



"""simple docstring"""


import argparse
import glob
import inspect
import os
import re
import unittest

from get_test_info import get_test_classes

from tests.test_pipeline_mixin import pipeline_test_mapping


snake_case_         = {}
for task, _ in pipeline_test_mapping.items():
				snake_case_         = {"""pt""": None, """tf""": None}


# DO **NOT** add item to this set (unless the reason is approved)
snake_case_         = {
    """tests/models/esm/test_modeling_esmfold.py""",  # The pipeline test mapping is added to `test_modeling_esm.py`
}

def 				_lowerCAmelCase   (     lowercase_		):

						if "ModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
												return "pt"
						elif "TFModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
												return "tf"
						elif "FlaxModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
												return "flax"
						else:
												return None

def 				_lowerCAmelCase   (     lowercase_	,			lowercase_		):
						# Use the cached results
						if PIPELINE_TEST_MAPPING[task].get(lowercase_	,			lowercase_		) is not None:
												return PIPELINE_TEST_MAPPING[task][framework]

						UpperCAmelCase    =				pipeline_test_mapping[task]['test']
						UpperCAmelCase    =				None

						if framework == "pt":
												UpperCAmelCase    =				getattr(lowercase_	,			'model_mapping'	,			lowercase_		)
						elif framework == "tf":
												UpperCAmelCase    =				getattr(lowercase_	,			'tf_model_mapping'	,			lowercase_		)

						if mapping is not None:
												UpperCAmelCase    =				dict(mapping.items()		)

						# cache the results
						UpperCAmelCase    =				mapping
						return mapping

def 				_lowerCAmelCase   (     lowercase_	,			lowercase_		):
						UpperCAmelCase    =				get_framework(lowercase_		)
						if framework is None:
												return None
						UpperCAmelCase    =				get_mapping_for_task(lowercase_	,			lowercase_		)
						if mapping is None:
												return None

						UpperCAmelCase    =				list({model_class.config_class for model_class in test_class.all_model_classes}		)
						if len(lowercase_		) != 1:
												raise ValueError('There should be exactly one configuration class from `test_class.all_model_classes`.'		)

						# This could be a list/tuple of model classes, but it's rare.
						UpperCAmelCase    =				mapping.get(config_classes[0]	,			lowercase_		)
						if isinstance(lowercase_	,			(tuple, list)		):
												UpperCAmelCase    =				sorted(lowercase_	,			key=lambda lowercase_		: x.__name__		)

						return model_class

def 				_lowerCAmelCase   (     lowercase_		):
						UpperCAmelCase    =				[(task, get_model_for_pipeline_test(lowercase_	,			lowercase_		)) for task in pipeline_test_mapping]
						UpperCAmelCase    =				sorted([(task, model) for task, model in mapping if model is not None]	,			key=lambda lowercase_		: x[0]		)

						return dict(lowercase_		)

def 				_lowerCAmelCase   (     lowercase_		):
						UpperCAmelCase    =				get_framework(lowercase_		)
						if framework == "pt":
												UpperCAmelCase    =				'torch'
						UpperCAmelCase    =				'{}'

						UpperCAmelCase    =				get_pipeline_model_mapping(lowercase_		)
						if len(lowercase_		) == 0:
												return ""

						UpperCAmelCase    =				[]
						for task, model_classes in mapping.items():
												if isinstance(lowercase_	,			(tuple, list)		):
																		# A list/tuple of model classes
																		UpperCAmelCase    =				'(' + ', '.join([x.__name__ for x in model_classes]		) + ')'
												else:
																		# A single model class
																		UpperCAmelCase    =				model_classes.__name__
												texts.append(F"""\"{task}\": {value}"""		)
						UpperCAmelCase    =				'{' + ', '.join(lowercase_		) + '}'
						UpperCAmelCase    =				F"""pipeline_model_mapping = {text} if is_{framework}_available() else {default_value}"""

						return text

def 				_lowerCAmelCase   (     lowercase_		):
						UpperCAmelCase    =				{'ModelTesterMixin', 'TFModelTesterMixin', 'FlaxModelTesterMixin'}
						if not issubclass(lowercase_	,			unittest.TestCase		):
												return False
						return len(base_class_names.intersection([x.__name__ for x in test_class.__bases__]		)		) > 0

def 				_lowerCAmelCase   (     lowercase_		):
						UpperCAmelCase    =				[x for x in get_test_classes(lowercase_		) if is_valid_test_class(lowercase_		)]

						UpperCAmelCase    =				None
						for test_class in test_classes:
												# If a test class has defined `pipeline_model_mapping`, let's take it
												if getattr(lowercase_	,			'pipeline_model_mapping'	,			lowercase_		) is not None:
																		UpperCAmelCase    =				test_class
																		break
    # Take the test class with the shortest name (just a heuristic)
						if target_test_class is None and len(lowercase_		) > 0:
												UpperCAmelCase    =				sorted(lowercase_	,			key=lambda lowercase_		: (len(x.__name__		), x.__name__)		)[0]

						return target_test_class

def 				_lowerCAmelCase   (     lowercase_	,			lowercase_	,			lowercase_		):
						UpperCAmelCase    =				start_idx
						for idx, line in enumerate(lines[start_idx:]		):
												UpperCAmelCase    =				len(lowercase_		) - len(line.lstrip()		)
												if idx == 0 or indent > indent_level or (indent == indent_level and line.strip() == ")"):
																		UpperCAmelCase    =				start_idx + idx
												elif idx > 0 and indent <= indent_level:
																		# Outside the definition block of `pipeline_model_mapping`
																		break

						return end_idx

def 				_lowerCAmelCase   (     lowercase_	,			lowercase_=False		):
						if getattr(lowercase_	,			'pipeline_model_mapping'	,			lowercase_		) is not None:
												if not overwrite:
																		return "", -1

						UpperCAmelCase    =				get_pipeline_model_mapping_string(lowercase_		)
						if len(lowercase_		) == 0:
												return "", -1
						UpperCAmelCase    =				line_to_add + '\n'

						# The code defined the class `test_class`
						UpperCAmelCase   ,					UpperCAmelCase    =				inspect.getsourcelines(lowercase_		)
						# `inspect` gives the code for an object, including decorator(s) if any.
						# We (only) need the exact line of the class definition.
						for idx, line in enumerate(lowercase_		):
												if line.lstrip().startswith('class '		):
																		UpperCAmelCase    =				class_lines[idx:]
																		class_start_line_no += idx
																		break
						UpperCAmelCase    =				class_start_line_no + len(lowercase_		) - 1

						# The index in `class_lines` that starts the definition of `all_model_classes`, `all_generative_model_classes` or
						# `pipeline_model_mapping`. This assumes they are defined in such order, and we take the start index of the last
						# block that appears in a `test_class`.
						UpperCAmelCase    =				None
						# The indent level of the line at `class_lines[start_idx]` (if defined)
						UpperCAmelCase    =				0
						# To record if `pipeline_model_mapping` is found in `test_class`.
						UpperCAmelCase    =				None
						for idx, line in enumerate(lowercase_		):
												if line.strip().startswith('all_model_classes = '		):
																		UpperCAmelCase    =				len(lowercase_		) - len(line.lstrip()		)
																		UpperCAmelCase    =				idx
												elif line.strip().startswith('all_generative_model_classes = '		):
																		UpperCAmelCase    =				len(lowercase_		) - len(line.lstrip()		)
																		UpperCAmelCase    =				idx
												elif line.strip().startswith('pipeline_model_mapping = '		):
																		UpperCAmelCase    =				len(lowercase_		) - len(line.lstrip()		)
																		UpperCAmelCase    =				idx
																		UpperCAmelCase    =				line
																		break

						if start_idx is None:
												return "", -1
						# Find the ending index (inclusive) of the above found block.
						UpperCAmelCase    =				find_block_ending(lowercase_	,			lowercase_	,			lowercase_		)

						# Extract `is_xxx_available()` from existing blocks: some models require specific libraries like `timm` and use
						# `is_timm_available()` instead of `is_torch_available()`.
						# Keep leading and trailing whitespaces
						UpperCAmelCase    =				re.compile(R'\s(is_\S+?_available\(\))\s'		)
						for line in class_lines[start_idx : end_idx + 1]:
												UpperCAmelCase    =				r.search(lowercase_		)
												if backend_condition is not None:
																		# replace the leading and trailing whitespaces to the space character " ".
																		UpperCAmelCase    =				' ' + backend_condition[0][1:-1] + ' '
																		UpperCAmelCase    =				r.sub(lowercase_	,			lowercase_		)
																		break

						if def_line is None:
												# `pipeline_model_mapping` is not defined. The target index is set to the ending index (inclusive) of
												# `all_model_classes` or `all_generative_model_classes`.
												UpperCAmelCase    =				end_idx
						else:
												# `pipeline_model_mapping` is defined. The target index is set to be one **BEFORE** its start index.
												UpperCAmelCase    =				start_idx - 1
												# mark the lines of the currently existing `pipeline_model_mapping` to be removed.
												for idx in range(lowercase_	,			end_idx + 1		):
																		# These lines are going to be removed before writing to the test file.
																		UpperCAmelCase    =				None  # noqa

    # Make sure the test class is a subclass of `PipelineTesterMixin`.
						UpperCAmelCase    =				[x.__name__ for x in test_class.__bases__]
						if "PipelineTesterMixin" not in parent_classes:
												# Put `PipelineTesterMixin` just before `unittest.TestCase`
												UpperCAmelCase    =				[x for x in parent_classes if x != 'TestCase'] + ['PipelineTesterMixin']
												if "TestCase" in parent_classes:
																		# Here we **assume** the original string is always with `unittest.TestCase`.
																		_parent_classes.append('unittest.TestCase'		)
												UpperCAmelCase    =				', '.join(_parent_classes		)
												for idx, line in enumerate(lowercase_		):
																		# Find the ending of the declaration of `test_class`
																		if line.strip().endswith('):'		):
																								# mark the lines of the declaration of `test_class` to be removed
																								for _idx in range(idx + 1		):
																														UpperCAmelCase    =				None  # noqa
																								break
        # Add the new, one-line, class declaration for `test_class`
												UpperCAmelCase    =				F"""class {test_class.__name__}({parent_classes}):\n"""

						# Add indentation
						UpperCAmelCase    =				' ' * indent_level + line_to_add
						# Insert `pipeline_model_mapping` to `class_lines`.
						# (The line at `target_idx` should be kept by definition!)
						UpperCAmelCase    =				class_lines[: target_idx + 1] + [line_to_add] + class_lines[target_idx + 1 :]
						# Remove the lines that are marked to be removed
						UpperCAmelCase    =				[x for x in class_lines if x is not None]

						# Move from test class to module (in order to write to the test file)
						UpperCAmelCase    =				inspect.getsourcelines(inspect.getmodule(lowercase_		)		)[0]
						# Be careful with the 1-off between line numbers and array indices
						UpperCAmelCase    =				module_lines[: class_start_line_no - 1] + class_lines + module_lines[class_end_line_no:]
						UpperCAmelCase    =				''.join(lowercase_		)

						UpperCAmelCase    =				inspect.getsourcefile(lowercase_		)
						with open(lowercase_	,			'w'	,			encoding='UTF-8'	,			newline='\n'		) as fp:
												fp.write(lowercase_		)

						return line_to_add

def 				_lowerCAmelCase   (     lowercase_	,			lowercase_=False		):
						UpperCAmelCase    =				find_test_class(lowercase_		)
						if test_class:
												add_pipeline_model_mapping(lowercase_	,			overwrite=lowercase_		)


if __name__ == "__main__":
				snake_case_         = argparse.ArgumentParser()
				parser.add_argument(
				    """--test_file""", type=str, help="""A path to the test file, starting with the repository's `tests` directory."""
				)
				parser.add_argument(
				    """--all""",
				    action="""store_true""",
				    help="""If to check and modify all test files.""",
				)
				parser.add_argument(
				    """--overwrite""",
				    action="""store_true""",
				    help="""If to overwrite a test class if it has already defined `pipeline_model_mapping`.""",
				)
				snake_case_         = parser.parse_args()

				if not args.all and not args.test_file:
								raise ValueError("""Please specify either `test_file` or pass `--all` to check/modify all test files.""")
				elif args.all and args.test_file:
								raise ValueError("""Only one of `--test_file` and `--all` could be specified.""")

				snake_case_         = []
				if args.test_file:
								snake_case_         = [args.test_file]
				else:
								snake_case_         = os.path.join("""tests""", """models""", """**""", """test_modeling_*.py""")
								for test_file in glob.glob(pattern):
												# `Flax` is not concerned at this moment
												if not test_file.startswith("""test_modeling_flax_"""):
																test_files.append(test_file)

				for test_file in test_files:
								if test_file in TEST_FILE_TO_IGNORE:
												print(f'''[SKIPPED] {test_file} is skipped as it is in `TEST_FILE_TO_IGNORE` in the file {__file__}.''')
												continue
								add_pipeline_model_mapping_to_test_file(test_file, overwrite=args.overwrite)










"""simple docstring"""


import math

import torch
from torch import nn
from torch.nn import init

from .binarizer import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer







class    A_    (  nn.Linear       ):



						"""simple docstring"""






						def __init__(      self				:List[str]     ,						lowercase_				:int     ,						lowercase_				:int     ,						lowercase_				:bool = True     ,						lowercase_				:str = "constant"     ,						lowercase_				:float = 0.0     ,						lowercase_				:str = "topK"     ,						)       ->    Union[str, Any]:
												super(lowercase_     ,						self      ).__init__(in_features=lowercase_     ,						out_features=lowercase_     ,						bias=lowercase_      )
												assert pruning_method in ["topK", "threshold", "sigmoied_threshold", "magnitude", "l0"]
												UpperCAmelCase    =				pruning_method

												if self.pruning_method in ["topK", "threshold", "sigmoied_threshold", "l0"]:
																		UpperCAmelCase    =				mask_scale
																		UpperCAmelCase    =				mask_init
																		UpperCAmelCase    =				nn.Parameter(torch.empty(self.weight.size()      )      )
																		self.init_mask()






						def 			UpperCAmelCase__  (      self				:Optional[Any]      )       ->    Dict:
												if self.mask_init == "constant":
																		init.constant_(self.mask_scores     ,						val=self.mask_scale      )
												elif self.mask_init == "uniform":
																		init.uniform_(self.mask_scores     ,						a=-self.mask_scale     ,						b=self.mask_scale      )
												elif self.mask_init == "kaiming":
																		init.kaiming_uniform_(self.mask_scores     ,						a=math.sqrt(5      )      )






						def 			UpperCAmelCase__  (      self				:Dict     ,						lowercase_				:torch.tensor     ,						lowercase_				:float      )       ->    List[str]:
												# Get the mask
												if self.pruning_method == "topK":
																		UpperCAmelCase    =				TopKBinarizer.apply(self.mask_scores     ,						lowercase_      )
												elif self.pruning_method in ["threshold", "sigmoied_threshold"]:
																		UpperCAmelCase    =				'sigmoied' in self.pruning_method
																		UpperCAmelCase    =				ThresholdBinarizer.apply(self.mask_scores     ,						lowercase_     ,						lowercase_      )
												elif self.pruning_method == "magnitude":
																		UpperCAmelCase    =				MagnitudeBinarizer.apply(self.weight     ,						lowercase_      )
												elif self.pruning_method == "l0":
																		UpperCAmelCase   ,					UpperCAmelCase   ,					UpperCAmelCase    =				-0.1, 1.1, 2 / 3
																		if self.training:
																								UpperCAmelCase    =				torch.zeros_like(self.mask_scores      ).uniform_().clamp(0.0001     ,						0.9999      )
																								UpperCAmelCase    =				torch.sigmoid((u.log() - (1 - u).log() + self.mask_scores) / b      )
																		else:
																								UpperCAmelCase    =				torch.sigmoid(self.mask_scores      )
																		UpperCAmelCase    =				s * (r - l) + l
																		UpperCAmelCase    =				s_bar.clamp(min=0.0     ,						max=1.0      )
												# Mask weights with computed mask
												UpperCAmelCase    =				mask * self.weight
												# Compute output (linear layer) with masked weights
												return nn.functional.linear(lowercase_     ,						lowercase_     ,						self.bias      )





