






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
__lowerCamelCase   :					Dict   							=					pytest.mark.integration


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

__lowerCamelCase   :					int   							=					{'''code_eval'''}
__lowerCamelCase   :					Dict   							=					os.name == '''nt'''

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

def 	__UpperCAmelCase       ( __magic_name__						)->    Union[str, Any]:



			"""simple docstring"""



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

			return wrapper

def 	__UpperCAmelCase       ( __magic_name__						)->    List[Any]:



			"""simple docstring"""



			@wraps(__magic_name__						)
			def wrapper(self     ,__magic_name__						):
						if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
									self.skipTest("\"test requires transformers\""						)
						else:
									test_case(self     ,__magic_name__						)

			return wrapper

def 	__UpperCAmelCase       ( __magic_name__						)->    Optional[int]:



			"""simple docstring"""



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

			return wrapper

def 	__UpperCAmelCase       ( )->    Optional[Any]:



			"""simple docstring"""



			snake_case_				:					Optional[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(
    a_						,					a_						,					a_							)
@local
class    A_	(parameterized.TestCase							):
							"""simple docstring"""




							a__   		=	{}
							a__   		=	None

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


										'''simple docstring'''




										snake_case_				:					Dict   =       "[...]"
										snake_case_				:					Union[str, Any]   =       importlib.import_module(
										    datasets.load.metric_module_factory(os.path.join("metrics"       ,							lowerCAmelCase__				)				).module_path				)
										snake_case_				:					Optional[Any]   =       datasets.load.import_main_class(metric_module.__name__       ,							dataset=lowerCAmelCase__				)
										# check parameters
										snake_case_				:					int   =       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(lowerCAmelCase__       ,							metric_module.__name__				):
													with self.use_local_metrics():
																try:
																			snake_case_				:					Optional[Any]   =       doctest.testmod(lowerCAmelCase__       ,							verbose=lowerCAmelCase__       ,							raise_on_error=lowerCAmelCase__				)
																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 							_A	(		self			:Union[str, Any]       ,							lowerCAmelCase__			:Optional[int]				)				->  Union[str, Any]:


										'''simple docstring'''




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

							@contextmanager
							def 							_A	(		self			:List[str]       ,							lowerCAmelCase__			:Union[str, Any]       ,							lowerCAmelCase__			:List[str]				)				->  Optional[Any]:


										'''simple docstring'''




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

							@contextmanager
							def 							_A	(		self			:Optional[int]				)				->  Optional[int]:


										'''simple docstring'''




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

										with patch("datasets.load_metric"				) as mock_load_metric:
													snake_case_				:					List[str]   =       load_local_metric
													yield






							@classmethod
							def 							_A	(		cls			:Optional[Any]       ,							lowerCAmelCase__			:str				)				->  str:


										'''simple docstring'''




										def wrapper(lowerCAmelCase__			:Any				):
													snake_case_				:					Optional[int]   =       contextmanager(lowerCAmelCase__				)
													snake_case_				:					List[Any]   =       patcher
													return patcher

										return wrapper

@LocalMetricTest.register_intensive_calls_patcher("bleurt"						)
def 	__UpperCAmelCase       ( __magic_name__						)->    List[Any]:



			"""simple docstring"""



			import tensorflow.compat.va as tf
			from bleurt.score import Predictor

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







			class    A_	(a_							):
										"""simple docstring"""




										def 							_A	(		self			:Any       ,							lowerCAmelCase__			:Optional[Any]				)				->  str:


													'''simple docstring'''




													assert len(input_dict["input_ids"]				) == 2
													return np.array([1.0_3, 1.0_4]				)

    # 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_				:					Dict   =       MockedPredictor()
						yield

@LocalMetricTest.register_intensive_calls_patcher("bertscore"						)
def 	__UpperCAmelCase       ( __magic_name__						)->    Tuple:



			"""simple docstring"""



			import torch

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

			# 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_				:					List[Any]   =       bert_cos_score_idf
						yield

@LocalMetricTest.register_intensive_calls_patcher("comet"						)
def 	__UpperCAmelCase       ( __magic_name__						)->    Optional[int]:



			"""simple docstring"""



			def load_from_checkpoint(__magic_name__						):







						class    A_	:
													"""simple docstring"""




													def 							_A	(		self			:Tuple       ,							lowerCAmelCase__			:Tuple       ,							*lowerCAmelCase__			:Optional[Any]       ,							**lowerCAmelCase__			:str				)				->  List[Any]:


																'''simple docstring'''




																assert len(lowerCAmelCase__				) == 2
																snake_case_				:					Tuple   =       [0.1_9, 0.9_2]
																return scores, sum(lowerCAmelCase__				) / len(lowerCAmelCase__				)
						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_				:					Union[str, Any]   =       None
						with patch("comet.load_from_checkpoint"						) as mock_load_from_checkpoint:
									snake_case_				:					int   =       load_from_checkpoint
									yield






def 	__UpperCAmelCase       ( )->    List[Any]:



			"""simple docstring"""



			snake_case_				:					Optional[int]   =       load_metric(os.path.join("metrics"     ,"seqeval"						)						)
			snake_case_				:					int   =       "ERROR"
			snake_case_				:					int   =       F'''Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {wrong_scheme}'''
			with pytest.raises(__magic_name__     ,match=re.escape(__magic_name__						)						):
						metric.compute(predictions=[]     ,references=[]     ,scheme=__magic_name__						)












'''simple docstring'''




import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class    A_	(a_						,					unittest.TestCase							):
							"""simple docstring"""




							a__   		=	MgpstrTokenizer
							a__   		=	False
							a__   		=	{}
							a__   		=	False

							def 							_A	(		self			:List[str]				)				->  List[str]:


										'''simple docstring'''




										super().setUp()

										# fmt: off
										snake_case_				:					Dict   =       ["[GO]", "[s]", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"]
										# fmt: on
										snake_case_				:					List[str]   =       dict(zip(lowerCAmelCase__       ,							range(len(lowerCAmelCase__				)				)				)				)

										snake_case_				:					Tuple   =       os.path.join(self.tmpdirname       ,							VOCAB_FILES_NAMES["vocab_file"]				)
										with open(self.vocab_file       ,							"w"       ,							encoding="utf-8"				) as fp:
													fp.write(json.dumps(lowerCAmelCase__				) + "\n"				)

							def 							_A	(		self			:Optional[Any]       ,							**lowerCAmelCase__			:Optional[Any]				)				->  Dict:


										'''simple docstring'''




										return MgpstrTokenizer.from_pretrained(self.tmpdirname       ,							**lowerCAmelCase__				)

							def 							_A	(		self			:Dict       ,							lowerCAmelCase__			:Any				)				->  str:


										'''simple docstring'''




										snake_case_				:					Dict   =       "tester"
										snake_case_				:					Tuple   =       "tester"
										return input_text, output_text

							@unittest.skip("MGP-STR always lower cases letters."				)
							def 							_A	(		self			:Dict				)				->  str:


										'''simple docstring'''




										pass

							def 							_A	(		self			:Tuple				)				->  Union[str, Any]:


										'''simple docstring'''




										snake_case_				:					List[str]   =       self.get_tokenizers(do_lower_case=lowerCAmelCase__				)
										for tokenizer in tokenizers:
													with self.subTest(F'''{tokenizer.__class__.__name__}'''				):
																snake_case_				:					Tuple   =       "[SPECIAL_TOKEN]"

																tokenizer.add_special_tokens({"cls_token": special_token}				)
																snake_case_				:					str   =       tokenizer.encode([special_token]       ,							add_special_tokens=lowerCAmelCase__				)
																self.assertEqual(len(lowerCAmelCase__				)       ,							1				)

																snake_case_				:					Tuple   =       tokenizer.decode(lowerCAmelCase__       ,							skip_special_tokens=lowerCAmelCase__				)
																self.assertTrue(special_token not in decoded				)

							def 							_A	(		self			:int				)				->  List[str]:


										'''simple docstring'''




										snake_case_				:					Dict   =       self.get_tokenizers()
										for tokenizer in tokenizers:
													with self.subTest(F'''{tokenizer.__class__.__name__}'''				):
																snake_case_,	snake_case_				:					str   =       self.get_input_output_texts(lowerCAmelCase__				)

																snake_case_				:					Union[str, Any]   =       tokenizer.tokenize(lowerCAmelCase__				)
																snake_case_				:					List[Any]   =       tokenizer.convert_tokens_to_ids(lowerCAmelCase__				)
																snake_case_				:					Dict   =       tokenizer.encode(lowerCAmelCase__       ,							add_special_tokens=lowerCAmelCase__				)
																self.assertListEqual(lowerCAmelCase__       ,							lowerCAmelCase__				)

																snake_case_				:					List[str]   =       tokenizer.convert_ids_to_tokens(lowerCAmelCase__				)
																self.assertNotEqual(len(lowerCAmelCase__				)       ,							0				)
																snake_case_				:					List[str]   =       tokenizer.decode(lowerCAmelCase__				)
																self.assertIsInstance(lowerCAmelCase__       ,							lowerCAmelCase__				)

																self.assertEqual(text_a.replace(" "       ,							""				)       ,							lowerCAmelCase__				)

							@unittest.skip("MGP-STR tokenizer only handles one sequence."				)
							def 							_A	(		self			:Union[str, Any]				)				->  Any:


										'''simple docstring'''




										pass






							@unittest.skip("inputs cannot be pretokenized in MgpstrTokenizer"				)
							def 							_A	(		self			:int				)				->  Dict:


										'''simple docstring'''




										pass




