



"""simple docstring"""






import random
import unittest

import numpy as np

import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax


if is_flax_available():
			import os

			import jax.numpy as jnp
			from jax import jit

			from transformers import AutoTokenizer, FlaxAutoModelForCausalLM
			from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model

			lowercase__  		=		"""0.12"""  # assumed parallelism: 8


if is_torch_available():
			import torch







def   _snake_case    (       lowercase__							,					lowercase__							,					lowercase__=None	):



				if rng is None:
								_lowerCamelCase  :    List[Any]					=					random.Random()

				_lowerCamelCase  :    Dict					=					1
				for dim in shape:
								total_dims *= dim

				_lowerCamelCase  :    Optional[Any]					=					[]
				for _ in range(_lowerCamelCase	):
								values.append(rng.randint(0							,					vocab_size - 1	)	)

				_lowerCamelCase  :    int					=					np.array(_lowerCamelCase							,					dtype=jnp.intaa	).reshape(_lowerCamelCase	)

				return output







def   _snake_case    (       lowercase__							,					lowercase__=None	):
				_lowerCamelCase  :    Tuple					=					ids_tensor(_lowerCamelCase							,					vocab_size=2							,					rng=_lowerCamelCase	)
				# make sure that at least one token is attended to for each batch
				_lowerCamelCase  :    str					=					1
				return attn_mask






@require_flax
class lowerCAmelCase__			:






			'''simple docstring'''



			lowerCamelCase__   =    None
			lowerCamelCase__   =    ()
			def       A_					(						self						):
							_lowerCamelCase  :    str					=					self.model_tester.prepare_config_and_inputs_for_common()

							# cut to half length & take max batch_size 3
							_lowerCamelCase  :    Union[str, Any]					=					2
							_lowerCamelCase  :    Union[str, Any]					=					inputs['input_ids'].shape[-1] // 2
							_lowerCamelCase  :    Tuple					=					inputs['input_ids'][:max_batch_size, :sequence_length]

							_lowerCamelCase  :    int					=					jnp.ones_like(_A						)
							_lowerCamelCase  :    List[Any]					=					attention_mask[:max_batch_size, :sequence_length]

							# generate max 5 tokens
							_lowerCamelCase  :    List[Any]					=					input_ids.shape[-1] + 5
							if config.eos_token_id is not None and config.pad_token_id is None:
											# hack to allow generate for models such as GPT2 as is done in `generate()`
											_lowerCamelCase  :    Union[str, Any]					=					config.eos_token_id
							return config, input_ids, attention_mask, max_length
			@is_pt_flax_cross_test
			def       A_					(						self						):
							_lowerCamelCase  :    Tuple					=					self._get_input_ids_and_config()
							_lowerCamelCase  :    Dict					=					False
							_lowerCamelCase  :    Dict					=					max_length
							_lowerCamelCase  :    Tuple					=					0

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    Dict					=					model_class(_A						)

											_lowerCamelCase  :    Any					=					model_class.__name__[4:]  # Skip the "Flax" at the beginning
											_lowerCamelCase  :    List[str]					=					getattr(_A						,   _A						)
											_lowerCamelCase  :    Union[str, Any]					=					pt_model_class(_A						).eval()
											_lowerCamelCase  :    Tuple					=					load_flax_weights_in_pytorch_model(_A						,   flax_model.params						)

											_lowerCamelCase  :    Union[str, Any]					=					flax_model.generate(_A						).sequences
											_lowerCamelCase  :    str					=					pt_model.generate(torch.tensor(_A						,   dtype=torch.long						)						)

											if flax_generation_outputs.shape[-1] > pt_generation_outputs.shape[-1]:
															_lowerCamelCase  :    int					=					flax_generation_outputs[:, : pt_generation_outputs.shape[-1]]

											self.assertListEqual(pt_generation_outputs.numpy().tolist()						,   flax_generation_outputs.tolist()						)
			def       A_					(						self						):
							_lowerCamelCase  :    Optional[int]					=					self._get_input_ids_and_config()
							_lowerCamelCase  :    str					=					False
							_lowerCamelCase  :    Optional[Any]					=					max_length

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    Union[str, Any]					=					model_class(_A						)

											_lowerCamelCase  :    Union[str, Any]					=					model.generate(_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    Any					=					jit(model.generate						)
											_lowerCamelCase  :    Dict					=					jit_generate(_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)
			def       A_					(						self						):
							_lowerCamelCase  :    Any					=					self._get_input_ids_and_config()
							_lowerCamelCase  :    Union[str, Any]					=					True
							_lowerCamelCase  :    Union[str, Any]					=					max_length

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    Tuple					=					model_class(_A						)

											_lowerCamelCase  :    Any					=					model.generate(_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    Optional[Any]					=					jit(model.generate						)
											_lowerCamelCase  :    Tuple					=					jit_generate(_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)
			def       A_					(						self						):
							_lowerCamelCase  :    Tuple					=					self._get_input_ids_and_config()
							_lowerCamelCase  :    str					=					False
							_lowerCamelCase  :    List[str]					=					max_length
							_lowerCamelCase  :    int					=					2

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    List[Any]					=					model_class(_A						)

											_lowerCamelCase  :    Tuple					=					model.generate(_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    List[str]					=					jit(model.generate						)
											_lowerCamelCase  :    Optional[Any]					=					jit_generate(_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)
			def       A_					(						self						):
							_lowerCamelCase  :    Union[str, Any]					=					self._get_input_ids_and_config()
							_lowerCamelCase  :    int					=					False
							_lowerCamelCase  :    Dict					=					max_length
							_lowerCamelCase  :    Optional[Any]					=					2
							_lowerCamelCase  :    List[str]					=					2

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    Optional[Any]					=					model_class(_A						)

											_lowerCamelCase  :    str					=					model.generate(_A						).sequences
											self.assertEqual(generation_outputs.shape[0]						,   input_ids.shape[0] * config.num_return_sequences						)
			def       A_					(						self						):
							_lowerCamelCase  :    Any					=					self._get_input_ids_and_config()
							_lowerCamelCase  :    Optional[int]					=					True
							_lowerCamelCase  :    int					=					max_length
							_lowerCamelCase  :    str					=					0.8
							_lowerCamelCase  :    List[Any]					=					10
							_lowerCamelCase  :    Any					=					0.3
							_lowerCamelCase  :    int					=					1
							_lowerCamelCase  :    int					=					8
							_lowerCamelCase  :    Tuple					=					9

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    List[Any]					=					model_class(_A						)

											_lowerCamelCase  :    Any					=					model.generate(_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    Any					=					jit(model.generate						)
											_lowerCamelCase  :    Optional[int]					=					jit_generate(_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)
			def       A_					(						self						):
							_lowerCamelCase  :    Optional[Any]					=					self._get_input_ids_and_config()
							_lowerCamelCase  :    Dict					=					max_length
							_lowerCamelCase  :    int					=					1
							_lowerCamelCase  :    str					=					8
							_lowerCamelCase  :    Optional[int]					=					9

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    int					=					model_class(_A						)

											_lowerCamelCase  :    Union[str, Any]					=					model.generate(_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    str					=					jit(model.generate						)
											_lowerCamelCase  :    Union[str, Any]					=					jit_generate(_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)
			def       A_					(						self						):
							_lowerCamelCase  :    int					=					self._get_input_ids_and_config()
							_lowerCamelCase  :    Optional[Any]					=					max_length
							_lowerCamelCase  :    Dict					=					2
							_lowerCamelCase  :    Optional[Any]					=					1
							_lowerCamelCase  :    List[Any]					=					8
							_lowerCamelCase  :    List[str]					=					9

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    List[str]					=					model_class(_A						)

											_lowerCamelCase  :    List[Any]					=					model.generate(_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    str					=					jit(model.generate						)
											_lowerCamelCase  :    str					=					jit_generate(_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)
			def       A_					(						self						):
							_lowerCamelCase  :    Union[str, Any]					=					self._get_input_ids_and_config()

							# pad attention mask on the left
							_lowerCamelCase  :    Union[str, Any]					=					attention_mask.at[(0, 0)].set(0						)

							_lowerCamelCase  :    Optional[Any]					=					False
							_lowerCamelCase  :    Optional[int]					=					max_length

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    List[str]					=					model_class(_A						)

											_lowerCamelCase  :    Optional[int]					=					model.generate(_A						,   attention_mask=_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    Optional[int]					=					jit(model.generate						)
											_lowerCamelCase  :    Optional[Any]					=					jit_generate(_A						,   attention_mask=_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)
			def       A_					(						self						):
							_lowerCamelCase  :    Optional[Any]					=					self._get_input_ids_and_config()

							# pad attention mask on the left
							_lowerCamelCase  :    Dict					=					attention_mask.at[(0, 0)].set(0						)

							_lowerCamelCase  :    List[Any]					=					True
							_lowerCamelCase  :    Any					=					max_length

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    str					=					model_class(_A						)

											_lowerCamelCase  :    Any					=					model.generate(_A						,   attention_mask=_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    Any					=					jit(model.generate						)
											_lowerCamelCase  :    Dict					=					jit_generate(_A						,   attention_mask=_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)






			def       A_					(						self						):
							_lowerCamelCase  :    Optional[int]					=					self._get_input_ids_and_config()

							# pad attention mask on the left
							_lowerCamelCase  :    Optional[int]					=					attention_mask.at[(0, 0)].set(0						)

							_lowerCamelCase  :    Dict					=					2
							_lowerCamelCase  :    Any					=					max_length

							for model_class in self.all_generative_model_classes:
											_lowerCamelCase  :    List[Any]					=					model_class(_A						)

											_lowerCamelCase  :    Union[str, Any]					=					model.generate(_A						,   attention_mask=_A						).sequences
											self.assertEqual(generation_outputs.shape[-1]						,   _A						)

											_lowerCamelCase  :    Any					=					jit(model.generate						)
											_lowerCamelCase  :    Any					=					jit_generate(_A						,   attention_mask=_A						).sequences

											self.assertListEqual(generation_outputs.tolist()						,   jit_generation_outputs.tolist()						)






@require_flax
class lowerCAmelCase__			(  unittest.TestCase		):






			'''simple docstring'''



			def       A_					(						self						):
							_lowerCamelCase  :    List[str]					=					AutoTokenizer.from_pretrained('hf-internal-testing/tiny-bert'						)
							_lowerCamelCase  :    List[Any]					=					FlaxAutoModelForCausalLM.from_pretrained('hf-internal-testing/tiny-bert-flax-only'						)

							_lowerCamelCase  :    Any					=					'Hello world'
							_lowerCamelCase  :    Tuple					=					tokenizer(_A						,   return_tensors='np'						).input_ids

							# typos are quickly detected (the correct argument is `do_sample`)
							with self.assertRaisesRegex(_A						,   'do_samples'						):
											model.generate(_A						,   do_samples=_A						)

							# arbitrary arguments that will not be used anywhere are also not accepted
							with self.assertRaisesRegex(_A						,   'foo'						):
											_lowerCamelCase  :    List[Any]					=					{'foo': 'bar'}
											model.generate(_A						,   **_A						)





"""simple docstring"""






lowercase__  		=		[
    999,
    800,
    799,
    600,
    599,
    500,
    400,
    399,
    377,
    355,
    333,
    311,
    288,
    266,
    244,
    222,
    200,
    199,
    177,
    155,
    133,
    111,
    88,
    66,
    44,
    22,
    0,
]

lowercase__  		=		[
    999,
    976,
    952,
    928,
    905,
    882,
    858,
    857,
    810,
    762,
    715,
    714,
    572,
    429,
    428,
    286,
    285,
    238,
    190,
    143,
    142,
    118,
    95,
    71,
    47,
    24,
    0,
]

lowercase__  		=		[
    999,
    988,
    977,
    966,
    955,
    944,
    933,
    922,
    911,
    900,
    899,
    879,
    859,
    840,
    820,
    800,
    799,
    766,
    733,
    700,
    699,
    650,
    600,
    599,
    500,
    499,
    400,
    399,
    350,
    300,
    299,
    266,
    233,
    200,
    199,
    179,
    159,
    140,
    120,
    100,
    99,
    88,
    77,
    66,
    55,
    44,
    33,
    22,
    11,
    0,
]

lowercase__  		=		[
    999,
    995,
    992,
    989,
    985,
    981,
    978,
    975,
    971,
    967,
    964,
    961,
    957,
    956,
    951,
    947,
    942,
    937,
    933,
    928,
    923,
    919,
    914,
    913,
    908,
    903,
    897,
    892,
    887,
    881,
    876,
    871,
    870,
    864,
    858,
    852,
    846,
    840,
    834,
    828,
    827,
    820,
    813,
    806,
    799,
    792,
    785,
    784,
    777,
    770,
    763,
    756,
    749,
    742,
    741,
    733,
    724,
    716,
    707,
    699,
    698,
    688,
    677,
    666,
    656,
    655,
    645,
    634,
    623,
    613,
    612,
    598,
    584,
    570,
    569,
    555,
    541,
    527,
    526,
    505,
    484,
    483,
    462,
    440,
    439,
    396,
    395,
    352,
    351,
    308,
    307,
    264,
    263,
    220,
    219,
    176,
    132,
    88,
    44,
    0,
]

lowercase__  		=		[
    999,
    997,
    995,
    992,
    990,
    988,
    986,
    984,
    981,
    979,
    977,
    975,
    972,
    970,
    968,
    966,
    964,
    961,
    959,
    957,
    956,
    954,
    951,
    949,
    946,
    944,
    941,
    939,
    936,
    934,
    931,
    929,
    926,
    924,
    921,
    919,
    916,
    914,
    913,
    910,
    907,
    905,
    902,
    899,
    896,
    893,
    891,
    888,
    885,
    882,
    879,
    877,
    874,
    871,
    870,
    867,
    864,
    861,
    858,
    855,
    852,
    849,
    846,
    843,
    840,
    837,
    834,
    831,
    828,
    827,
    824,
    821,
    817,
    814,
    811,
    808,
    804,
    801,
    798,
    795,
    791,
    788,
    785,
    784,
    780,
    777,
    774,
    770,
    766,
    763,
    760,
    756,
    752,
    749,
    746,
    742,
    741,
    737,
    733,
    730,
    726,
    722,
    718,
    714,
    710,
    707,
    703,
    699,
    698,
    694,
    690,
    685,
    681,
    677,
    673,
    669,
    664,
    660,
    656,
    655,
    650,
    646,
    641,
    636,
    632,
    627,
    622,
    618,
    613,
    612,
    607,
    602,
    596,
    591,
    586,
    580,
    575,
    570,
    569,
    563,
    557,
    551,
    545,
    539,
    533,
    527,
    526,
    519,
    512,
    505,
    498,
    491,
    484,
    483,
    474,
    466,
    457,
    449,
    440,
    439,
    428,
    418,
    407,
    396,
    395,
    381,
    366,
    352,
    351,
    330,
    308,
    307,
    286,
    264,
    263,
    242,
    220,
    219,
    176,
    175,
    132,
    131,
    88,
    44,
    0,
]

lowercase__  		=		[
    999,
    991,
    982,
    974,
    966,
    958,
    950,
    941,
    933,
    925,
    916,
    908,
    900,
    899,
    874,
    850,
    825,
    800,
    799,
    700,
    600,
    500,
    400,
    300,
    200,
    100,
    0,
]

lowercase__  		=		[
    999,
    992,
    985,
    978,
    971,
    964,
    957,
    949,
    942,
    935,
    928,
    921,
    914,
    907,
    900,
    899,
    879,
    859,
    840,
    820,
    800,
    799,
    766,
    733,
    700,
    699,
    650,
    600,
    599,
    500,
    499,
    400,
    399,
    300,
    299,
    200,
    199,
    100,
    99,
    0,
]

lowercase__  		=		[
    999,
    996,
    992,
    989,
    985,
    982,
    979,
    975,
    972,
    968,
    965,
    961,
    958,
    955,
    951,
    948,
    944,
    941,
    938,
    934,
    931,
    927,
    924,
    920,
    917,
    914,
    910,
    907,
    903,
    900,
    899,
    891,
    884,
    876,
    869,
    861,
    853,
    846,
    838,
    830,
    823,
    815,
    808,
    800,
    799,
    788,
    777,
    766,
    755,
    744,
    733,
    722,
    711,
    700,
    699,
    688,
    677,
    666,
    655,
    644,
    633,
    622,
    611,
    600,
    599,
    585,
    571,
    557,
    542,
    528,
    514,
    500,
    499,
    485,
    471,
    457,
    442,
    428,
    414,
    400,
    399,
    379,
    359,
    340,
    320,
    300,
    299,
    279,
    259,
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