def backward_gpu(self, x, gy):
gx = cuda.empty_like(x[0])
if cudnn.enabled and self.use_cudnn:
handle = cudnn.get_default_handle()
desc = cudnn.get_tensor_desc(self.y, 1, 1)
libcudnn.cudnnActivationBackward(handle, _mode, 1, desc.value,
cudnn.get_ptr(self.y), desc.value,
cudnn.get_ptr(gy[0]), desc.value,
cudnn.get_ptr(x[0]), 0,
desc.value, cudnn.get_ptr(gx))
else:
cuda.elementwise('float* gx, const float* y, const float* gy',
'gx[i] = gy[i] * y[i] * (1 - y[i])',
'sigmoid_bwd')(gx, self.y, gy[0])
return gx,
def backward_gpu(self, x, gy):
gx = cuda.empty_like(x[0])
if cudnn.enabled and self.use_cudnn:
handle = cudnn.get_default_handle()
desc = cudnn.get_tensor_desc(self.y, 1, 1)
libcudnn.cudnnActivationBackward(
handle, _mode, 1, desc.value, cudnn.get_ptr(self.y),
desc.value, cudnn.get_ptr(gy[0]), desc.value, cudnn.get_ptr(x[0]),
0, desc.value, cudnn.get_ptr(gx))
else:
cuda.elementwise(
'float* gx, const float* y, const float* gy',
'gx[i] = gy[i] * y[i] * (1 - y[i])',
'sigmoid_bwd')(gx, self.y, gy[0])
return gx,
def backward_gpu(self, x, gy):
gx = cuda.empty_like(x[0])
if cudnn.enabled and self.use_cudnn:
handle = cudnn.get_default_handle()
desc = cudnn.get_tensor_desc(self.y, 1, 1)
libcudnn.cudnnActivationBackward(
handle,
_mode,
1,
desc.value,
cudnn.get_ptr(self.y),
desc.value,
cudnn.get_ptr(gy[0]),
desc.value,
cudnn.get_ptr(x[0]),
0,
desc.value,
cudnn.get_ptr(gx),
)
else:
cuda.elementwise("float* gx, const float* x, const float* gy", "gx[i] = x[i] > 0 ? gy[i] : 0", "relu_bwd")(
gx, x[0], gy[0]
)
return (gx,)