
'''simple docstring'''







import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: Union[str, Any]							):



						"""simple docstring"""





						return EnvironmentCommand()
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: Dict							):



						"""simple docstring"""





						return EnvironmentCommand(args.accelerate_config_file							)






class  lowerCAmelCase__   (  lowerCamelCase_     ):






					@staticmethod
					def 	_snake_case    (   __SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_	:     List[str]													=       parser.add_parser('''env'''		)
											download_parser.set_defaults(func=__SCREAMING_SNAKE_CASE		)
											download_parser.add_argument(
											    '''--accelerate-config_file'''				,							default=__SCREAMING_SNAKE_CASE				,							help='''The accelerate config file to use for the default values in the launching script.'''				,							)
											download_parser.set_defaults(func=__SCREAMING_SNAKE_CASE		)






					def __init__(   self				,							__SCREAMING_SNAKE_CASE				,							*__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_	:     Optional[int]													=       accelerate_config_file






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Any													=       '''not installed'''
											if is_safetensors_available():
																	import safetensors

																	lowercase_	:     int													=       safetensors.__version__
											elif importlib.util.find_spec('''safetensors'''		) is not None:
																	import safetensors

																	lowercase_	:     Any													=       F'''{safetensors.__version__} but is ignored because of PyTorch version too old.'''

											lowercase_	:     Optional[Any]													=       '''not installed'''
											lowercase_	:     str													=       '''not found'''
											if is_accelerate_available():
																	import accelerate
																	from accelerate.commands.config import default_config_file, load_config_from_file

																	lowercase_	:     Union[str, Any]													=       accelerate.__version__
																	# Get the default from the config file.
																	if self._accelerate_config_file is not None or os.path.isfile(__SCREAMING_SNAKE_CASE		):
																							lowercase_	:     List[Any]													=       load_config_from_file(self._accelerate_config_file		).to_dict()

																	lowercase_	:     List[str]													=       (
																	    '''\n'''.join([F'''\t- {prop}: {val}''' for prop, val in accelerate_config.items()]		)
																	    if isinstance(__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		)
																	    else F'''\t{accelerate_config}'''
																	)

											lowercase_	:     str													=       '''not installed'''
											lowercase_	:     Any													=       '''NA'''
											if is_torch_available():
																	import torch

																	lowercase_	:     str													=       torch.__version__
																	lowercase_	:     Dict													=       torch.cuda.is_available()

											lowercase_	:     Optional[int]													=       '''not installed'''
											lowercase_	:     str													=       '''NA'''
											if is_tf_available():
																	import tensorflow as tf

																	lowercase_	:     int													=       tf.__version__
																	try:
																							# deprecated in v2.1
																							lowercase_	:     List[Any]													=       tf.test.is_gpu_available()
																	except AttributeError:
																							# returns list of devices, convert to bool
																							lowercase_	:     Dict													=       bool(tf.config.list_physical_devices('''GPU'''		)		)

											lowercase_	:     List[str]													=       '''not installed'''
											lowercase_	:     Dict													=       '''not installed'''
											lowercase_	:     List[Any]													=       '''not installed'''
											lowercase_	:     Optional[Any]													=       '''NA'''
											if is_flax_available():
																	import flax
																	import jax
																	import jaxlib

																	lowercase_	:     str													=       flax.__version__
																	lowercase_	:     List[str]													=       jax.__version__
																	lowercase_	:     int													=       jaxlib.__version__
																	lowercase_	:     Any													=       jax.lib.xla_bridge.get_backend().platform

											lowercase_	:     Dict													=       {
											    '''`transformers` version''': version,
											    '''Platform''': platform.platform(),
											    '''Python version''': platform.python_version(),
											    '''Huggingface_hub version''': huggingface_hub.__version__,
											    '''Safetensors version''': F'''{safetensors_version}''',
											    '''Accelerate version''': F'''{accelerate_version}''',
											    '''Accelerate config''': F'''{accelerate_config_str}''',
											    '''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(__SCREAMING_SNAKE_CASE		)		)

											return info






					@staticmethod
					def 	_snake_case    (   __SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]		) + "\n"





'''simple docstring'''







import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
							from transformers import AutoModelForSeqaSeqLM, AutoTokenizer






@require_torch
@require_sentencepiece
@require_tokenizers
class  lowerCAmelCase__   (  unittest.TestCase     ):






					@slow
					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Dict													=       AutoModelForSeqaSeqLM.from_pretrained('''google/mt5-small'''				,							return_dict=__SCREAMING_SNAKE_CASE		).to(__SCREAMING_SNAKE_CASE		)
											lowercase_	:     Union[str, Any]													=       AutoTokenizer.from_pretrained('''google/mt5-small'''		)

											lowercase_	:     int													=       tokenizer('''Hello there'''				,							return_tensors='''pt'''		).input_ids
											lowercase_	:     Union[str, Any]													=       tokenizer('''Hi I am'''				,							return_tensors='''pt'''		).input_ids

											lowercase_	:     Union[str, Any]													=       model(input_ids.to(__SCREAMING_SNAKE_CASE		)				,							labels=labels.to(__SCREAMING_SNAKE_CASE		)		).loss
											lowercase_	:     int													=       -(labels.shape[-1] * loss.item())

											lowercase_	:     Any													=       -84.9_127
											self.assertTrue(abs(mtf_score - EXPECTED_SCORE		) < 1E-4		)



