






'''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
A:      int  				=				pytest.mark.integration


A:      List[Any]  				=				{"comet"}
A:      Dict  				=				importlib.util.find_spec("fairseq") is not None

A:      Dict  				=				{"code_eval"}
A:      str  				=				os.name == "nt"

A:      Optional[int]  				=				{"bertscore", "frugalscore", "perplexity"}
A:      Optional[Any]  				=				importlib.util.find_spec("transformers") is not None






def 	_UpperCAmelCase    (  a		:	Tuple							)			->			Tuple:





						"""simple docstring"""
						@wraps(a							)
						def wrapper(self		:	Optional[Any]						,			a		:	Any							):
												if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
																		self.skipTest('"test requires Fairseq"'							)
												else:
																		test_case(self						,			a							)

						return wrapper






def 	_UpperCAmelCase    (  a		:	int							)			->			Dict:





						"""simple docstring"""
						@wraps(a							)
						def wrapper(self		:	Dict						,			a		:	List[Any]							):
												if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
																		self.skipTest('"test requires transformers"'							)
												else:
																		test_case(self						,			a							)

						return wrapper






def 	_UpperCAmelCase    (  a		:	Any							)			->			Tuple:





						"""simple docstring"""
						@wraps(a							)
						def wrapper(self		:	Optional[int]						,			a		:	str							):
												if _on_windows and metric_name in UNSUPPORTED_ON_WINDOWS:
																		self.skipTest('"test not supported on Windows"'							)
												else:
																		test_case(self						,			a							)

						return wrapper






def 	_UpperCAmelCase    (  )			->			List[str]:





						"""simple docstring"""
						lowercase_      :   Union[str, Any]        =			[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(
    UpperCAmelCase_,						UpperCAmelCase_,						UpperCAmelCase_				)
@local
class 							__magic_name__     (	parameterized.TestCase				):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_					:      Optional[int]        =  {}
	SCREAMING_SNAKE_CASE_					:      Tuple        =  None
	@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'       )
	@pytest.mark.filterwarnings('ignore:load_metric is deprecated:FutureWarning'       )
	def        lowerCamelCase__		(							self  ,      _lowercase       )						->  Optional[int]:
							lowercase_      :   str        =			'[...]'
							lowercase_      :   int        =			importlib.import_module(
							    datasets.load.metric_module_factory(os.path.join('metrics'  ,      _lowercase       )       ).module_path       )
							lowercase_      :   int        =			datasets.load.import_main_class(metric_module.__name__  ,      dataset=_lowercase       )
							# check parameters
							lowercase_      :   str        =			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(_lowercase  ,      metric_module.__name__       ):
													with self.use_local_metrics():
																			try:
																									lowercase_      :   Optional[Any]        =			doctest.testmod(_lowercase  ,      verbose=_lowercase  ,      raise_on_error=_lowercase       )
																			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  ,      _lowercase       )						->  Any:
							lowercase_      :   List[str]        =			'[...]'
							lowercase_      :   Dict        =			importlib.import_module(
							    datasets.load.metric_module_factory(os.path.join('metrics'  ,      _lowercase       )       ).module_path       )
							# run doctest
							with self.use_local_metrics():
													lowercase_      :   Optional[int]        =			doctest.testmod(_lowercase  ,      verbose=_lowercase  ,      raise_on_error=_lowercase       )
							self.assertEqual(results.failed  ,      0       )
							self.assertGreater(results.attempted  ,      1       )
	@contextmanager
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase       )						->  Tuple:
							if metric_name in self.INTENSIVE_CALLS_PATCHER:
													with self.INTENSIVE_CALLS_PATCHER[metric_name](_lowercase       ):
																			yield
							else:
													yield
	@contextmanager
	def        lowerCamelCase__		(							self       )						->  int:
							def load_local_metric(_lowercase  ,      *_lowercase  ,      **_lowercase       ):
													return load_metric(os.path.join('metrics'  ,      _lowercase       )  ,      *_lowercase  ,      **_lowercase       )

							with patch('datasets.load_metric'       ) as mock_load_metric:
													lowercase_      :   Dict        =			load_local_metric
													yield







	@classmethod
	def        lowerCamelCase__		(							cls  ,      _lowercase       )						->  Dict:
							def wrapper(_lowercase       ):
													lowercase_      :   Optional[int]        =			contextmanager(_lowercase       )
													lowercase_      :   int        =			patcher
													return patcher

							return wrapper






@LocalMetricTest.register_intensive_calls_patcher('bleurt'							)
def 	_UpperCAmelCase    (  a		:	Dict							)			->			Any:





						"""simple docstring"""
						import tensorflow.compat.va as tf
						from bleurt.score import Predictor

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






						class 							__magic_name__     (	UpperCAmelCase_				):







							"""simple docstring"""



							def        lowerCamelCase__		(							self  ,      _lowercase       )						->  Dict:
													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:
												lowercase_      :   Dict        =			MockedPredictor()
												yield






@LocalMetricTest.register_intensive_calls_patcher('bertscore'							)
def 	_UpperCAmelCase    (  a		:	Union[str, Any]							)			->			Tuple:





						"""simple docstring"""
						import torch

						def bert_cos_score_idf(a		:	Any						,			a		:	List[str]						,			*a		:	Tuple						,			**a		:	int							):
												return torch.tensor([[1.0, 1.0, 1.0]] * len(a							)							)

						# 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:
												lowercase_      :   int        =			bert_cos_score_idf
												yield






@LocalMetricTest.register_intensive_calls_patcher('comet'							)
def 	_UpperCAmelCase    (  a		:	Dict							)			->			Any:





						"""simple docstring"""
						def load_from_checkpoint(a		:	Any							):






												class 							__magic_name__     :







													"""simple docstring"""



													def        lowerCamelCase__		(							self  ,      _lowercase  ,      *_lowercase  ,      **_lowercase       )						->  int:
																			assert len(_lowercase       ) == 2
																			lowercase_      :   Dict        =			[0.19, 0.92]
																			return scores, sum(_lowercase       ) / len(_lowercase       )


												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:
												lowercase_      :   List[Any]        =			None
												with patch('comet.load_from_checkpoint'							) as mock_load_from_checkpoint:
																		lowercase_      :   List[str]        =			load_from_checkpoint
																		yield






def 	_UpperCAmelCase    (  )			->			Optional[Any]:





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








'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A:      Dict  				=				logging.get_logger(__name__)

A:      Optional[Any]  				=				{
    "google/vit-base-patch16-224": "https://huggingface.co/vit-base-patch16-224/resolve/main/config.json",
    # See all ViT models at https://huggingface.co/models?filter=vit
}






class 							__magic_name__     (	UpperCAmelCase_				):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_					:      Optional[Any]        =  'vit'
	def __init__(							self  ,      _lowercase=768  ,      _lowercase=12  ,      _lowercase=12  ,      _lowercase=3072  ,      _lowercase="gelu"  ,      _lowercase=0.0  ,      _lowercase=0.0  ,      _lowercase=0.02  ,      _lowercase=1E-1_2  ,      _lowercase=224  ,      _lowercase=16  ,      _lowercase=3  ,      _lowercase=True  ,      _lowercase=16  ,      **_lowercase  ,      )						->  List[str]:
							super().__init__(**_lowercase       )

							lowercase_      :   Optional[int]        =			hidden_size
							lowercase_      :   str        =			num_hidden_layers
							lowercase_      :   str        =			num_attention_heads
							lowercase_      :   int        =			intermediate_size
							lowercase_      :   List[Any]        =			hidden_act
							lowercase_      :   Any        =			hidden_dropout_prob
							lowercase_      :   List[str]        =			attention_probs_dropout_prob
							lowercase_      :   str        =			initializer_range
							lowercase_      :   List[str]        =			layer_norm_eps
							lowercase_      :   Any        =			image_size
							lowercase_      :   Tuple        =			patch_size
							lowercase_      :   Optional[Any]        =			num_channels
							lowercase_      :   str        =			qkv_bias
							lowercase_      :   List[str]        =			encoder_stride






class 							__magic_name__     (	UpperCAmelCase_				):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_					:      Any        =  version.parse('1.11'				)
	@property
	def        lowerCamelCase__		(							self       )						->  Mapping[str, Mapping[int, str]]:
							return OrderedDict(
							    [
							        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
							    ]       )







	@property
	def        lowerCamelCase__		(							self       )						->  float:
							return 1E-4
