'''simple docstring'''
import unittest

import numpy as np
import timeout_decorator  # noqa

from transformers import OPTConfig, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, slow

from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor


if is_flax_available():
 import os

 # The slow tests are often failing with OOM error on GPU
 # This makes JAX allocate exactly what is needed on demand, and deallocate memory that is no longer needed
 # but will be slower as stated here https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html
 _A		:      Tuple						   ="""platform"""

 import jax
 import jax.numpy as jnp

 from transformers import FlaxOPTForCausalLM, FlaxOPTModel, GPTaTokenizer







def 				__UpperCamelCase (					__UpperCAmelCase  :					List[str] ,   __UpperCAmelCase  :					Any ,   __UpperCAmelCase  :					Any=None ,   __UpperCAmelCase  :					int=None			)							->	str:
  if attention_mask is None:
    lowercase				:							Union[str, Any]									=   np.where(input_ids != config.pad_token_id ,   1 ,   0			)
  return {
      "input_ids": input_ids,
      "attention_mask": attention_mask,
  }




@require_flax
class _lowerCAmelCase			:







      def __init__(  self  ,    lowercase  ,    lowercase=13  ,    lowercase=7  ,    lowercase=True  ,    lowercase=False  ,    lowercase=99  ,    lowercase=16  ,    lowercase=2  ,    lowercase=4  ,    lowercase=4  ,    lowercase="gelu"  ,    lowercase=0.1  ,    lowercase=0.1  ,    lowercase=20  ,    lowercase=2  ,    lowercase=1  ,    lowercase=0  ,    lowercase=16  ,    lowercase=16  ,    lowercase=0.02  ,    ):
        lowercase				:							str									=   parent
        lowercase				:							Optional[int]									=   batch_size
        lowercase				:							Union[str, Any]									=   seq_length
        lowercase				:							Tuple									=   is_training
        lowercase				:							List[Any]									=   use_labels
        lowercase				:							Optional[int]									=   vocab_size
        lowercase				:							List[str]									=   hidden_size
        lowercase				:							Tuple									=   num_hidden_layers
        lowercase				:							Any									=   num_attention_heads
        lowercase				:							int									=   intermediate_size
        lowercase				:							Optional[int]									=   hidden_act
        lowercase				:							Tuple									=   hidden_dropout_prob
        lowercase				:							int									=   attention_probs_dropout_prob
        lowercase				:							Optional[Any]									=   max_position_embeddings
        lowercase				:							Any									=   eos_token_id
        lowercase				:							List[Any]									=   pad_token_id
        lowercase				:							Any									=   bos_token_id
        lowercase				:							Any									=   embed_dim
        lowercase				:							Dict									=   word_embed_proj_dim
        lowercase				:							List[str]									=   initializer_range
        lowercase				:							List[str]									=   False







      def      lowerCamelCase__      (  self     ):
        lowercase				:							List[str]									=   np.clip(ids_tensor([self.batch_size, self.seq_length - 1]  ,    self.vocab_size     )  ,    3  ,    self.vocab_size     )
        lowercase				:							List[Any]									=   np.concatenate((input_ids, 2 * np.ones((self.batch_size, 1)  ,    dtype=np.intaa     ))  ,    -1     )

        lowercase				:							int									=   OPTConfig(
            vocab_size=self.vocab_size  ,    hidden_size=self.hidden_size  ,    num_hidden_layers=self.num_hidden_layers  ,    num_attention_heads=self.num_attention_heads  ,    ffn_dim=self.intermediate_size  ,    dropout=self.hidden_dropout_prob  ,    attention_dropout=self.attention_probs_dropout_prob  ,    max_position_embeddings=self.max_position_embeddings  ,    eos_token_id=self.eos_token_id  ,    bos_token_id=self.bos_token_id  ,    pad_token_id=self.pad_token_id  ,    embed_dim=self.embed_dim  ,    is_encoder_decoder=__lowercase  ,    word_embed_proj_dim=self.word_embed_proj_dim  ,    initializer_range=self.initializer_range  ,    use_cache=__lowercase  ,    )
        lowercase				:							List[str]									=   prepare_opt_inputs_dict(__lowercase  ,    __lowercase     )
        return config, inputs_dict







      def      lowerCamelCase__      (  self     ):
        lowercase				:							Tuple									=   self.prepare_config_and_inputs()
        return config, inputs_dict







      def      lowerCamelCase__      (  self  ,    lowercase  ,    lowercase  ,    lowercase     ):
        lowercase				:							int									=   20
        lowercase				:							List[str]									=   model_class_name(__lowercase     )

        lowercase				:							Optional[int]									=   inputs_dict['''input_ids''']
        lowercase				:							Tuple									=   inputs_dict['''attention_mask''']

        lowercase				:							List[str]									=   model.init_cache(input_ids.shape[0]  ,    __lowercase     )
        lowercase				:							List[Any]									=   jnp.ones((input_ids.shape[0], max_length)  ,    dtype='''i4'''     )

        lowercase				:							Optional[Any]									=   jnp.broadcast_to(
            jnp.arange(input_ids.shape[-1] - 1     )[None, :]  ,    (input_ids.shape[0], input_ids.shape[-1] - 1)  ,    )
        lowercase				:							Optional[int]									=   model(
            input_ids[:, :-1]  ,    attention_mask=__lowercase  ,    past_key_values=__lowercase  ,    position_ids=__lowercase  ,    )

        lowercase				:							Dict									=   jnp.array(input_ids.shape[0] * [[input_ids.shape[-1] - 1]]  ,    dtype='''i4'''     )
        lowercase				:							Optional[Any]									=   model(
            input_ids[:, -1:]  ,    attention_mask=__lowercase  ,    past_key_values=outputs_cache.past_key_values  ,    position_ids=__lowercase  ,    )

        lowercase				:							Dict									=   model(__lowercase     )

        lowercase				:							int									=   np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])     )     )
        self.parent.assertTrue(diff < 1e-3  ,    msg=F"""Max diff is {diff}"""     )







      def      lowerCamelCase__      (  self  ,    lowercase  ,    lowercase  ,    lowercase     ):
        lowercase				:							Tuple									=   20
        lowercase				:							Union[str, Any]									=   model_class_name(__lowercase     )

        lowercase				:							List[Any]									=   (
            inputs_dict['''input_ids'''],
            inputs_dict['''attention_mask'''],
        )

        lowercase				:							Optional[int]									=   jnp.concatenate(
            [
                attention_mask,
                jnp.zeros((attention_mask.shape[0], max_length - attention_mask.shape[1])     ),
            ]  ,    axis=-1  ,    )

        lowercase				:							List[str]									=   model.init_cache(input_ids.shape[0]  ,    __lowercase     )
        lowercase				:							List[str]									=   jnp.broadcast_to(
            jnp.arange(input_ids.shape[-1] - 1     )[None, :]  ,    (input_ids.shape[0], input_ids.shape[-1] - 1)  ,    )

        lowercase				:							Union[str, Any]									=   model(
            input_ids[:, :-1]  ,    attention_mask=__lowercase  ,    past_key_values=__lowercase  ,    position_ids=__lowercase  ,    )
        lowercase				:							Union[str, Any]									=   jnp.array(input_ids.shape[0] * [[input_ids.shape[-1] - 1]]  ,    dtype='''i4'''     )
        lowercase				:							Dict									=   model(
            input_ids[:, -1:]  ,    past_key_values=outputs_cache.past_key_values  ,    attention_mask=__lowercase  ,    position_ids=__lowercase  ,    )

        lowercase				:							Union[str, Any]									=   model(__lowercase  ,    attention_mask=__lowercase     )

        lowercase				:							List[str]									=   np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])     )     )
        self.parent.assertTrue(diff < 1e-3  ,    msg=F"""Max diff is {diff}"""     )





@require_flax
class _lowerCAmelCase			(	UpperCAmelCase__							,   unittest.TestCase							,   UpperCAmelCase__					):
      UpperCAmelCase_	:						Optional[int]	 =       (FlaxOPTModel, FlaxOPTForCausalLM) if is_flax_available() else ()
      UpperCAmelCase_	:						Tuple	 =       () if is_flax_available() else ()







      def      lowerCamelCase__      (  self     ):
        lowercase				:							str									=   FlaxOPTModelTester(self     )







      def      lowerCamelCase__      (  self     ):
        lowercase				:							List[Any]									=   self.model_tester.prepare_config_and_inputs()
        for model_class in self.all_model_classes:
          self.model_tester.check_use_cache_forward(__lowercase  ,    __lowercase  ,    __lowercase     )







      def      lowerCamelCase__      (  self     ):
        lowercase				:							List[str]									=   self.model_tester.prepare_config_and_inputs()
        for model_class in self.all_model_classes:
          self.model_tester.check_use_cache_forward_with_attn_mask(__lowercase  ,    __lowercase  ,    __lowercase     )







      @slow
      def      lowerCamelCase__      (  self     ):
        for model_class_name in self.all_model_classes:
          lowercase				:							Optional[int]									=   model_class_name.from_pretrained('''facebook/opt-125m'''     )
          lowercase				:							str									=   np.ones((1, 1)     ) * model.config.eos_token_id
          lowercase				:							Any									=   model(__lowercase     )
          self.assertIsNotNone(__lowercase     )





@require_sentencepiece
@require_flax
class _lowerCAmelCase			(	unittest.TestCase					):







      @slow
      def      lowerCamelCase__      (  self     ):
        lowercase				:							int									=   FlaxOPTModel.from_pretrained('''facebook/opt-350m'''     )
        lowercase				:							List[str]									=   jnp.array([[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]]     )
        lowercase				:							List[str]									=   model(input_ids=__lowercase     ).last_hidden_state
        lowercase				:							Tuple									=   (1, 11, 512)
        self.assertEqual(output.shape  ,    __lowercase     )
        lowercase				:							Union[str, Any]									=   jnp.array(
            [[-0.2867, -1.9256, -0.3062], [-1.2711, -0.1337, -0.1897], [0.4109, 0.1187, -1.3142]]     )
        self.assertTrue(jnp.allclose(output[:, :3, :3]  ,    __lowercase  ,    atol=4e-2     )     )





@require_flax
@slow
class _lowerCAmelCase			(	unittest.TestCase					):







      def      lowerCamelCase__      (  self     ):
        super().setUp()
        lowercase				:							Any									=   '''facebook/opt-350m'''







      def      lowerCamelCase__      (  self     ):
        lowercase				:							Optional[Any]									=   FlaxOPTForCausalLM.from_pretrained(self.path_model     )
        lowercase				:							List[Any]									=   GPTaTokenizer.from_pretrained(self.path_model     )

        lowercase				:							List[Any]									=   [
            '''Today is a beautiful day and I want to''',
            '''In the city of''',
            '''Paris is the capital of France and''',
            '''Computers and mobile phones have taken''',
        ]
        # verify that prompt without BOS token is identical to Metaseq -> add_special_tokens=False
        lowercase				:							Tuple									=   tokenizer(__lowercase  ,    return_tensors='''jax'''  ,    padding=__lowercase  ,    add_special_tokens=__lowercase     )
        lowercase				:							List[str]									=   model(inputs.input_ids  ,    attention_mask=inputs.attention_mask     )[0].mean(axis=-1     )
        lowercase				:							List[str]									=   jnp.array(
            [
                [1.3851, -13.8923, -10.5229, -10.7533, -0.2309, -10.2384, -0.5365, -9.0947, -5.1670],
                [-4.7073, -10.6276, -3.9415, -21.5242, -0.2822, -0.2822, -0.2822, -0.2822, -0.2822],
                [0.6247, -3.4229, -8.9179, -1.4297, -14.1650, 1.4146, -9.0218, -0.2703, -0.2703],
                [6.4783, -1.9913, -10.7926, -2.3336, 1.5092, -0.9974, -6.8213, 1.3477, 1.3477],
            ]     )
        self.assertTrue(jnp.allclose(__lowercase  ,    __lowercase  ,    atol=4e-2     )     )

        lowercase				:							str									=   jax.jit(__lowercase     )
        lowercase				:							List[str]									=   model(inputs.input_ids  ,    attention_mask=inputs.attention_mask     )[0].mean(axis=-1     )
        self.assertTrue(jnp.allclose(__lowercase  ,    __lowercase  ,    atol=4e-2     )     )





@require_flax
@slow
class _lowerCAmelCase			(	unittest.TestCase					):







      @property
      def      lowerCamelCase__      (  self     ):
        return [
            "Today is a beautiful day and I want",
            "In the city of",
            "Paris is the capital of France and",
            "Computers and mobile phones have taken",
        ]







      def      lowerCamelCase__      (  self     ):
        lowercase				:							List[str]									=   '''facebook/opt-125m'''

        lowercase				:							int									=   [
            '''Today is a beautiful day and I want to''',
            '''In the city of New York, the city''',
            '''Paris is the capital of France and the capital''',
            '''Computers and mobile phones have taken over the''',
        ]

        lowercase				:							Any									=   []

        lowercase				:							List[Any]									=   FlaxOPTForCausalLM.from_pretrained(__lowercase     )
        lowercase				:							int									=   GPTaTokenizer.from_pretrained(__lowercase     )

        for prompt in self.prompts:
          lowercase				:							Tuple									=   tokenizer(__lowercase  ,    return_tensors='''jax'''     ).input_ids

          lowercase				:							Optional[int]									=   model.generate(__lowercase  ,    max_length=10     )
          lowercase				:							List[Any]									=   generated_ids[0]

          lowercase				:							Union[str, Any]									=   tokenizer.batch_decode(__lowercase  ,    skip_special_tokens=__lowercase     )
          predicted_outputs += generated_string

        self.assertListEqual(__lowercase  ,    __lowercase     )







      def      lowerCamelCase__      (  self     ):
        lowercase				:							Optional[Any]									=   '''facebook/opt-350m'''

        lowercase				:							Optional[Any]									=   [
            '''Today is a beautiful day and I want to''',
            '''In the city of San Francisco, the city''',
            '''Paris is the capital of France and the capital''',
            '''Computers and mobile phones have taken over the''',
        ]

        lowercase				:							Optional[Any]									=   []
        lowercase				:							Optional[int]									=   FlaxOPTForCausalLM.from_pretrained(__lowercase     )
        lowercase				:							Optional[Any]									=   GPTaTokenizer.from_pretrained(__lowercase     )

        for prompt in self.prompts:
          lowercase				:							Optional[int]									=   tokenizer(__lowercase  ,    return_tensors='''jax'''     ).input_ids

          lowercase				:							str									=   model.generate(__lowercase  ,    max_length=10     )
          lowercase				:							Optional[int]									=   generated_ids[0]

          lowercase				:							Union[str, Any]									=   tokenizer.batch_decode(__lowercase  ,    skip_special_tokens=__lowercase     )
          predicted_outputs += generated_string

        self.assertListEqual(__lowercase  ,    __lowercase     )







      def      lowerCamelCase__      (  self     ):
        lowercase				:							Optional[Any]									=   '''facebook/opt-125m'''
        lowercase				:							Union[str, Any]									=   [
            '''Today is a beautiful day and I want to thank''',
            '''In the city of Rome Canaver Canaver Canaver Canaver''',
        ]
        lowercase				:							Optional[int]									=   FlaxOPTForCausalLM.from_pretrained(__lowercase     )
        lowercase				:							int									=   GPTaTokenizer.from_pretrained(__lowercase     )
        lowercase				:							Optional[Any]									=   tokenizer(
            [
                '''Today is a beautiful day and I want to''',
                '''In the city of''',
            ]  ,    return_tensors='''jax'''  ,    padding=__lowercase  ,    )

        lowercase				:							str									=   jax.jit(model.generate     )

        lowercase				:							str									=   jit_generate(inputs['''input_ids''']  ,    attention_mask=inputs['''attention_mask''']     ).sequences

        lowercase				:							List[str]									=   tokenizer.batch_decode(__lowercase  ,    skip_special_tokens=__lowercase     )

        self.assertIsNotNone(__lowercase  ,    __lowercase     )







      def      lowerCamelCase__      (  self     ):
        lowercase				:							Optional[int]									=   '''facebook/opt-350m'''

        lowercase				:							str									=   GPTaTokenizer.from_pretrained(__lowercase     )
        lowercase				:							Optional[int]									=   FlaxOPTForCausalLM.from_pretrained(__lowercase     )

        lowercase				:							Tuple									=   '''left'''

        # use different length sentences to test batching
        lowercase				:							Any									=   [
            '''Hello, my dog is a little''',
            '''Today, I''',
        ]

        lowercase				:							int									=   tokenizer(__lowercase  ,    return_tensors='''jax'''  ,    padding=__lowercase     )
        lowercase				:							List[Any]									=   inputs['''input_ids''']

        lowercase				:							Optional[Any]									=   model.generate(input_ids=__lowercase  ,    attention_mask=inputs['''attention_mask''']  ,    trace=__lowercase     )

        lowercase				:							List[str]									=   tokenizer(sentences[0]  ,    return_tensors='''jax'''     ).input_ids
        lowercase				:							Optional[Any]									=   model.generate(input_ids=__lowercase     )

        lowercase				:							Tuple									=   inputs_non_padded.shape[-1] - inputs['''attention_mask'''][-1].sum()
        lowercase				:							int									=   tokenizer(sentences[1]  ,    return_tensors='''jax'''     ).input_ids
        lowercase				:							Tuple									=   model.generate(input_ids=__lowercase  ,    max_length=model.config.max_length - num_paddings     )

        lowercase				:							List[Any]									=   tokenizer.batch_decode(outputs[0]  ,    skip_special_tokens=__lowercase     )
        lowercase				:							List[Any]									=   tokenizer.decode(output_non_padded[0][0]  ,    skip_special_tokens=__lowercase     )
        lowercase				:							Any									=   tokenizer.decode(output_padded[0][0]  ,    skip_special_tokens=__lowercase     )

        lowercase				:							int									=   [
            '''Hello, my dog is a little bit of a dork.\nI\'m a little bit''',
            '''Today, I was in the middle of a conversation with a friend about the''',
        ]
        self.assertListEqual(__lowercase  ,    __lowercase     )
        self.assertListEqual(__lowercase  ,    [non_padded_sentence, padded_sentence]     )



from transformers import PretrainedConfig







class 					snake_case__(				UpperCAmelCase__				):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__   :	Optional[int]       =				"""custom"""




						def __init__(					self ,    __lowercase=1 ,    **__lowercase				)       ->     Dict:
										lowerCAmelCase_			:   List[Any]     					=					attribute
										super().__init__(**__lowercase				)







class 					snake_case__(				UpperCAmelCase__				):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__   :	int       =				"""custom"""




						def __init__(					self ,    __lowercase=1 ,    **__lowercase				)       ->     List[Any]:
										lowerCAmelCase_			:   Optional[Any]     					=					attribute