




'''simple docstring'''



# 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_							:	str	     =		'''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)












# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


a__		     =     logging.get_logger(__name__)

a__		     =     {}
a__		     =     {}
a__		     =     {}





def 				A__ (snake_case   :		type		,	snake_case   :		Optional[str]		,	snake_case   :		Optional[List[str]] = None		,	)     ->						str:
					__UpperCamelCase					:	int             =      aliases if aliases is not None else []
					if format_type in _FORMAT_TYPES:
										logger.warning(
										    F'''Overwriting format type \'{format_type}\' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})'''				)
					__UpperCamelCase					:	Optional[Any]             =      formatter_cls
					for alias in set(aliases + [format_type]				):
										if alias in _FORMAT_TYPES_ALIASES:
															logger.warning(
															    F'''Overwriting format type alias \'{alias}\' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})'''				)
										__UpperCamelCase					:	Optional[int]             =      format_type





def 				A__ (snake_case   :		Exception		,	snake_case   :		Optional[str]		,	snake_case   :		Optional[List[str]] = None				)     ->						Tuple:
					__UpperCamelCase					:	List[Any]             =      aliases if aliases is not None else []
					for alias in set(aliases + [format_type]				):
										__UpperCamelCase					:	Optional[int]             =      unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=['''python'''])
_register_formatter(ArrowFormatter, '''arrow''', aliases=['''pa''', '''pyarrow'''])
_register_formatter(NumpyFormatter, '''numpy''', aliases=['''np'''])
_register_formatter(PandasFormatter, '''pandas''', aliases=['''pd'''])
_register_formatter(CustomFormatter, '''custom''')

if config.TORCH_AVAILABLE:
	from .torch_formatter import TorchFormatter

	_register_formatter(TorchFormatter, '''torch''', aliases=['''pt''', '''pytorch'''])
else:
	a__		     =     ValueError('''PyTorch needs to be installed to be able to return PyTorch tensors.''')
	_register_unavailable_formatter(_torch_error, '''torch''', aliases=['''pt''', '''pytorch'''])

if config.TF_AVAILABLE:
	from .tf_formatter import TFFormatter

	_register_formatter(TFFormatter, '''tensorflow''', aliases=['''tf'''])
else:
	a__		     =     ValueError('''Tensorflow needs to be installed to be able to return Tensorflow tensors.''')
	_register_unavailable_formatter(_tf_error, '''tensorflow''', aliases=['''tf'''])

if config.JAX_AVAILABLE:
	from .jax_formatter import JaxFormatter

	_register_formatter(JaxFormatter, '''jax''', aliases=[])
else:
	a__		     =     ValueError('''JAX needs to be installed to be able to return JAX arrays.''')
	_register_unavailable_formatter(_jax_error, '''jax''', aliases=[])





def 				A__ (snake_case   :		Optional[str]				)     ->						Optional[str]:
					if format_type in _FORMAT_TYPES_ALIASES:
										return _FORMAT_TYPES_ALIASES[format_type]
					else:
										return format_type







def 				A__ (snake_case   :		Optional[str]		,	**snake_case   :		List[str]				)     ->						Formatter:
					__UpperCamelCase					:	int             =      get_format_type_from_alias(snake_case				)
					if format_type in _FORMAT_TYPES:
										return _FORMAT_TYPES[format_type](**snake_case				)
					if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
										raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
					else:
										raise ValueError(
										    F'''Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None				)}, but got \'{format_type}\''''				)






