


import unittest

import numpy as np

from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask


if is_flax_available():
			from transformers.models.roberta.modeling_flax_roberta import (
			    FlaxRobertaForCausalLM,
			    FlaxRobertaForMaskedLM,
			    FlaxRobertaForMultipleChoice,
			    FlaxRobertaForQuestionAnswering,
			    FlaxRobertaForSequenceClassification,
			    FlaxRobertaForTokenClassification,
			    FlaxRobertaModel,
			)

class        a	(unittest.TestCase   ):




							"""simple docstring"""


							def __init__(							self :						Union[str, Any]					,			lowerCamelCase :						List[Any]					,			lowerCamelCase :						Tuple=13					,			lowerCamelCase :						Any=7					,			lowerCamelCase :						Optional[int]=True					,			lowerCamelCase :						Any=True					,			lowerCamelCase :						Any=True					,			lowerCamelCase :						Tuple=True					,			lowerCamelCase :						Dict=99					,			lowerCamelCase :						Tuple=32					,			lowerCamelCase :						Tuple=5					,			lowerCamelCase :						List[Any]=4					,			lowerCamelCase :						Optional[int]=37					,			lowerCamelCase :						List[str]="gelu"					,			lowerCamelCase :						str=0.1					,			lowerCamelCase :						Union[str, Any]=0.1					,			lowerCamelCase :						List[str]=512					,			lowerCamelCase :						Tuple=16					,			lowerCamelCase :						str=2					,			lowerCamelCase :						Tuple=0.02					,			lowerCamelCase :						Tuple=4					,			)			->					Union[str, Any]:
														__snake_case	:    Union[str, Any]											=     parent
														__snake_case	:    List[Any]											=     batch_size
														__snake_case	:    int											=     seq_length
														__snake_case	:    List[Any]											=     is_training
														__snake_case	:    List[Any]											=     use_attention_mask
														__snake_case	:    int											=     use_token_type_ids
														__snake_case	:    str											=     use_labels
														__snake_case	:    Optional[int]											=     vocab_size
														__snake_case	:    Optional[Any]											=     hidden_size
														__snake_case	:    str											=     num_hidden_layers
														__snake_case	:    List[Any]											=     num_attention_heads
														__snake_case	:    Optional[int]											=     intermediate_size
														__snake_case	:    List[Any]											=     hidden_act
														__snake_case	:    Optional[Any]											=     hidden_dropout_prob
														__snake_case	:    str											=     attention_probs_dropout_prob
														__snake_case	:    int											=     max_position_embeddings
														__snake_case	:    List[Any]											=     type_vocab_size
														__snake_case	:    str											=     type_sequence_label_size
														__snake_case	:    List[str]											=     initializer_range
														__snake_case	:    Optional[int]											=     num_choices

							def 					__snake_case      (							self :						Any       )			->					List[str]:
														__snake_case	:    Dict											=     ids_tensor([self.batch_size, self.seq_length]					,			self.vocab_size       )

														__snake_case	:    Optional[Any]											=     None
														if self.use_attention_mask:
																					__snake_case	:    List[Any]											=     random_attention_mask([self.batch_size, self.seq_length]       )

														__snake_case	:    Any											=     None
														if self.use_token_type_ids:
																					__snake_case	:    str											=     ids_tensor([self.batch_size, self.seq_length]					,			self.type_vocab_size       )

														__snake_case	:    List[str]											=     RobertaConfig(
														    vocab_size=self.vocab_size					,			hidden_size=self.hidden_size					,			num_hidden_layers=self.num_hidden_layers					,			num_attention_heads=self.num_attention_heads					,			intermediate_size=self.intermediate_size					,			hidden_act=self.hidden_act					,			hidden_dropout_prob=self.hidden_dropout_prob					,			attention_probs_dropout_prob=self.attention_probs_dropout_prob					,			max_position_embeddings=self.max_position_embeddings					,			type_vocab_size=self.type_vocab_size					,			is_decoder=lowerCamelCase					,			initializer_range=self.initializer_range					,			)

														return config, input_ids, token_type_ids, attention_mask

							def 					__snake_case      (							self :						Any       )			->					Any:
														__snake_case	:    Optional[Any]											=     self.prepare_config_and_inputs()
														__snake_case				,    __snake_case				,    __snake_case				,    __snake_case	:    Tuple											=     config_and_inputs
														__snake_case	:    str											=     {"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask}
														return config, inputs_dict






							def 					__snake_case      (							self :						Union[str, Any]       )			->					Tuple:
														__snake_case	:    int											=     self.prepare_config_and_inputs()
														__snake_case				,    __snake_case				,    __snake_case				,    __snake_case	:    Optional[Any]											=     config_and_inputs

														__snake_case	:    Dict											=     True
														__snake_case	:    str											=     floats_tensor([self.batch_size, self.seq_length, self.hidden_size]       )
														__snake_case	:    Any											=     ids_tensor([self.batch_size, self.seq_length]					,			vocab_size=2       )

														return (
														    config,
														    input_ids,
														    token_type_ids,
														    encoder_hidden_states,
														    encoder_attention_mask,
														)

@require_flax
class        a	(_lowerCAmelCase  ,       unittest.TestCase   ):




							"""simple docstring"""


							__UpperCAmelCase					:							Union[str, Any]  						=						True

							__UpperCAmelCase					:							Any  						=						(
							    (
							        FlaxRobertaModel,
							        FlaxRobertaForCausalLM,
							        FlaxRobertaForMaskedLM,
							        FlaxRobertaForSequenceClassification,
							        FlaxRobertaForTokenClassification,
							        FlaxRobertaForMultipleChoice,
							        FlaxRobertaForQuestionAnswering,
							    )
							    if is_flax_available()
							    else ()
							)

							def 					__snake_case      (							self :						List[Any]       )			->					int:
														__snake_case	:    Union[str, Any]											=     FlaxRobertaModelTester(self       )






							@slow
							def 					__snake_case      (							self :						Optional[Any]       )			->					int:
														for model_class_name in self.all_model_classes:
																					__snake_case	:    str											=     model_class_name.from_pretrained("roberta-base"					,			from_pt=lowerCamelCase       )
																					__snake_case	:    Tuple											=     model(np.ones((1, 1)       )       )
																					self.assertIsNotNone(lowerCamelCase       )





import argparse
import glob
import importlib.util
import os
import re

import black
from doc_builder.style_doc import style_docstrings_in_code


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_snake_case  :	List[Any]			      =       "src/diffusers"
_snake_case  :	str			      =       "."


# This is to make sure the diffusers module imported is the one in the repo.
_snake_case  :	List[str]			      =       importlib.util.spec_from_file_location(
    "diffusers",
    os.path.join(DIFFUSERS_PATH, "__init__.py"),
    submodule_search_locations=[DIFFUSERS_PATH],
)
_snake_case  :	Dict			      =       spec.loader.load_module()







def        lowerCAmelCase_  (      __lowerCamelCase							,			__lowerCamelCase			):
							return line.startswith(__lowerCamelCase			) or len(__lowerCamelCase			) <= 1 or re.search(R"^\s*\)(\s*->.*:|:)\s*$"							,			__lowerCamelCase			) is not None







def        lowerCAmelCase_  (      __lowerCamelCase			):
							__snake_case	:    str											=     object_name.split("."			)
							__snake_case	:    Any											=     0

							# First let's find the module where our object lives.
							__snake_case	:    Optional[int]											=     parts[i]
							while i < len(__lowerCamelCase			) and not os.path.isfile(os.path.join(__lowerCamelCase							,			F'{module}.py'			)			):
														i += 1
														if i < len(__lowerCamelCase			):
																					__snake_case	:    Dict											=     os.path.join(__lowerCamelCase							,			parts[i]			)
							if i >= len(__lowerCamelCase			):
														raise ValueError(F'`object_name` should begin with the name of a module of diffusers but got {object_name}.'			)

							with open(os.path.join(__lowerCamelCase							,			F'{module}.py'			)							,			"r"							,			encoding="utf-8"							,			newline="\n"			) as f:
														__snake_case	:    Optional[Any]											=     f.readlines()

							# Now let's find the class / func in the code!
							__snake_case	:    Any											=     ""
							__snake_case	:    Any											=     0
							for name in parts[i + 1 :]:
														while (
														    line_index < len(__lowerCamelCase			) and re.search(RF'^{indent}(class|def)\s+{name}(\(|\:)'							,			lines[line_index]			) is None
														):
																					line_index += 1
														indent += "    "
														line_index += 1

							if line_index >= len(__lowerCamelCase			):
														raise ValueError(F' {object_name} does not match any function or class in {module}.'			)

							# We found the beginning of the class / func, now let's find the end (when the indent diminishes).
							__snake_case	:    Optional[Any]											=     line_index
							while line_index < len(__lowerCamelCase			) and _should_continue(lines[line_index]							,			__lowerCamelCase			):
														line_index += 1
							# Clean up empty lines at the end (if any).
							while len(lines[line_index - 1]			) <= 1:
														line_index -= 1

							__snake_case	:    Dict											=     lines[start_index:line_index]
							return "".join(__lowerCamelCase			)


_snake_case  :	Any			      =       re.compile(R"^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)")
_snake_case  :	Union[str, Any]			      =       re.compile(R"^\s*(\S+)->(\S+)(\s+.*|$)")
_snake_case  :	Optional[int]			      =       re.compile(R"<FILL\s+[^>]*>")







def        lowerCAmelCase_  (      __lowerCamelCase			):
							__snake_case	:    Dict											=     code.split("\n"			)
							__snake_case	:    List[str]											=     0
							while idx < len(__lowerCamelCase			) and len(lines[idx]			) == 0:
														idx += 1
							if idx < len(__lowerCamelCase			):
														return re.search(R"^(\s*)\S"							,			lines[idx]			).groups()[0]
							return ""







def        lowerCAmelCase_  (      __lowerCamelCase			):
							__snake_case	:    List[str]											=     len(get_indent(__lowerCamelCase			)			) > 0
							if has_indent:
														__snake_case	:    str											=     F'class Bla:\n{code}'
							__snake_case	:    List[Any]											=     black.Mode(target_versions={black.TargetVersion.PYaa}							,			line_length=1_1_9							,			preview=__lowerCamelCase			)
							__snake_case	:    int											=     black.format_str(__lowerCamelCase							,			mode=__lowerCamelCase			)
							__snake_case				,    __snake_case	:    List[str]											=     style_docstrings_in_code(__lowerCamelCase			)
							return result[len("class Bla:\n"			) :] if has_indent else result







def        lowerCAmelCase_  (      __lowerCamelCase							,			__lowerCamelCase=False			):
							with open(__lowerCamelCase							,			"r"							,			encoding="utf-8"							,			newline="\n"			) as f:
														__snake_case	:    List[Any]											=     f.readlines()
							__snake_case	:    int											=     []
							__snake_case	:    Optional[Any]											=     0
							# Not a for loop cause `lines` is going to change (if `overwrite=True`).
							while line_index < len(__lowerCamelCase			):
														__snake_case	:    List[Any]											=     _re_copy_warning.search(lines[line_index]			)
														if search is None:
																					line_index += 1
																					continue

														# There is some copied code here, let's retrieve the original.
														__snake_case				,    __snake_case				,    __snake_case	:    List[str]											=     search.groups()
														__snake_case	:    List[str]											=     find_code_in_diffusers(__lowerCamelCase			)
														__snake_case	:    str											=     get_indent(__lowerCamelCase			)

														__snake_case	:    Optional[Any]											=     line_index + 1 if indent == theoretical_indent else line_index + 2
														__snake_case	:    Tuple											=     theoretical_indent
														__snake_case	:    str											=     start_index

														# Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
														__snake_case	:    str											=     True
														while line_index < len(__lowerCamelCase			) and should_continue:
																					line_index += 1
																					if line_index >= len(__lowerCamelCase			):
																												break
																					__snake_case	:    Union[str, Any]											=     lines[line_index]
																					__snake_case	:    Any											=     _should_continue(__lowerCamelCase							,			__lowerCamelCase			) and re.search(F'^{indent}# End copy'							,			__lowerCamelCase			) is None
														# Clean up empty lines at the end (if any).
														while len(lines[line_index - 1]			) <= 1:
																					line_index -= 1

														__snake_case	:    int											=     lines[start_index:line_index]
														__snake_case	:    int											=     "".join(__lowerCamelCase			)

														# Remove any nested `Copied from` comments to avoid circular copies
														__snake_case	:    Union[str, Any]											=     [line for line in theoretical_code.split("\n"			) if _re_copy_warning.search(__lowerCamelCase			) is None]
														__snake_case	:    Optional[Any]											=     "\n".join(__lowerCamelCase			)

														# Before comparing, use the `replace_pattern` on the original code.
														if len(__lowerCamelCase			) > 0:
																					__snake_case	:    Optional[int]											=     replace_pattern.replace("with"							,			""			).split(","			)
																					__snake_case	:    Tuple											=     [_re_replace_pattern.search(__lowerCamelCase			) for p in patterns]
																					for pattern in patterns:
																												if pattern is None:
																																			continue
																												__snake_case				,    __snake_case				,    __snake_case	:    Optional[Any]											=     pattern.groups()
																												__snake_case	:    Tuple											=     re.sub(__lowerCamelCase							,			__lowerCamelCase							,			__lowerCamelCase			)
																												if option.strip() == "all-casing":
																																			__snake_case	:    List[Any]											=     re.sub(obja.lower()							,			obja.lower()							,			__lowerCamelCase			)
																																			__snake_case	:    Union[str, Any]											=     re.sub(obja.upper()							,			obja.upper()							,			__lowerCamelCase			)

            # Blackify after replacement. To be able to do that, we need the header (class or function definition)
            # from the previous line
																					__snake_case	:    str											=     blackify(lines[start_index - 1] + theoretical_code			)
																					__snake_case	:    Tuple											=     theoretical_code[len(lines[start_index - 1]			) :]

														# Test for a diff and act accordingly.
														if observed_code != theoretical_code:
																					diffs.append([object_name, start_index]			)
																					if overwrite:
																												__snake_case	:    str											=     lines[:start_index] + [theoretical_code] + lines[line_index:]
																												__snake_case	:    List[Any]											=     start_index + 1

							if overwrite and len(__lowerCamelCase			) > 0:
														# Warn the user a file has been modified.
														print(F'Detected changes, rewriting {filename}.'			)
														with open(__lowerCamelCase							,			"w"							,			encoding="utf-8"							,			newline="\n"			) as f:
																					f.writelines(__lowerCamelCase			)
							return diffs







def        lowerCAmelCase_  (      __lowerCamelCase = False			):
							__snake_case	:    Optional[Any]											=     glob.glob(os.path.join(__lowerCamelCase							,			"**/*.py"			)							,			recursive=__lowerCamelCase			)
							__snake_case	:    Dict											=     []
							for filename in all_files:
														__snake_case	:    Union[str, Any]											=     is_copy_consistent(__lowerCamelCase							,			__lowerCamelCase			)
														diffs += [F'- {filename}: copy does not match {d[0]} at line {d[1]}' for d in new_diffs]
							if not overwrite and len(__lowerCamelCase			) > 0:
														__snake_case	:    Optional[Any]											=     "\n".join(__lowerCamelCase			)
														raise Exception(
														    "Found the following copy inconsistencies:\n"
														    + diff
														    + "\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them."			)


if __name__ == "__main__":
			_snake_case  :	Optional[int]			      =       argparse.ArgumentParser()
			parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
			_snake_case  :	Union[str, Any]			      =       parser.parse_args()

			check_copies(args.fix_and_overwrite)

