def ref_convolution(x, w, b, base_axis, pad, stride, dilation, group):
y = []
for xx in x.reshape((-1,) + x.shape[base_axis:]):
y += [refs.convolution_nd(xx, w, b, pad, stride,
dilation, group)[np.newaxis]]
y = np.vstack(y)
return y.reshape(x.shape[:base_axis] + y.shape[1:])
def ref_convolution(x, w, b, base_axis, pad, stride, dilation, group, channel_last):
if channel_last:
t = refs.ChannelLastToFirstTranspose(x.ndim, len(pad))
x = t(x)
tw = refs.ChannelLastToFirstTranspose(w.ndim, len(pad))
w = tw(w)
y = ref_convolution(x, w, b, base_axis, pad,
stride, dilation, group, False)
return t.inv(y)
y = []
for xx in x.reshape((-1,) + x.shape[base_axis:]):
y += [refs.convolution_nd(xx, w, b, pad, stride,
dilation, group)[np.newaxis]]
y = np.vstack(y)
return y.reshape(x.shape[:base_axis] + y.shape[1:])