






import unittest

from transformers import (
    MODEL_FOR_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_CAUSAL_LM_MAPPING,
    TextGenerationPipeline,
    logging,
    pipeline,
)
from transformers.testing_utils import (
    CaptureLogger,
    is_pipeline_test,
    require_accelerate,
    require_tf,
    require_torch,
    require_torch_gpu,
    require_torch_or_tf,
)

from .test_pipelines_common import ANY
@is_pipeline_test
@require_torch_or_tf
class  lowerCAmelCase_       (				unittest.TestCase					):
							UpperCamelCase_		:Any		      =    MODEL_FOR_CAUSAL_LM_MAPPING
							UpperCamelCase_		:str		      =    TF_MODEL_FOR_CAUSAL_LM_MAPPING




							@require_torch
							def 						__snake_case					(   self     :   Union[str, Any]	):
											lowerCAmelCase__      			=						pipeline(task='''text-generation''' ,							model='''sshleifer/tiny-ctrl''' ,							framework='''pt'''	)
											# Using `do_sample=False` to force deterministic output
											lowerCAmelCase__      			=						text_generator('''This is a test''' ,							do_sample=SCREAMING_SNAKE_CASE_	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        {
											            '''generated_text''': (
											                '''This is a test ☃ ☃ segmental segmental segmental 议议eski eski flutter flutter Lacy oscope.'''
											                ''' oscope. FiliFili@@'''
											            )
											        }
											    ] ,							)

											lowerCAmelCase__      			=						text_generator(['''This is a test''', '''This is a second test''']	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        [
											            {
											                '''generated_text''': (
											                    '''This is a test ☃ ☃ segmental segmental segmental 议议eski eski flutter flutter Lacy oscope.'''
											                    ''' oscope. FiliFili@@'''
											                )
											            }
											        ],
											        [
											            {
											                '''generated_text''': (
											                    '''This is a second test ☃ segmental segmental segmental 议议eski eski flutter flutter Lacy'''
											                    ''' oscope. oscope. FiliFili@@'''
											                )
											            }
											        ],
											    ] ,							)

											lowerCAmelCase__      			=						text_generator('''This is a test''' ,							do_sample=SCREAMING_SNAKE_CASE_ ,							num_return_sequences=2 ,							return_tensors=SCREAMING_SNAKE_CASE_	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        {'''generated_token_ids''': ANY(SCREAMING_SNAKE_CASE_	)},
											        {'''generated_token_ids''': ANY(SCREAMING_SNAKE_CASE_	)},
											    ] ,							)
											lowerCAmelCase__      			=						text_generator.model.config.eos_token_id
											lowerCAmelCase__      			=						'''<pad>'''
											lowerCAmelCase__      			=						text_generator(
											    ['''This is a test''', '''This is a second test'''] ,							do_sample=SCREAMING_SNAKE_CASE_ ,							num_return_sequences=2 ,							batch_size=2 ,							return_tensors=SCREAMING_SNAKE_CASE_ ,							)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        [
											            {'''generated_token_ids''': ANY(SCREAMING_SNAKE_CASE_	)},
											            {'''generated_token_ids''': ANY(SCREAMING_SNAKE_CASE_	)},
											        ],
											        [
											            {'''generated_token_ids''': ANY(SCREAMING_SNAKE_CASE_	)},
											            {'''generated_token_ids''': ANY(SCREAMING_SNAKE_CASE_	)},
											        ],
											    ] ,							)




							@require_tf
							def 						__snake_case					(   self     :   Optional[Any]	):
											lowerCAmelCase__      			=						pipeline(task='''text-generation''' ,							model='''sshleifer/tiny-ctrl''' ,							framework='''tf'''	)

											# Using `do_sample=False` to force deterministic output
											lowerCAmelCase__      			=						text_generator('''This is a test''' ,							do_sample=SCREAMING_SNAKE_CASE_	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        {
											            '''generated_text''': (
											                '''This is a test FeyFeyFey(Croatis.), s.), Cannes Cannes Cannes 閲閲Cannes Cannes Cannes 攵'''
											                ''' please,'''
											            )
											        }
											    ] ,							)

											lowerCAmelCase__      			=						text_generator(['''This is a test''', '''This is a second test'''] ,							do_sample=SCREAMING_SNAKE_CASE_	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        [
											            {
											                '''generated_text''': (
											                    '''This is a test FeyFeyFey(Croatis.), s.), Cannes Cannes Cannes 閲閲Cannes Cannes Cannes 攵'''
											                    ''' please,'''
											                )
											            }
											        ],
											        [
											            {
											                '''generated_text''': (
											                    '''This is a second test Chieftain Chieftain prefecture prefecture prefecture Cannes Cannes'''
											                    ''' Cannes 閲閲Cannes Cannes Cannes 攵 please,'''
											                )
											            }
											        ],
											    ] ,							)




							def 						__snake_case					(   self     :   int ,							SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Dict	):
											lowerCAmelCase__      			=						TextGenerationPipeline(model=SCREAMING_SNAKE_CASE_ ,							tokenizer=SCREAMING_SNAKE_CASE_	)
											return text_generator, ["This is a test", "Another test"]




							def 						__snake_case					(   self     :   Optional[Any]	):
											lowerCAmelCase__      			=						'''Hello I believe in'''
											lowerCAmelCase__      			=						pipeline('''text-generation''' ,							model='''hf-internal-testing/tiny-random-gpt2'''	)
											lowerCAmelCase__      			=						text_generator(SCREAMING_SNAKE_CASE_	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[{'''generated_text''': '''Hello I believe in fe fe fe fe fe fe fe fe fe fe fe fe'''}] ,							)

											lowerCAmelCase__      			=						text_generator(SCREAMING_SNAKE_CASE_ ,							stop_sequence=''' fe'''	)
											self.assertEqual(SCREAMING_SNAKE_CASE_ ,							[{'''generated_text''': '''Hello I believe in fe'''}]	)




							def 						__snake_case					(   self     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   int	):
											lowerCAmelCase__      			=						text_generator.model
											lowerCAmelCase__      			=						text_generator.tokenizer

											lowerCAmelCase__      			=						text_generator('''This is a test'''	)
											self.assertEqual(SCREAMING_SNAKE_CASE_ ,							[{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}]	)
											self.assertTrue(outputs[0]['''generated_text'''].startswith('''This is a test'''	)	)

											lowerCAmelCase__      			=						text_generator('''This is a test''' ,							return_full_text=SCREAMING_SNAKE_CASE_	)
											self.assertEqual(SCREAMING_SNAKE_CASE_ ,							[{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}]	)
											self.assertNotIn('''This is a test''' ,							outputs[0]['''generated_text''']	)

											lowerCAmelCase__      			=						pipeline(task='''text-generation''' ,							model=SCREAMING_SNAKE_CASE_ ,							tokenizer=SCREAMING_SNAKE_CASE_ ,							return_full_text=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						text_generator('''This is a test'''	)
											self.assertEqual(SCREAMING_SNAKE_CASE_ ,							[{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}]	)
											self.assertNotIn('''This is a test''' ,							outputs[0]['''generated_text''']	)

											lowerCAmelCase__      			=						text_generator('''This is a test''' ,							return_full_text=SCREAMING_SNAKE_CASE_	)
											self.assertEqual(SCREAMING_SNAKE_CASE_ ,							[{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}]	)
											self.assertTrue(outputs[0]['''generated_text'''].startswith('''This is a test'''	)	)

											lowerCAmelCase__      			=						text_generator(['''This is great !''', '''Something else'''] ,							num_return_sequences=2 ,							do_sample=SCREAMING_SNAKE_CASE_	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        [{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}, {'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}],
											        [{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}, {'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}],
											    ] ,							)

											if text_generator.tokenizer.pad_token is not None:
															lowerCAmelCase__      			=						text_generator(
															    ['''This is great !''', '''Something else'''] ,							num_return_sequences=2 ,							batch_size=2 ,							do_sample=SCREAMING_SNAKE_CASE_	)
															self.assertEqual(
															    SCREAMING_SNAKE_CASE_ ,							[
															        [{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}, {'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}],
															        [{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}, {'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}],
															    ] ,							)

											with self.assertRaises(SCREAMING_SNAKE_CASE_	):
															lowerCAmelCase__      			=						text_generator('''test''' ,							return_full_text=SCREAMING_SNAKE_CASE_ ,							return_text=SCREAMING_SNAKE_CASE_	)
											with self.assertRaises(SCREAMING_SNAKE_CASE_	):
															lowerCAmelCase__      			=						text_generator('''test''' ,							return_full_text=SCREAMING_SNAKE_CASE_ ,							return_tensors=SCREAMING_SNAKE_CASE_	)
											with self.assertRaises(SCREAMING_SNAKE_CASE_	):
															lowerCAmelCase__      			=						text_generator('''test''' ,							return_text=SCREAMING_SNAKE_CASE_ ,							return_tensors=SCREAMING_SNAKE_CASE_	)

											# Empty prompt is slighly special
											# it requires BOS token to exist.
											# Special case for Pegasus which will always append EOS so will
											# work even without BOS.
											if (
											    text_generator.tokenizer.bos_token_id is not None
											    or "Pegasus" in tokenizer.__class__.__name__
											    or "Git" in model.__class__.__name__
											):
															lowerCAmelCase__      			=						text_generator(''''''	)
															self.assertEqual(SCREAMING_SNAKE_CASE_ ,							[{'''generated_text''': ANY(SCREAMING_SNAKE_CASE_	)}]	)
											else:
															with self.assertRaises((ValueError, AssertionError)	):
																			lowerCAmelCase__      			=						text_generator(''''''	)

											if text_generator.framework == "tf":
															# TF generation does not support max_new_tokens, and it's impossible
															# to control long generation with only max_length without
															# fancy calculation, dismissing tests for now.
															return
											# We don't care about infinite range models.
											# They already work.
											# Skip this test for XGLM, since it uses sinusoidal positional embeddings which are resized on-the-fly.
											lowerCAmelCase__      			=						['''RwkvForCausalLM''', '''XGLMForCausalLM''', '''GPTNeoXForCausalLM''']
											if (
											    tokenizer.model_max_length < 10_000
											    and text_generator.model.__class__.__name__ not in EXTRA_MODELS_CAN_HANDLE_LONG_INPUTS
											):
															# Handling of large generations
															with self.assertRaises((RuntimeError, IndexError, ValueError, AssertionError)	):
																			text_generator('''This is a test''' * 500 ,							max_new_tokens=20	)

															lowerCAmelCase__      			=						text_generator('''This is a test''' * 500 ,							handle_long_generation='''hole''' ,							max_new_tokens=20	)
															# Hole strategy cannot work
															with self.assertRaises(SCREAMING_SNAKE_CASE_	):
																			text_generator(
																			    '''This is a test''' * 500 ,							handle_long_generation='''hole''' ,							max_new_tokens=tokenizer.model_max_length + 10 ,							)




							@require_torch
							@require_accelerate
							@require_torch_gpu
							def 						__snake_case					(   self     :   Optional[int]	):
											import torch

											# Classic `model_kwargs`
											lowerCAmelCase__      			=						pipeline(
											    model='''hf-internal-testing/tiny-random-bloom''' ,							model_kwargs={'''device_map''': '''auto''', '''torch_dtype''': torch.bfloataa} ,							)
											self.assertEqual(pipe.model.device ,							torch.device(0	)	)
											self.assertEqual(pipe.model.lm_head.weight.dtype ,							torch.bfloataa	)
											lowerCAmelCase__      			=						pipe('''This is a test'''	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        {
											            '''generated_text''': (
											                '''This is a test test test test test test test test test test test test test test test test'''
											                ''' test'''
											            )
											        }
											    ] ,							)

											# Upgraded those two to real pipeline arguments (they just get sent for the model as they're unlikely to mean anything else.)
											lowerCAmelCase__      			=						pipeline(model='''hf-internal-testing/tiny-random-bloom''' ,							device_map='''auto''' ,							torch_dtype=torch.bfloataa	)
											self.assertEqual(pipe.model.device ,							torch.device(0	)	)
											self.assertEqual(pipe.model.lm_head.weight.dtype ,							torch.bfloataa	)
											lowerCAmelCase__      			=						pipe('''This is a test'''	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        {
											            '''generated_text''': (
											                '''This is a test test test test test test test test test test test test test test test test'''
											                ''' test'''
											            )
											        }
											    ] ,							)

											# torch_dtype will be automatically set to float32 if not provided - check: https://github.com/huggingface/transformers/pull/20602
											lowerCAmelCase__      			=						pipeline(model='''hf-internal-testing/tiny-random-bloom''' ,							device_map='''auto'''	)
											self.assertEqual(pipe.model.device ,							torch.device(0	)	)
											self.assertEqual(pipe.model.lm_head.weight.dtype ,							torch.floataa	)
											lowerCAmelCase__      			=						pipe('''This is a test'''	)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        {
											            '''generated_text''': (
											                '''This is a test test test test test test test test test test test test test test test test'''
											                ''' test'''
											            )
											        }
											    ] ,							)




							@require_torch
							@require_torch_gpu
							def 						__snake_case					(   self     :   int	):
											import torch

											lowerCAmelCase__      			=						pipeline(model='''hf-internal-testing/tiny-random-bloom''' ,							device=0 ,							torch_dtype=torch.floataa	)
											pipe('''This is a test'''	)




							@require_torch
							@require_accelerate
							@require_torch_gpu
							def 						__snake_case					(   self     :   List[Any]	):
											import torch

											lowerCAmelCase__      			=						pipeline(model='''hf-internal-testing/tiny-random-bloom''' ,							device_map='''auto''' ,							torch_dtype=torch.floataa	)
											pipe('''This is a test''' ,							do_sample=SCREAMING_SNAKE_CASE_ ,							top_p=0.5	)




							def 						__snake_case					(   self     :   Dict	):
											lowerCAmelCase__      			=						'''Hello world'''
											lowerCAmelCase__      			=						pipeline('''text-generation''' ,							model='''hf-internal-testing/tiny-random-gpt2'''	)
											if text_generator.model.framework == "tf":
															lowerCAmelCase__      			=						logging.get_logger('''transformers.generation.tf_utils'''	)
											else:
															lowerCAmelCase__      			=						logging.get_logger('''transformers.generation.utils'''	)
											lowerCAmelCase__      			=						'''Both `max_new_tokens`'''  # The beggining of the message to be checked in this test

											# Both are set by the user -> log warning
											with CaptureLogger(SCREAMING_SNAKE_CASE_	) as cl:
															lowerCAmelCase__      			=						text_generator(SCREAMING_SNAKE_CASE_ ,							max_length=10 ,							max_new_tokens=1	)
											self.assertIn(SCREAMING_SNAKE_CASE_ ,							cl.out	)

											# The user only sets one -> no warning
											with CaptureLogger(SCREAMING_SNAKE_CASE_	) as cl:
															lowerCAmelCase__      			=						text_generator(SCREAMING_SNAKE_CASE_ ,							max_new_tokens=1	)
											self.assertNotIn(SCREAMING_SNAKE_CASE_ ,							cl.out	)

											with CaptureLogger(SCREAMING_SNAKE_CASE_	) as cl:
															lowerCAmelCase__      			=						text_generator(SCREAMING_SNAKE_CASE_ ,							max_length=10	)
											self.assertNotIn(SCREAMING_SNAKE_CASE_ ,							cl.out	)













from ...configuration_utils import PretrainedConfig
class  lowerCAmelCase_       (				snake_case__					):
							UpperCamelCase_		:List[str]		      =    'bert-generation'




							def __init__(   self     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   List[str]=50_358 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=1_024 ,							SCREAMING_SNAKE_CASE_     :   Optional[Any]=24 ,							SCREAMING_SNAKE_CASE_     :   Any=16 ,							SCREAMING_SNAKE_CASE_     :   Tuple=4_096 ,							SCREAMING_SNAKE_CASE_     :   str="gelu" ,							SCREAMING_SNAKE_CASE_     :   List[str]=0.1 ,							SCREAMING_SNAKE_CASE_     :   Tuple=0.1 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=512 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=0.02 ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]=1e-12 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=0 ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]=2 ,							SCREAMING_SNAKE_CASE_     :   int=1 ,							SCREAMING_SNAKE_CASE_     :   str="absolute" ,							SCREAMING_SNAKE_CASE_     :   Tuple=True ,							**SCREAMING_SNAKE_CASE_     :   str ,							):
											super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_ ,							bos_token_id=SCREAMING_SNAKE_CASE_ ,							eos_token_id=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						vocab_size
											lowerCAmelCase__      			=						hidden_size
											lowerCAmelCase__      			=						num_hidden_layers
											lowerCAmelCase__      			=						num_attention_heads
											lowerCAmelCase__      			=						hidden_act
											lowerCAmelCase__      			=						intermediate_size
											lowerCAmelCase__      			=						hidden_dropout_prob
											lowerCAmelCase__      			=						attention_probs_dropout_prob
											lowerCAmelCase__      			=						max_position_embeddings
											lowerCAmelCase__      			=						initializer_range
											lowerCAmelCase__      			=						layer_norm_eps
											lowerCAmelCase__      			=						position_embedding_type
											lowerCAmelCase__      			=						use_cache





