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