Method and system to support kernel division for transposed convolution for machine learning

A method, comprising:

• accepting and padding an input tensor with a number of zeros according to a set of padding parameters for a transposed convolution operation;
• accepting an original kernel for the transposed convolution operation and dividing the original kernel into a plurality of sub-kernels, wherein the original kernel corresponds to an output channel for the transposed convolution operation;
• performing a plurality of direct sub-convolutions by sequentially and directly applying each sub-kernel of the plurality of sub-kernels of the original kernel over the padded input tensor without flattening either the input tensor or the plurality of sub-kernels;
• and
• combining outputs of the plurality of direct sub-convolutions by the plurality of sub-kernels to form a complete output tensor for the transposed convolution operation for the output channel corresponding to the original kernel.

A system, comprising:

• a means for accepting and padding an input tensor with a number of zeros according to a set of padding parameters for a transposed convolution operation;
• a means for accepting an original kernel for the transposed convolution operation and dividing the original kernel into a plurality of sub-kernels, wherein the original kernel corresponds to an output channel for the transposed convolution operation;
• a means for performing a plurality of direct sub-convolutions by sequentially and directly applying each sub-kernel of the plurality of sub-kernels of the original kernel over the padded input tensor without flattening either the input tensor or the plurality of sub-kernels;
• and
• a means for combining outputs of the plurality of direct sub-convolutions by the plurality of sub-kernels to form a complete output tensor for the transposed convolution operation for the output channel corresponding to the original kernel.