<?xml version='1.0'?>
<!DOCTYPE signatures SYSTEM "file://localhost/System/Library/DTDs/BridgeSupport.dtd">
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<enum name='MLCActivationTypeThreshold' value64='17'/>
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<enum name='MLCArithmeticOperationSqrt' value64='7'/>
<enum name='MLCArithmeticOperationSubtract' value64='1'/>
<enum name='MLCArithmeticOperationTan' value64='11'/>
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<enum name='MLCComparisonOperationCount' value64='12'/>
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<enum name='MLCComparisonOperationLessOrEqual' value64='4'/>
<enum name='MLCComparisonOperationLogicalAND' value64='6'/>
<enum name='MLCComparisonOperationLogicalNAND' value64='9'/>
<enum name='MLCComparisonOperationLogicalNOR' value64='10'/>
<enum name='MLCComparisonOperationLogicalNOT' value64='8'/>
<enum name='MLCComparisonOperationLogicalOR' value64='7'/>
<enum name='MLCComparisonOperationLogicalXOR' value64='11'/>
<enum name='MLCComparisonOperationNotEqual' value64='1'/>
<enum name='MLCConvolutionTypeDepthwise' value64='2'/>
<enum name='MLCConvolutionTypeStandard' value64='0'/>
<enum name='MLCConvolutionTypeTransposed' value64='1'/>
<enum name='MLCDataTypeBoolean' value64='4'/>
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<enum name='MLCDataTypeFloat32' value64='1'/>
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<enum name='MLCDataTypeInt64' value64='5'/>
<enum name='MLCDataTypeInt8' value64='8'/>
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<enum name='MLCDeviceTypeGPU' value64='1'/>
<enum name='MLCExecutionOptionsForwardForInference' value64='8'/>
<enum name='MLCExecutionOptionsNone' value64='0'/>
<enum name='MLCExecutionOptionsPerLayerProfiling' value64='16'/>
<enum name='MLCExecutionOptionsProfiling' value64='4'/>
<enum name='MLCExecutionOptionsSkipWritingInputDataToDevice' value64='1'/>
<enum name='MLCExecutionOptionsSynchronous' value64='2'/>
<enum name='MLCGradientClippingTypeByGlobalNorm' value64='2'/>
<enum name='MLCGradientClippingTypeByNorm' value64='1'/>
<enum name='MLCGradientClippingTypeByValue' value64='0'/>
<enum name='MLCGraphCompilationOptionsComputeAllGradients' value64='8'/>
<enum name='MLCGraphCompilationOptionsDebugLayers' value64='1'/>
<enum name='MLCGraphCompilationOptionsDisableLayerFusion' value64='2'/>
<enum name='MLCGraphCompilationOptionsLinkGraphs' value64='4'/>
<enum name='MLCGraphCompilationOptionsNone' value64='0'/>
<enum name='MLCLSTMResultModeOutput' value64='0'/>
<enum name='MLCLSTMResultModeOutputAndStates' value64='1'/>
<enum name='MLCLossTypeCategoricalCrossEntropy' value64='4'/>
<enum name='MLCLossTypeCosineDistance' value64='7'/>
<enum name='MLCLossTypeCount' value64='9'/>
<enum name='MLCLossTypeHinge' value64='5'/>
<enum name='MLCLossTypeHuber' value64='6'/>
<enum name='MLCLossTypeLog' value64='8'/>
<enum name='MLCLossTypeMeanAbsoluteError' value64='0'/>
<enum name='MLCLossTypeMeanSquaredError' value64='1'/>
<enum name='MLCLossTypeSigmoidCrossEntropy' value64='3'/>
<enum name='MLCLossTypeSoftmaxCrossEntropy' value64='2'/>
<enum name='MLCPaddingPolicySame' value64='0'/>
<enum name='MLCPaddingPolicyUsePaddingSize' value64='2'/>
<enum name='MLCPaddingPolicyValid' value64='1'/>
<enum name='MLCPaddingTypeConstant' value64='3'/>
<enum name='MLCPaddingTypeReflect' value64='1'/>
<enum name='MLCPaddingTypeSymmetric' value64='2'/>
<enum name='MLCPaddingTypeZero' value64='0'/>
<enum name='MLCPoolingTypeAverage' value64='2'/>
<enum name='MLCPoolingTypeCount' value64='4'/>
<enum name='MLCPoolingTypeL2Norm' value64='3'/>
<enum name='MLCPoolingTypeMax' value64='1'/>
<enum name='MLCRandomInitializerTypeCount' value64='4'/>
<enum name='MLCRandomInitializerTypeGlorotUniform' value64='2'/>
<enum name='MLCRandomInitializerTypeInvalid' value64='0'/>
<enum name='MLCRandomInitializerTypeUniform' value64='1'/>
<enum name='MLCRandomInitializerTypeXavier' value64='3'/>
<enum name='MLCReductionTypeAll' value64='9'/>
<enum name='MLCReductionTypeAny' value64='8'/>
<enum name='MLCReductionTypeArgMax' value64='5'/>
<enum name='MLCReductionTypeArgMin' value64='6'/>
<enum name='MLCReductionTypeCount' value64='10'/>
<enum name='MLCReductionTypeL1Norm' value64='7'/>
<enum name='MLCReductionTypeMax' value64='3'/>
<enum name='MLCReductionTypeMean' value64='2'/>
<enum name='MLCReductionTypeMin' value64='4'/>
<enum name='MLCReductionTypeNone' value64='0'/>
<enum name='MLCReductionTypeSum' value64='1'/>
<enum name='MLCRegularizationTypeL1' value64='1'/>
<enum name='MLCRegularizationTypeL2' value64='2'/>
<enum name='MLCRegularizationTypeNone' value64='0'/>
<enum name='MLCSampleModeLinear' value64='1'/>
<enum name='MLCSampleModeNearest' value64='0'/>
<enum name='MLCSoftmaxOperationLogSoftmax' value64='1'/>
<enum name='MLCSoftmaxOperationSoftmax' value64='0'/>
<function name='MLCActivationTypeDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCArithmeticOperationDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCComparisonOperationDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCConvolutionTypeDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCGradientClippingTypeDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCLSTMResultModeDebugDescription'>
<arg type64='Q'/>
<retval type64='@'/>
</function>
<function name='MLCLossTypeDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCPaddingPolicyDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCPaddingTypeDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCPoolingTypeDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCReductionTypeDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCSampleModeDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<function name='MLCSoftmaxOperationDebugDescription'>
<arg type64='i'/>
<retval type64='@'/>
</function>
<class name='MLCAdamOptimizer'>
<method class_method='true' selector='optimizerWithDescriptor:beta1:beta2:epsilon:usesAMSGrad:timeStep:'>
<arg index='4' type64='B'/>
</method>
<method selector='usesAMSGrad'>
<retval type64='B'/>
</method>
</class>
<class name='MLCAdamWOptimizer'>
<method class_method='true' selector='optimizerWithDescriptor:beta1:beta2:epsilon:usesAMSGrad:timeStep:'>
<arg index='4' type64='B'/>
</method>
<method selector='usesAMSGrad'>
<retval type64='B'/>
</method>
</class>
<class name='MLCConvolutionDescriptor'>
<method selector='isConvolutionTranspose'>
<retval type64='B'/>
</method>
<method selector='usesDepthwiseConvolution'>
<retval type64='B'/>
</method>
</class>
<class name='MLCDevice'>
<method class_method='true' selector='deviceWithType:selectsMultipleComputeDevices:'>
<arg index='1' type64='B'/>
</method>
</class>
<class name='MLCEmbeddingDescriptor'>
<method class_method='true' selector='descriptorWithEmbeddingCount:embeddingDimension:paddingIndex:maximumNorm:pNorm:scalesGradientByFrequency:'>
<arg index='5' type64='B'/>
</method>
<method selector='scalesGradientByFrequency'>
<retval type64='B'/>
</method>
</class>
<class name='MLCGraph'>
<method selector='bindAndWriteData:forInputs:toDevice:batchSize:synchronous:'>
<arg index='4' type64='B'/>
<retval type64='B'/>
</method>
<method selector='bindAndWriteData:forInputs:toDevice:synchronous:'>
<arg index='3' type64='B'/>
<retval type64='B'/>
</method>
<method selector='nodeWithLayer:sources:disableUpdate:'>
<arg index='2' type64='B'/>
</method>
</class>
<class name='MLCInferenceGraph'>
<method selector='addInputs:'>
<retval type64='B'/>
</method>
<method selector='addInputs:lossLabels:lossLabelWeights:'>
<retval type64='B'/>
</method>
<method selector='addOutputs:'>
<retval type64='B'/>
</method>
<method selector='compileWithOptions:device:'>
<retval type64='B'/>
</method>
<method selector='compileWithOptions:device:inputTensors:inputTensorsData:'>
<retval type64='B'/>
</method>
<method selector='executeWithInputsData:batchSize:options:completionHandler:'>
<arg function_pointer='true' index='3' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeWithInputsData:lossLabelsData:lossLabelWeightsData:batchSize:options:completionHandler:'>
<arg function_pointer='true' index='5' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeWithInputsData:lossLabelsData:lossLabelWeightsData:outputsData:batchSize:options:completionHandler:'>
<arg function_pointer='true' index='6' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeWithInputsData:outputsData:batchSize:options:completionHandler:'>
<arg function_pointer='true' index='4' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='linkWithGraphs:'>
<retval type64='B'/>
</method>
</class>
<class name='MLCLSTMDescriptor'>
<method selector='batchFirst'>
<retval type64='B'/>
</method>
<method class_method='true' selector='descriptorWithInputSize:hiddenSize:layerCount:usesBiases:batchFirst:isBidirectional:dropout:'>
<arg index='3' type64='B'/>
<arg index='4' type64='B'/>
<arg index='5' type64='B'/>
</method>
<method class_method='true' selector='descriptorWithInputSize:hiddenSize:layerCount:usesBiases:batchFirst:isBidirectional:returnsSequences:dropout:'>
<arg index='3' type64='B'/>
<arg index='4' type64='B'/>
<arg index='5' type64='B'/>
<arg index='6' type64='B'/>
</method>
<method class_method='true' selector='descriptorWithInputSize:hiddenSize:layerCount:usesBiases:batchFirst:isBidirectional:returnsSequences:dropout:resultMode:'>
<arg index='3' type64='B'/>
<arg index='4' type64='B'/>
<arg index='5' type64='B'/>
<arg index='6' type64='B'/>
</method>
<method class_method='true' selector='descriptorWithInputSize:hiddenSize:layerCount:usesBiases:isBidirectional:dropout:'>
<arg index='3' type64='B'/>
<arg index='4' type64='B'/>
</method>
<method selector='isBidirectional'>
<retval type64='B'/>
</method>
<method selector='returnsSequences'>
<retval type64='B'/>
</method>
<method selector='usesBiases'>
<retval type64='B'/>
</method>
</class>
<class name='MLCLayer'>
<method selector='isDebuggingEnabled'>
<retval type64='B'/>
</method>
<method selector='setIsDebuggingEnabled:'>
<arg index='0' type64='B'/>
</method>
<method class_method='true' selector='supportsDataType:onDevice:'>
<retval type64='B'/>
</method>
</class>
<class name='MLCMatMulDescriptor'>
<method class_method='true' selector='descriptorWithAlpha:transposesX:transposesY:'>
<arg index='1' type64='B'/>
<arg index='2' type64='B'/>
</method>
<method selector='transposesX'>
<retval type64='B'/>
</method>
<method selector='transposesY'>
<retval type64='B'/>
</method>
</class>
<class name='MLCMultiheadAttentionDescriptor'>
<method selector='addsZeroAttention'>
<retval type64='B'/>
</method>
<method class_method='true' selector='descriptorWithModelDimension:keyDimension:valueDimension:headCount:dropout:hasBiases:hasAttentionBiases:addsZeroAttention:'>
<arg index='5' type64='B'/>
<arg index='6' type64='B'/>
<arg index='7' type64='B'/>
</method>
<method selector='hasAttentionBiases'>
<retval type64='B'/>
</method>
<method selector='hasBiases'>
<retval type64='B'/>
</method>
</class>
<class name='MLCOptimizer'>
<method selector='appliesGradientClipping'>
<retval type64='B'/>
</method>
<method selector='setAppliesGradientClipping:'>
<arg index='0' type64='B'/>
</method>
</class>
<class name='MLCOptimizerDescriptor'>
<method selector='appliesGradientClipping'>
<retval type64='B'/>
</method>
<method class_method='true' selector='descriptorWithLearningRate:gradientRescale:appliesGradientClipping:gradientClipMax:gradientClipMin:regularizationType:regularizationScale:'>
<arg index='2' type64='B'/>
</method>
<method class_method='true' selector='descriptorWithLearningRate:gradientRescale:appliesGradientClipping:gradientClippingType:gradientClipMax:gradientClipMin:maximumClippingNorm:customGlobalNorm:regularizationType:regularizationScale:'>
<arg index='2' type64='B'/>
</method>
</class>
<class name='MLCPoolingDescriptor'>
<method class_method='true' selector='averagePoolingDescriptorWithKernelSizes:strides:dilationRates:paddingPolicy:paddingSizes:countIncludesPadding:'>
<arg index='5' type64='B'/>
</method>
<method class_method='true' selector='averagePoolingDescriptorWithKernelSizes:strides:paddingPolicy:paddingSizes:countIncludesPadding:'>
<arg index='4' type64='B'/>
</method>
<method selector='countIncludesPadding'>
<retval type64='B'/>
</method>
</class>
<class name='MLCRMSPropOptimizer'>
<method selector='isCentered'>
<retval type64='B'/>
</method>
<method class_method='true' selector='optimizerWithDescriptor:momentumScale:alpha:epsilon:isCentered:'>
<arg index='4' type64='B'/>
</method>
</class>
<class name='MLCSGDOptimizer'>
<method class_method='true' selector='optimizerWithDescriptor:momentumScale:usesNesterovMomentum:'>
<arg index='2' type64='B'/>
</method>
<method selector='usesNesterovMomentum'>
<retval type64='B'/>
</method>
</class>
<class name='MLCTensor'>
<method selector='bindAndWriteData:toDevice:'>
<retval type64='B'/>
</method>
<method selector='bindOptimizerData:deviceData:'>
<retval type64='B'/>
</method>
<method selector='copyDataFromDeviceMemoryToBytes:length:synchronizeWithDevice:'>
<arg index='2' type64='B'/>
<retval type64='B'/>
</method>
<method selector='hasValidNumerics'>
<retval type64='B'/>
</method>
<method selector='synchronizeData'>
<retval type64='B'/>
</method>
<method selector='synchronizeOptimizerData'>
<retval type64='B'/>
</method>
<method class_method='true' selector='tensorWithSequenceLengths:sortedSequences:featureChannelCount:batchSize:data:'>
<arg index='1' type64='B'/>
</method>
<method class_method='true' selector='tensorWithSequenceLengths:sortedSequences:featureChannelCount:batchSize:randomInitializerType:'>
<arg index='1' type64='B'/>
</method>
</class>
<class name='MLCTensorData'>
<method class_method='true' selector='dataWithBytesNoCopy:length:deallocator:'>
<arg function_pointer='true' index='2' type64='@?'>
<arg type64='^v'/>
<arg type64='Q'/>
<retval type64='v'/>
</arg>
</method>
</class>
<class name='MLCTensorDescriptor'>
<method class_method='true' selector='descriptorWithShape:sequenceLengths:sortedSequences:dataType:'>
<arg index='2' type64='B'/>
</method>
<method selector='sortedSequences'>
<retval type64='B'/>
</method>
</class>
<class name='MLCTensorParameter'>
<method selector='isUpdatable'>
<retval type64='B'/>
</method>
<method selector='setIsUpdatable:'>
<arg index='0' type64='B'/>
</method>
</class>
<class name='MLCTrainingGraph'>
<method selector='addInputs:lossLabels:'>
<retval type64='B'/>
</method>
<method selector='addInputs:lossLabels:lossLabelWeights:'>
<retval type64='B'/>
</method>
<method selector='addOutputs:'>
<retval type64='B'/>
</method>
<method selector='bindOptimizerData:deviceData:withTensor:'>
<retval type64='B'/>
</method>
<method selector='compileOptimizer:'>
<retval type64='B'/>
</method>
<method selector='compileWithOptions:device:'>
<retval type64='B'/>
</method>
<method selector='compileWithOptions:device:inputTensors:inputTensorsData:'>
<retval type64='B'/>
</method>
<method selector='executeForwardWithBatchSize:options:completionHandler:'>
<arg function_pointer='true' index='2' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeForwardWithBatchSize:options:outputsData:completionHandler:'>
<arg function_pointer='true' index='3' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeGradientWithBatchSize:options:completionHandler:'>
<arg function_pointer='true' index='2' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeGradientWithBatchSize:options:outputsData:completionHandler:'>
<arg function_pointer='true' index='3' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeOptimizerUpdateWithOptions:completionHandler:'>
<arg function_pointer='true' index='1' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeWithInputsData:lossLabelsData:lossLabelWeightsData:batchSize:options:completionHandler:'>
<arg function_pointer='true' index='5' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='executeWithInputsData:lossLabelsData:lossLabelWeightsData:outputsData:batchSize:options:completionHandler:'>
<arg function_pointer='true' index='6' type64='@?'>
<arg type64='@'/>
<arg type64='@'/>
<arg type64='d'/>
<retval type64='v'/>
</arg>
<retval type64='B'/>
</method>
<method selector='linkWithGraphs:'>
<retval type64='B'/>
</method>
<method selector='setTrainingTensorParameters:'>
<retval type64='B'/>
</method>
<method selector='stopGradientForTensors:'>
<retval type64='B'/>
</method>
</class>
<class name='MLCUpsampleLayer'>
<method selector='alignsCorners'>
<retval type64='B'/>
</method>
<method class_method='true' selector='layerWithShape:sampleMode:alignsCorners:'>
<arg index='2' type64='B'/>
</method>
</class>
<class name='MLCYOLOLossDescriptor'>
<method selector='setShouldRescore:'>
<arg index='0' type64='B'/>
</method>
<method selector='shouldRescore'>
<retval type64='B'/>
</method>
</class>
</signatures>
