





"""simple docstring"""





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			):
       """simple docstring"""




       __magic_name__	:Optional[int]						    =   MODEL_FOR_CAUSAL_LM_MAPPING
       __magic_name__	:Optional[Any]						    =   TF_MODEL_FOR_CAUSAL_LM_MAPPING






       @require_torch
       def 	snake_case		(       self ):



         '''simple docstring'''

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

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






       @require_tf
       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :List[Any]											=				pipeline(task='text-generation'       ,					model='sshleifer/tiny-ctrl'       ,					framework='tf' )

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

         lowerCAmelCase__     :Union[str, Any]											=				text_generator(['This is a test', 'This is a second test']       ,					do_sample=__UpperCAmelCase )
         self.assertEqual(
             __UpperCAmelCase       ,					[
                 [
                     {
                         '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       ,					__UpperCAmelCase       ,					__UpperCAmelCase       ,					__UpperCAmelCase ):



         '''simple docstring'''

         lowerCAmelCase__     :Union[str, Any]											=				TextGenerationPipeline(model=__UpperCAmelCase       ,					tokenizer=__UpperCAmelCase )
         return text_generator, ["This is a test", "Another test"]






       def 	snake_case		(       self ):



         '''simple docstring'''

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

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






       def 	snake_case		(       self       ,					__UpperCAmelCase       ,					__UpperCAmelCase ):



         '''simple docstring'''

         lowerCAmelCase__     :Any											=				text_generator.model
         lowerCAmelCase__     :Dict											=				text_generator.tokenizer

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

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

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

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

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

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

         with self.assertRaises(__UpperCAmelCase ):
           lowerCAmelCase__     :List[Any]											=				text_generator('test'       ,					return_full_text=__UpperCAmelCase       ,					return_text=__UpperCAmelCase )
         with self.assertRaises(__UpperCAmelCase ):
           lowerCAmelCase__     :Union[str, Any]											=				text_generator('test'       ,					return_full_text=__UpperCAmelCase       ,					return_tensors=__UpperCAmelCase )
         with self.assertRaises(__UpperCAmelCase ):
           lowerCAmelCase__     :str											=				text_generator('test'       ,					return_text=__UpperCAmelCase       ,					return_tensors=__UpperCAmelCase )

         # 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__     :Dict											=				text_generator('' )
           self.assertEqual(__UpperCAmelCase       ,					[{'generated_text': ANY(__UpperCAmelCase )}] )
         else:
           with self.assertRaises((ValueError, AssertionError) ):
             lowerCAmelCase__     :str											=				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__     :int											=				['RwkvForCausalLM', 'XGLMForCausalLM', 'GPTNeoXForCausalLM']
         if (
             tokenizer.model_max_length < 1_0_0_0_0
             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' * 5_0_0       ,					max_new_tokens=2_0 )

           lowerCAmelCase__     :int											=				text_generator('This is a test' * 5_0_0       ,					handle_long_generation='hole'       ,					max_new_tokens=2_0 )
           # Hole strategy cannot work
           with self.assertRaises(__UpperCAmelCase ):
             text_generator(
                 'This is a test' * 5_0_0       ,					handle_long_generation='hole'       ,					max_new_tokens=tokenizer.model_max_length + 1_0       ,					)






       @require_torch
       @require_accelerate
       @require_torch_gpu
       def 	snake_case		(       self ):



         '''simple docstring'''

         import torch

         # Classic `model_kwargs`
         lowerCAmelCase__     :Optional[int]											=				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__     :Dict											=				pipe('This is a test' )
         self.assertEqual(
             __UpperCAmelCase       ,					[
                 {
                     '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__     :Union[str, Any]											=				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__     :Union[str, Any]											=				pipe('This is a test' )
         self.assertEqual(
             __UpperCAmelCase       ,					[
                 {
                     '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__     :List[str]											=				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__     :Any											=				pipe('This is a test' )
         self.assertEqual(
             __UpperCAmelCase       ,					[
                 {
                     '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 ):



         '''simple docstring'''

         import torch

         lowerCAmelCase__     :List[str]											=				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 ):



         '''simple docstring'''

         import torch

         lowerCAmelCase__     :Union[str, Any]											=				pipeline(model='hf-internal-testing/tiny-random-bloom'       ,					device_map='auto'       ,					torch_dtype=torch.floataa )
         pipe('This is a test'       ,					do_sample=__UpperCAmelCase       ,					top_p=0.5 )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :str											=				'Hello world'
         lowerCAmelCase__     :Optional[Any]											=				pipeline('text-generation'       ,					model='hf-internal-testing/tiny-random-gpt2' )
         if text_generator.model.framework == "tf":
           lowerCAmelCase__     :Any											=				logging.get_logger('transformers.generation.tf_utils' )
         else:
           lowerCAmelCase__     :List[str]											=				logging.get_logger('transformers.generation.utils' )
         lowerCAmelCase__     :Union[str, Any]											=				'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(__UpperCAmelCase ) as cl:
           lowerCAmelCase__     :Optional[Any]											=				text_generator(__UpperCAmelCase       ,					max_length=1_0       ,					max_new_tokens=1 )
         self.assertIn(__UpperCAmelCase       ,					cl.out )

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

         with CaptureLogger(__UpperCAmelCase ) as cl:
           lowerCAmelCase__     :Dict											=				text_generator(__UpperCAmelCase       ,					max_length=1_0 )
         self.assertNotIn(__UpperCAmelCase       ,					cl.out )





import math
from collections.abc import Iterator
from itertools import takewhile






def     __a					(		__UpperCAmelCase       ):

 if 1 < number < 4:
  # 2 and 3 are primes
  return True
 elif number < 2 or number % 2 == 0 or number % 3 == 0:
  # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
  return False

 # All primes number are in format of 6k +/- 1
 for i in range(5							,  int(math.sqrt(__UpperCAmelCase       ) + 1       )							,  6       ):
  if number % i == 0 or number % (i + 2) == 0:
   return False
 return True






def     __a					(		):
 a__												= 2
 while True:
  if is_prime(__UpperCAmelCase       ):
   yield num
  num += 1






def     __a					(		__UpperCAmelCase = 200_0000       ):
 return sum(takewhile(lambda __UpperCAmelCase       : x < n							,  prime_generator()       )       )


if __name__ == "__main__":
     print(f'{solution() = }')





