






'''simple docstring'''







import unittest

import numpy as np

from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
			import jax.numpy as jnp

			from transformers.models.albert.modeling_flax_albert import (
			    FlaxAlbertForMaskedLM,
			    FlaxAlbertForMultipleChoice,
			    FlaxAlbertForPreTraining,
			    FlaxAlbertForQuestionAnswering,
			    FlaxAlbertForSequenceClassification,
			    FlaxAlbertForTokenClassification,
			    FlaxAlbertModel,
			)

class _lowercase	(				unittest.TestCase		):




							def __init__(							self:				List[Any]			,							UpperCamelCase__:				str			,							UpperCamelCase__:				List[Any]=13			,							UpperCamelCase__:				Any=7			,							UpperCamelCase__:				List[Any]=True			,							UpperCamelCase__:				List[str]=True			,							UpperCamelCase__:				Optional[int]=True			,							UpperCamelCase__:				Optional[Any]=True			,							UpperCamelCase__:				List[str]=99			,							UpperCamelCase__:				Union[str, Any]=32			,							UpperCamelCase__:				Any=5			,							UpperCamelCase__:				Optional[Any]=4			,							UpperCamelCase__:				List[str]=37			,							UpperCamelCase__:				List[Any]="gelu"			,							UpperCamelCase__:				List[str]=0.1			,							UpperCamelCase__:				str=0.1			,							UpperCamelCase__:				Optional[Any]=512			,							UpperCamelCase__:				Any=16			,							UpperCamelCase__:				Dict=2			,							UpperCamelCase__:				Optional[int]=0.02			,							UpperCamelCase__:				Any=4			,							):
														lowerCamelCase__					:	str         =       parent
														lowerCamelCase__					:	Optional[Any]         =       batch_size
														lowerCamelCase__					:	List[str]         =       seq_length
														lowerCamelCase__					:	str         =       is_training
														lowerCamelCase__					:	Tuple         =       use_attention_mask
														lowerCamelCase__					:	int         =       use_token_type_ids
														lowerCamelCase__					:	Optional[Any]         =       use_labels
														lowerCamelCase__					:	Union[str, Any]         =       vocab_size
														lowerCamelCase__					:	int         =       hidden_size
														lowerCamelCase__					:	Dict         =       num_hidden_layers
														lowerCamelCase__					:	Dict         =       num_attention_heads
														lowerCamelCase__					:	List[str]         =       intermediate_size
														lowerCamelCase__					:	List[str]         =       hidden_act
														lowerCamelCase__					:	str         =       hidden_dropout_prob
														lowerCamelCase__					:	Dict         =       attention_probs_dropout_prob
														lowerCamelCase__					:	str         =       max_position_embeddings
														lowerCamelCase__					:	Tuple         =       type_vocab_size
														lowerCamelCase__					:	Optional[Any]         =       type_sequence_label_size
														lowerCamelCase__					:	List[Any]         =       initializer_range
														lowerCamelCase__					:	Optional[int]         =       num_choices




							def 		lowerCamelCase_				(							self:				Optional[Any]     ):
														lowerCamelCase__					:	Any         =       ids_tensor([self.batch_size, self.seq_length]			,							self.vocab_size     )

														lowerCamelCase__					:	str         =       None
														if self.use_attention_mask:
																					lowerCamelCase__					:	Optional[Any]         =       random_attention_mask([self.batch_size, self.seq_length]     )

														lowerCamelCase__					:	Union[str, Any]         =       None
														if self.use_token_type_ids:
																					lowerCamelCase__					:	Any         =       ids_tensor([self.batch_size, self.seq_length]			,							self.type_vocab_size     )

														lowerCamelCase__					:	Tuple         =       AlbertConfig(
														    vocab_size=self.vocab_size			,							hidden_size=self.hidden_size			,							num_hidden_layers=self.num_hidden_layers			,							num_attention_heads=self.num_attention_heads			,							intermediate_size=self.intermediate_size			,							hidden_act=self.hidden_act			,							hidden_dropout_prob=self.hidden_dropout_prob			,							attention_probs_dropout_prob=self.attention_probs_dropout_prob			,							max_position_embeddings=self.max_position_embeddings			,							type_vocab_size=self.type_vocab_size			,							is_decoder=SCREAMING_SNAKE_CASE__			,							initializer_range=self.initializer_range			,							)

														return config, input_ids, token_type_ids, attention_mask




							def 		lowerCamelCase_				(							self:				Any     ):
														lowerCamelCase__					:	Any         =       self.prepare_config_and_inputs()
														lowerCamelCase__					:	Tuple         =       config_and_inputs
														lowerCamelCase__					:	int         =       {'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
														return config, inputs_dict



@require_flax
class _lowercase	(				_lowercase				,      unittest.TestCase		):
							a				      =       (
							    (
							        FlaxAlbertModel,
							        FlaxAlbertForPreTraining,
							        FlaxAlbertForMaskedLM,
							        FlaxAlbertForMultipleChoice,
							        FlaxAlbertForQuestionAnswering,
							        FlaxAlbertForSequenceClassification,
							        FlaxAlbertForTokenClassification,
							        FlaxAlbertForQuestionAnswering,
							    )
							    if is_flax_available()
							    else ()
							)




							def 		lowerCamelCase_				(							self:				Optional[Any]     ):
														lowerCamelCase__					:	Any         =       FlaxAlbertModelTester(self     )




							@slow
							def 		lowerCamelCase_				(							self:				Dict     ):






														for model_class_name in self.all_model_classes:
																					lowerCamelCase__					:	Optional[Any]         =       model_class_name.from_pretrained("""albert-base-v2"""     )
																					lowerCamelCase__					:	int         =       model(np.ones((1, 1)     )     )
																					self.assertIsNotNone(SCREAMING_SNAKE_CASE__     )



@require_flax
class _lowercase	(				unittest.TestCase		):




							@slow
							def 		lowerCamelCase_				(							self:				Any     ):
														lowerCamelCase__					:	str         =       FlaxAlbertModel.from_pretrained("""albert-base-v2"""     )
														lowerCamelCase__					:	List[Any]         =       np.array([[0, 345, 232, 328, 740, 140, 1_695, 69, 6_078, 1_588, 2]]     )
														lowerCamelCase__					:	Dict         =       np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]     )
														lowerCamelCase__					:	Optional[Any]         =       model(SCREAMING_SNAKE_CASE__			,							attention_mask=SCREAMING_SNAKE_CASE__     )[0]
														lowerCamelCase__					:	Union[str, Any]         =       (1, 11, 768)
														self.assertEqual(output.shape			,							SCREAMING_SNAKE_CASE__     )
														lowerCamelCase__					:	List[str]         =       np.array(
														    [[[-0.6_513, 1.5_035, -0.2_766], [-0.6_515, 1.5_046, -0.2_780], [-0.6_512, 1.5_049, -0.2_784]]]     )

														self.assertTrue(jnp.allclose(output[:, 1:4, 1:4]			,							SCREAMING_SNAKE_CASE__			,							atol=1e-4     )     )








"""simple docstring"""
# Copyright 2021 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.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser



def      __lowerCamelCase   (							)			->      Any:
      __SCREAMING_SNAKE_CASE   :Tuple						=  ArgumentParser('''Accelerate CLI tool''' ,   usage='''accelerate <command> [<args>]''' ,   allow_abbrev=a_							)
      __SCREAMING_SNAKE_CASE   :str						=  parser.add_subparsers(help='''accelerate command helpers'''							)

      # Register commands
      get_config_parser(subparsers=a_							)
      env_command_parser(subparsers=a_							)
      launch_command_parser(subparsers=a_							)
      tpu_command_parser(subparsers=a_							)
      test_command_parser(subparsers=a_							)

      # Let's go
      __SCREAMING_SNAKE_CASE   :int						=  parser.parse_args()

      if not hasattr(a_ ,   '''func'''							):
            parser.print_help()
            exit(1							)

      # Run
      args.func(a_							)


if __name__ == "__main__":
  main()