prop}: {val}" for prop, val in d.items()]) + "\n" def run(self): pt_version = "not installed" pt_cuda_available = "NA" if is_torch_available(): import torch pt_version = torch.__version__ pt_cuda_available = torch.cuda.is_available() tf_version = "not installed" tf_cuda_available = "NA" if is_tf_available(): import tensorflow as tf tf_version = tf.__version__ try: # deprecated in v2.1 tf_cuda_available = tf.test.is_gpu_available() except AttributeError: # returns list of devices, convert to bool tf_cuda_available = bool(tf.config.list_physical_devices("GPU")) info = { "`optimum` version": version, "`transformers` version": transformers_version, "Platform": platform.platform(), "Python version": platform.python_version(), "Huggingface_hub version": huggingface_hub.__version__, "PyTorch version (GPU?)": f"{pt_version} (cuda availabe: {pt_cuda_available})", "Tensorflow version (GPU?)": f"{tf_version} (cuda availabe: {tf_cuda_available})", } print("\nCopy-and-paste the text below in your GitHub issue:\n") print(self.format_dict(info)) return info