

"""simple docstring"""




from typing import TYPE_CHECKING

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


a_         =      {
    'configuration_utils': ['GenerationConfig'],
    'streamers': ['TextIteratorStreamer', 'TextStreamer'],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_         =      [
			    'Constraint',
			    'ConstraintListState',
			    'DisjunctiveConstraint',
			    'PhrasalConstraint',
			]
			a_         =      [
			    'BeamHypotheses',
			    'BeamScorer',
			    'BeamSearchScorer',
			    'ConstrainedBeamSearchScorer',
			]
			a_         =      [
			    'EpsilonLogitsWarper',
			    'EtaLogitsWarper',
			    'ForcedBOSTokenLogitsProcessor',
			    'ForcedEOSTokenLogitsProcessor',
			    'HammingDiversityLogitsProcessor',
			    'InfNanRemoveLogitsProcessor',
			    'LogitsProcessor',
			    'LogitsProcessorList',
			    'LogitsWarper',
			    'MinLengthLogitsProcessor',
			    'MinNewTokensLengthLogitsProcessor',
			    'NoBadWordsLogitsProcessor',
			    'NoRepeatNGramLogitsProcessor',
			    'PrefixConstrainedLogitsProcessor',
			    'RepetitionPenaltyLogitsProcessor',
			    'SequenceBiasLogitsProcessor',
			    'EncoderRepetitionPenaltyLogitsProcessor',
			    'TemperatureLogitsWarper',
			    'TopKLogitsWarper',
			    'TopPLogitsWarper',
			    'TypicalLogitsWarper',
			    'EncoderNoRepeatNGramLogitsProcessor',
			    'ExponentialDecayLengthPenalty',
			    'LogitNormalization',
			]
			a_         =      [
			    'MaxNewTokensCriteria',
			    'MaxLengthCriteria',
			    'MaxTimeCriteria',
			    'StoppingCriteria',
			    'StoppingCriteriaList',
			    'validate_stopping_criteria',
			]
			a_         =      [
			    'GenerationMixin',
			    'top_k_top_p_filtering',
			    'GreedySearchEncoderDecoderOutput',
			    'GreedySearchDecoderOnlyOutput',
			    'SampleEncoderDecoderOutput',
			    'SampleDecoderOnlyOutput',
			    'BeamSearchEncoderDecoderOutput',
			    'BeamSearchDecoderOnlyOutput',
			    'BeamSampleEncoderDecoderOutput',
			    'BeamSampleDecoderOnlyOutput',
			    'ContrastiveSearchEncoderDecoderOutput',
			    'ContrastiveSearchDecoderOnlyOutput',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_         =      [
			    'TFForcedBOSTokenLogitsProcessor',
			    'TFForcedEOSTokenLogitsProcessor',
			    'TFLogitsProcessor',
			    'TFLogitsProcessorList',
			    'TFLogitsWarper',
			    'TFMinLengthLogitsProcessor',
			    'TFNoBadWordsLogitsProcessor',
			    'TFNoRepeatNGramLogitsProcessor',
			    'TFRepetitionPenaltyLogitsProcessor',
			    'TFTemperatureLogitsWarper',
			    'TFTopKLogitsWarper',
			    'TFTopPLogitsWarper',
			    'TFForceTokensLogitsProcessor',
			    'TFSuppressTokensAtBeginLogitsProcessor',
			    'TFSuppressTokensLogitsProcessor',
			]
			a_         =      [
			    'TFGenerationMixin',
			    'tf_top_k_top_p_filtering',
			    'TFGreedySearchDecoderOnlyOutput',
			    'TFGreedySearchEncoderDecoderOutput',
			    'TFSampleEncoderDecoderOutput',
			    'TFSampleDecoderOnlyOutput',
			    'TFBeamSearchEncoderDecoderOutput',
			    'TFBeamSearchDecoderOnlyOutput',
			    'TFBeamSampleEncoderDecoderOutput',
			    'TFBeamSampleDecoderOnlyOutput',
			    'TFContrastiveSearchEncoderDecoderOutput',
			    'TFContrastiveSearchDecoderOnlyOutput',
			]

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_         =      [
			    'FlaxForcedBOSTokenLogitsProcessor',
			    'FlaxForcedEOSTokenLogitsProcessor',
			    'FlaxLogitsProcessor',
			    'FlaxLogitsProcessorList',
			    'FlaxLogitsWarper',
			    'FlaxMinLengthLogitsProcessor',
			    'FlaxTemperatureLogitsWarper',
			    'FlaxTopKLogitsWarper',
			    'FlaxTopPLogitsWarper',
			]
			a_         =      [
			    'FlaxGenerationMixin',
			    'FlaxGreedySearchOutput',
			    'FlaxSampleOutput',
			    'FlaxBeamSearchOutput',
			]

if TYPE_CHECKING:
			from .configuration_utils import GenerationConfig
			from .streamers import TextIteratorStreamer, TextStreamer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .beam_constraints import Constraint, ConstraintListState, DisjunctiveConstraint, PhrasalConstraint
						from .beam_search import BeamHypotheses, BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
						from .logits_process import (
						    EncoderNoRepeatNGramLogitsProcessor,
						    EncoderRepetitionPenaltyLogitsProcessor,
						    EpsilonLogitsWarper,
						    EtaLogitsWarper,
						    ExponentialDecayLengthPenalty,
						    ForcedBOSTokenLogitsProcessor,
						    ForcedEOSTokenLogitsProcessor,
						    HammingDiversityLogitsProcessor,
						    InfNanRemoveLogitsProcessor,
						    LogitNormalization,
						    LogitsProcessor,
						    LogitsProcessorList,
						    LogitsWarper,
						    MinLengthLogitsProcessor,
						    MinNewTokensLengthLogitsProcessor,
						    NoBadWordsLogitsProcessor,
						    NoRepeatNGramLogitsProcessor,
						    PrefixConstrainedLogitsProcessor,
						    RepetitionPenaltyLogitsProcessor,
						    SequenceBiasLogitsProcessor,
						    TemperatureLogitsWarper,
						    TopKLogitsWarper,
						    TopPLogitsWarper,
						    TypicalLogitsWarper,
						)
						from .stopping_criteria import (
						    MaxLengthCriteria,
						    MaxNewTokensCriteria,
						    MaxTimeCriteria,
						    StoppingCriteria,
						    StoppingCriteriaList,
						    validate_stopping_criteria,
						)
						from .utils import (
						    BeamSampleDecoderOnlyOutput,
						    BeamSampleEncoderDecoderOutput,
						    BeamSearchDecoderOnlyOutput,
						    BeamSearchEncoderDecoderOutput,
						    ContrastiveSearchDecoderOnlyOutput,
						    ContrastiveSearchEncoderDecoderOutput,
						    GenerationMixin,
						    GreedySearchDecoderOnlyOutput,
						    GreedySearchEncoderDecoderOutput,
						    SampleDecoderOnlyOutput,
						    SampleEncoderDecoderOutput,
						    top_k_top_p_filtering,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tf_logits_process import (
						    TFForcedBOSTokenLogitsProcessor,
						    TFForcedEOSTokenLogitsProcessor,
						    TFForceTokensLogitsProcessor,
						    TFLogitsProcessor,
						    TFLogitsProcessorList,
						    TFLogitsWarper,
						    TFMinLengthLogitsProcessor,
						    TFNoBadWordsLogitsProcessor,
						    TFNoRepeatNGramLogitsProcessor,
						    TFRepetitionPenaltyLogitsProcessor,
						    TFSuppressTokensAtBeginLogitsProcessor,
						    TFSuppressTokensLogitsProcessor,
						    TFTemperatureLogitsWarper,
						    TFTopKLogitsWarper,
						    TFTopPLogitsWarper,
						)
						from .tf_utils import (
						    TFBeamSampleDecoderOnlyOutput,
						    TFBeamSampleEncoderDecoderOutput,
						    TFBeamSearchDecoderOnlyOutput,
						    TFBeamSearchEncoderDecoderOutput,
						    TFContrastiveSearchDecoderOnlyOutput,
						    TFContrastiveSearchEncoderDecoderOutput,
						    TFGenerationMixin,
						    TFGreedySearchDecoderOnlyOutput,
						    TFGreedySearchEncoderDecoderOutput,
						    TFSampleDecoderOnlyOutput,
						    TFSampleEncoderDecoderOutput,
						    tf_top_k_top_p_filtering,
						)

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .flax_logits_process import (
						    FlaxForcedBOSTokenLogitsProcessor,
						    FlaxForcedEOSTokenLogitsProcessor,
						    FlaxLogitsProcessor,
						    FlaxLogitsProcessorList,
						    FlaxLogitsWarper,
						    FlaxMinLengthLogitsProcessor,
						    FlaxTemperatureLogitsWarper,
						    FlaxTopKLogitsWarper,
						    FlaxTopPLogitsWarper,
						)
						from .flax_utils import FlaxBeamSearchOutput, FlaxGenerationMixin, FlaxGreedySearchOutput, FlaxSampleOutput
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()