Local Response Normalization Layer

Local Response Normalization Layer#

Local Response Normalization types and functions.

miopenLRNMode_t#

enum miopenLRNMode_t#

Local Response Normalization layer mode

Values:

enumerator miopenLRNWithinChannel#

Channel independent

enumerator miopenLRNCrossChannel#

Cross Channel

miopenCreateLRNDescriptor#

miopenStatus_t miopenCreateLRNDescriptor(miopenLRNDescriptor_t *lrnDesc)#

Creates a local response normalization (LRN) layer descriptor.

Parameters:

lrnDesc – Pointer to a local response normalization layer descriptor type

Returns:

miopenStatus_t

miopenSetLRNDescriptor#

miopenStatus_t miopenSetLRNDescriptor(const miopenLRNDescriptor_t lrnDesc, miopenLRNMode_t mode, unsigned int lrnN, double lrnAlpha, double lrnBeta, double lrnK)#

Sets a LRN layer descriptor details.

Sets all of the descriptor details for the LRN layer. The number of window elements lrnN is a diameter and always odd.

Parameters:

  • lrnDesc – Pointer to a LRN layer descriptor (output)

  • mode – LRN mode enum (input)

  • lrnN – Number of normalization window elements (input)

  • lrnAlpha – Scaling factor (input)

  • lrnBeta – Shift factor (input)

  • lrnK – K factor (input)

Returns:

miopenStatus_t

miopenGetLRNDescriptor#

miopenStatus_t miopenGetLRNDescriptor(const miopenLRNDescriptor_t lrnDesc, miopenLRNMode_t *mode, unsigned int *lrnN, double *lrnAlpha, double *lrnBeta, double *lrnK)#

Gets a LRN layer descriptor details.

Retrieve the LRN descriptor details.

Parameters:

  • lrnDesc – Pointer to a LRN layer descriptor (input)

  • mode – LRN mode enum (output)

  • lrnN – Number of normalization window elements (output)

  • lrnAlpha – Scaling factor (output)

  • lrnBeta – Shift factor (output)

  • lrnK – K factor (output)

Returns:

miopenStatus_t

miopenLRNGetWorkSpaceSize#

miopenStatus_t miopenLRNGetWorkSpaceSize(const miopenTensorDescriptor_t yDesc, size_t *workSpaceSize)#

Determine the workspace requirements.

This function determines the GPU memory allocation required to execute the LRN layer based on the LRN descriptor.

Parameters:

  • yDesc – Pointer to a LRN layer descriptor (input)

  • workSpaceSize – Output variable for workspace size (output)

Returns:

miopenStatus_t

miopenLRNForward#

miopenStatus_t miopenLRNForward(miopenHandle_t handle, const miopenLRNDescriptor_t lrnDesc, const void *alpha, const miopenTensorDescriptor_t xDesc, const void *x, const void *beta, const miopenTensorDescriptor_t yDesc, void *y, bool do_backward, void *workSpace)#

Execute a LRN forward layer.

Runs the forward layer normalization in the forward direction. If do_backward == 0, then set workSpace = nullptr and workSpaceSize = 0. However, if the user wishes to execute backwards, then they must set do_backwards = 1 in miopenLRNForward().

Parameters:

  • handle – MIOpen handle (input)

  • lrnDesc – Descriptor for LRN layer (input)

  • alpha – Floating point scaling factor, allocated on the host (input)

  • xDesc – Tensor descriptor for data input tensor x (input)

  • x – Data tensor x (input)

  • beta – Floating point shift factor, allocated on the host (input)

  • yDesc – Tensor descriptor for output data tensor y (input)

  • y – Data tensor y (output)

  • do_backward – Boolean to toggle save data in workspace for backwards pass (input)

  • workSpace – Pointer user allocated memory (input)

Returns:

miopenStatus_t

miopenLRNBackward#

miopenStatus_t miopenLRNBackward(miopenHandle_t handle, const miopenLRNDescriptor_t lrnDesc, const void *alpha, const miopenTensorDescriptor_t yDesc, const void *y, const miopenTensorDescriptor_t dyDesc, const void *dy, const miopenTensorDescriptor_t xDesc, const void *x, const void *beta, const miopenTensorDescriptor_t dxDesc, void *dx, const void *workSpace)#

Execute a LRN backward layer.

Parameters:

  • handle – MIOpen handle (input)

  • lrnDesc – Descriptor for LRN layer (input)

  • alpha – Floating point scaling factor, allocated on the host (input)

  • yDesc – Tensor descriptor for data input tensor y (input)

  • y – Data tensor y (input)

  • dyDesc – Tensor descriptor for data input tensor dy (input)

  • dy – Data delta tensor dy (input)

  • xDesc – Tensor descriptor for input data tensor x (input)

  • x – Data tensor x (input)

  • beta – Floating point shift factor, allocated on the host (input)

  • dxDesc – Tensor descriptor for output data tensor dx(input)

  • dx – Data delta tensor x (output)

  • workSpace – Pointer user allocated memory (input)

Returns:

miopenStatus_t

miopenDestroyLRNDescriptor#

miopenStatus_t miopenDestroyLRNDescriptor(miopenLRNDescriptor_t lrnDesc)#

Destroys the LRN descriptor object.

Parameters:

lrnDesc – LRN tensor descriptor type (input)

Returns:

miopenStatus_t

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