Batch Processing

Layer Input

The forward reshape layer accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.

Input ID

Input

data

Pointer to tensor of size n1 × n2 × ... × np that stores the input data for the forward reshape layer. This input can be an object of any class derived from Tensor.

Layer Parameters

For common parameters of neural network layers, see Common Parameters.

In addition to the common parameters, the forward reshape layer has the following parameters:

Parameter

Default Value

Description

reshapeDimensions

Not applicable

Collection of dimension sizes: m1, m2, ... , mq for the output Tensor.

Layer Output

The forward reshape layer calculates the result described below. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.

Result ID

Result

value

Pointer to tensor of size m1 × m2 × ... x mq that stores the result of the forward reshape layer. This input can be an object of any class derived from Tensor.

layerData

Collection of data needed for the backward reshape layer.

Element ID

Element

auxInputDimensions

Collection of integers that stores the dimension sizes of the input tensor in the forward computation step: n1, n2, ... np.

For more complete information about compiler optimizations, see our Optimization Notice.
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