

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


a_         =      {
    'auto_factory': ['get_values'],
    'configuration_auto': ['ALL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CONFIG_MAPPING', 'MODEL_NAMES_MAPPING', 'AutoConfig'],
    'feature_extraction_auto': ['FEATURE_EXTRACTOR_MAPPING', 'AutoFeatureExtractor'],
    'image_processing_auto': ['IMAGE_PROCESSOR_MAPPING', 'AutoImageProcessor'],
    'processing_auto': ['PROCESSOR_MAPPING', 'AutoProcessor'],
    'tokenization_auto': ['TOKENIZER_MAPPING', 'AutoTokenizer'],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_         =      [
			    'MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING',
			    'MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING',
			    'MODEL_FOR_AUDIO_XVECTOR_MAPPING',
			    'MODEL_FOR_BACKBONE_MAPPING',
			    'MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING',
			    'MODEL_FOR_CAUSAL_LM_MAPPING',
			    'MODEL_FOR_CTC_MAPPING',
			    'MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING',
			    'MODEL_FOR_DEPTH_ESTIMATION_MAPPING',
			    'MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING',
			    'MODEL_FOR_IMAGE_SEGMENTATION_MAPPING',
			    'MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING',
			    'MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING',
			    'MODEL_FOR_MASKED_LM_MAPPING',
			    'MODEL_FOR_MASK_GENERATION_MAPPING',
			    'MODEL_FOR_MULTIPLE_CHOICE_MAPPING',
			    'MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING',
			    'MODEL_FOR_OBJECT_DETECTION_MAPPING',
			    'MODEL_FOR_PRETRAINING_MAPPING',
			    'MODEL_FOR_QUESTION_ANSWERING_MAPPING',
			    'MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING',
			    'MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING',
			    'MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING',
			    'MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING',
			    'MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING',
			    'MODEL_FOR_TEXT_ENCODING_MAPPING',
			    'MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING',
			    'MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING',
			    'MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING',
			    'MODEL_FOR_VISION_2_SEQ_MAPPING',
			    'MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING',
			    'MODEL_MAPPING',
			    'MODEL_WITH_LM_HEAD_MAPPING',
			    'MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING',
			    'MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING',
			    'AutoModel',
			    'AutoBackbone',
			    'AutoModelForAudioClassification',
			    'AutoModelForAudioFrameClassification',
			    'AutoModelForAudioXVector',
			    'AutoModelForCausalLM',
			    'AutoModelForCTC',
			    'AutoModelForDepthEstimation',
			    'AutoModelForImageClassification',
			    'AutoModelForImageSegmentation',
			    'AutoModelForInstanceSegmentation',
			    'AutoModelForMaskGeneration',
			    'AutoModelForTextEncoding',
			    'AutoModelForMaskedImageModeling',
			    'AutoModelForMaskedLM',
			    'AutoModelForMultipleChoice',
			    'AutoModelForNextSentencePrediction',
			    'AutoModelForObjectDetection',
			    'AutoModelForPreTraining',
			    'AutoModelForQuestionAnswering',
			    'AutoModelForSemanticSegmentation',
			    'AutoModelForSeq2SeqLM',
			    'AutoModelForSequenceClassification',
			    'AutoModelForSpeechSeq2Seq',
			    'AutoModelForTableQuestionAnswering',
			    'AutoModelForTokenClassification',
			    'AutoModelForUniversalSegmentation',
			    'AutoModelForVideoClassification',
			    'AutoModelForVision2Seq',
			    'AutoModelForVisualQuestionAnswering',
			    'AutoModelForDocumentQuestionAnswering',
			    'AutoModelWithLMHead',
			    'AutoModelForZeroShotImageClassification',
			    'AutoModelForZeroShotObjectDetection',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_         =      [
			    'TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING',
			    'TF_MODEL_FOR_CAUSAL_LM_MAPPING',
			    'TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING',
			    'TF_MODEL_FOR_MASK_GENERATION_MAPPING',
			    'TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING',
			    'TF_MODEL_FOR_MASKED_LM_MAPPING',
			    'TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING',
			    'TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING',
			    'TF_MODEL_FOR_PRETRAINING_MAPPING',
			    'TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING',
			    'TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING',
			    'TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING',
			    'TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING',
			    'TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING',
			    'TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING',
			    'TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING',
			    'TF_MODEL_FOR_TEXT_ENCODING_MAPPING',
			    'TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING',
			    'TF_MODEL_FOR_VISION_2_SEQ_MAPPING',
			    'TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING',
			    'TF_MODEL_MAPPING',
			    'TF_MODEL_WITH_LM_HEAD_MAPPING',
			    'TFAutoModel',
			    'TFAutoModelForAudioClassification',
			    'TFAutoModelForCausalLM',
			    'TFAutoModelForImageClassification',
			    'TFAutoModelForMaskedImageModeling',
			    'TFAutoModelForMaskedLM',
			    'TFAutoModelForMaskGeneration',
			    'TFAutoModelForMultipleChoice',
			    'TFAutoModelForNextSentencePrediction',
			    'TFAutoModelForPreTraining',
			    'TFAutoModelForDocumentQuestionAnswering',
			    'TFAutoModelForQuestionAnswering',
			    'TFAutoModelForSemanticSegmentation',
			    'TFAutoModelForSeq2SeqLM',
			    'TFAutoModelForSequenceClassification',
			    'TFAutoModelForSpeechSeq2Seq',
			    'TFAutoModelForTableQuestionAnswering',
			    'TFAutoModelForTextEncoding',
			    'TFAutoModelForTokenClassification',
			    'TFAutoModelForVision2Seq',
			    'TFAutoModelForZeroShotImageClassification',
			    'TFAutoModelWithLMHead',
			]

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_         =      [
			    'FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING',
			    'FLAX_MODEL_FOR_CAUSAL_LM_MAPPING',
			    'FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING',
			    'FLAX_MODEL_FOR_MASKED_LM_MAPPING',
			    'FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING',
			    'FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING',
			    'FLAX_MODEL_FOR_PRETRAINING_MAPPING',
			    'FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING',
			    'FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING',
			    'FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING',
			    'FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING',
			    'FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING',
			    'FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING',
			    'FLAX_MODEL_MAPPING',
			    'FlaxAutoModel',
			    'FlaxAutoModelForCausalLM',
			    'FlaxAutoModelForImageClassification',
			    'FlaxAutoModelForMaskedLM',
			    'FlaxAutoModelForMultipleChoice',
			    'FlaxAutoModelForNextSentencePrediction',
			    'FlaxAutoModelForPreTraining',
			    'FlaxAutoModelForQuestionAnswering',
			    'FlaxAutoModelForSeq2SeqLM',
			    'FlaxAutoModelForSequenceClassification',
			    'FlaxAutoModelForSpeechSeq2Seq',
			    'FlaxAutoModelForTokenClassification',
			    'FlaxAutoModelForVision2Seq',
			]


if TYPE_CHECKING:
			from .auto_factory import get_values
			from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, CONFIG_MAPPING, MODEL_NAMES_MAPPING, AutoConfig
			from .feature_extraction_auto import FEATURE_EXTRACTOR_MAPPING, AutoFeatureExtractor
			from .image_processing_auto import IMAGE_PROCESSOR_MAPPING, AutoImageProcessor
			from .processing_auto import PROCESSOR_MAPPING, AutoProcessor
			from .tokenization_auto import TOKENIZER_MAPPING, AutoTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_auto import (
						    MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
						    MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING,
						    MODEL_FOR_AUDIO_XVECTOR_MAPPING,
						    MODEL_FOR_BACKBONE_MAPPING,
						    MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING,
						    MODEL_FOR_CAUSAL_LM_MAPPING,
						    MODEL_FOR_CTC_MAPPING,
						    MODEL_FOR_DEPTH_ESTIMATION_MAPPING,
						    MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
						    MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
						    MODEL_FOR_IMAGE_SEGMENTATION_MAPPING,
						    MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING,
						    MODEL_FOR_MASK_GENERATION_MAPPING,
						    MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
						    MODEL_FOR_MASKED_LM_MAPPING,
						    MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
						    MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
						    MODEL_FOR_OBJECT_DETECTION_MAPPING,
						    MODEL_FOR_PRETRAINING_MAPPING,
						    MODEL_FOR_QUESTION_ANSWERING_MAPPING,
						    MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
						    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
						    MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
						    MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
						    MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
						    MODEL_FOR_TEXT_ENCODING_MAPPING,
						    MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
						    MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING,
						    MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING,
						    MODEL_FOR_VISION_2_SEQ_MAPPING,
						    MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING,
						    MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
						    MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING,
						    MODEL_MAPPING,
						    MODEL_WITH_LM_HEAD_MAPPING,
						    AutoBackbone,
						    AutoModel,
						    AutoModelForAudioClassification,
						    AutoModelForAudioFrameClassification,
						    AutoModelForAudioXVector,
						    AutoModelForCausalLM,
						    AutoModelForCTC,
						    AutoModelForDepthEstimation,
						    AutoModelForDocumentQuestionAnswering,
						    AutoModelForImageClassification,
						    AutoModelForImageSegmentation,
						    AutoModelForInstanceSegmentation,
						    AutoModelForMaskedImageModeling,
						    AutoModelForMaskedLM,
						    AutoModelForMaskGeneration,
						    AutoModelForMultipleChoice,
						    AutoModelForNextSentencePrediction,
						    AutoModelForObjectDetection,
						    AutoModelForPreTraining,
						    AutoModelForQuestionAnswering,
						    AutoModelForSemanticSegmentation,
						    AutoModelForSeqaSeqLM,
						    AutoModelForSequenceClassification,
						    AutoModelForSpeechSeqaSeq,
						    AutoModelForTableQuestionAnswering,
						    AutoModelForTextEncoding,
						    AutoModelForTokenClassification,
						    AutoModelForUniversalSegmentation,
						    AutoModelForVideoClassification,
						    AutoModelForVisionaSeq,
						    AutoModelForVisualQuestionAnswering,
						    AutoModelForZeroShotImageClassification,
						    AutoModelForZeroShotObjectDetection,
						    AutoModelWithLMHead,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_auto import (
						    TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
						    TF_MODEL_FOR_CAUSAL_LM_MAPPING,
						    TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
						    TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
						    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
						    TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
						    TF_MODEL_FOR_MASKED_LM_MAPPING,
						    TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
						    TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
						    TF_MODEL_FOR_PRETRAINING_MAPPING,
						    TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
						    TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
						    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
						    TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
						    TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
						    TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
						    TF_MODEL_FOR_TEXT_ENCODING_MAPPING,
						    TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
						    TF_MODEL_FOR_VISION_2_SEQ_MAPPING,
						    TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
						    TF_MODEL_MAPPING,
						    TF_MODEL_WITH_LM_HEAD_MAPPING,
						    TFAutoModel,
						    TFAutoModelForAudioClassification,
						    TFAutoModelForCausalLM,
						    TFAutoModelForDocumentQuestionAnswering,
						    TFAutoModelForImageClassification,
						    TFAutoModelForMaskedImageModeling,
						    TFAutoModelForMaskedLM,
						    TFAutoModelForMaskGeneration,
						    TFAutoModelForMultipleChoice,
						    TFAutoModelForNextSentencePrediction,
						    TFAutoModelForPreTraining,
						    TFAutoModelForQuestionAnswering,
						    TFAutoModelForSemanticSegmentation,
						    TFAutoModelForSeqaSeqLM,
						    TFAutoModelForSequenceClassification,
						    TFAutoModelForSpeechSeqaSeq,
						    TFAutoModelForTableQuestionAnswering,
						    TFAutoModelForTextEncoding,
						    TFAutoModelForTokenClassification,
						    TFAutoModelForVisionaSeq,
						    TFAutoModelForZeroShotImageClassification,
						    TFAutoModelWithLMHead,
						)

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_auto import (
						    FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
						    FLAX_MODEL_FOR_CAUSAL_LM_MAPPING,
						    FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
						    FLAX_MODEL_FOR_MASKED_LM_MAPPING,
						    FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
						    FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
						    FLAX_MODEL_FOR_PRETRAINING_MAPPING,
						    FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
						    FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
						    FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
						    FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
						    FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
						    FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING,
						    FLAX_MODEL_MAPPING,
						    FlaxAutoModel,
						    FlaxAutoModelForCausalLM,
						    FlaxAutoModelForImageClassification,
						    FlaxAutoModelForMaskedLM,
						    FlaxAutoModelForMultipleChoice,
						    FlaxAutoModelForNextSentencePrediction,
						    FlaxAutoModelForPreTraining,
						    FlaxAutoModelForQuestionAnswering,
						    FlaxAutoModelForSeqaSeqLM,
						    FlaxAutoModelForSequenceClassification,
						    FlaxAutoModelForSpeechSeqaSeq,
						    FlaxAutoModelForTokenClassification,
						    FlaxAutoModelForVisionaSeq,
						)

else:
			import sys

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


import math
import os

import cva
import numpy as np

a_         =      255.0

def 	lowerCamelCase__	(   _a							,     _a):
	SCREAMING_SNAKE_CASE				: Optional[int]			       =    np.mean((original - contrast) ** 2)
	if mse == 0:
		return 100

	return 20 * math.logaa(PIXEL_MAX / math.sqrt(_a))

def 	lowerCamelCase__	(   ):
	SCREAMING_SNAKE_CASE				: List[Any]			       =    os.path.dirname(os.path.realpath(_a))
	# Loading images (original image and compressed image)
	SCREAMING_SNAKE_CASE				: Any			       =    cva.imread(os.path.join(_a							,     "image_data/original_image.png"))
	SCREAMING_SNAKE_CASE				: List[str]			       =    cva.imread(os.path.join(_a							,     "image_data/compressed_image.png")							,     1)

	SCREAMING_SNAKE_CASE				: List[Any]			       =    cva.imread(os.path.join(_a							,     "image_data/PSNR-example-base.png"))
	SCREAMING_SNAKE_CASE				: List[str]			       =    cva.imread(
	    os.path.join(_a							,     "image_data/PSNR-example-comp-10.jpg")							,     1)

	# Value expected: 29.73dB
	print("-- First Test --")
	print(f"PSNR value is {peak_signal_to_noise_ratio(_a							,     _a)} dB")

	# # Value expected: 31.53dB (Wikipedia Example)
	print("\n-- Second Test --")
	print(f"PSNR value is {peak_signal_to_noise_ratio(_a							,     _a)} dB")


if __name__ == "__main__":
			main()