FM / commands

/usr/local/lib/python3.6/site-packages/transformers/commands/

/usr/local/lib/python3.6/site-packages/transformers/commands

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
add_new_model.py	10664	0644	edit dl rm
add_new_model_like.py	63801	0644	edit dl rm
convert.py	7871	0644	edit dl rm
download.py	1860	0644	edit dl rm
env.py	3310	0644	edit dl rm
lfs.py	7948	0644	edit dl rm
run.py	4249	0644	edit dl rm
serving.py	8027	0644	edit dl rm
train.py	6347	0644	edit dl rm
transformers_cli.py	1956	0644	edit dl rm
user.py	8415	0644	edit dl rm
__init__.py	923	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/commands/env.py (3310B)

# Copyright 2020 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
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_flax_available, is_tf_available, is_torch_available
from . import BaseTransformersCLICommand

def info_command_factory(_):
    return EnvironmentCommand()

class EnvironmentCommand(BaseTransformersCLICommand):
    @staticmethod
    def register_subcommand(parser: ArgumentParser):
        download_parser = parser.add_parser("env")
        download_parser.set_defaults(func=info_command_factory)

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"))

flax_version = "not installed"
        jax_version = "not installed"
        jaxlib_version = "not installed"
        jax_backend = "NA"
        if is_flax_available():
            import flax
            import jax
            import jaxlib

flax_version = flax.__version__
            jax_version = jax.__version__
            jaxlib_version = jaxlib.__version__
            jax_backend = jax.lib.xla_bridge.get_backend().platform

info = {
            "`transformers` version": version,
            "Platform": platform.platform(),
            "Python version": platform.python_version(),
            "Huggingface_hub version": huggingface_hub.__version__,
            "PyTorch version (GPU?)": f"{pt_version} ({pt_cuda_available})",
            "Tensorflow version (GPU?)": f"{tf_version} ({tf_cuda_available})",
            "Flax version (CPU?/GPU?/TPU?)": f"{flax_version} ({jax_backend})",
            "Jax version": f"{jax_version}",
            "JaxLib version": f"{jaxlib_version}",
            "Using GPU in script?": "<fill in>",
            "Using distributed or parallel set-up in script?": "<fill in>",
        }

print("\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n")
        print(self.format_dict(info))

return info

@staticmethod
    def format_dict(d):
        return "\n".join([f"- {prop}: {val}" for prop, val in d.items()]) + "\n"

cmd: