[Add] avgpool1d avgpool3d #5165
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zev123456
commented
Jun 10, 2021
•
zev123456
commented
| out = out.reshape(out_shape) | ||
| return out | ||
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| def backward(self, d_loss): |
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这个numpy模拟的grad没有使用吧？没用的话可以删掉
| output = output.sum() | ||
| output.backward() | ||
| doutput = np.ones_like(numpy_output, dtype=np.float64) | ||
| #numpy_grad = m_numpy.backward(doutput) |
| output.backward() | ||
| doutput = np.ones_like(numpy_output, dtype=np.float64) | ||
| #numpy_grad = m_numpy.backward(doutput) | ||
| numpy_grad = np.array(#torch grad out |
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numpy_grad可以直接用：numpy_grad = np.zeros(shape=xxx) + numpy_grad[...] = 0.125完成
Flowingsun007
approved these changes
Jun 17, 2021
| >>> inputarr = np.array([[[[[-0.74832135, 0.03151652],[ 1.08632752, 0.53338843]],[[ 0.70026413, -0.62565466], [-0.59692776, -1.00883888]]],[[[-0.26829566, -0.31759021],[ 1.46828945, -2.61885422]],[[-0.67331338, 1.31144767],[-0.85747376, -0.38252167]]]],[[[[-1.54668075, -0.935113 ],[ 0.19119924, -0.83618886]],[[ 0.17532863, 0.6574685 ],[-1.10141786, 1.1819236 ]]],[[[-1.1367412 , 0.68027652],[ 0.98564578, 0.04861313]],[[-0.69807858, 0.75021497],[ 0.62720175, -0.76607257]]]]]) | ||
| >>> of_avgpool3d = flow.nn.AvgPool3d(kernel_size=(2,2,2),padding=(0,0,0),stride=(1,1,1),) | ||
| >>> x = flow.Tensor(inputarr) | ||
| >>> flow.enable_eager_execution() |
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flow.enable_eager_execution()这个放上面吧
| >>> of_y = of_avgpool3d(x) | ||
| >>> print(of_y.dtype) | ||
| oneflow.float32 | ||
| >>> print(of_y.numpy().sum()) |
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直接>>>of_y 就行，不需要.numpy().sum()了
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