tensorflow-fpga/doku/layer/conv2d.md

Zweidimensionale Konvolution

Tensorgröße

Input:

• in TF: [batchSize, imageY, imageX, channels]
• an FPGA: [imageY, imageX]

Kernel:

• in TF: [kernelY, kernelX, channels, outputChannels]
• an FPGA: [kernelY, kernelX]

Output:

• vom FPGA: [imageY2, imageX2]
• an TF: [batchSize, imageY2, imageX2, outputChannels]

Parallelisierung

1. Ohne FPGA-seitigem Speicher

   FPGA Recheneinheiten werden verteilt (batchSize * channels * outputChannels) Mal verwendet.

   for sample in range(batchSize):
     for outputChannel in range(outputChannels):
       output[sample][outputChannel] = sum([f(
         input[sample][channel], 
         kernel[channel][outputChannel]
       ) for channel in range(channels)])