


import unittest

import numpy as np
import timeout_decorator  # noqa

from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, 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			:						Union[str, Any]        =  'platform'

	import jax
	import jax.numpy as jnp

	from transformers import BlenderbotTokenizer
	from transformers.models.blenderbot.modeling_flax_blenderbot import (
	    FlaxBlenderbotForConditionalGeneration,
	    FlaxBlenderbotModel,
	    shift_tokens_right,
	)






def 					UpperCamelCase   (      __magic_name__	:				Union[str, Any]       ,       __magic_name__	:				Union[str, Any]       ,       __magic_name__	:				str=None       ,       __magic_name__	:				str=None       ,       __magic_name__	:				Union[str, Any]=None       ,       __magic_name__	:				Union[str, Any]=None       ,       __magic_name__	:				List[Any]=None       ,       __magic_name__	:				int=None       ,       )  ->    List[str]:
		"""simple docstring"""




		if attention_mask is None:
				lowercase__	     =						np.where(input_ids != config.pad_token_id       ,       1       ,       0	)
		if decoder_attention_mask is None:
				lowercase__	     =						np.where(decoder_input_ids != config.pad_token_id       ,       1       ,       0	)
		if head_mask is None:
				lowercase__	     =						np.ones((config.encoder_layers, config.encoder_attention_heads)	)
		if decoder_head_mask is None:
				lowercase__	     =						np.ones((config.decoder_layers, config.decoder_attention_heads)	)
		if cross_attn_head_mask is None:
				lowercase__	     =						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 				A       :
					'''simple docstring'''






					def __init__(self       :		str ,   _UpperCAmelCase       :		Optional[Any] ,   _UpperCAmelCase       :		Dict=13 ,   _UpperCAmelCase       :		List[Any]=7 ,   _UpperCAmelCase       :		Any=True ,   _UpperCAmelCase       :		Any=False ,   _UpperCAmelCase       :		Any=99 ,   _UpperCAmelCase       :		Dict=16 ,   _UpperCAmelCase       :		List[str]=2 ,   _UpperCAmelCase       :		Union[str, Any]=4 ,   _UpperCAmelCase       :		List[Any]=4 ,   _UpperCAmelCase       :		Any="gelu" ,   _UpperCAmelCase       :		Tuple=0.1 ,   _UpperCAmelCase       :		Dict=0.1 ,   _UpperCAmelCase       :		List[str]=32 ,   _UpperCAmelCase       :		Optional[int]=2 ,   _UpperCAmelCase       :		str=1 ,   _UpperCAmelCase       :		Optional[Any]=0 ,   _UpperCAmelCase       :		Dict=0.02 ,   )		->  Dict:




							"""simple docstring"""


							lowercase__	     =						parent
							lowercase__	     =						batch_size
							lowercase__	     =						seq_length
							lowercase__	     =						is_training
							lowercase__	     =						use_labels
							lowercase__	     =						vocab_size
							lowercase__	     =						hidden_size
							lowercase__	     =						num_hidden_layers
							lowercase__	     =						num_attention_heads
							lowercase__	     =						intermediate_size
							lowercase__	     =						hidden_act
							lowercase__	     =						hidden_dropout_prob
							lowercase__	     =						attention_probs_dropout_prob
							lowercase__	     =						max_position_embeddings
							lowercase__	     =						eos_token_id
							lowercase__	     =						pad_token_id
							lowercase__	     =						bos_token_id
							lowercase__	     =						initializer_range

					def     lowerCamelCase__	(self       :		Tuple						)		->  Dict:




							"""simple docstring"""


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

							lowercase__	     =						shift_tokens_right(_UpperCAmelCase ,   1 ,   2						)

							lowercase__	     =						BlenderbotConfig(
							    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=_UpperCAmelCase ,   )
							lowercase__	     =						prepare_blenderbot_inputs_dict(_UpperCAmelCase ,   _UpperCAmelCase ,   _UpperCAmelCase						)
							return config, inputs_dict

					def     lowerCamelCase__	(self       :		str						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__     ,      lowercase__	     =						self.prepare_config_and_inputs()
							return config, inputs_dict

					def     lowerCamelCase__	(self       :		Dict ,   _UpperCAmelCase       :		List[str] ,   _UpperCAmelCase       :		Tuple ,   _UpperCAmelCase       :		Union[str, Any]						)		->  str:




							"""simple docstring"""


							lowercase__	     =						20
							lowercase__	     =						model_class_name(_UpperCAmelCase						)

							lowercase__	     =						model.encode(inputs_dict["""input_ids"""]						)

							lowercase__     ,      lowercase__	     =						(
							    inputs_dict["""decoder_input_ids"""],
							    inputs_dict["""decoder_attention_mask"""],
							)

							lowercase__	     =						model.init_cache(decoder_input_ids.shape[0] ,   _UpperCAmelCase ,   _UpperCAmelCase						)
							lowercase__	     =						jnp.ones((decoder_input_ids.shape[0], max_decoder_length) ,   dtype="""i4"""						)

							lowercase__	     =						jnp.broadcast_to(
							    jnp.arange(decoder_input_ids.shape[-1] - 1						)[None, :] ,   (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1) ,   )
							lowercase__	     =						model.decode(
							    decoder_input_ids[:, :-1] ,   _UpperCAmelCase ,   decoder_attention_mask=_UpperCAmelCase ,   past_key_values=_UpperCAmelCase ,   decoder_position_ids=_UpperCAmelCase ,   )

							lowercase__	     =						jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]] ,   dtype="""i4"""						)
							lowercase__	     =						model.decode(
							    decoder_input_ids[:, -1:] ,   _UpperCAmelCase ,   decoder_attention_mask=_UpperCAmelCase ,   past_key_values=outputs_cache.past_key_values ,   decoder_position_ids=_UpperCAmelCase ,   )

							lowercase__	     =						model.decode(_UpperCAmelCase ,   _UpperCAmelCase						)

							lowercase__	     =						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       :		Union[str, Any] ,   _UpperCAmelCase       :		Dict ,   _UpperCAmelCase       :		Union[str, Any] ,   _UpperCAmelCase       :		List[str]						)		->  Union[str, Any]:




							"""simple docstring"""


							lowercase__	     =						20
							lowercase__	     =						model_class_name(_UpperCAmelCase						)

							lowercase__	     =						model.encode(inputs_dict["""input_ids"""]						)

							lowercase__     ,      lowercase__	     =						(
							    inputs_dict["""decoder_input_ids"""],
							    inputs_dict["""decoder_attention_mask"""],
							)

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

							lowercase__	     =						model.init_cache(decoder_input_ids.shape[0] ,   _UpperCAmelCase ,   _UpperCAmelCase						)
							lowercase__	     =						jnp.broadcast_to(
							    jnp.arange(decoder_input_ids.shape[-1] - 1						)[None, :] ,   (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1) ,   )

							lowercase__	     =						model.decode(
							    decoder_input_ids[:, :-1] ,   _UpperCAmelCase ,   decoder_attention_mask=_UpperCAmelCase ,   past_key_values=_UpperCAmelCase ,   decoder_position_ids=_UpperCAmelCase ,   )
							lowercase__	     =						jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]] ,   dtype="""i4"""						)
							lowercase__	     =						model.decode(
							    decoder_input_ids[:, -1:] ,   _UpperCAmelCase ,   past_key_values=outputs_cache.past_key_values ,   decoder_attention_mask=_UpperCAmelCase ,   decoder_position_ids=_UpperCAmelCase ,   )

							lowercase__	     =						model.decode(_UpperCAmelCase ,   _UpperCAmelCase ,   decoder_attention_mask=_UpperCAmelCase						)

							lowercase__	     =						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 				A       (			unittest.TestCase				):
					'''simple docstring'''






					A__     =					99

					def     lowerCamelCase__	(self       :		Optional[Any]						)		->  int:




							"""simple docstring"""


							lowercase__	     =						np.array(
							    [
							        [71, 82, 18, 33, 46, 91, 2],
							        [68, 34, 26, 58, 30, 82, 2],
							        [5, 97, 17, 39, 94, 40, 2],
							        [76, 83, 94, 25, 70, 78, 2],
							        [87, 59, 41, 35, 48, 66, 2],
							        [55, 13, 16, 58, 5, 2, 1],  # note padding
							        [64, 27, 31, 51, 12, 75, 2],
							        [52, 64, 86, 17, 83, 39, 2],
							        [48, 61, 9, 24, 71, 82, 2],
							        [26, 1, 60, 48, 22, 13, 2],
							        [21, 5, 62, 28, 14, 76, 2],
							        [45, 98, 37, 86, 59, 48, 2],
							        [70, 70, 50, 9, 28, 0, 2],
							    ] ,   dtype=np.intaa ,   )

							lowercase__	     =						input_ids.shape[0]
							lowercase__	     =						BlenderbotConfig(
							    vocab_size=self.vocab_size ,   d_model=24 ,   encoder_layers=2 ,   decoder_layers=2 ,   encoder_attention_heads=2 ,   decoder_attention_heads=2 ,   encoder_ffn_dim=32 ,   decoder_ffn_dim=32 ,   max_position_embeddings=48 ,   eos_token_id=2 ,   pad_token_id=1 ,   bos_token_id=0 ,   )
							return config, input_ids, batch_size

					def     lowerCamelCase__	(self       :		List[str]						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__     ,      lowercase__     ,      lowercase__	     =						self._get_config_and_data()
							lowercase__	     =						FlaxBlenderbotForConditionalGeneration(_UpperCAmelCase						)
							lowercase__	     =						lm_model(input_ids=_UpperCAmelCase						)
							lowercase__	     =						(batch_size, input_ids.shape[1], config.vocab_size)
							self.assertEqual(outputs["""logits"""].shape ,   _UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		int						)		->  str:




							"""simple docstring"""


							lowercase__	     =						BlenderbotConfig(
							    vocab_size=self.vocab_size ,   d_model=14 ,   encoder_layers=2 ,   decoder_layers=2 ,   encoder_attention_heads=2 ,   decoder_attention_heads=2 ,   encoder_ffn_dim=8 ,   decoder_ffn_dim=8 ,   max_position_embeddings=48 ,   )
							lowercase__	     =						FlaxBlenderbotForConditionalGeneration(_UpperCAmelCase						)
							lowercase__	     =						np.array([[71, 82, 18, 33, 46, 91, 2], [68, 34, 26, 58, 30, 2, 1]] ,   dtype=np.intaa						)
							lowercase__	     =						np.array([[82, 71, 82, 18, 2], [58, 68, 2, 1, 1]] ,   dtype=np.intaa						)
							lowercase__	     =						lm_model(input_ids=_UpperCAmelCase ,   decoder_input_ids=_UpperCAmelCase						)
							lowercase__	     =						(*summary.shape, config.vocab_size)
							self.assertEqual(outputs["""logits"""].shape ,   _UpperCAmelCase						)


					def     lowerCamelCase__	(self       :		int						)		->  int:




							"""simple docstring"""


							lowercase__	     =						np.array([[71, 82, 18, 33, 2, 1, 1], [68, 34, 26, 58, 30, 82, 2]] ,   dtype=np.intaa						)
							lowercase__	     =						shift_tokens_right(_UpperCAmelCase ,   1 ,   2						)
							lowercase__	     =						np.equal(_UpperCAmelCase ,   1						).astype(np.floataa						).sum()
							lowercase__	     =						np.equal(_UpperCAmelCase ,   1						).astype(np.floataa						).sum()
							self.assertEqual(shifted.shape ,   input_ids.shape						)
							self.assertEqual(_UpperCAmelCase ,   n_pad_before - 1						)
							self.assertTrue(np.equal(shifted[:, 0] ,   2						).all()						)






@require_flax
class 				A       (			UpperCAmelCase__					,    unittest.TestCase					,    UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					True
					A__     =					(
					    (
					        FlaxBlenderbotModel,
					        FlaxBlenderbotForConditionalGeneration,
					    )
					    if is_flax_available()
					    else ()
					)
					A__     =					(FlaxBlenderbotForConditionalGeneration,) if is_flax_available() else ()

					def     lowerCamelCase__	(self       :		Dict						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						FlaxBlenderbotModelTester(self						)

					def     lowerCamelCase__	(self       :		List[str]						)		->  Union[str, Any]:




							"""simple docstring"""


							lowercase__     ,      lowercase__	     =						self.model_tester.prepare_config_and_inputs()
							for model_class in self.all_model_classes:
									self.model_tester.check_use_cache_forward(_UpperCAmelCase ,   _UpperCAmelCase ,   _UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Any						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__     ,      lowercase__	     =						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(_UpperCAmelCase ,   _UpperCAmelCase ,   _UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Dict						)		->  Union[str, Any]:




							"""simple docstring"""


							lowercase__     ,      lowercase__	     =						self.model_tester.prepare_config_and_inputs_for_common()

							for model_class in self.all_model_classes:
									with self.subTest(model_class.__name__						):
											lowercase__	     =						self._prepare_for_class(_UpperCAmelCase ,   _UpperCAmelCase						)
											lowercase__	     =						model_class(_UpperCAmelCase						)

											@jax.jit
											def encode_jitted(_UpperCAmelCase       :		str ,   _UpperCAmelCase       :		Optional[Any]=None ,   **_UpperCAmelCase       :		Any						):
													return model.encode(input_ids=_UpperCAmelCase ,   attention_mask=_UpperCAmelCase						)

											with self.subTest("""JIT Enabled"""						):
													lowercase__	     =						encode_jitted(**_UpperCAmelCase						).to_tuple()

											with self.subTest("""JIT Disabled"""						):
													with jax.disable_jit():
															lowercase__	     =						encode_jitted(**_UpperCAmelCase						).to_tuple()

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

					def     lowerCamelCase__	(self       :		List[str]						)		->  Any:




							"""simple docstring"""


							lowercase__     ,      lowercase__	     =						self.model_tester.prepare_config_and_inputs_for_common()

							for model_class in self.all_model_classes:
									with self.subTest(model_class.__name__						):
											lowercase__	     =						model_class(_UpperCAmelCase						)
											lowercase__	     =						model.encode(inputs_dict["""input_ids"""] ,   inputs_dict["""attention_mask"""]						)

											lowercase__	     =						{
											    """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(_UpperCAmelCase       :		int ,   _UpperCAmelCase       :		str ,   _UpperCAmelCase       :		Union[str, Any]						):
													return model.decode(
													    decoder_input_ids=_UpperCAmelCase ,   decoder_attention_mask=_UpperCAmelCase ,   encoder_outputs=_UpperCAmelCase ,   )

											with self.subTest("""JIT Enabled"""						):
													lowercase__	     =						decode_jitted(**_UpperCAmelCase						).to_tuple()

											with self.subTest("""JIT Disabled"""						):
													with jax.disable_jit():
															lowercase__	     =						decode_jitted(**_UpperCAmelCase						).to_tuple()

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

					@slow
					def     lowerCamelCase__	(self       :		Optional[Any]						)		->  Tuple:




							"""simple docstring"""


							for model_class_name in self.all_model_classes:
									lowercase__	     =						model_class_name.from_pretrained("""facebook/blenderbot-400M-distill"""						)
									# FlaxBlenderbotForSequenceClassification expects eos token in input_ids
									lowercase__	     =						np.ones((1, 1)						) * model.config.eos_token_id
									lowercase__	     =						model(_UpperCAmelCase						)
									self.assertIsNotNone(_UpperCAmelCase						)


					@unittest.skipUnless(jax_device != """cpu""" ,   """3B test too slow on CPU."""						)
					@slow
					def     lowerCamelCase__	(self       :		Optional[Any]						)		->  List[Any]:




							"""simple docstring"""


							lowercase__	     =						{"""num_beams""": 1, """early_stopping""": True, """min_length""": 15, """max_length""": 25}
							lowercase__	     =						{"""skip_special_tokens""": True, """clean_up_tokenization_spaces""": True}

							lowercase__	     =						FlaxBlenderbotForConditionalGeneration.from_pretrained("""facebook/blenderbot-3B""" ,   from_pt=_UpperCAmelCase						)
							lowercase__	     =						BlenderbotTokenizer.from_pretrained("""facebook/blenderbot-3B"""						)

							lowercase__	     =						["""Sam"""]
							lowercase__	     =						tokenizer(_UpperCAmelCase ,   return_tensors="""jax"""						)

							lowercase__	     =						model.generate(**_UpperCAmelCase ,   **_UpperCAmelCase						)
							lowercase__	     =						"""Sam is a great name. It means \"sun\" in Gaelic."""

							lowercase__	     =						tokenizer.batch_decode(_UpperCAmelCase ,   **_UpperCAmelCase						)
							assert generated_txt[0].strip() == tgt_text







# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser







def      lowerCamelCase_						(			)	->			Union[str, Any]:





				"""simple docstring"""


				__lowerCamelCase									=       ArgumentParser('Accelerate CLI tool'					,	usage='accelerate <command> [<args>]'					,	allow_abbrev=UpperCamelCase__ )
				__lowerCamelCase									=       parser.add_subparsers(help='accelerate command helpers' )

				# Register commands
				get_config_parser(subparsers=UpperCamelCase__ )
				env_command_parser(subparsers=UpperCamelCase__ )
				launch_command_parser(subparsers=UpperCamelCase__ )
				tpu_command_parser(subparsers=UpperCamelCase__ )
				test_command_parser(subparsers=UpperCamelCase__ )

				# Let's go
				__lowerCamelCase									=       parser.parse_args()

				if not hasattr(UpperCamelCase__					,	'func' ):
								parser.print_help()
								exit(1 )

				# Run
				args.func(UpperCamelCase__ )


if __name__ == "__main__":
					main()


