

'''simple docstring'''







import argparse
import json
import re
import string
import sys

import numpy as np


_lowerCamelCase    =  0.5






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_	):
	_lowercase							=     [""".""", """,""", """;""", """:"""]

	for token in remove_tokens:
		_lowercase							=     ground_truth.replace(snake_case_							,       """"""	)
		_lowercase							=     prediction.replace(snake_case_							,       """"""	)

	_lowercase		,		_lowercase							=     ground_truth.lower(), prediction.lower()
	_lowercase		,		_lowercase							=     ground_truth.replace("""/"""							,       """ """	), prediction.replace("""/"""							,       """ """	)
	_lowercase		,		_lowercase							=     set(ground_truth.split(""" """	)	), set(prediction.split(""" """	)	)

	_lowercase							=     ground_truth.intersection(snake_case_	)
	_lowercase							=     ground_truth.union(snake_case_	)
	_lowercase							=     len(snake_case_	) / len(snake_case_	)
	return jaccard






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):

	def remove_articles(snake_case_	):
		return re.sub(r"""\b(a|an|the)\b"""							,       """ """							,       snake_case_	)

	def white_space_fix(snake_case_	):
		return " ".join(text.split()	)

	def remove_punc(snake_case_	):
		_lowercase							=     set(string.punctuation	)
		return "".join(ch for ch in text if ch not in exclude	)

	def lower(snake_case_	):
		return text.lower()

	return white_space_fix(remove_articles(remove_punc(lower(snake_case_	)	)	)	)






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_							,       snake_case_	):
	_lowercase		,		_lowercase		,		_lowercase							=     0, 0, 0

	_lowercase							=     """Parties""" in qa_id

	# first check if ground truth is empty
	if len(snake_case_	) == 0:
		if len(snake_case_	) > 0:
			fp += len(snake_case_	)  # false positive for each one
	else:
		for ground_truth in ground_truths:
			assert len(snake_case_	) > 0
			# check if there is a match
			_lowercase							=     False
			for pred in predictions:
				if substr_ok:
					_lowercase							=     get_jaccard(snake_case_							,       snake_case_	) >= IOU_THRESH or ground_truth in pred
				else:
					_lowercase							=     get_jaccard(snake_case_							,       snake_case_	) >= IOU_THRESH
				if is_match:
					_lowercase							=     True

			if match_found:
				tp += 1
			else:
				fn += 1

        # now also get any fps by looping through preds
		for pred in predictions:
			# Check if there's a match. if so, don't count (don't want to double count based on the above)
			# but if there's no match, then this is a false positive.
			# (Note: we get the true positives in the above loop instead of this loop so that we don't double count
			# multiple predictions that are matched with the same answer.)
			_lowercase							=     False
			for ground_truth in ground_truths:
				assert len(snake_case_	) > 0
				if substr_ok:
					_lowercase							=     get_jaccard(snake_case_							,       snake_case_	) >= IOU_THRESH or ground_truth in pred
				else:
					_lowercase							=     get_jaccard(snake_case_							,       snake_case_	) >= IOU_THRESH
				if is_match:
					_lowercase							=     True

			if not match_found:
				fp += 1

	_lowercase							=     tp / (tp + fp) if tp + fp > 0 else np.nan
	_lowercase							=     tp / (tp + fn) if tp + fn > 0 else np.nan

	return precision, recall






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):
	_lowercase							=     precisions[::-1]
	for i in range(1							,       len(snake_case_	)	):
		_lowercase							=     max(precision_best[i - 1]							,       precision_best[i]	)
	_lowercase							=     precision_best[::-1]
	return precisions






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_	):
	_lowercase							=     process_precisions(snake_case_	)
	_lowercase							=     np.trapz(snake_case_							,       snake_case_	)
	if np.isnan(snake_case_	):
		return 0
	return aupr






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_							,       snake_case_	):
	_lowercase							=     process_precisions(snake_case_	)
	_lowercase							=     0
	for prec, recall in zip(snake_case_							,       snake_case_	):
		if recall >= recall_thresh:
			_lowercase							=     prec
			break
	return prec_at_recall






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_	):
	return normalize_answer(snake_case_	) == normalize_answer(snake_case_	)






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_							,       snake_case_	):
	_lowercase							=     0
	for pred in predictions:
		for ground_truth in ground_truths:
			_lowercase							=     metric_fn(snake_case_							,       snake_case_	)
			if score == 1:  # break the loop when one prediction matches the ground truth
				break
		if score == 1:
			break
	return score






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_	):
	_lowercase							=     _lowercase							=     _lowercase							=     0
	_lowercase							=     []
	_lowercase							=     []
	for article in dataset:
		for paragraph in article["paragraphs"]:
			for qa in paragraph["qas"]:
				total += 1
				if qa["id"] not in predictions:
					_lowercase							=     """Unanswered question """ + qa["""id"""] + """ will receive score 0."""
					print(snake_case_							,       file=sys.stderr	)
					continue
				_lowercase							=     [x["""text"""] for x in qa["""answers"""]]
				_lowercase							=     predictions[qa["""id"""]]
				_lowercase		,		_lowercase							=     compute_precision_recall(snake_case_							,       snake_case_							,       qa["""id"""]	)

				precisions.append(snake_case_	)
				recalls.append(snake_case_	)

				if precision == 0 and recall == 0:
					fa += 0
				else:
					fa += 2 * (precision * recall) / (precision + recall)

				exact_match += metric_max_over_ground_truths(snake_case_							,       snake_case_							,       snake_case_	)

	_lowercase							=     [x for _, x in sorted(zip(snake_case_							,       snake_case_	)	)]
	recalls.sort()

	_lowercase							=     100.0 * fa / total
	_lowercase							=     100.0 * exact_match / total
	_lowercase							=     get_aupr(snake_case_							,       snake_case_	)

	_lowercase							=     get_prec_at_recall(snake_case_							,       snake_case_							,       recall_thresh=0.9	)
	_lowercase							=     get_prec_at_recall(snake_case_							,       snake_case_							,       recall_thresh=0.8	)

	return {
	    "exact_match": exact_match,
	    "f1": fa,
	    "aupr": aupr,
	    "prec_at_80_recall": prec_at_aa_recall,
	    "prec_at_90_recall": prec_at_aa_recall,
	}


if __name__ == "__main__":
							_lowerCamelCase    =  argparse.ArgumentParser(description='Evaluation for CUAD')
							parser.add_argument('dataset_file', help='Dataset file')
							parser.add_argument('prediction_file', help='Prediction File')
							_lowerCamelCase    =  parser.parse_args()
							with open(args.dataset_file) as dataset_file:
														_lowerCamelCase    =  json.load(dataset_file)
														_lowerCamelCase    =  dataset_json['data']
							with open(args.prediction_file) as prediction_file:
														_lowerCamelCase    =  json.load(prediction_file)
							print(json.dumps(evaluate(dataset, predictions)))







'''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


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


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






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):

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

	_lowercase							=     pipeline_test_mapping[task]["""test"""]
	_lowercase							=     None

	if framework == "pt":
		_lowercase							=     getattr(snake_case_							,       """model_mapping"""							,       snake_case_	)
	elif framework == "tf":
		_lowercase							=     getattr(snake_case_							,       """tf_model_mapping"""							,       snake_case_	)

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

	# cache the results
	_lowercase							=     mapping
	return mapping






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_	):
	_lowercase							=     get_framework(snake_case_	)
	if framework is None:
		return None
	_lowercase							=     get_mapping_for_task(snake_case_							,       snake_case_	)
	if mapping is None:
		return None

	_lowercase							=     list({model_class.config_class for model_class in test_class.all_model_classes}	)
	if len(snake_case_	) != 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.
	_lowercase							=     mapping.get(config_classes[0]							,       snake_case_	)
	if isinstance(snake_case_							,       (tuple, list)	):
		_lowercase							=     sorted(snake_case_							,       key=lambda snake_case_	: x.__name__	)

	return model_class






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

	return dict(snake_case_	)






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):
	_lowercase							=     get_framework(snake_case_	)
	if framework == "pt":
		_lowercase							=     """torch"""
	_lowercase							=     """{}"""

	_lowercase							=     get_pipeline_model_mapping(snake_case_	)
	if len(snake_case_	) == 0:
		return ""

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

	return text






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






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):
	_lowercase							=     [x for x in get_test_classes(snake_case_	) if is_valid_test_class(snake_case_	)]

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

	return target_test_class






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

	return end_idx






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_=False	):
	if getattr(snake_case_							,       """pipeline_model_mapping"""							,       snake_case_	) is not None:
		if not overwrite:
			return "", -1

	_lowercase							=     get_pipeline_model_mapping_string(snake_case_	)
	if len(snake_case_	) == 0:
		return "", -1
	_lowercase							=     line_to_add + """\n"""

	# The code defined the class `test_class`
	_lowercase		,		_lowercase							=     inspect.getsourcelines(snake_case_	)
	# `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(snake_case_	):
		if line.lstrip().startswith("""class """	):
			_lowercase							=     class_lines[idx:]
			class_start_line_no += idx
			break
	_lowercase							=     class_start_line_no + len(snake_case_	) - 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`.
	_lowercase							=     None
	# The indent level of the line at `class_lines[start_idx]` (if defined)
	_lowercase							=     0
	# To record if `pipeline_model_mapping` is found in `test_class`.
	_lowercase							=     None
	for idx, line in enumerate(snake_case_	):
		if line.strip().startswith("""all_model_classes = """	):
			_lowercase							=     len(snake_case_	) - len(line.lstrip()	)
			_lowercase							=     idx
		elif line.strip().startswith("""all_generative_model_classes = """	):
			_lowercase							=     len(snake_case_	) - len(line.lstrip()	)
			_lowercase							=     idx
		elif line.strip().startswith("""pipeline_model_mapping = """	):
			_lowercase							=     len(snake_case_	) - len(line.lstrip()	)
			_lowercase							=     idx
			_lowercase							=     line
			break

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

	# 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
	_lowercase							=     re.compile(r"""\s(is_\S+?_available\(\))\s"""	)
	for line in class_lines[start_idx : end_idx + 1]:
		_lowercase							=     r.search(snake_case_	)
		if backend_condition is not None:
			# replace the leading and trailing whitespaces to the space character " ".
			_lowercase							=     """ """ + backend_condition[0][1:-1] + """ """
			_lowercase							=     r.sub(snake_case_							,       snake_case_	)
			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`.
		_lowercase							=     end_idx
	else:
		# `pipeline_model_mapping` is defined. The target index is set to be one **BEFORE** its start index.
		_lowercase							=     start_idx - 1
		# mark the lines of the currently existing `pipeline_model_mapping` to be removed.
		for idx in range(snake_case_							,       end_idx + 1	):
			# These lines are going to be removed before writing to the test file.
			_lowercase							=     None  # noqa

    # Make sure the test class is a subclass of `PipelineTesterMixin`.
	_lowercase							=     [x.__name__ for x in test_class.__bases__]
	if "PipelineTesterMixin" not in parent_classes:
		# Put `PipelineTesterMixin` just before `unittest.TestCase`
		_lowercase							=     [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"""	)
		_lowercase							=     """, """.join(_parent_classes	)
		for idx, line in enumerate(snake_case_	):
			# 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	):
					_lowercase							=     None  # noqa
				break
        # Add the new, one-line, class declaration for `test_class`
		_lowercase							=     F"""class {test_class.__name__}({parent_classes}):\n"""

	# Add indentation
	_lowercase							=     """ """ * indent_level + line_to_add
	# Insert `pipeline_model_mapping` to `class_lines`.
	# (The line at `target_idx` should be kept by definition!)
	_lowercase							=     class_lines[: target_idx + 1] + [line_to_add] + class_lines[target_idx + 1 :]
	# Remove the lines that are marked to be removed
	_lowercase							=     [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)
	_lowercase							=     inspect.getsourcelines(inspect.getmodule(snake_case_	)	)[0]
	# Be careful with the 1-off between line numbers and array indices
	_lowercase							=     module_lines[: class_start_line_no - 1] + class_lines + module_lines[class_end_line_no:]
	_lowercase							=     """""".join(snake_case_	)

	_lowercase							=     inspect.getsourcefile(snake_case_	)
	with open(snake_case_							,       """w"""							,       encoding="""UTF-8"""							,       newline="""\n"""	) as fp:
		fp.write(snake_case_	)

	return line_to_add






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_=False	):
	_lowercase							=     find_test_class(snake_case_	)
	if test_class:
		add_pipeline_model_mapping(snake_case_							,       overwrite=snake_case_	)


if __name__ == "__main__":
							_lowerCamelCase    =  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`.',
							)
							_lowerCamelCase    =  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.')

							_lowerCamelCase    =  []
							if args.test_file:
														_lowerCamelCase    =  [args.test_file]
							else:
														_lowerCamelCase    =  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)




