

'''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

     _UpperCamelCase						:  Union[str, Any]							       =				"0.12"  # assumed parallelism: 8


if is_torch_available():
     import torch


def       snake_case   (	snake_case      : List[Any]					,		snake_case      : Any					,		snake_case      : Tuple=None			) ->  Tuple:


    """simple docstring"""


    if rng is None:
        lowerCAmelCase 						=							random.Random()

    lowerCAmelCase 						=							1
    for dim in shape:
        total_dims *= dim

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

    lowerCAmelCase 						=							np.array(snake_case					,		dtype=jnp.intaa			).reshape(snake_case			)

    return output


def       snake_case   (	snake_case      : int					,		snake_case      : int=None			) ->  int:


    """simple docstring"""


    lowerCAmelCase 						=							ids_tensor(snake_case					,		vocab_size=2					,		rng=snake_case			)
    # make sure that at least one token is attended to for each batch
    lowerCAmelCase 						=							1
    return attn_mask



@require_flax
class 				_snake_case					:
  SCREAMING_SNAKE_CASE			:       int				=     None
  SCREAMING_SNAKE_CASE			:       Union[str, Any]				=     ()

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase 						=							self.model_tester.prepare_config_and_inputs_for_common()

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

      lowerCAmelCase 						=							jnp.ones_like(_SCREAMING_SNAKE_CASE	)
      lowerCAmelCase 						=							attention_mask[:max_batch_size, :sequence_length]

      # generate max 5 tokens
      lowerCAmelCase 						=							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 						=							config.eos_token_id
      return config, input_ids, attention_mask, max_length

  @is_pt_flax_cross_test
  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()
      lowerCAmelCase 						=							False
      lowerCAmelCase 						=							max_length
      lowerCAmelCase 						=							0

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model_class.__name__[4:]  # Skip the "Flax" at the beginning
          lowerCAmelCase 						=							getattr(_SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE	)
          lowerCAmelCase 						=							pt_model_class(_SCREAMING_SNAKE_CASE	).eval()
          lowerCAmelCase 						=							load_flax_weights_in_pytorch_model(_SCREAMING_SNAKE_CASE      , flax_model.params	)

          lowerCAmelCase 						=							flax_model.generate(_SCREAMING_SNAKE_CASE	).sequences
          lowerCAmelCase 						=							pt_model.generate(torch.tensor(_SCREAMING_SNAKE_CASE      , dtype=torch.long	)	)

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

          self.assertListEqual(pt_generation_outputs.numpy().tolist()      , flax_generation_outputs.tolist()	)

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()
      lowerCAmelCase 						=							False
      lowerCAmelCase 						=							max_length

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE	).sequences

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

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()
      lowerCAmelCase 						=							True
      lowerCAmelCase 						=							max_length

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE	).sequences

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

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()
      lowerCAmelCase 						=							False
      lowerCAmelCase 						=							max_length
      lowerCAmelCase 						=							2

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE	).sequences

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

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()
      lowerCAmelCase 						=							False
      lowerCAmelCase 						=							max_length
      lowerCAmelCase 						=							2
      lowerCAmelCase 						=							2

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[0]      , input_ids.shape[0] * config.num_return_sequences	)

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()
      lowerCAmelCase 						=							True
      lowerCAmelCase 						=							max_length
      lowerCAmelCase 						=							0.8
      lowerCAmelCase 						=							10
      lowerCAmelCase 						=							0.3
      lowerCAmelCase 						=							1
      lowerCAmelCase 						=							8
      lowerCAmelCase 						=							9

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE	).sequences

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

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()
      lowerCAmelCase 						=							max_length
      lowerCAmelCase 						=							1
      lowerCAmelCase 						=							8
      lowerCAmelCase 						=							9

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE	).sequences

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

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()
      lowerCAmelCase 						=							max_length
      lowerCAmelCase 						=							2
      lowerCAmelCase 						=							1
      lowerCAmelCase 						=							8
      lowerCAmelCase 						=							9

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE	).sequences

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

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()

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

      lowerCAmelCase 						=							False
      lowerCAmelCase 						=							max_length

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE      , attention_mask=_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE      , attention_mask=_SCREAMING_SNAKE_CASE	).sequences

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

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()

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

      lowerCAmelCase 						=							True
      lowerCAmelCase 						=							max_length

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE      , attention_mask=_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE      , attention_mask=_SCREAMING_SNAKE_CASE	).sequences

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


  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase						,   lowerCAmelCase 						=							self._get_input_ids_and_config()

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

      lowerCAmelCase 						=							2
      lowerCAmelCase 						=							max_length

      for model_class in self.all_generative_model_classes:
          lowerCAmelCase 						=							model_class(_SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							model.generate(_SCREAMING_SNAKE_CASE      , attention_mask=_SCREAMING_SNAKE_CASE	).sequences
          self.assertEqual(generation_outputs.shape[-1]      , _SCREAMING_SNAKE_CASE	)

          lowerCAmelCase 						=							jit(model.generate	)
          lowerCAmelCase 						=							jit_generate(_SCREAMING_SNAKE_CASE      , attention_mask=_SCREAMING_SNAKE_CASE	).sequences

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



@require_flax
class 				_snake_case					(   unittest.TestCase			):

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase 						=							AutoTokenizer.from_pretrained('hf-internal-testing/tiny-bert'	)
      lowerCAmelCase 						=							FlaxAutoModelForCausalLM.from_pretrained('hf-internal-testing/tiny-bert-flax-only'	)

      lowerCAmelCase 						=							'Hello world'
      lowerCAmelCase 						=							tokenizer(_SCREAMING_SNAKE_CASE      , return_tensors='np'	).input_ids

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

      # arbitrary arguments that will not be used anywhere are also not accepted
      with self.assertRaisesRegex(_SCREAMING_SNAKE_CASE      , 'foo'	):
          lowerCAmelCase 						=							{'foo': 'bar'}
          model.generate(_SCREAMING_SNAKE_CASE      , **_SCREAMING_SNAKE_CASE	)








'''simple docstring'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCamelCase						:  Optional[int]							       =				logging.get_logger(__name__)

_UpperCamelCase						:  Tuple							       =				{
    "google/canine-s": "https://huggingface.co/google/canine-s/resolve/main/config.json",
    # See all CANINE models at https://huggingface.co/models?filter=canine
}



class 				_snake_case					(   a_			):
  SCREAMING_SNAKE_CASE			:       List[Any]				=     '''canine'''

  def __init__(				self      , _SCREAMING_SNAKE_CASE=7_68      , _SCREAMING_SNAKE_CASE=12      , _SCREAMING_SNAKE_CASE=12      , _SCREAMING_SNAKE_CASE=30_72      , _SCREAMING_SNAKE_CASE="gelu"      , _SCREAMING_SNAKE_CASE=0.1      , _SCREAMING_SNAKE_CASE=0.1      , _SCREAMING_SNAKE_CASE=1_63_84      , _SCREAMING_SNAKE_CASE=16      , _SCREAMING_SNAKE_CASE=0.02      , _SCREAMING_SNAKE_CASE=1e-12      , _SCREAMING_SNAKE_CASE=0      , _SCREAMING_SNAKE_CASE=0Xe0_00      , _SCREAMING_SNAKE_CASE=0Xe0_01      , _SCREAMING_SNAKE_CASE=4      , _SCREAMING_SNAKE_CASE=4      , _SCREAMING_SNAKE_CASE=8      , _SCREAMING_SNAKE_CASE=1_63_84      , _SCREAMING_SNAKE_CASE=1_28      , **_SCREAMING_SNAKE_CASE      , ):





      '''simple docstring'''

      super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE      , bos_token_id=_SCREAMING_SNAKE_CASE      , eos_token_id=_SCREAMING_SNAKE_CASE      , **_SCREAMING_SNAKE_CASE	)

      lowerCAmelCase 						=							max_position_embeddings
      lowerCAmelCase 						=							hidden_size
      lowerCAmelCase 						=							num_hidden_layers
      lowerCAmelCase 						=							num_attention_heads
      lowerCAmelCase 						=							intermediate_size
      lowerCAmelCase 						=							hidden_act
      lowerCAmelCase 						=							hidden_dropout_prob
      lowerCAmelCase 						=							attention_probs_dropout_prob
      lowerCAmelCase 						=							initializer_range
      lowerCAmelCase 						=							type_vocab_size
      lowerCAmelCase 						=							layer_norm_eps

      # Character config:
      lowerCAmelCase 						=							downsampling_rate
      lowerCAmelCase 						=							upsampling_kernel_size
      lowerCAmelCase 						=							num_hash_functions
      lowerCAmelCase 						=							num_hash_buckets
      lowerCAmelCase 						=							local_transformer_stride





