MPSCNNBatchNormalizationStatisticsGradient(3)		 MetalPerformanceShaders.framework	     MPSCNNBatchNormalizationStatisticsGradient(3)

NAME

       MPSCNNBatchNormalizationStatisticsGradient

SYNOPSIS

       #import <MPSCNNBatchNormalization.h>

       Inherits MPSCNNGradientKernel.

   Instance Methods
       (void) - encodeBatchToCommandBuffer:sourceGradients:sourceImages:batchNormalizationState:
       (MPSImage *__nonnull) - encodeToCommandBuffer:sourceGradient:sourceImage:gradientState:
       (void) - encodeToCommandBuffer:sourceGradient:sourceImage:gradientState:destinationGradient:
       (MPSImageBatch *__nonnull) - encodeBatchToCommandBuffer:sourceGradients:sourceImages:gradientStates:

   Additional Inherited Members
Detailed Description
       This depends on Metal.framework	MPSCNNBatchNormalizationStatisticsGradient updates a MPSCNNBatchNormalizationState with the gradient of
       the loss function with respect to the batch statistics and batch normalization weights used to perform a batch normalization.

Method Documentation
   - (void) encodeBatchToCommandBuffer: (nonnull id< MTLCommandBuffer >) commandBuffer(MPSImageBatch *__nonnull) sourceGradients(MPSImageBatch
       *__nonnull) sourceImages(MPSCNNBatchNormalizationState *__nonnull) batchNormalizationState
       Encode this operation to a command buffer.

       Parameters:
	   commandBuffer The command buffer.
	   sourceGradients An MPSImageBatch containing the gradient of the loss function with respect to the results of batch normalization on the
	   source images.
	   sourceImages An MPSImageBatch containing the source images for batch normalization.
	   batchNormalizationState A valid MPSCNNBatchNormalizationState object which has been previously updated using a
	   MPSCNNBatchNormalizationStatistics kernel and the source images. Upon completion of the command buffer, will contain the (possibly
	   partially updated) gradients for the loss function with respect to the scale and bias parameters used to compute the batch
	   normalization. The state will be considered to be completely updated when all MPSImages in the training batch have been processed.

   - (MPSImageBatch*__nonnull) encodeBatchToCommandBuffer: (__nonnull id< MTLCommandBuffer >) commandBuffer(MPSImageBatch *__nonnull)
       sourceGradients(MPSImageBatch *__nonnull) sourceImages(MPSStateBatch *__nonnull) gradientStates
       Encode a gradient filter and return a gradient  During training, gradient filters are used to calculate the gradient associated with the
       loss for each feature channel in the forward pass source image. For those nodes that are trainable, these are then used to refine the value
       used in the trainable parameter. They consume a source gradient image which contains the gradients corresponding with the forward pass
       destination image, and calculate the gradients corresponding to the forward pass source image.

       A gradient filter consumes a MPSNNGradientState object which captured various forward pass properties such as offset and edgeMode at the
       time the forward pass was encoded. These are transferred to the MPSCNNBinaryKernel secondary image properties automatically when this
       method creates its destination image.

       Parameters:
	   commandBuffer The MTLCommandBuffer on which to encode
	   sourceGradients The gradient images from the 'next' filter in the graph
	   sourceImages The images used as source image from the forward pass
	   gradientStates The MPSNNGradientState or MPSNNBinaryGradientState subclass produced by the forward pass

       Reimplemented from MPSCNNGradientKernel.

   - (MPSImage*__nonnull) encodeToCommandBuffer: (__nonnull id< MTLCommandBuffer >) commandBuffer(MPSImage *__nonnull) sourceGradient(MPSImage
       *__nonnull) sourceImage(MPSState *__nonnull) gradientState
       Encode a gradient filter and return a gradient  During training, gradient filters are used to calculate the gradient associated with the
       loss for each feature channel in the forward pass source image. For those nodes that are trainable, these are then used to refine the value
       used in the trainable parameter. They consume a source gradient image which contains the gradients corresponding with the forward pass
       destination image, and calculate the gradients corresponding to the forward pass source image.

       A gradient filter consumes a MPSNNGradientState object which captured various forward pass properties such as offset and edgeMode at the
       time the forward pass was encoded. These are transferred to the MPSCNNBinaryKernel secondary image properties automatically when this
       method creates its destination image.

       Parameters:
	   commandBuffer The MTLCommandBuffer on which to encode
	   sourceGradient The gradient image from the 'next' filter in the graph (in the inference direction)
	   sourceImage The image used as source image by the forward inference pass
	   gradientState The MPSNNGradientState or MPSNNBinaryGradientState subclass produced by the forward inference pass

       Returns:
	   The result gradient from the gradient filter

       Reimplemented from MPSCNNGradientKernel.

   - (void) encodeToCommandBuffer: (__nonnull id< MTLCommandBuffer >) commandBuffer(MPSImage *__nonnull) sourceGradient(MPSImage *__nonnull)
       sourceImage(MPSState *__nonnull) gradientState(MPSImage *__nonnull) destinationGradient
       Encode a gradient filter and return a gradient  During training, gradient filters are used to calculate the gradient associated with the
       loss for each feature channel in the forward pass source image. For those nodes that are trainable, these are then used to refine the value
       used in the trainable parameter. They consume a source gradient image which contains the gradients corresponding with the forward pass
       destination image, and calculate the gradients corresponding to the forward pass source image.

       A gradient filter consumes a MPSNNGradientState object which captured various forward pass properties such as offset and edgeMode at the
       time the forward pass was encoded. These are transferred to the MPSCNNBinaryKernel secondary image properties automatically when you use
       -[MPSCNNGradientKernel destinationImageDescriptorForSourceImages:sourceStates:]. If you do not call this method, then you are responsible
       for configuring all of the primary and secondary image properties in MPSCNNBinaryKernel. Please see class description for expected ordering
       of operations.

       Parameters:
	   commandBuffer The MTLCommandBuffer on which to encode
	   sourceGradient The gradient image from the 'next' filter in the graph
	   sourceImage The image used as source image from the forward pass
	   gradientState The MPSNNGradientState and MPSNNBinaryGradientState subclass produced by the forward pass
	   destinationGradient The MPSImage into which to write the filter result

       Reimplemented from MPSCNNGradientKernel.

Author
       Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code.

Version MetalPerformanceShaders-100				  Thu Feb 8 2018		     MPSCNNBatchNormalizationStatisticsGradient(3)