




'''simple docstring'''




from __future__ import annotations

import unittest

from transformers import CTRLConfig, 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, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
     import tensorflow as tf

     from transformers.models.ctrl.modeling_tf_ctrl import (
         TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
         TFCTRLForSequenceClassification,
         TFCTRLLMHeadModel,
         TFCTRLModel,
     )


class 						__UpperCamelCase (				lowerCamelCase__       ):






       def __init__(							self,	lowerCAmelCase,	):



              """simple docstring"""







              lowerCamelCase_							=parent
              lowerCamelCase_							=13
              lowerCamelCase_							=7
              lowerCamelCase_							=True
              lowerCamelCase_							=True
              lowerCamelCase_							=True
              lowerCamelCase_							=True
              lowerCamelCase_							=True
              lowerCamelCase_							=99
              lowerCamelCase_							=32
              lowerCamelCase_							=2
              lowerCamelCase_							=4
              lowerCamelCase_							=37
              lowerCamelCase_							='''gelu'''
              lowerCamelCase_							=0.1
              lowerCamelCase_							=0.1
              lowerCamelCase_							=512
              lowerCamelCase_							=16
              lowerCamelCase_							=2
              lowerCamelCase_							=0.0_2
              lowerCamelCase_							=3
              lowerCamelCase_							=4
              lowerCamelCase_							=None
              lowerCamelCase_							=self.vocab_size - 1






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=ids_tensor([self.batch_size, self.seq_length],	self.vocab_size						)

              lowerCamelCase_							=None
              if self.use_input_mask:
                     lowerCamelCase_							=random_attention_mask([self.batch_size, self.seq_length]						)

              lowerCamelCase_							=None
              if self.use_token_type_ids:
                     lowerCamelCase_							=ids_tensor([self.batch_size, self.seq_length],	self.type_vocab_size						)

              lowerCamelCase_							=None
              if self.use_mc_token_ids:
                     lowerCamelCase_							=ids_tensor([self.batch_size, self.num_choices],	self.seq_length						)

              lowerCamelCase_							=None
              lowerCamelCase_							=None
              lowerCamelCase_							=None
              if self.use_labels:
                     lowerCamelCase_							=ids_tensor([self.batch_size],	self.type_sequence_label_size						)
                     lowerCamelCase_							=ids_tensor([self.batch_size, self.seq_length],	self.num_labels						)
                     lowerCamelCase_							=ids_tensor([self.batch_size],	self.num_choices						)

              lowerCamelCase_							=CTRLConfig(
                  vocab_size=self.vocab_size,	n_embd=self.hidden_size,	n_layer=self.num_hidden_layers,	n_head=self.num_attention_heads,	n_positions=self.max_position_embeddings,	pad_token_id=self.pad_token_id,	)

              lowerCamelCase_							=ids_tensor([self.num_hidden_layers, self.num_attention_heads],	2						)

              return (
                  config,
                  input_ids,
                  input_mask,
                  head_mask,
                  token_type_ids,
                  mc_token_ids,
                  sequence_labels,
                  token_labels,
                  choice_labels,
              )






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	*lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=TFCTRLModel(config=lowerCAmelCase						)
              lowerCamelCase_							={'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
              lowerCamelCase_							=model(lowerCAmelCase						)

              lowerCamelCase_							=[input_ids, None, input_mask]  # None is the input for 'past'
              lowerCamelCase_							=model(lowerCAmelCase						)

              lowerCamelCase_							=model(lowerCAmelCase						)

              self.parent.assertEqual(result.last_hidden_state.shape,	(self.batch_size, self.seq_length, self.hidden_size)						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	*lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=TFCTRLLMHeadModel(config=lowerCAmelCase						)
              lowerCamelCase_							={'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
              lowerCamelCase_							=model(lowerCAmelCase						)
              self.parent.assertEqual(result.logits.shape,	(self.batch_size, self.seq_length, self.vocab_size)						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	*lowerCAmelCase						):



              """simple docstring"""







              lowerCamelCase_							=self.num_labels
              lowerCamelCase_							=ids_tensor([self.batch_size],	self.type_sequence_label_size						)
              lowerCamelCase_							={
                  '''input_ids''': input_ids,
                  '''token_type_ids''': token_type_ids,
                  '''labels''': sequence_labels,
              }
              lowerCamelCase_							=TFCTRLForSequenceClassification(lowerCAmelCase						)
              lowerCamelCase_							=model(lowerCAmelCase						)
              self.parent.assertEqual(result.logits.shape,	(self.batch_size, self.num_labels)						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.prepare_config_and_inputs()

              (
                  (
                  lowerCamelCase_
              ),   (
                  lowerCamelCase_
              ),   (
                  lowerCamelCase_
              ),   (
                  lowerCamelCase_
              ),   (
                  lowerCamelCase_
              ),   (
                  lowerCamelCase_
              ),   (
                  lowerCamelCase_
              ),   (
                  lowerCamelCase_
              ),   (
                  lowerCamelCase_
              ),   
              )							=config_and_inputs

              lowerCamelCase_							={'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': input_mask}
              return config, inputs_dict





@require_tf
class 						__UpperCamelCase (				lowerCamelCase__    ,      lowerCamelCase__    ,      unittest.TestCase       ):
       lowercase			:					Optional[int]   		=(TFCTRLModel, TFCTRLLMHeadModel, TFCTRLForSequenceClassification) if is_tf_available() else ()
       lowercase			:					str   		=(TFCTRLLMHeadModel,) if is_tf_available() else ()
       lowercase			:					Optional[int]   		=(
           {
               'feature-extraction': TFCTRLModel,
               'text-classification': TFCTRLForSequenceClassification,
               'text-generation': TFCTRLLMHeadModel,
               'zero-shot': TFCTRLForSequenceClassification,
           }
           if is_tf_available()
           else {}
       )
       lowercase			:					str   		=False
       lowercase			:					Union[str, Any]   		=False






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase,	lowerCAmelCase						):



              """simple docstring"""







              if pipeline_test_casse_name == "ZeroShotClassificationPipelineTests":
                     # Get `tokenizer does not have a padding token` error for both fast/slow tokenizers.
                     # `CTRLConfig` was never used in pipeline tests, either because of a missing checkpoint or because a tiny
                     # config could not be created.
                     return True

              return False






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=TFCTRLModelTester(self						)
              lowerCamelCase_							=ConfigTester(self,	config_class=lowerCAmelCase,	n_embd=37						)






       def   lowercase__  (							self						):



              """simple docstring"""







              self.config_tester.run_common_tests()






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_ctrl_model(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_ctrl_lm_head(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.model_tester.prepare_config_and_inputs()
              self.model_tester.create_and_check_ctrl_for_sequence_classification(*lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_,   lowerCamelCase_							=self.model_tester.prepare_config_and_inputs_for_common()
              lowerCamelCase_							=[TFCTRLLMHeadModel]
              lowerCamelCase_							=[TFCTRLForSequenceClassification]

              for model_class in self.all_model_classes:
                     lowerCamelCase_							=model_class(lowerCAmelCase						)
                     model.build()  # may be needed for the get_bias() call below
                     assert isinstance(model.get_input_embeddings(),	tf.keras.layers.Layer						)

                     if model_class in list_lm_models:
                            lowerCamelCase_							=model.get_output_embeddings()
                            assert isinstance(lowerCAmelCase,	tf.keras.layers.Layer						)
                            lowerCamelCase_							=model.get_bias()
                            assert isinstance(lowerCAmelCase,	lowerCAmelCase						)
                            for k, v in name.items():
                                   assert isinstance(lowerCAmelCase,	tf.Variable						)
                     elif model_class in list_other_models_with_output_ebd:
                            lowerCamelCase_							=model.get_output_embeddings()
                            assert isinstance(lowerCAmelCase,	tf.keras.layers.Layer						)
                            lowerCamelCase_							=model.get_bias()
                            assert name is None
                     else:
                            lowerCamelCase_							=model.get_output_embeddings()
                            assert x is None
                            lowerCamelCase_							=model.get_bias()
                            assert name is None






       @slow
       def   lowercase__  (							self						):



              """simple docstring"""







              for model_name in TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
                     lowerCamelCase_							=TFCTRLModel.from_pretrained(lowerCAmelCase						)
                     self.assertIsNotNone(lowerCAmelCase						)





@require_tf
class 						__UpperCamelCase (				unittest.TestCase       ):






       @slow
       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=TFCTRLLMHeadModel.from_pretrained('''ctrl'''						)
              lowerCamelCase_							=tf.convert_to_tensor([[11_859, 0, 1_611, 8]],	dtype=tf.intaa						)  # Legal the president is
              lowerCamelCase_							=[
                  11_859,
                  0,
                  1_611,
                  8,
                  5,
                  150,
                  26_449,
                  2,
                  19,
                  348,
                  469,
                  3,
                  2_595,
                  48,
                  20_740,
                  246_533,
                  246_533,
                  19,
                  30,
                  5,
              ]  # Legal the president is a good guy and I don't want to lose my job. \n \n I have a

              lowerCamelCase_							=model.generate(lowerCAmelCase,	do_sample=lowerCAmelCase						)
              self.assertListEqual(output_ids[0].numpy().tolist(),	lowerCAmelCase						)










'''simple docstring'''




import warnings

from .generation import FlaxGenerationMixin


class 						__UpperCamelCase (				lowerCamelCase__       ):
       # warning at import time
       warnings.warn(
           'Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will '
           'be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead.'    ,      lowerCamelCase__    ,      )




