Python convWeightActs Examples

Example #1

File: layer.py Project: phecy/striate

 def bprop(self, grad, input, output, outGrad):
   cudaconv2.convImgActs(grad, self.weight, outGrad, self.imgSize, self.imgSize,
       self.outputSize, -self.padding, self.stride, self.numColor, 1, 0.0, 1.0)
   # bprop weight
   self.weightGrad.fill(0)
   cudaconv2.convWeightActs(input, grad, self.weightGrad, self.imgSize, self.outputSize,
       self.outputSize, self.filterSize, -self.padding, self.stride, self.numColor, 1, 0, 0, 1)
   # bprop bias
   self.biasGrad.fill(0)
   gpu_copy_to(grad, self.tmp)
   add_row_sum_to_vec(self.biasGrad, self.tmp)

Example #2

File: __init__.py Project: allenbo/distnet

def convWeightActs(input, ingrad, weight_grad, bias_grad, padding, stride, color, *args):
  image_y = input.shape[ConvDataLayout.HEIGHT]
  output_y =  ingrad.shape[ConvDataLayout.HEIGHT]
  output_x =  ingrad.shape[ConvDataLayout.WIDTH]
  filter_size =  weight_grad.shape[FilterLayout.HEIGHT]
  color = input.shape[ConvDataLayout.CHANNEL]
  cudaconv2.convWeightActs(input, ingrad, weight_grad, image_y, output_y, output_x, filter_size, padding, stride, color, 1, 0)

  batch_size = ingrad.shape[ConvDataLayout.BATCH]
  channel = ingrad.shape[ConvDataLayout.CHANNEL]

  cudaconv2.sum(ingrad.reshape((channel, output_y * output_x * batch_size)), 1, bias_grad)

Example #3

File: layer.py Project: phecy/striate

 def bprop(self, grad, input, output, outGrad):
     cudaconv2.convImgActs(grad, self.weight, outGrad, self.imgSize,
                           self.imgSize, self.outputSize, -self.padding,
                           self.stride, self.numColor, 1, 0.0, 1.0)
     # bprop weight
     self.weightGrad.fill(0)
     cudaconv2.convWeightActs(input, grad, self.weightGrad, self.imgSize,
                              self.outputSize, self.outputSize,
                              self.filterSize, -self.padding, self.stride,
                              self.numColor, 1, 0, 0, 1)
     # bprop bias
     self.biasGrad.fill(0)
     gpu_copy_to(grad, self.tmp)
     add_row_sum_to_vec(self.biasGrad, self.tmp)

Example #4

File: layer.py Project: alemagnani/fastnet

 def bprop(self, grad, input, output, outGrad):
   self.weight.grad.fill(0)
   self.bias.grad.fill(0)
  
   # bprop to next layer
   cudaconv2.convImgActs(grad, self.weight.wt, outGrad, self.img_size, self.img_size,
       self.outputSize, -self.padding, self.stride, self.numColor, 1, 0.0, 1.0)
   
   # bprop weight
   cudaconv2.convWeightActs(input, grad, self.weight.grad, self.img_size, self.outputSize,
       self.outputSize, self.filterSize, -self.padding, self.stride, self.numColor, 1, 0, 0, 1)
   
   # bprop bias
   gpu_copy_to(grad, self.tmp)
   add_row_sum_to_vec(self.bias.grad, self.tmp)

Example #5

File: layer.py Project: sportsbitenews/fastnet

 def bprop(self, grad, input, output, outGrad):
   self.weight.grad.fill(0)
   self.bias.grad.fill(0)
  
   # bprop to next layer
   cudaconv2.convImgActs(grad, self.weight.wt, outGrad, self.img_size, self.img_size,
       self.outputSize, -self.padding, self.stride, self.numColor, 1, 0.0, 1.0)
   
   # bprop weight
   cudaconv2.convWeightActs(input, grad, self.weight.grad, self.img_size, self.outputSize,
       self.outputSize, self.filterSize, -self.padding, self.stride, self.numColor, 1, 0, 0, 1)
   
   # bprop bias
   gpu_copy_to(grad, self.tmp)
   add_row_sum_to_vec(self.bias.grad, self.tmp)