






'''simple docstring'''




from __future__ import annotations

import random
import unittest

from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
		import tensorflow as tf

		from transformers import (
		    TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFTransfoXLForSequenceClassification,
		    TFTransfoXLLMHeadModel,
		    TFTransfoXLModel,
		)

class       __lowercase					:

	def __init__(      self   :						Optional[Any]  ,					UpperCAmelCase_   :						Any  ,					):
			UpperCamelCase__				:					Optional[Any]					=					parent
			UpperCamelCase__				:					Union[str, Any]					=					13
			UpperCamelCase__				:					Dict					=					7
			UpperCamelCase__				:					Optional[int]					=					30
			UpperCamelCase__				:					Optional[Any]					=					self.seq_length + self.mem_len
			UpperCamelCase__				:					Optional[Any]					=					15
			UpperCamelCase__				:					Optional[int]					=					True
			UpperCamelCase__				:					Union[str, Any]					=					True
			UpperCamelCase__				:					Dict					=					99
			UpperCamelCase__				:					Optional[Any]					=					[10, 50, 80]
			UpperCamelCase__				:					List[str]					=					32
			UpperCamelCase__				:					str					=					32
			UpperCamelCase__				:					Tuple					=					4
			UpperCamelCase__				:					Tuple					=					8
			UpperCamelCase__				:					Dict					=					128
			UpperCamelCase__				:					str					=					2
			UpperCamelCase__				:					Tuple					=					2
			UpperCamelCase__				:					Tuple					=					None
			UpperCamelCase__				:					Dict					=					1
			UpperCamelCase__				:					Optional[Any]					=					0
			UpperCamelCase__				:					List[str]					=					3
			UpperCamelCase__				:					Dict					=					self.vocab_size - 1
			UpperCamelCase__				:					Tuple					=					0.01

	def      __UpperCamelCase							(      self   :						Optional[int]):
			UpperCamelCase__				:					Union[str, Any]					=					ids_tensor([self.batch_size, self.seq_length]  ,					self.vocab_size)
			UpperCamelCase__				:					int					=					ids_tensor([self.batch_size, self.seq_length]  ,					self.vocab_size)

			UpperCamelCase__				:					List[Any]					=					None
			if self.use_labels:
					UpperCamelCase__				:					List[str]					=					ids_tensor([self.batch_size, self.seq_length]  ,					self.vocab_size)

			UpperCamelCase__				:					List[str]					=					TransfoXLConfig(
			    vocab_size=self.vocab_size  ,					mem_len=self.mem_len  ,					clamp_len=self.clamp_len  ,					cutoffs=self.cutoffs  ,					d_model=self.hidden_size  ,					d_embed=self.d_embed  ,					n_head=self.num_attention_heads  ,					d_head=self.d_head  ,					d_inner=self.d_inner  ,					div_val=self.div_val  ,					n_layer=self.num_hidden_layers  ,					eos_token_id=self.eos_token_id  ,					pad_token_id=self.vocab_size - 1  ,					init_range=self.init_range  ,					num_labels=self.num_labels  ,					)

			return (config, input_ids_a, input_ids_a, lm_labels)

	def      __UpperCamelCase							(      self   :						List[str]):
			random.seed(self.seed)
			tf.random.set_seed(self.seed)

	def      __UpperCamelCase							(      self   :						str  ,					UpperCAmelCase_   :						List[str]  ,					UpperCAmelCase_   :						Optional[Any]  ,					UpperCAmelCase_   :						Tuple  ,					UpperCAmelCase_   :						Dict):
			UpperCamelCase__				:					Optional[int]					=					TFTransfoXLModel(lowercase__)

			UpperCamelCase__				:					List[Any]					=					model(lowercase__).to_tuple()

			UpperCamelCase__				:					Union[str, Any]					=					{'''input_ids''': input_ids_a, '''mems''': mems_a}

			UpperCamelCase__				:					Tuple					=					model(lowercase__).to_tuple()

			self.parent.assertEqual(hidden_states_a.shape  ,					(self.batch_size, self.seq_length, self.hidden_size))
			self.parent.assertEqual(hidden_states_a.shape  ,					(self.batch_size, self.seq_length, self.hidden_size))
			self.parent.assertListEqual(
			    [mem.shape for mem in mems_a]  ,					[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers  ,					)
			self.parent.assertListEqual(
			    [mem.shape for mem in mems_a]  ,					[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers  ,					)

	def      __UpperCamelCase							(      self   :						Union[str, Any]  ,					UpperCAmelCase_   :						Tuple  ,					UpperCAmelCase_   :						str  ,					UpperCAmelCase_   :						int  ,					UpperCAmelCase_   :						Union[str, Any]):
			UpperCamelCase__				:					str					=					TFTransfoXLLMHeadModel(lowercase__)

			UpperCamelCase__				:					Dict					=					model(lowercase__).to_tuple()

			UpperCamelCase__				:					int					=					{'''input_ids''': input_ids_a, '''labels''': lm_labels}
			UpperCamelCase__				:					Optional[int]					=					model(lowercase__).to_tuple()

			UpperCamelCase__				:					List[str]					=					model([input_ids_a, mems_a]).to_tuple()

			UpperCamelCase__				:					Optional[Any]					=					{'''input_ids''': input_ids_a, '''mems''': mems_a, '''labels''': lm_labels}

			UpperCamelCase__				:					List[str]					=					model(lowercase__).to_tuple()

			self.parent.assertEqual(lm_logits_a.shape  ,					(self.batch_size, self.seq_length, self.vocab_size))
			self.parent.assertListEqual(
			    [mem.shape for mem in mems_a]  ,					[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers  ,					)

			self.parent.assertEqual(lm_logits_a.shape  ,					(self.batch_size, self.seq_length, self.vocab_size))
			self.parent.assertListEqual(
			    [mem.shape for mem in mems_a]  ,					[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers  ,					)

	def      __UpperCamelCase							(      self   :						Any  ,					UpperCAmelCase_   :						Optional[int]  ,					UpperCAmelCase_   :						List[str]  ,					UpperCAmelCase_   :						Union[str, Any]  ,					UpperCAmelCase_   :						List[str]):
			UpperCamelCase__				:					Optional[Any]					=					TFTransfoXLForSequenceClassification(lowercase__)
			UpperCamelCase__				:					Dict					=					model(lowercase__)
			self.parent.assertEqual(result.logits.shape  ,					(self.batch_size, self.num_labels))





	def      __UpperCamelCase							(      self   :						Optional[Any]):
			UpperCamelCase__				:					Optional[Any]					=					self.prepare_config_and_inputs()
			(UpperCamelCase__)				:					Tuple					=					config_and_inputs
			UpperCamelCase__				:					int					=					{'''input_ids''': input_ids_a}
			return config, inputs_dict


@require_tf
class       __lowercase					(a__   ,				a__   ,				unittest.TestCase    ):
	_lowerCamelCase              =  (
	    (TFTransfoXLModel, TFTransfoXLLMHeadModel, TFTransfoXLForSequenceClassification) if is_tf_available() else ()
	)
	_lowerCamelCase              =  () if is_tf_available() else ()
	_lowerCamelCase              =  (
	    {
	        """feature-extraction""": TFTransfoXLModel,
	        """text-classification""": TFTransfoXLForSequenceClassification,
	        """text-generation""": TFTransfoXLLMHeadModel,
	        """zero-shot""": TFTransfoXLForSequenceClassification,
	    }
	    if is_tf_available()
	    else {}
	)
	# TODO: add this test when TFTransfoXLLMHead has a linear output layer implemented
	_lowerCamelCase              =  False
	_lowerCamelCase              =  False
	_lowerCamelCase              =  False
	_lowerCamelCase              =  False

	def      __UpperCamelCase							(      self   :						Union[str, Any]  ,					UpperCAmelCase_   :						Any  ,					UpperCAmelCase_   :						Any  ,					UpperCAmelCase_   :						Dict  ,					UpperCAmelCase_   :						str  ,					UpperCAmelCase_   :						Optional[Any]):





			if pipeline_test_casse_name == "TextGenerationPipelineTests":
					# Get `ValueError: AttributeError: 'NoneType' object has no attribute 'new_ones'` or `AssertionError`.
					# `TransfoXLConfig` was never used in pipeline tests: cannot create a simple
					# tokenizer.
					return True

			return False

	def      __UpperCamelCase							(      self   :						Any):
			UpperCamelCase__				:					List[Any]					=					TFTransfoXLModelTester(self)
			UpperCamelCase__				:					Any					=					ConfigTester(self  ,					config_class=lowercase__  ,					d_embed=37)

	def      __UpperCamelCase							(      self   :						str):
			self.config_tester.run_common_tests()

	def      __UpperCamelCase							(      self   :						Optional[int]):
			self.model_tester.set_seed()
			UpperCamelCase__				:					Optional[Any]					=					self.model_tester.prepare_config_and_inputs()
			self.model_tester.create_and_check_transfo_xl_model(*lowercase__)

	def      __UpperCamelCase							(      self   :						Any):
			self.model_tester.set_seed()
			UpperCamelCase__				:					Dict					=					self.model_tester.prepare_config_and_inputs()
			self.model_tester.create_and_check_transfo_xl_lm_head(*lowercase__)

	def      __UpperCamelCase							(      self   :						List[str]):
			UpperCamelCase__				:					Any					=					self.model_tester.prepare_config_and_inputs()
			self.model_tester.create_and_check_transfo_xl_for_sequence_classification(*lowercase__)

	def      __UpperCamelCase							(      self   :						List[str]):
			UpperCamelCase__				:					int					=					self.model_tester.prepare_config_and_inputs_for_common()
			UpperCamelCase__				:					Optional[Any]					=					[TFTransfoXLForSequenceClassification]

			for model_class in self.all_model_classes:
					UpperCamelCase__				:					Optional[Any]					=					model_class(lowercase__)
					assert isinstance(model.get_input_embeddings()  ,					tf.keras.layers.Layer)
					if model_class in list_other_models_with_output_ebd:
							UpperCamelCase__				:					List[Any]					=					model.get_output_embeddings()
							assert isinstance(lowercase__  ,					tf.keras.layers.Layer)
							UpperCamelCase__				:					str					=					model.get_bias()
							assert name is None
					else:
							UpperCamelCase__				:					Optional[Any]					=					model.get_output_embeddings()
							assert x is None
							UpperCamelCase__				:					List[str]					=					model.get_bias()
							assert name is None

	def      __UpperCamelCase							(      self   :						int):
			pass

	@slow
	def      __UpperCamelCase							(      self   :						Optional[Any]):





			for model_name in TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
					UpperCamelCase__				:					List[str]					=					TFTransfoXLModel.from_pretrained(lowercase__)
					self.assertIsNotNone(lowercase__)





	@unittest.skip(reason='This model doesn\'t play well with fit() due to not returning a single loss.')
	def      __UpperCamelCase							(      self   :						int):
			pass


@require_tf
class       __lowercase					(unittest.TestCase    ):

	@unittest.skip('Skip test until #12651 is resolved.')
	@slow
	def      __UpperCamelCase							(      self   :						Dict):
			UpperCamelCase__				:					Any					=					TFTransfoXLLMHeadModel.from_pretrained('transfo-xl-wt103')
			# fmt: off
			UpperCamelCase__				:					Union[str, Any]					=					tf.convert_to_tensor([[33,1_297,2,1,1_009,4,1_109,11_739,4_762,358,5,25,245,22,1_706,17,20_098,5,3_215,21,37,1_110,3,13,1_041,4,24,603,490,2,71_477,20_098,104_447,2,20_961,1,2_604,4,1,329,3,6_224,831,16_002,2,8,603,78_967,29_546,23,803,20,25,416,5,8,232,4,277,6,1_855,4_601,3,29_546,54,8,3_609,5,57_211,49,4,1,277,18,8,1_755,15_691,3,341,25,416,693,42_573,71,17,401,94,31,17_919,2,29_546,7_873,18,1,435,23,11_011,755,5,5_167,3,7_983,98,84,2,29_546,3_267,8,3_609,4,1,4_865,1_075,2,6_087,71,6,346,8,5_854,3,29_546,824,1_400,1_868,2,19,160,2,311,8,5_496,2,20_920,17,25,15_097,3,24,24,0]]  ,					dtype=tf.intaa)  # noqa: E231
			# fmt: on
			#  In 1991 , the remains of Russian Tsar Nicholas II and his family
			#  ( except for Alexei and Maria ) are discovered .
			#  The voice of Nicholas's young son , Tsarevich Alexei Nikolaevich , narrates the
			#  remainder of the story . 1883 Western Siberia ,
			#  a young Grigori Rasputin is asked by his father and a group of men to perform magic .
			#  Rasputin has a vision and denounces one of the men as a horse thief . Although his
			#  father initially slaps him for making such an accusation , Rasputin watches as the
			#  man is chased outside and beaten . Twenty years later , Rasputin sees a vision of
			#  the Virgin Mary , prompting him to become a priest . Rasputin quickly becomes famous ,
			#  with people , even a bishop , begging for his blessing . <eod> </s> <eos>

			# fmt: off
			UpperCamelCase__				:					Optional[int]					=					[33,1_297,2,1,1_009,4,1_109,11_739,4_762,358,5,25,245,22,1_706,17,20_098,5,3_215,21,37,1_110,3,13,1_041,4,24,603,490,2,71_477,20_098,104_447,2,20_961,1,2_604,4,1,329,3,6_224,831,16_002,2,8,603,78_967,29_546,23,803,20,25,416,5,8,232,4,277,6,1_855,4_601,3,29_546,54,8,3_609,5,57_211,49,4,1,277,18,8,1_755,15_691,3,341,25,416,693,42_573,71,17,401,94,31,17_919,2,29_546,7_873,18,1,435,23,11_011,755,5,5_167,3,7_983,98,84,2,29_546,3_267,8,3_609,4,1,4_865,1_075,2,6_087,71,6,346,8,5_854,3,29_546,824,1_400,1_868,2,19,160,2,311,8,5_496,2,20_920,17,25,15_097,3,24,24,0,33,1,1_857,2,1,1_009,4,1_109,11_739,4_762,358,5,25,245,28,1_110,3,13,1_041,4,24,603,490,2,71_477,20_098,104_447,2,20_961,1,2_604,4,1,329,3,0]  # noqa: E231
			# fmt: on
			#  In 1991, the remains of Russian Tsar Nicholas II and his family (
			#  except for Alexei and Maria ) are discovered. The voice of young son,
			#  Tsarevich Alexei Nikolaevich, narrates the remainder of the story.
			#  1883 Western Siberia, a young Grigori Rasputin is asked by his father
			#  and a group of men to perform magic. Rasputin has a vision and
			#  denounces one of the men as a horse thief. Although his father initially
			#  slaps him for making such an accusation, Rasputin watches as the man
			#  is chased outside and beaten. Twenty years later, Rasputin sees a vision
			#  of the Virgin Mary, prompting him to become a priest.
			#  Rasputin quickly becomes famous, with people, even a bishop, begging for
			#  his blessing. <unk> <unk> <eos> In the 1990s, the remains of Russian Tsar
			# Nicholas II and his family were discovered. The voice of <unk> young son,
			# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.<eos>

			UpperCamelCase__				:					str					=					model.generate(lowercase__  ,					max_length=200  ,					do_sample=lowercase__)
			self.assertListEqual(output_ids[0].numpy().tolist()  ,					lowercase__)












'''simple docstring'''




def       __UpperCAmelCase						(  lowerCamelCase_     ,      lowerCamelCase_)							->     list[str]:
		return [sentence[i : i + ngram_size] for i in range(len(lowerCamelCase_) - ngram_size + 1)]


if __name__ == "__main__":
		from doctest import testmod

		testmod()




