


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       	=  pytest.mark.integration


a       	=  {'comet'}
a       	=  importlib.util.find_spec('fairseq') is not None

a       	=  {'code_eval'}
a       	=  os.name == 'nt'

a       	=  {'bertscore', 'frugalscore', 'perplexity'}
a       	=  importlib.util.find_spec('transformers') is not None


def       UpperCAmelCase_					(   UpperCAmelCase__	):

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

					return wrapper


def       UpperCAmelCase_					(   UpperCAmelCase__	):

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

					return wrapper


def       UpperCAmelCase_					(   UpperCAmelCase__	):

					@wraps(a_	)
					def wrapper(self    ,				UpperCAmelCase__	):
										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_					(   ):
					lowercase_					=      [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(
    SCREAMING_SNAKE_CASE__				,					SCREAMING_SNAKE_CASE__				,					SCREAMING_SNAKE_CASE__ )
@local
class 							UpperCamelCase__ (						parameterized.TestCase ):
					__SCREAMING_SNAKE_CASE							:	Dict            = {}
					__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 	UpperCAmelCase__							(  self							: Optional[int]				,       UpperCamelCase__							: Optional[int]							):






										'''simple docstring'''






										lowercase_					=      """[...]"""
										lowercase_					=      importlib.import_module(
										    datasets.load.metric_module_factory(os.path.join("""metrics"""				,       __lowerCAmelCase							)							).module_path							)
										lowercase_					=      datasets.load.import_main_class(metric_module.__name__				,       dataset=__lowerCAmelCase							)
										# check parameters
										lowercase_					=      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:
																									lowercase_					=      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 	UpperCAmelCase__							(  self							: Any				,       UpperCamelCase__							: str							):






										'''simple docstring'''






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

					@contextmanager
					def 	UpperCAmelCase__							(  self							: Tuple				,       UpperCamelCase__							: Union[str, Any]				,       UpperCamelCase__							: Optional[int]							):






										'''simple docstring'''






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

					@contextmanager
					def 	UpperCAmelCase__							(  self							: Union[str, Any]							):






										'''simple docstring'''






										def load_local_metric(UpperCamelCase__							: Optional[int]				,       *UpperCamelCase__							: Any				,       **UpperCamelCase__							: Optional[Any]							):
															return load_metric(os.path.join("""metrics"""				,       __lowerCAmelCase							)				,       *__lowerCAmelCase				,       **__lowerCAmelCase							)

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







					@classmethod
					def 	UpperCAmelCase__							(  cls							: Optional[Any]				,       UpperCamelCase__							: List[Any]							):






										'''simple docstring'''






										def wrapper(UpperCamelCase__							: Optional[Any]							):
															lowercase_					=      contextmanager(__lowerCAmelCase							)
															lowercase_					=      patcher
															return patcher

										return wrapper



@LocalMetricTest.register_intensive_calls_patcher("""bleurt"""	)
def       UpperCAmelCase_					(   UpperCAmelCase__	):
					import tensorflow.compat.va as tf
					from bleurt.score import Predictor

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







					class 							UpperCamelCase__ (						SCREAMING_SNAKE_CASE__ ):

										def 	UpperCAmelCase__							(  self							: Any				,       UpperCamelCase__							: Any							):






															'''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:
										lowercase_					=      MockedPredictor()
										yield


@LocalMetricTest.register_intensive_calls_patcher("""bertscore"""	)
def       UpperCAmelCase_					(   UpperCAmelCase__	):
					import torch

					def bert_cos_score_idf(UpperCAmelCase__    ,				UpperCAmelCase__    ,				*UpperCAmelCase__    ,				**UpperCAmelCase__	):
										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_					=      bert_cos_score_idf
										yield


@LocalMetricTest.register_intensive_calls_patcher("""comet"""	)
def       UpperCAmelCase_					(   UpperCAmelCase__	):

					def load_from_checkpoint(UpperCAmelCase__	):







										class 							UpperCamelCase__ :

															def 	UpperCAmelCase__							(  self							: List[str]				,       UpperCamelCase__							: Optional[int]				,       *UpperCamelCase__							: Optional[int]				,       **UpperCamelCase__							: List[Any]							):






																				'''simple docstring'''






																				assert len(__lowerCAmelCase							) == 2
																				lowercase_					=      [0.19, 0.92]
																				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:
										lowercase_					=      None
										with patch("""comet.load_from_checkpoint"""	) as mock_load_from_checkpoint:
															lowercase_					=      load_from_checkpoint
															yield



def       UpperCAmelCase_					(   ):
					lowercase_					=      load_metric(os.path.join("""metrics"""    ,				"""seqeval"""	)	)
					lowercase_					=      """ERROR"""
					lowercase_					=      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 ...utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_torch_available,
    is_transformers_available,
)


try:
      if not (is_transformers_available() and is_torch_available()):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
      from .multicontrolnet import MultiControlNetModel
      from .pipeline_controlnet import StableDiffusionControlNetPipeline
      from .pipeline_controlnet_imgaimg import StableDiffusionControlNetImgaImgPipeline
      from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline


if is_transformers_available() and is_flax_available():
      from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline






