


"""simple docstring"""
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch

import numpy as np
import pytest
from absl.testing import parameterized

import datasets
from datasets import load_metric

from .utils import for_all_test_methods, local, slow


# mark all tests as integration
__SCREAMING_SNAKE_CASE							:    Union[str, Any]		=    pytest.mark.integration


__SCREAMING_SNAKE_CASE							:    Optional[int]		=    {'comet'}
__SCREAMING_SNAKE_CASE							:    Union[str, Any]		=    importlib.util.find_spec('fairseq') is not None

__SCREAMING_SNAKE_CASE							:    Dict		=    {'code_eval'}
__SCREAMING_SNAKE_CASE							:    str		=    os.name == 'nt'

__SCREAMING_SNAKE_CASE							:    Union[str, Any]		=    {'bertscore', 'frugalscore', 'perplexity'}
__SCREAMING_SNAKE_CASE							:    Any		=    importlib.util.find_spec('transformers') is not None







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				str:
							@wraps(_SCREAMING_SNAKE_CASE				)
							def wrapper(self				, _SCREAMING_SNAKE_CASE				):
														if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
																					self.skipTest("""\"test requires Fairseq\""""				)
														else:
																					test_case(self				, _SCREAMING_SNAKE_CASE				)

							return wrapper







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				Optional[int]:
							@wraps(_SCREAMING_SNAKE_CASE				)
							def wrapper(self				, _SCREAMING_SNAKE_CASE				):
														if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
																					self.skipTest("""\"test requires transformers\""""				)
														else:
																					test_case(self				, _SCREAMING_SNAKE_CASE				)

							return wrapper







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				str:
							@wraps(_SCREAMING_SNAKE_CASE				)
							def wrapper(self				, _SCREAMING_SNAKE_CASE				):
														if _on_windows and metric_name in UNSUPPORTED_ON_WINDOWS:
																					self.skipTest("""\"test not supported on Windows\""""				)
														else:
																					test_case(self				, _SCREAMING_SNAKE_CASE				)

							return wrapper







def 						_a				(      )    ->				List[str]:
							snake_case_           =		[metric_dir.split(os.sep				)[-2] for metric_dir in glob.glob("""./metrics/*/"""				)]
							return [{"testcase_name": x, "metric_name": x} for x in metrics if x != "gleu"]  # gleu is unfinished





@parameterized.named_parameters(get_local_metric_names())
@for_all_test_methods(
    snake_case__						,		snake_case__						,		snake_case__)
@local
class      __A     (parameterized.TestCase):





							'''simple docstring'''

							__lowercase:		Tuple							      =    {}
							__lowercase:		Tuple							      =    None



							@pytest.mark.filterwarnings("""ignore:metric_module_factory is deprecated:FutureWarning"""       )
							@pytest.mark.filterwarnings("""ignore:load_metric is deprecated:FutureWarning"""       )
							def 		lowerCAmelCase       (				self							:      Any		,       UpperCAmelCase_							:      List[str]       )					->Optional[Any]:



														"""simple docstring"""



														snake_case_           =		"""[...]"""
														snake_case_           =		importlib.import_module(
														    datasets.load.metric_module_factory(os.path.join("""metrics"""		,       UpperCAmelCase_       )       ).module_path       )
														snake_case_           =		datasets.load.import_main_class(metric_module.__name__		,       dataset=UpperCAmelCase_       )
														# check parameters
														snake_case_           =		inspect.signature(metric._compute       ).parameters
														self.assertTrue(all(p.kind != p.VAR_KEYWORD for p in parameters.values()       )       )  # no **kwargs
														# run doctest
														with self.patch_intensive_calls(UpperCAmelCase_		,       metric_module.__name__       ):
																					with self.use_local_metrics():
																												try:
																																			snake_case_           =		doctest.testmod(UpperCAmelCase_		,       verbose=UpperCAmelCase_		,       raise_on_error=UpperCAmelCase_       )
																												except doctest.UnexpectedException as e:
																																			raise e.exc_info[1]  # raise the exception that doctest caught
														self.assertEqual(results.failed		,       0       )
														self.assertGreater(results.attempted		,       1       )



							@slow
							def 		lowerCAmelCase       (				self							:      Optional[int]		,       UpperCAmelCase_							:      List[str]       )					->Any:



														"""simple docstring"""



														snake_case_           =		"""[...]"""
														snake_case_           =		importlib.import_module(
														    datasets.load.metric_module_factory(os.path.join("""metrics"""		,       UpperCAmelCase_       )       ).module_path       )
														# run doctest
														with self.use_local_metrics():
																					snake_case_           =		doctest.testmod(UpperCAmelCase_		,       verbose=UpperCAmelCase_		,       raise_on_error=UpperCAmelCase_       )
														self.assertEqual(results.failed		,       0       )
														self.assertGreater(results.attempted		,       1       )



							@contextmanager
							def 		lowerCAmelCase       (				self							:      Union[str, Any]		,       UpperCAmelCase_							:      str		,       UpperCAmelCase_							:      Optional[int]       )					->int:



														"""simple docstring"""



														if metric_name in self.INTENSIVE_CALLS_PATCHER:
																					with self.INTENSIVE_CALLS_PATCHER[metric_name](UpperCAmelCase_       ):
																												yield
														else:
																					yield



							@contextmanager
							def 		lowerCAmelCase       (				self							:      List[Any]       )					->Optional[Any]:



														"""simple docstring"""



														def load_local_metric(UpperCAmelCase_							:      Optional[Any]		,       *UpperCAmelCase_							:      Optional[Any]		,       **UpperCAmelCase_							:      str       ):
																					return load_metric(os.path.join("""metrics"""		,       UpperCAmelCase_       )		,       *UpperCAmelCase_		,       **UpperCAmelCase_       )

														with patch("""datasets.load_metric"""       ) as mock_load_metric:
																					snake_case_           =		load_local_metric
																					yield



							@classmethod
							def 		lowerCAmelCase       (				cls							:      Any		,       UpperCAmelCase_							:      Dict       )					->List[Any]:



														"""simple docstring"""



														def wrapper(UpperCAmelCase_							:      Optional[int]       ):
																					snake_case_           =		contextmanager(UpperCAmelCase_       )
																					snake_case_           =		patcher
																					return patcher

														return wrapper







@LocalMetricTest.register_intensive_calls_patcher("""bleurt"""				)
def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				str:
							import tensorflow.compat.va as tf
							from bleurt.score import Predictor

							tf.flags.DEFINE_string("""sv"""				, """"""				, """"""				)  # handle pytest cli flags





							class      __A     (snake_case__):





														'''simple docstring'''

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



																					"""simple docstring"""



																					assert len(input_dict["""input_ids"""]       ) == 2
																					return np.array([1.03, 1.04]       )

    # mock predict_fn which is supposed to do a forward pass with a bleurt model
							with patch("""bleurt.score._create_predictor"""				) as mock_create_predictor:
														snake_case_           =		MockedPredictor()
														yield







@LocalMetricTest.register_intensive_calls_patcher("""bertscore"""				)
def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				Optional[Any]:
							import torch

							def bert_cos_score_idf(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				, *_SCREAMING_SNAKE_CASE				, **_SCREAMING_SNAKE_CASE				):
														return torch.tensor([[1.0, 1.0, 1.0]] * len(_SCREAMING_SNAKE_CASE				)				)

							# mock get_model which is supposed to do download a bert model
							# mock bert_cos_score_idf which is supposed to do a forward pass with a bert model
							with patch("""bert_score.scorer.get_model"""				), patch(
							    """bert_score.scorer.bert_cos_score_idf"""				) as mock_bert_cos_score_idf:
														snake_case_           =		bert_cos_score_idf
														yield







@LocalMetricTest.register_intensive_calls_patcher("""comet"""				)
def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				Any:
							def load_from_checkpoint(_SCREAMING_SNAKE_CASE				):





														class      __A     :





																					'''simple docstring'''

																					def 		lowerCAmelCase       (				self							:      Union[str, Any]		,       UpperCAmelCase_							:      Union[str, Any]		,       *UpperCAmelCase_							:      Optional[int]		,       **UpperCAmelCase_							:      str       )					->Any:



																												"""simple docstring"""



																												assert len(UpperCAmelCase_       ) == 2
																												snake_case_           =		[0.19, 0.92]
																												return scores, sum(UpperCAmelCase_       ) / len(UpperCAmelCase_       )


														return Model()

							# mock load_from_checkpoint which is supposed to do download a bert model
							# mock load_from_checkpoint which is supposed to do download a bert model
							with patch("""comet.download_model"""				) as mock_download_model:
														snake_case_           =		None
														with patch("""comet.load_from_checkpoint"""				) as mock_load_from_checkpoint:
																					snake_case_           =		load_from_checkpoint
																					yield







def 						_a				(      )    ->				List[str]:
							snake_case_           =		load_metric(os.path.join("""metrics"""				, """seqeval"""				)				)
							snake_case_           =		"""ERROR"""
							snake_case_           =		f"""Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {wrong_scheme}"""
							with pytest.raises(_SCREAMING_SNAKE_CASE				, match=re.escape(_SCREAMING_SNAKE_CASE				)				):
														metric.compute(predictions=[]				, references=[]				, scheme=_SCREAMING_SNAKE_CASE				)







"""simple docstring"""
def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				list:

							# bit count represents no. of bits in the gray code
							if bit_count < 0:
														raise ValueError("""The given input must be positive"""				)

							# get the generated string sequence
							snake_case_           =		gray_code_sequence_string(_SCREAMING_SNAKE_CASE				)
							#
							# convert them to integers
							for i in range(len(_SCREAMING_SNAKE_CASE				)				):
														snake_case_           =		int(sequence[i]				, 2				)

							return sequence







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				list:

							# The approach is a recursive one
							# Base case achieved when either n = 0 or n=1
							if bit_count == 0:
														return ["0"]

							if bit_count == 1:
														return ["0", "1"]

							snake_case_           =		1 << bit_count  # defines the length of the sequence
							# 1<< n is equivalent to 2^n

							# recursive answer will generate answer for n-1 bits
							snake_case_           =		gray_code_sequence_string(bit_count - 1				)

							snake_case_           =		[]

							# append 0 to first half of the smaller sequence generated
							for i in range(seq_len // 2				):
														snake_case_           =		"""0""" + smaller_sequence[i]
														sequence.append(_SCREAMING_SNAKE_CASE				)

							# append 1 to second half ... start from the end of the list
							for i in reversed(range(seq_len // 2				)				):
														snake_case_           =		"""1""" + smaller_sequence[i]
														sequence.append(_SCREAMING_SNAKE_CASE				)

							return sequence


if __name__ == "__main__":
				import doctest

				doctest.testmod()



