


"""simple docstring"""






import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs


class 			lowerCamelCase_		(			__lowerCAmelCase   ):





				"""simple docstring"""







				def __init__(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__=None       ,		UpperCAmelCase__=True       ,		UpperCAmelCase__=None       ,		**UpperCAmelCase__     ):
								SCREAMING_SNAKE_CASE__     							=				parent
								SCREAMING_SNAKE_CASE__     							=				config_class
								SCREAMING_SNAKE_CASE__     							=				has_text_modality
								SCREAMING_SNAKE_CASE__     							=				kwargs
								SCREAMING_SNAKE_CASE__     							=				common_properties



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.config_class(**self.inputs_dict     )
								SCREAMING_SNAKE_CASE__     							=				(
								    ['''hidden_size''', '''num_attention_heads''', '''num_hidden_layers''']
								    if self.common_properties is None
								    else self.common_properties
								)

								# Add common fields for text models
								if self.has_text_modality:
												common_properties.extend(["vocab_size"]     )

								# Test that config has the common properties as getters
								for prop in common_properties:
												self.parent.assertTrue(hasattr(lowerCamelCase__       ,		lowerCamelCase__     )       ,		msg=f'''`{prop}` does not exist'''     )

								# Test that config has the common properties as setter
								for idx, name in enumerate(lowerCamelCase__     ):
												try:
																setattr(lowerCamelCase__       ,		lowerCamelCase__       ,		lowerCamelCase__     )
																self.parent.assertEqual(
																    getattr(lowerCamelCase__       ,		lowerCamelCase__     )       ,		lowerCamelCase__       ,		msg=f'''`{name} value {idx} expected, but was {getattr(lowerCamelCase__       ,		lowerCamelCase__     )}'''     )
												except NotImplementedError:
																# Some models might not be able to implement setters for common_properties
																# In that case, a NotImplementedError is raised
																pass

																# Test if config class can be called with Config(prop_name=..)
								for idx, name in enumerate(lowerCamelCase__     ):
												try:
																SCREAMING_SNAKE_CASE__     							=				self.config_class(**{name: idx}     )
																self.parent.assertEqual(
																    getattr(lowerCamelCase__       ,		lowerCamelCase__     )       ,		lowerCamelCase__       ,		msg=f'''`{name} value {idx} expected, but was {getattr(lowerCamelCase__       ,		lowerCamelCase__     )}'''     )
												except NotImplementedError:
																# Some models might not be able to implement setters for common_properties
																# In that case, a NotImplementedError is raised
																pass



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.config_class(**self.inputs_dict     )
								SCREAMING_SNAKE_CASE__     							=				json.loads(config.to_json_string()     )
								for key, value in self.inputs_dict.items():
												self.parent.assertEqual(obj[key]       ,		lowerCamelCase__     )



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.config_class(**self.inputs_dict     )

								with tempfile.TemporaryDirectory() as tmpdirname:
												SCREAMING_SNAKE_CASE__     							=				os.path.join(lowerCamelCase__       ,		"config.json"     )
												config_first.to_json_file(lowerCamelCase__     )
												SCREAMING_SNAKE_CASE__     							=				self.config_class.from_json_file(lowerCamelCase__     )

								self.parent.assertEqual(config_second.to_dict()       ,		config_first.to_dict()     )



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.config_class(**self.inputs_dict     )

								with tempfile.TemporaryDirectory() as tmpdirname:
												config_first.save_pretrained(lowerCamelCase__     )
												SCREAMING_SNAKE_CASE__     							=				self.config_class.from_pretrained(lowerCamelCase__     )

								self.parent.assertEqual(config_second.to_dict()       ,		config_first.to_dict()     )



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.config_class(**self.inputs_dict     )

								SCREAMING_SNAKE_CASE__     							=				'''test'''
								with tempfile.TemporaryDirectory() as tmpdirname:
												SCREAMING_SNAKE_CASE__     							=				os.path.join(lowerCamelCase__       ,		lowerCamelCase__     )
												config_first.save_pretrained(lowerCamelCase__     )
												SCREAMING_SNAKE_CASE__     							=				self.config_class.from_pretrained(lowerCamelCase__       ,		subfolder=lowerCamelCase__     )

								self.parent.assertEqual(config_second.to_dict()       ,		config_first.to_dict()     )



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.config_class(**self.inputs_dict       ,		num_labels=5     )
								self.parent.assertEqual(len(config.idalabel     )       ,		5     )
								self.parent.assertEqual(len(config.labelaid     )       ,		5     )

								SCREAMING_SNAKE_CASE__     							=				3
								self.parent.assertEqual(len(config.idalabel     )       ,		3     )
								self.parent.assertEqual(len(config.labelaid     )       ,		3     )



				def   lowerCAmelCase__		(						self     ):






								if self.config_class.is_composition:
												return
								SCREAMING_SNAKE_CASE__     							=				self.config_class()
								self.parent.assertIsNotNone(lowerCamelCase__     )



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				copy.deepcopy(lowerCamelCase__     )
								SCREAMING_SNAKE_CASE__     							=				self.config_class(**lowerCamelCase__     )
								SCREAMING_SNAKE_CASE__     							=				[]
								for key, value in config_common_kwargs.items():
												if key == "torch_dtype":
																if not is_torch_available():
																				continue
																else:
																				import torch

																				if config.torch_dtype != torch.floataa:
																								wrong_values.append(("torch_dtype", config.torch_dtype, torch.floataa)     )
												elif getattr(lowerCamelCase__       ,		lowerCamelCase__     ) != value:
																wrong_values.append((key, getattr(lowerCamelCase__       ,		lowerCamelCase__     ), value)     )

								if len(lowerCamelCase__     ) > 0:
												SCREAMING_SNAKE_CASE__     							=				'''\n'''.join([f'''- {v[0]}: got {v[1]} instead of {v[2]}''' for v in wrong_values]     )
												raise ValueError(f'''The following keys were not properly set in the config:\n{errors}'''     )






				def   lowerCAmelCase__		(						self     ):
								self.create_and_test_config_common_properties()
								self.create_and_test_config_to_json_string()
								self.create_and_test_config_to_json_file()
								self.create_and_test_config_from_and_save_pretrained()
								self.create_and_test_config_from_and_save_pretrained_subfolder()
								self.create_and_test_config_with_num_labels()
								self.check_config_can_be_init_without_params()
								self.check_config_arguments_init()




"""simple docstring"""






from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase     =  {
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase     =  [
	    'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'AutoformerForPrediction',
	    'AutoformerModel',
	    'AutoformerPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_autoformer import (
	    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    AutoformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_autoformer import (
		    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    AutoformerForPrediction,
		    AutoformerModel,
		    AutoformerPreTrainedModel,
		)

else:
	import sys

	_lowerCamelCase     =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
