


"""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     					=   "0.12"  # assumed parallelism: 8


if is_torch_available():
   import torch





def      lowercase__						(	lowerCamelCase  :	List[str]					,						lowerCamelCase  :	List[str]					,						lowerCamelCase  :	Optional[Any]=None					)       ->  Optional[Any]:




  if rng is None:
    lowerCAmelCase__     :     int										=       random.Random()

  lowerCAmelCase__     :     Optional[Any]										=       1
  for dim in shape:
    total_dims *= dim

  lowerCAmelCase__     :     Optional[int]										=       []
  for _ in range(lowerCamelCase__					):
    values.append(rng.randint(0					,						vocab_size - 1					)					)

  lowerCAmelCase__     :     Optional[Any]										=       np.array(lowerCamelCase__					,						dtype=jnp.intaa					).reshape(lowerCamelCase__					)

  return output





def      lowercase__						(	lowerCamelCase  :	Optional[Any]					,						lowerCamelCase  :	Optional[int]=None					)       ->  Optional[int]:
  lowerCAmelCase__     :     Union[str, Any]										=       ids_tensor(lowerCamelCase__					,						vocab_size=2					,						rng=lowerCamelCase__					)
  # make sure that at least one token is attended to for each batch
  lowerCAmelCase__     :     List[str]										=       1
  return attn_mask

@require_flax
class 			lowercase_	:
      __magic_name__  :				Dict 							=					None
      __magic_name__  :				Optional[Any] 							=					()







      def 					_lowerCAmelCase							(   self			:				int     ):
        lowerCAmelCase__					,		lowerCAmelCase__     :     Dict										=       self.model_tester.prepare_config_and_inputs_for_common()

        # cut to half length & take max batch_size 3
        lowerCAmelCase__     :     int										=       2
        lowerCAmelCase__     :     Optional[int]										=       inputs["input_ids"].shape[-1] // 2
        lowerCAmelCase__     :     List[str]										=       inputs["input_ids"][:max_batch_size, :sequence_length]

        lowerCAmelCase__     :     List[Any]										=       jnp.ones_like(_lowercase     )
        lowerCAmelCase__     :     Optional[int]										=       attention_mask[:max_batch_size, :sequence_length]

        # generate max 5 tokens
        lowerCAmelCase__     :     List[str]										=       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__     :     Optional[Any]										=       config.eos_token_id
        return config, input_ids, attention_mask, max_length







      @is_pt_flax_cross_test
      def 					_lowerCAmelCase							(   self			:				Union[str, Any]     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     Optional[int]										=       self._get_input_ids_and_config()
        lowerCAmelCase__     :     str										=       False
        lowerCAmelCase__     :     Optional[Any]										=       max_length
        lowerCAmelCase__     :     str										=       0

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     List[Any]										=       model_class(_lowercase     )

          lowerCAmelCase__     :     Dict										=       model_class.__name__[4:]  # Skip the "Flax" at the beginning
          lowerCAmelCase__     :     List[Any]										=       getattr(_lowercase		,	_lowercase     )
          lowerCAmelCase__     :     str										=       pt_model_class(_lowercase     ).eval()
          lowerCAmelCase__     :     Optional[int]										=       load_flax_weights_in_pytorch_model(_lowercase		,	flax_model.params     )

          lowerCAmelCase__     :     int										=       flax_model.generate(_lowercase     ).sequences
          lowerCAmelCase__     :     Any										=       pt_model.generate(torch.tensor(_lowercase		,	dtype=torch.long     )     )

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

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







      def 					_lowerCAmelCase							(   self			:				Any     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     Optional[Any]										=       self._get_input_ids_and_config()
        lowerCAmelCase__     :     Dict										=       False
        lowerCAmelCase__     :     Optional[int]										=       max_length

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     int										=       model_class(_lowercase     )

          lowerCAmelCase__     :     int										=       model.generate(_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     int										=       jit(model.generate     )
          lowerCAmelCase__     :     List[Any]										=       jit_generate(_lowercase     ).sequences

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







      def 					_lowerCAmelCase							(   self			:				Union[str, Any]     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     List[str]										=       self._get_input_ids_and_config()
        lowerCAmelCase__     :     int										=       True
        lowerCAmelCase__     :     List[str]										=       max_length

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     Union[str, Any]										=       model_class(_lowercase     )

          lowerCAmelCase__     :     int										=       model.generate(_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     Optional[int]										=       jit(model.generate     )
          lowerCAmelCase__     :     Optional[Any]										=       jit_generate(_lowercase     ).sequences

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







      def 					_lowerCAmelCase							(   self			:				Any     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     Tuple										=       self._get_input_ids_and_config()
        lowerCAmelCase__     :     Optional[int]										=       False
        lowerCAmelCase__     :     Any										=       max_length
        lowerCAmelCase__     :     str										=       2

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     int										=       model_class(_lowercase     )

          lowerCAmelCase__     :     List[str]										=       model.generate(_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     Any										=       jit(model.generate     )
          lowerCAmelCase__     :     List[str]										=       jit_generate(_lowercase     ).sequences

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







      def 					_lowerCAmelCase							(   self			:				Union[str, Any]     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     Any										=       self._get_input_ids_and_config()
        lowerCAmelCase__     :     Union[str, Any]										=       False
        lowerCAmelCase__     :     List[str]										=       max_length
        lowerCAmelCase__     :     Union[str, Any]										=       2
        lowerCAmelCase__     :     Dict										=       2

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     int										=       model_class(_lowercase     )

          lowerCAmelCase__     :     Union[str, Any]										=       model.generate(_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[0]		,	input_ids.shape[0] * config.num_return_sequences     )







      def 					_lowerCAmelCase							(   self			:				Optional[int]     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     Union[str, Any]										=       self._get_input_ids_and_config()
        lowerCAmelCase__     :     str										=       True
        lowerCAmelCase__     :     int										=       max_length
        lowerCAmelCase__     :     Tuple										=       0.8
        lowerCAmelCase__     :     Optional[Any]										=       1_0
        lowerCAmelCase__     :     Tuple										=       0.3
        lowerCAmelCase__     :     Any										=       1
        lowerCAmelCase__     :     str										=       8
        lowerCAmelCase__     :     List[str]										=       9

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     Optional[Any]										=       model_class(_lowercase     )

          lowerCAmelCase__     :     Optional[int]										=       model.generate(_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     Dict										=       jit(model.generate     )
          lowerCAmelCase__     :     List[Any]										=       jit_generate(_lowercase     ).sequences

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







      def 					_lowerCAmelCase							(   self			:				List[str]     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     str										=       self._get_input_ids_and_config()
        lowerCAmelCase__     :     Any										=       max_length
        lowerCAmelCase__     :     List[Any]										=       1
        lowerCAmelCase__     :     List[str]										=       8
        lowerCAmelCase__     :     List[Any]										=       9

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     str										=       model_class(_lowercase     )

          lowerCAmelCase__     :     Union[str, Any]										=       model.generate(_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     List[str]										=       jit(model.generate     )
          lowerCAmelCase__     :     Tuple										=       jit_generate(_lowercase     ).sequences

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







      def 					_lowerCAmelCase							(   self			:				Optional[int]     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     Optional[Any]										=       self._get_input_ids_and_config()
        lowerCAmelCase__     :     Optional[Any]										=       max_length
        lowerCAmelCase__     :     Optional[int]										=       2
        lowerCAmelCase__     :     str										=       1
        lowerCAmelCase__     :     Any										=       8
        lowerCAmelCase__     :     Any										=       9

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     List[Any]										=       model_class(_lowercase     )

          lowerCAmelCase__     :     int										=       model.generate(_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     int										=       jit(model.generate     )
          lowerCAmelCase__     :     Union[str, Any]										=       jit_generate(_lowercase     ).sequences

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







      def 					_lowerCAmelCase							(   self			:				Tuple     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     List[str]										=       self._get_input_ids_and_config()

        # pad attention mask on the left
        lowerCAmelCase__     :     List[str]										=       attention_mask.at[(0, 0)].set(0     )

        lowerCAmelCase__     :     Union[str, Any]										=       False
        lowerCAmelCase__     :     Union[str, Any]										=       max_length

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     int										=       model_class(_lowercase     )

          lowerCAmelCase__     :     Any										=       model.generate(_lowercase		,	attention_mask=_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     int										=       jit(model.generate     )
          lowerCAmelCase__     :     Union[str, Any]										=       jit_generate(_lowercase		,	attention_mask=_lowercase     ).sequences

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







      def 					_lowerCAmelCase							(   self			:				List[Any]     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     List[str]										=       self._get_input_ids_and_config()

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

        lowerCAmelCase__     :     int										=       True
        lowerCAmelCase__     :     Dict										=       max_length

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     Dict										=       model_class(_lowercase     )

          lowerCAmelCase__     :     Any										=       model.generate(_lowercase		,	attention_mask=_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     str										=       jit(model.generate     )
          lowerCAmelCase__     :     str										=       jit_generate(_lowercase		,	attention_mask=_lowercase     ).sequences

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







      def 					_lowerCAmelCase							(   self			:				Tuple     ):
        lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__					,		lowerCAmelCase__     :     Optional[Any]										=       self._get_input_ids_and_config()

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

        lowerCAmelCase__     :     int										=       2
        lowerCAmelCase__     :     int										=       max_length

        for model_class in self.all_generative_model_classes:
          lowerCAmelCase__     :     Union[str, Any]										=       model_class(_lowercase     )

          lowerCAmelCase__     :     Dict										=       model.generate(_lowercase		,	attention_mask=_lowercase     ).sequences
          self.assertEqual(generation_outputs.shape[-1]		,	_lowercase     )

          lowerCAmelCase__     :     Union[str, Any]										=       jit(model.generate     )
          lowerCAmelCase__     :     Tuple										=       jit_generate(_lowercase		,	attention_mask=_lowercase     ).sequences

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

@require_flax
class 			lowercase_	(			unittest.TestCase    ):







      def 					_lowerCAmelCase							(   self			:				List[Any]     ):
        lowerCAmelCase__     :     List[Any]										=       AutoTokenizer.from_pretrained("hf-internal-testing/tiny-bert"     )
        lowerCAmelCase__     :     List[str]										=       FlaxAutoModelForCausalLM.from_pretrained("hf-internal-testing/tiny-bert-flax-only"     )

        lowerCAmelCase__     :     Any										=       "Hello world"
        lowerCAmelCase__     :     Any										=       tokenizer(_lowercase		,	return_tensors="np"     ).input_ids

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

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




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


UpperCAmelCase   :    Union[str, Any]     =		logging.get_logger(__name__)

UpperCAmelCase   :    List[Any]     =		{
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}







class        __lowercase       (							a_  ):



		"""simple docstring"""

		UpperCamelCase     :					List[str]			       =		"lilt"







		def __init__( self		,      A=3_05_22		,      A=7_68		,      A=12		,      A=12		,      A=30_72		,      A="gelu"		,      A=0.1		,      A=0.1		,      A=5_12		,      A=2		,      A=0.02		,      A=1e-1_2		,      A=0		,      A="absolute"		,      A=None		,      A=4		,      A=10_24		,      **A		,      )  -> List[Any]:







					'''simple docstring'''







					super().__init__(pad_token_id=A		,      **A	)

					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    		=  type_vocab_size
					lowerCamelCase    		=  initializer_range
					lowerCamelCase    		=  layer_norm_eps
					lowerCamelCase    		=  position_embedding_type
					lowerCamelCase    		=  classifier_dropout
					lowerCamelCase    		=  channel_shrink_ratio
					lowerCamelCase    		=  max_ad_position_embeddings

