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// Assumes: | |
// - input is (N, C, H, W) | |
// - gradOutput is (N, C, goH, goW) | |
// - gradWeight is (C, 1, kH, kW) --> (C, kH, kW) | |
// Naive Loop: No striding, padding, dilation handled | |
// These three loops would be parallelized, such that each is computed by a single block | |
for (int ch = 0; ch < C; ++ch) { | |
for (gw_h_offset = 0; gw_h_offset < kH; ++gw_h_offset) { | |
for (gw_w_offset = 0; gw_w_offset < kH; ++gw_w_offset) { | |
// Here is where the individual threads would compute their values, will need to be smart | |
// about the memory layout and ordering of these loops but I did not think about | |
// that here | |
float grad = 0.0; | |
for (bsz = 0; bsz < N; ++bsz) { | |
for (go_h_offset = 0; go_h_offset < goH; ++go_h_offset) { | |
for (go_w_offset = 0; go_w_offset < goW; ++go_w_offset) { | |
grad += input[bsz][ch][go_h_offset + gw_h_offset][go_w_offset + gw_w_offset] * | |
gradOutput[bsz][ch][go_h_offset][gw_w_offset]; | |
} | |
} | |
} | |
// At this point, we would do a blockwise reduction, but in the naive loop, we don't | |
// have to do this | |
gradWeight[ch][gw_h_offset][gw_w_offset] = grad; | |
} | |
} | |
} |
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