2D Convolution layer operation - average pooling 2d
input (NUMERIC) - the input to average pooling 2d operation - 4d CNN (image) activations in NCHW format (shape [minibatch, channels, height, width]) or NHWC format (shape [minibatch, height, width, channels])
Pooling2DConfig - see Pooling2DConfig
3D convolution layer operation - average pooling 3d
input (NUMERIC) - the input to average pooling 3d operation - 5d activations in NCDHW format (shape [minibatch, channels, depth, height, width]) or NDHWC format (shape [minibatch, depth, height, width, channels])
Pooling3DConfig - see Pooling3DConfig
Convolution 2d layer batch to space operation on 4d input.
Reduces input batch dimension by rearranging data into a larger spatial dimensions
x (NUMERIC) - Input variable. 4d input
blocks - Block size, in the height/width dimension (Size: Exactly(count=2))
croppingTop - (Size: Exactly(count=2))
croppingBottom - (Size: Exactly(count=2))
col2im operation for use in 2D convolution operations. Outputs a 4d array with shape
[minibatch, inputChannels, height, width]
in (NUMERIC) - Input - rank 6 input with shape [minibatch, inputChannels, kernelHeight, kernelWidth, outputHeight, outputWidth]
Conv2DConfig - see Conv2DConfig