



"""simple docstring"""






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
		_lowercase : List[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      snake_case__   (		__lowerCamelCase				:    int							,		__lowerCamelCase				:    str							,		__lowerCamelCase				:    Optional[Any]=None							,		__lowerCamelCase				:    str=None							,		__lowerCamelCase				:    Tuple=None							,		__lowerCamelCase				:    List[Any]=None							,		__lowerCamelCase				:    Tuple=None							,		__lowerCamelCase				:    str=None							,		):
			"""simple docstring"""
			if attention_mask is None:
						lowerCamelCase__		:		Any			=np.where(input_ids != config.pad_token_id							,		1							,		0	)
			if decoder_attention_mask is None:
						lowerCamelCase__		:		str			=np.where(decoder_input_ids != config.pad_token_id							,		1							,		0	)
			if head_mask is None:
						lowerCamelCase__		:		Dict			=np.ones((config.encoder_layers, config.encoder_attention_heads)	)
			if decoder_head_mask is None:
						lowerCamelCase__		:		str			=np.ones((config.decoder_layers, config.decoder_attention_heads)	)
			if cross_attn_head_mask is None:
						lowerCamelCase__		:		Dict			=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	:


					'''simple docstring'''





					def __init__(       self							:  str,  lowerCamelCase							:  Tuple,  lowerCamelCase							:  List[str]=13,  lowerCamelCase							:  Dict=7,  lowerCamelCase							:  Union[str, Any]=True,  lowerCamelCase							:  Union[str, Any]=False,  lowerCamelCase							:  int=99,  lowerCamelCase							:  Union[str, Any]=16,  lowerCamelCase							:  List[str]=2,  lowerCamelCase							:  int=4,  lowerCamelCase							:  Tuple=4,  lowerCamelCase							:  Optional[Any]="gelu",  lowerCamelCase							:  List[str]=0.1,  lowerCamelCase							:  str=0.1,  lowerCamelCase							:  Optional[int]=32,  lowerCamelCase							:  List[str]=2,  lowerCamelCase							:  Tuple=1,  lowerCamelCase							:  Optional[int]=0,  lowerCamelCase							:  int=0.02,  )->					Optional[Any]:
								lowerCamelCase__		:		List[str]			=parent
								lowerCamelCase__		:		Dict			=batch_size
								lowerCamelCase__		:		Optional[int]			=seq_length
								lowerCamelCase__		:		Any			=is_training
								lowerCamelCase__		:		Optional[int]			=use_labels
								lowerCamelCase__		:		List[str]			=vocab_size
								lowerCamelCase__		:		List[Any]			=hidden_size
								lowerCamelCase__		:		List[Any]			=num_hidden_layers
								lowerCamelCase__		:		Tuple			=num_attention_heads
								lowerCamelCase__		:		List[Any]			=intermediate_size
								lowerCamelCase__		:		Union[str, Any]			=hidden_act
								lowerCamelCase__		:		Optional[Any]			=hidden_dropout_prob
								lowerCamelCase__		:		Tuple			=attention_probs_dropout_prob
								lowerCamelCase__		:		Optional[Any]			=max_position_embeddings
								lowerCamelCase__		:		List[Any]			=eos_token_id
								lowerCamelCase__		:		Tuple			=pad_token_id
								lowerCamelCase__		:		Union[str, Any]			=bos_token_id
								lowerCamelCase__		:		List[Any]			=initializer_range



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

								lowerCamelCase__		:		Dict			=shift_tokens_right(lowerCamelCase,  1,  2     )

								lowerCamelCase__		:		Optional[Any]			=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=lowerCamelCase,  )
								lowerCamelCase__		:		List[str]			=prepare_blenderbot_inputs_dict(lowerCamelCase,  lowerCamelCase,  lowerCamelCase     )
								return config, inputs_dict



					def 		snake_case       (       self							:  str     )->					Optional[Any]:
								lowerCamelCase__	,   lowerCamelCase__		:		Any			=self.prepare_config_and_inputs()
								return config, inputs_dict



					def 		snake_case       (       self							:  int,  lowerCamelCase							:  Tuple,  lowerCamelCase							:  Dict,  lowerCamelCase							:  Tuple     )->					Optional[Any]:
								lowerCamelCase__		:		Union[str, Any]			=20
								lowerCamelCase__		:		Optional[int]			=model_class_name(lowerCamelCase     )

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

								lowerCamelCase__	,   lowerCamelCase__		:		Optional[int]			=(
								    inputs_dict['''decoder_input_ids'''],
								    inputs_dict['''decoder_attention_mask'''],
								)

								lowerCamelCase__		:		Any			=model.init_cache(decoder_input_ids.shape[0],  lowerCamelCase,  lowerCamelCase     )
								lowerCamelCase__		:		Dict			=jnp.ones((decoder_input_ids.shape[0], max_decoder_length),  dtype='''i4'''     )

								lowerCamelCase__		:		List[Any]			=jnp.broadcast_to(
								    jnp.arange(decoder_input_ids.shape[-1] - 1     )[None, :],  (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1),  )
								lowerCamelCase__		:		int			=model.decode(
								    decoder_input_ids[:, :-1],  lowerCamelCase,  decoder_attention_mask=lowerCamelCase,  past_key_values=lowerCamelCase,  decoder_position_ids=lowerCamelCase,  )

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

								lowerCamelCase__		:		int			=model.decode(lowerCamelCase,  lowerCamelCase     )

								lowerCamelCase__		:		Dict			=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 		snake_case       (       self							:  str,  lowerCamelCase							:  str,  lowerCamelCase							:  str,  lowerCamelCase							:  str     )->					List[str]:
								lowerCamelCase__		:		List[Any]			=20
								lowerCamelCase__		:		List[Any]			=model_class_name(lowerCamelCase     )

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

								lowerCamelCase__	,   lowerCamelCase__		:		str			=(
								    inputs_dict['''decoder_input_ids'''],
								    inputs_dict['''decoder_attention_mask'''],
								)

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

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

								lowerCamelCase__		:		Optional[Any]			=model.decode(lowerCamelCase,  lowerCamelCase,  decoder_attention_mask=lowerCamelCase     )

								lowerCamelCase__		:		List[Any]			=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	(      unittest.TestCase   ):


					'''simple docstring'''





					_a   			=							9_9



					def 		snake_case       (       self							:  Optional[int]     )->					Optional[Any]:
								lowerCamelCase__		:		Union[str, Any]			=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,  )

								lowerCamelCase__		:		Any			=input_ids.shape[0]
								lowerCamelCase__		:		Any			=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 		snake_case       (       self							:  Any     )->					Union[str, Any]:
								lowerCamelCase__	,   lowerCamelCase__	,   lowerCamelCase__		:		List[Any]			=self._get_config_and_data()
								lowerCamelCase__		:		int			=FlaxBlenderbotForConditionalGeneration(lowerCamelCase     )
								lowerCamelCase__		:		str			=lm_model(input_ids=lowerCamelCase     )
								lowerCamelCase__		:		List[Any]			=(batch_size, input_ids.shape[1], config.vocab_size)
								self.assertEqual(outputs['''logits'''].shape,  lowerCamelCase     )



					def 		snake_case       (       self							:  Tuple     )->					Optional[Any]:
								lowerCamelCase__		:		Union[str, Any]			=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,  )
								lowerCamelCase__		:		Union[str, Any]			=FlaxBlenderbotForConditionalGeneration(lowerCamelCase     )
								lowerCamelCase__		:		List[Any]			=np.array([[71, 82, 18, 33, 46, 91, 2], [68, 34, 26, 58, 30, 2, 1]],  dtype=np.intaa     )
								lowerCamelCase__		:		Optional[Any]			=np.array([[82, 71, 82, 18, 2], [58, 68, 2, 1, 1]],  dtype=np.intaa     )
								lowerCamelCase__		:		Optional[int]			=lm_model(input_ids=lowerCamelCase,  decoder_input_ids=lowerCamelCase     )
								lowerCamelCase__		:		List[str]			=(*summary.shape, config.vocab_size)
								self.assertEqual(outputs['''logits'''].shape,  lowerCamelCase     )




					def 		snake_case       (       self							:  Union[str, Any]     )->					Union[str, Any]:
								lowerCamelCase__		:		Optional[int]			=np.array([[71, 82, 18, 33, 2, 1, 1], [68, 34, 26, 58, 30, 82, 2]],  dtype=np.intaa     )
								lowerCamelCase__		:		Optional[Any]			=shift_tokens_right(lowerCamelCase,  1,  2     )
								lowerCamelCase__		:		str			=np.equal(lowerCamelCase,  1     ).astype(np.floataa     ).sum()
								lowerCamelCase__		:		List[str]			=np.equal(lowerCamelCase,  1     ).astype(np.floataa     ).sum()
								self.assertEqual(shifted.shape,  input_ids.shape     )
								self.assertEqual(lowerCamelCase,  n_pad_before - 1     )
								self.assertTrue(np.equal(shifted[:, 0],  2     ).all()     )





@require_flax
class        __SCREAMING_SNAKE_CASE	(      lowerCAmelCase_		,   unittest.TestCase		,   lowerCAmelCase_   ):


					'''simple docstring'''





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



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



					def 		snake_case       (       self							:  Optional[int]     )->					int:
								lowerCamelCase__	,   lowerCamelCase__		:		Optional[int]			=self.model_tester.prepare_config_and_inputs()
								for model_class in self.all_model_classes:
											self.model_tester.check_use_cache_forward(lowerCamelCase,  lowerCamelCase,  lowerCamelCase     )



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



					def 		snake_case       (       self							:  List[Any]     )->					Tuple:
								lowerCamelCase__	,   lowerCamelCase__		:		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__		:		List[Any]			=self._prepare_for_class(lowerCamelCase,  lowerCamelCase     )
														lowerCamelCase__		:		int			=model_class(lowerCamelCase     )

														@jax.jit
														def encode_jitted(lowerCamelCase							:  int,  lowerCamelCase							:  Union[str, Any]=None,  **lowerCamelCase							:  List[str]     ):
																	return model.encode(input_ids=lowerCamelCase,  attention_mask=lowerCamelCase     )

														with self.subTest('''JIT Enabled'''     ):
																	lowerCamelCase__		:		Any			=encode_jitted(**lowerCamelCase     ).to_tuple()

														with self.subTest('''JIT Disabled'''     ):
																	with jax.disable_jit():
																				lowerCamelCase__		:		Dict			=encode_jitted(**lowerCamelCase     ).to_tuple()

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



					def 		snake_case       (       self							:  List[str]     )->					Dict:
								lowerCamelCase__	,   lowerCamelCase__		:		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__		:		Optional[Any]			=model_class(lowerCamelCase     )
														lowerCamelCase__		:		List[Any]			=model.encode(inputs_dict['''input_ids'''],  inputs_dict['''attention_mask''']     )

														lowerCamelCase__		:		Optional[int]			={
														    '''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(lowerCamelCase							:  Union[str, Any],  lowerCamelCase							:  Any,  lowerCamelCase							:  Tuple     ):
																	return model.decode(
																	    decoder_input_ids=lowerCamelCase,  decoder_attention_mask=lowerCamelCase,  encoder_outputs=lowerCamelCase,  )

														with self.subTest('''JIT Enabled'''     ):
																	lowerCamelCase__		:		Union[str, Any]			=decode_jitted(**lowerCamelCase     ).to_tuple()

														with self.subTest('''JIT Disabled'''     ):
																	with jax.disable_jit():
																				lowerCamelCase__		:		Optional[Any]			=decode_jitted(**lowerCamelCase     ).to_tuple()

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



					@slow
					def 		snake_case       (       self							:  Tuple     )->					Tuple:
								for model_class_name in self.all_model_classes:
											lowerCamelCase__		:		int			=model_class_name.from_pretrained('''facebook/blenderbot-400M-distill'''     )
											# FlaxBlenderbotForSequenceClassification expects eos token in input_ids
											lowerCamelCase__		:		Union[str, Any]			=np.ones((1, 1)     ) * model.config.eos_token_id
											lowerCamelCase__		:		Optional[Any]			=model(lowerCamelCase     )
											self.assertIsNotNone(lowerCamelCase     )




					@unittest.skipUnless(jax_device != '''cpu''',  '''3B test too slow on CPU.'''     )
					@slow
					def 		snake_case       (       self							:  Optional[int]     )->					Tuple:
								lowerCamelCase__		:		List[Any]			={'''num_beams''': 1, '''early_stopping''': True, '''min_length''': 15, '''max_length''': 25}
								lowerCamelCase__		:		Optional[int]			={'''skip_special_tokens''': True, '''clean_up_tokenization_spaces''': True}

								lowerCamelCase__		:		Tuple			=FlaxBlenderbotForConditionalGeneration.from_pretrained('''facebook/blenderbot-3B''',  from_pt=lowerCamelCase     )
								lowerCamelCase__		:		int			=BlenderbotTokenizer.from_pretrained('''facebook/blenderbot-3B'''     )

								lowerCamelCase__		:		str			=['''Sam''']
								lowerCamelCase__		:		Union[str, Any]			=tokenizer(lowerCamelCase,  return_tensors='''jax'''     )

								lowerCamelCase__		:		Tuple			=model.generate(**lowerCamelCase,  **lowerCamelCase     )
								lowerCamelCase__		:		Tuple			='''Sam is a great name. It means "sun" in Gaelic.'''

								lowerCamelCase__		:		Union[str, Any]			=tokenizer.batch_decode(lowerCamelCase,  **lowerCamelCase     )
								assert generated_txt[0].strip() == tgt_text









"""simple docstring"""






import argparse
import os
import re


_lowercase : str      						=						"src/diffusers"

# Pattern that looks at the indentation in a line.
_lowercase : List[Any]      						=						re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase : int      						=						re.compile(r"^\s*\"([^\"]+)\":")
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
_lowercase : Optional[int]      						=						re.compile(r"^\s*_import_structure\[\"([^\"]+)\"\]")
# Pattern that matches `"key",` and puts `key` in group 0.
_lowercase : List[Any]      						=						re.compile(r"^\s*\"([^\"]+)\",\s*$")
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
_lowercase : str      						=						re.compile(r"\[([^\]]+)\]")






def      snake_case__   (		__lowerCamelCase				:    Optional[int]	):
			"""simple docstring"""
			lowerCamelCase__		:		List[str]			=_re_indent.search(__lowerCamelCase	)
			return "" if search is None else search.groups()[0]






def      snake_case__   (		__lowerCamelCase				:    Any							,		__lowerCamelCase				:    List[Any]=""							,		__lowerCamelCase				:    int=None							,		__lowerCamelCase				:    Optional[int]=None	):
			"""simple docstring"""
			lowerCamelCase__		:		Optional[int]			=0
			lowerCamelCase__		:		Any			=code.split('''\n'''	)
			if start_prompt is not None:
						while not lines[index].startswith(__lowerCamelCase	):
									index += 1
						lowerCamelCase__		:		Dict			=['''\n'''.join(lines[:index]	)]
			else:
						lowerCamelCase__		:		Tuple			=[]

			# We split into blocks until we get to the `end_prompt` (or the end of the block).
			lowerCamelCase__		:		int			=[lines[index]]
			index += 1
			while index < len(__lowerCamelCase	) and (end_prompt is None or not lines[index].startswith(__lowerCamelCase	)):
						if len(lines[index]	) > 0 and get_indent(lines[index]	) == indent_level:
									if len(__lowerCamelCase	) > 0 and get_indent(current_block[-1]	).startswith(indent_level + ''' '''	):
												current_block.append(lines[index]	)
												blocks.append('''\n'''.join(__lowerCamelCase	)	)
												if index < len(__lowerCamelCase	) - 1:
															lowerCamelCase__		:		str			=[lines[index + 1]]
															index += 1
												else:
															lowerCamelCase__		:		str			=[]
									else:
												blocks.append('''\n'''.join(__lowerCamelCase	)	)
												lowerCamelCase__		:		str			=[lines[index]]
						else:
									current_block.append(lines[index]	)
						index += 1

			# Adds current block if it's nonempty.
			if len(__lowerCamelCase	) > 0:
						blocks.append('''\n'''.join(__lowerCamelCase	)	)

			# Add final block after end_prompt if provided.
			if end_prompt is not None and index < len(__lowerCamelCase	):
						blocks.append('''\n'''.join(lines[index:]	)	)

			return blocks






def      snake_case__   (		__lowerCamelCase				:    Any	):
			"""simple docstring"""

			def _inner(__lowerCamelCase				:    Any	):
						return key(__lowerCamelCase	).lower().replace('''_'''							,		''''''	)

			return _inner






def      snake_case__   (		__lowerCamelCase				:    int							,		__lowerCamelCase				:    Any=None	):
			"""simple docstring"""

			# If no key is provided, we use a noop.
			def noop(__lowerCamelCase				:    List[str]	):
						return x

			if key is None:
						lowerCamelCase__		:		Tuple			=noop
			# Constants are all uppercase, they go first.
			lowerCamelCase__		:		Union[str, Any]			=[obj for obj in objects if key(__lowerCamelCase	).isupper()]
			# Classes are not all uppercase but start with a capital, they go second.
			lowerCamelCase__		:		Optional[int]			=[obj for obj in objects if key(__lowerCamelCase	)[0].isupper() and not key(__lowerCamelCase	).isupper()]
			# Functions begin with a lowercase, they go last.
			lowerCamelCase__		:		Optional[Any]			=[obj for obj in objects if not key(__lowerCamelCase	)[0].isupper()]

			lowerCamelCase__		:		int			=ignore_underscore(__lowerCamelCase	)
			return sorted(__lowerCamelCase							,		key=__lowerCamelCase	) + sorted(__lowerCamelCase							,		key=__lowerCamelCase	) + sorted(__lowerCamelCase							,		key=__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    Optional[Any]	):
			"""simple docstring"""

			# This inner function sort imports between [ ].
			def _replace(__lowerCamelCase				:    Optional[Any]	):
						lowerCamelCase__		:		Dict			=match.groups()[0]
						if "," not in imports:
									return f'''[{imports}]'''
						lowerCamelCase__		:		List[Any]			=[part.strip().replace('''"'''							,		''''''	) for part in imports.split(''','''	)]
						# We will have a final empty element if the line finished with a comma.
						if len(keys[-1]	) == 0:
									lowerCamelCase__		:		Optional[int]			=keys[:-1]
						return "[" + ", ".join([f'''"{k}"''' for k in sort_objects(__lowerCamelCase	)]	) + "]"

			lowerCamelCase__		:		List[Any]			=import_statement.split('''\n'''	)
			if len(__lowerCamelCase	) > 3:
						# Here we have to sort internal imports that are on several lines (one per name):
						# key: [
						#     "object1",
						#     "object2",
						#     ...
						# ]

						# We may have to ignore one or two lines on each side.
						lowerCamelCase__		:		Tuple			=2 if lines[1].strip() == '''[''' else 1
						lowerCamelCase__		:		Any			=[(i, _re_strip_line.search(__lowerCamelCase	).groups()[0]) for i, line in enumerate(lines[idx:-idx]	)]
						lowerCamelCase__		:		List[Any]			=sort_objects(__lowerCamelCase							,		key=lambda __lowerCamelCase	: x[1]	)
						lowerCamelCase__		:		Union[str, Any]			=[lines[x[0] + idx] for x in sorted_indices]
						return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]	)
			elif len(__lowerCamelCase	) == 3:
						# Here we have to sort internal imports that are on one separate line:
						# key: [
						#     "object1", "object2", ...
						# ]
						if _re_bracket_content.search(lines[1]	) is not None:
									lowerCamelCase__		:		List[str]			=_re_bracket_content.sub(_replace							,		lines[1]	)
						else:
									lowerCamelCase__		:		str			=[part.strip().replace('''"'''							,		''''''	) for part in lines[1].split(''','''	)]
									# We will have a final empty element if the line finished with a comma.
									if len(keys[-1]	) == 0:
												lowerCamelCase__		:		Any			=keys[:-1]
									lowerCamelCase__		:		List[Any]			=get_indent(lines[1]	) + ''', '''.join([f'''"{k}"''' for k in sort_objects(__lowerCamelCase	)]	)
						return "\n".join(__lowerCamelCase	)
			else:
						# Finally we have to deal with imports fitting on one line
						lowerCamelCase__		:		Union[str, Any]			=_re_bracket_content.sub(_replace							,		__lowerCamelCase	)
						return import_statement






def      snake_case__   (		__lowerCamelCase				:    Optional[int]							,		__lowerCamelCase				:    List[Any]=True	):
			"""simple docstring"""
			with open(__lowerCamelCase							,		'''r'''	) as f:
						lowerCamelCase__		:		Optional[int]			=f.read()

			if "_import_structure" not in code:
						return

			# Blocks of indent level 0
			lowerCamelCase__		:		int			=split_code_in_indented_blocks(
			    __lowerCamelCase							,		start_prompt='''_import_structure = {'''							,		end_prompt='''if TYPE_CHECKING:'''	)

			# We ignore block 0 (everything until start_prompt) and the last block (everything after end_prompt).
			for block_idx in range(1							,		len(__lowerCamelCase	) - 1	):
						# Check if the block contains some `_import_structure`s thingy to sort.
						lowerCamelCase__		:		Optional[Any]			=main_blocks[block_idx]
						lowerCamelCase__		:		List[str]			=block.split('''\n'''	)

						# Get to the start of the imports.
						lowerCamelCase__		:		Any			=0
						while line_idx < len(__lowerCamelCase	) and "_import_structure" not in block_lines[line_idx]:
									# Skip dummy import blocks
									if "import dummy" in block_lines[line_idx]:
												lowerCamelCase__		:		Tuple			=len(__lowerCamelCase	)
									else:
												line_idx += 1
						if line_idx >= len(__lowerCamelCase	):
									continue

						# Ignore beginning and last line: they don't contain anything.
						lowerCamelCase__		:		Any			='''\n'''.join(block_lines[line_idx:-1]	)
						lowerCamelCase__		:		Dict			=get_indent(block_lines[1]	)
						# Slit the internal block into blocks of indent level 1.
						lowerCamelCase__		:		List[Any]			=split_code_in_indented_blocks(__lowerCamelCase							,		indent_level=__lowerCamelCase	)
						# We have two categories of import key: list or _import_structure[key].append/extend
						lowerCamelCase__		:		List[Any]			=_re_direct_key if '''_import_structure''' in block_lines[0] else _re_indirect_key
						# Grab the keys, but there is a trap: some lines are empty or just comments.
						lowerCamelCase__		:		Union[str, Any]			=[(pattern.search(__lowerCamelCase	).groups()[0] if pattern.search(__lowerCamelCase	) is not None else None) for b in internal_blocks]
						# We only sort the lines with a key.
						lowerCamelCase__		:		Optional[Any]			=[(i, key) for i, key in enumerate(__lowerCamelCase	) if key is not None]
						lowerCamelCase__		:		List[Any]			=[x[0] for x in sorted(__lowerCamelCase							,		key=lambda __lowerCamelCase	: x[1]	)]

						# We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
						lowerCamelCase__		:		Optional[Any]			=0
						lowerCamelCase__		:		Tuple			=[]
						for i in range(len(__lowerCamelCase	)	):
									if keys[i] is None:
												reordered_blocks.append(internal_blocks[i]	)
									else:
												lowerCamelCase__		:		List[Any]			=sort_objects_in_import(internal_blocks[sorted_indices[count]]	)
												reordered_blocks.append(__lowerCamelCase	)
												count += 1

        # And we put our main block back together with its first and last line.
						lowerCamelCase__		:		str			='''\n'''.join(block_lines[:line_idx] + reordered_blocks + [block_lines[-1]]	)

			if code != "\n".join(__lowerCamelCase	):
						if check_only:
									return True
						else:
									print(f'''Overwriting {file}.'''	)
									with open(__lowerCamelCase							,		'''w'''	) as f:
												f.write('''\n'''.join(__lowerCamelCase	)	)






def      snake_case__   (		__lowerCamelCase				:    Optional[Any]=True	):
			"""simple docstring"""
			lowerCamelCase__		:		Any			=[]
			for root, _, files in os.walk(__lowerCamelCase	):
						if "__init__.py" in files:
									lowerCamelCase__		:		Tuple			=sort_imports(os.path.join(__lowerCamelCase							,		'''__init__.py'''	)							,		check_only=__lowerCamelCase	)
									if result:
												lowerCamelCase__		:		List[str]			=[os.path.join(__lowerCamelCase							,		'''__init__.py'''	)]
			if len(__lowerCamelCase	) > 0:
						raise ValueError(f'''Would overwrite {len(__lowerCamelCase	)} files, run `make style`.'''	)


if __name__ == "__main__":
		_lowercase : Any      						=						argparse.ArgumentParser()
		parser.add_argument("--check_only", action="store_true", help="Whether to only check or fix style.")
		_lowercase : List[Any]      						=						parser.parse_args()

		sort_imports_in_all_inits(check_only=args.check_only)




