




import unittest

import numpy as np
import timeout_decorator  # noqa

from transformers import MarianConfig, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

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
							UpperCamelCase__  =		'platform'

							import jax
							import jax.numpy as jnp

							from transformers import MarianTokenizer
							from transformers.models.marian.modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, shift_tokens_right






def       snake_case      (							A		,     A		,     A=None		,     A=None		,     A=None		,     A=None		,     A=None		,     A=None		,     )							->							Optional[Any]:




	'''simple docstring'''


	if attention_mask is None:
		lowerCamelCase_							:	Optional[int]							     =							np.where(input_ids != config.pad_token_id		,     1		,     0    )
	if decoder_attention_mask is None:
		lowerCamelCase_							:	List[str]							     =							np.where(decoder_input_ids != config.pad_token_id		,     1		,     0    )
	if head_mask is None:
		lowerCamelCase_							:	str							     =							np.ones((config.encoder_layers, config.encoder_attention_heads)    )
	if decoder_head_mask is None:
		lowerCamelCase_							:	Optional[Any]							     =							np.ones((config.decoder_layers, config.decoder_attention_heads)    )
	if cross_attn_head_mask is None:
		lowerCamelCase_							:	int							     =							np.ones((config.decoder_layers, config.decoder_attention_heads)    )
	return {
	    "input_ids": input_ids,
	    "decoder_input_ids": decoder_input_ids,
	    "attention_mask": attention_mask,
	    "decoder_attention_mask": attention_mask,
	}


class        __SCREAMING_SNAKE_CASE							:

					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=32				, __lowercase=2				, __lowercase=1				, __lowercase=0				, __lowercase=0.02				, ):







						'''simple docstring'''




						lowerCamelCase_							:	Optional[Any]							     =							parent
						lowerCamelCase_							:	str							     =							batch_size
						lowerCamelCase_							:	int							     =							seq_length
						lowerCamelCase_							:	Optional[int]							     =							is_training
						lowerCamelCase_							:	Optional[Any]							     =							use_labels
						lowerCamelCase_							:	Union[str, Any]							     =							vocab_size
						lowerCamelCase_							:	List[str]							     =							hidden_size
						lowerCamelCase_							:	Optional[Any]							     =							num_hidden_layers
						lowerCamelCase_							:	str							     =							num_attention_heads
						lowerCamelCase_							:	Any							     =							intermediate_size
						lowerCamelCase_							:	str							     =							hidden_act
						lowerCamelCase_							:	List[str]							     =							hidden_dropout_prob
						lowerCamelCase_							:	Optional[int]							     =							attention_probs_dropout_prob
						lowerCamelCase_							:	Dict							     =							max_position_embeddings
						lowerCamelCase_							:	Dict							     =							eos_token_id
						lowerCamelCase_							:	Optional[int]							     =							pad_token_id
						lowerCamelCase_							:	Optional[Any]							     =							bos_token_id
						lowerCamelCase_							:	Dict							     =							initializer_range

					def 			lowercase_							(       self      ):







						'''simple docstring'''




						lowerCamelCase_							:	Dict							     =							np.clip(ids_tensor([self.batch_size, self.seq_length - 1]				, self.vocab_size      )				, 3				, self.vocab_size      )
						lowerCamelCase_							:	Tuple							     =							np.concatenate((input_ids, 2 * np.ones((self.batch_size, 1)				, dtype=np.intaa      ))				, -1      )

						lowerCamelCase_							:	int							     =							shift_tokens_right(__lowercase				, 1				, 2      )

						lowerCamelCase_							:	Tuple							     =							MarianConfig(
						    vocab_size=self.vocab_size				, d_model=self.hidden_size				, encoder_layers=self.num_hidden_layers				, decoder_layers=self.num_hidden_layers				, encoder_attention_heads=self.num_attention_heads				, decoder_attention_heads=self.num_attention_heads				, encoder_ffn_dim=self.intermediate_size				, decoder_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				, initializer_range=self.initializer_range				, use_cache=__lowercase				, )
						lowerCamelCase_							:	Dict							     =							prepare_marian_inputs_dict(__lowercase				, __lowercase				, __lowercase      )
						return config, inputs_dict

					def 			lowercase_							(       self      ):







						'''simple docstring'''




						lowerCamelCase_     ,    lowerCamelCase_							:	str							     =							self.prepare_config_and_inputs()
						return config, inputs_dict

					def 			lowercase_							(       self				, __lowercase				, __lowercase				, __lowercase      ):







						'''simple docstring'''




						lowerCamelCase_							:	Any							     =							20
						lowerCamelCase_							:	str							     =							model_class_name(__lowercase      )

						lowerCamelCase_							:	Optional[Any]							     =							model.encode(inputs_dict['input_ids']      )

						lowerCamelCase_     ,    lowerCamelCase_							:	Union[str, Any]							     =							(
						    inputs_dict['decoder_input_ids'],
						    inputs_dict['decoder_attention_mask'],
						)

						lowerCamelCase_							:	List[Any]							     =							model.init_cache(decoder_input_ids.shape[0]				, __lowercase				, __lowercase      )
						lowerCamelCase_							:	Optional[Any]							     =							jnp.ones((decoder_input_ids.shape[0], max_decoder_length)				, dtype='i4'      )

						lowerCamelCase_							:	Dict							     =							jnp.broadcast_to(
						    jnp.arange(decoder_input_ids.shape[-1] - 1      )[None, :]				, (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)				, )
						lowerCamelCase_							:	List[str]							     =							model.decode(
						    decoder_input_ids[:, :-1]				, __lowercase				, decoder_attention_mask=__lowercase				, past_key_values=__lowercase				, decoder_position_ids=__lowercase				, )

						lowerCamelCase_							:	Optional[int]							     =							jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]				, dtype='i4'      )
						lowerCamelCase_							:	Dict							     =							model.decode(
						    decoder_input_ids[:, -1:]				, __lowercase				, decoder_attention_mask=__lowercase				, past_key_values=outputs_cache.past_key_values				, decoder_position_ids=__lowercase				, )

						lowerCamelCase_							:	List[str]							     =							model.decode(__lowercase				, __lowercase      )

						lowerCamelCase_							:	Tuple							     =							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 			lowercase_							(       self				, __lowercase				, __lowercase				, __lowercase      ):







						'''simple docstring'''




						lowerCamelCase_							:	List[str]							     =							20
						lowerCamelCase_							:	Any							     =							model_class_name(__lowercase      )

						lowerCamelCase_							:	Union[str, Any]							     =							model.encode(inputs_dict['input_ids']      )

						lowerCamelCase_     ,    lowerCamelCase_							:	Union[str, Any]							     =							(
						    inputs_dict['decoder_input_ids'],
						    inputs_dict['decoder_attention_mask'],
						)

						lowerCamelCase_							:	Dict							     =							jnp.concatenate(
						    [
						        decoder_attention_mask,
						        jnp.zeros((decoder_attention_mask.shape[0], max_decoder_length - decoder_attention_mask.shape[1])      ),
						    ]				, axis=-1				, )

						lowerCamelCase_							:	Optional[int]							     =							model.init_cache(decoder_input_ids.shape[0]				, __lowercase				, __lowercase      )
						lowerCamelCase_							:	Dict							     =							jnp.broadcast_to(
						    jnp.arange(decoder_input_ids.shape[-1] - 1      )[None, :]				, (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)				, )

						lowerCamelCase_							:	Optional[Any]							     =							model.decode(
						    decoder_input_ids[:, :-1]				, __lowercase				, decoder_attention_mask=__lowercase				, past_key_values=__lowercase				, decoder_position_ids=__lowercase				, )
						lowerCamelCase_							:	List[str]							     =							jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]				, dtype='i4'      )
						lowerCamelCase_							:	Any							     =							model.decode(
						    decoder_input_ids[:, -1:]				, __lowercase				, past_key_values=outputs_cache.past_key_values				, decoder_attention_mask=__lowercase				, decoder_position_ids=__lowercase				, )

						lowerCamelCase_							:	List[Any]							     =							model.decode(__lowercase				, __lowercase				, decoder_attention_mask=__lowercase      )

						lowerCamelCase_							:	Tuple							     =							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        __SCREAMING_SNAKE_CASE							(	lowerCamelCase     ,  unittest.TestCase     ,  lowerCamelCase						):
					_lowerCamelCase							=				True
					_lowerCamelCase							=				(FlaxMarianModel, FlaxMarianMTModel) if is_flax_available() else ()
					_lowerCamelCase							=				(FlaxMarianMTModel,) if is_flax_available() else ()

					def 			lowercase_							(       self      ):







						'''simple docstring'''




						lowerCamelCase_							:	Union[str, Any]							     =							FlaxMarianModelTester(self      )

					def 			lowercase_							(       self      ):







						'''simple docstring'''




						lowerCamelCase_     ,    lowerCamelCase_							:	Dict							     =							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 			lowercase_							(       self      ):







						'''simple docstring'''




						lowerCamelCase_     ,    lowerCamelCase_							:	Tuple							     =							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      )

					def 			lowercase_							(       self      ):







						'''simple docstring'''




						lowerCamelCase_     ,    lowerCamelCase_							:	Optional[int]							     =							self.model_tester.prepare_config_and_inputs_for_common()

						for model_class in self.all_model_classes:
							with self.subTest(model_class.__name__      ):
								lowerCamelCase_							:	str							     =							self._prepare_for_class(__lowercase				, __lowercase      )
								lowerCamelCase_							:	Optional[Any]							     =							model_class(__lowercase      )

								@jax.jit
								def encode_jitted(__lowercase				, __lowercase=None				, **__lowercase      ):
									return model.encode(input_ids=__lowercase				, attention_mask=__lowercase      )

								with self.subTest('JIT Enabled'      ):
									lowerCamelCase_							:	Optional[Any]							     =							encode_jitted(**__lowercase      ).to_tuple()

								with self.subTest('JIT Disabled'      ):
									with jax.disable_jit():
										lowerCamelCase_							:	Optional[int]							     =							encode_jitted(**__lowercase      ).to_tuple()

								self.assertEqual(len(__lowercase      )				, len(__lowercase      )      )
								for jitted_output, output in zip(__lowercase				, __lowercase      ):
									self.assertEqual(jitted_output.shape				, output.shape      )

					def 			lowercase_							(       self      ):







						'''simple docstring'''




						lowerCamelCase_     ,    lowerCamelCase_							:	List[Any]							     =							self.model_tester.prepare_config_and_inputs_for_common()

						for model_class in self.all_model_classes:
							with self.subTest(model_class.__name__      ):
								lowerCamelCase_							:	int							     =							model_class(__lowercase      )
								lowerCamelCase_							:	Optional[int]							     =							model.encode(inputs_dict['input_ids']				, inputs_dict['attention_mask']      )

								lowerCamelCase_							:	Tuple							     =							{
								    'decoder_input_ids': inputs_dict['decoder_input_ids'],
								    'decoder_attention_mask': inputs_dict['decoder_attention_mask'],
								    'encoder_outputs': encoder_outputs,
								}

								@jax.jit
								def decode_jitted(__lowercase				, __lowercase				, __lowercase      ):
									return model.decode(
									    decoder_input_ids=__lowercase				, decoder_attention_mask=__lowercase				, encoder_outputs=__lowercase				, )

								with self.subTest('JIT Enabled'      ):
									lowerCamelCase_							:	Tuple							     =							decode_jitted(**__lowercase      ).to_tuple()

								with self.subTest('JIT Disabled'      ):
									with jax.disable_jit():
										lowerCamelCase_							:	int							     =							decode_jitted(**__lowercase      ).to_tuple()

								self.assertEqual(len(__lowercase      )				, len(__lowercase      )      )
								for jitted_output, output in zip(__lowercase				, __lowercase      ):
									self.assertEqual(jitted_output.shape				, output.shape      )





					@slow
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						for model_class_name in self.all_model_classes:
							lowerCamelCase_							:	List[Any]							     =							model_class_name.from_pretrained('Helsinki-NLP/opus-mt-en-de'      )
							# FlaxMarianForSequenceClassification expects eos token in input_ids
							lowerCamelCase_							:	List[Any]							     =							np.ones((1, 1)      ) * model.config.eos_token_id
							lowerCamelCase_							:	str							     =							model(__lowercase      )
							self.assertIsNotNone(__lowercase      )


@require_flax
@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE							(	unittest.TestCase						):
					_lowerCamelCase							=				None
					_lowerCamelCase							=				None

					@classmethod
					def 			lowercase_							(       cls      ):







						'''simple docstring'''




						lowerCamelCase_							:	List[Any]							     =							f"Helsinki-NLP/opus-mt-{cls.src}-{cls.tgt}"
						return cls

					@cached_property
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						return MarianTokenizer.from_pretrained(self.model_name      )

					@property
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						return self.tokenizer.eos_token_id

					@cached_property
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						lowerCamelCase_							:	FlaxMarianMTModel							     =							FlaxMarianMTModel.from_pretrained(self.model_name      )
						self.assertEqual(model.config.decoder_start_token_id				, model.config.pad_token_id      )
						return model

					def 			lowercase_							(       self				, **__lowercase      ):







						'''simple docstring'''




						lowerCamelCase_							:	List[str]							     =							self.translate_src_text(**__lowercase      )
						self.assertListEqual(self.expected_text				, __lowercase      )





					def 			lowercase_							(       self				, **__lowercase      ):







						'''simple docstring'''




						lowerCamelCase_							:	Optional[Any]							     =							self.tokenizer(self.src_text				, padding=__lowercase				, return_tensors='np'				, **__lowercase      )
						lowerCamelCase_							:	List[str]							     =							self.model.generate(
						    model_inputs.input_ids				, attention_mask=model_inputs.attention_mask				, num_beams=2				, max_length=128				, ).sequences
						lowerCamelCase_							:	List[str]							     =							self.tokenizer.batch_decode(__lowercase				, skip_special_tokens=__lowercase      )
						return generated_words


@require_flax
@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):
					_lowerCamelCase							=				"""en"""
					_lowerCamelCase							=				"""fr"""
					_lowerCamelCase							=				[
					    """I am a small frog.""",
					    """Now I can forget the 100 words of german that I know.""",
					]
					_lowerCamelCase							=				[
					    """Je suis une petite grenouille.""",
					    """Maintenant, je peux oublier les 100 mots d'allemand que je connais.""",
					]

					@slow
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):
					_lowerCamelCase							=				"""fr"""
					_lowerCamelCase							=				"""en"""
					_lowerCamelCase							=				[
					    """Donnez moi le micro.""",
					    """Tom et Mary étaient assis à une table.""",  # Accents
					]
					_lowerCamelCase							=				[
					    """Give me the microphone.""",
					    """Tom and Mary were sitting at a table.""",
					]

					@slow
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):
					_lowerCamelCase							=				"""mt"""
					_lowerCamelCase							=				"""en"""
					_lowerCamelCase							=				["""Billi messu b'mod ġentili, Ġesù fejjaq raġel li kien milqut bil - marda kerha tal - ġdiem."""]
					_lowerCamelCase							=				["""Touching gently, Jesus healed a man who was affected by the sad disease of leprosy."""]

					@slow
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):
					_lowerCamelCase							=				"""en"""
					_lowerCamelCase							=				"""de"""
					_lowerCamelCase							=				[
					    """I am a small frog.""",
					    """Now I can forget the 100 words of german that I know.""",
					    """Tom asked his teacher for advice.""",
					    """That's how I would do it.""",
					    """Tom really admired Mary's courage.""",
					    """Turn around and close your eyes.""",
					]
					_lowerCamelCase							=				[
					    """Ich bin ein kleiner Frosch.""",
					    """Jetzt kann ich die 100 Wörter des Deutschen vergessen, die ich kenne.""",
					    """Tom bat seinen Lehrer um Rat.""",
					    """So würde ich das machen.""",
					    """Tom bewunderte Marias Mut wirklich.""",
					    """Drehen Sie sich um und schließen Sie die Augen.""",
					]

					@slow
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):
					_lowerCamelCase							=				"""en"""
					_lowerCamelCase							=				"""zh"""
					_lowerCamelCase							=				["""My name is Wolfgang and I live in Berlin"""]
					_lowerCamelCase							=				["""我叫沃尔夫冈 我住在柏林"""]

					@slow
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):
					_lowerCamelCase							=				"""ru"""
					_lowerCamelCase							=				"""fr"""
					_lowerCamelCase							=				["""Он показал мне рукопись своей новой пьесы."""]
					_lowerCamelCase							=				["""Il m'a montré le manuscrit de sa nouvelle pièce."""]

					@slow
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						self._assert_generated_batch_equal_expected()


@require_flax
@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):
					_lowerCamelCase							=				"""en"""
					_lowerCamelCase							=				"""ROMANCE"""
					_lowerCamelCase							=				[
					    """>>fr<< Don't spend so much time watching TV.""",
					    """>>pt<< Your message has been sent.""",
					    """>>es<< He's two years older than me.""",
					]
					_lowerCamelCase							=				[
					    """Ne passez pas autant de temps à regarder la télé.""",
					    """A sua mensagem foi enviada.""",
					    """Es dos años más viejo que yo.""",
					]

					@slow
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						self._assert_generated_batch_equal_expected()






from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
							from .image_encoder import PaintByExampleImageEncoder
							from .pipeline_paint_by_example import PaintByExamplePipeline
