



import inspect
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase							 =					"""src/transformers"""


# This is to make sure the transformers module imported is the one in the repo.
UpperCAmelCase							 =					direct_transformers_import(PATH_TO_TRANSFORMERS)

UpperCAmelCase							 =					transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
UpperCAmelCase							 =					re.compile(R"""\[(.+?)\]\((https://huggingface\.co/.+?)\)""")


UpperCAmelCase							 =					{
    """DecisionTransformerConfig""",
    """EncoderDecoderConfig""",
    """MusicgenConfig""",
    """RagConfig""",
    """SpeechEncoderDecoderConfig""",
    """TimmBackboneConfig""",
    """VisionEncoderDecoderConfig""",
    """VisionTextDualEncoderConfig""",
    """LlamaConfig""",
}

def 			A_      (	__a     :				Optional[Any]		):

				"""simple docstring"""
				a__				      =		None

				# source code of `config_class`
				a__				      =		inspect.getsource(__a		)
				a__				      =		_re_checkpoint.findall(__a		)

				# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
				# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
				for ckpt_name, ckpt_link in checkpoints:
								# allow the link to end with `/`
								if ckpt_link.endswith("""/"""		):
												a__				      =		ckpt_link[:-1]

								# verify the checkpoint name corresponds to the checkpoint link
								a__				      =		F'''https://huggingface.co/{ckpt_name}'''
								if ckpt_link == ckpt_link_from_name:
												a__				      =		ckpt_name
												break

				return checkpoint

def 			A_      (	):

				"""simple docstring"""
				a__				      =		[]

				for config_class in list(CONFIG_MAPPING.values()		):
								# Skip deprecated models
								if "models.deprecated" in config_class.__module__:
												continue
								a__				      =		get_checkpoint_from_config_class(__a		)

								a__				      =		config_class.__name__
								if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
												configs_without_checkpoint.append(__a		)

				if len(__a		) > 0:
								a__				      =		"""\n""".join(sorted(__a		)		)
								raise ValueError(F'''The following configurations don\'t contain any valid checkpoint:\n{message}'''		)


if __name__ == "__main__":
	check_config_docstrings_have_checkpoints()






# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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.

# this script dumps information about the environment

import os
import sys

import transformers


UpperCAmelCase							 =					"""3"""

print("""Python version:""", sys.version)
print("""transformers version:""", transformers.__version__)

try:
	import torch

	print("""Torch version:""", torch.__version__)
	print("""Cuda available:""", torch.cuda.is_available())
	print("""Cuda version:""", torch.version.cuda)
	print("""CuDNN version:""", torch.backends.cudnn.version())
	print("""Number of GPUs available:""", torch.cuda.device_count())
	print("""NCCL version:""", torch.cuda.nccl.version())
except ImportError:
	print("""Torch version:""", None)

try:
	import deepspeed

	print("""DeepSpeed version:""", deepspeed.__version__)
except ImportError:
	print("""DeepSpeed version:""", None)

try:
	import tensorflow as tf

	print("""TensorFlow version:""", tf.__version__)
	print("""TF GPUs available:""", bool(tf.config.list_physical_devices("""GPU""")))
	print("""Number of TF GPUs available:""", len(tf.config.list_physical_devices("""GPU""")))
except ImportError:
	print("""TensorFlow version:""", None)

