log_softmax.py 文件源码

def backward(self, x, gy):
        xp = cuda.get_array_module(*x)
        if (xp != numpy and cuda.cudnn_enabled and self.use_cudnn and
                _cudnn_version >= 3000):
            oz_dtype = 'd' if x[0].dtype == 'd' else 'f'
            one = numpy.array(1, dtype=oz_dtype).ctypes
            zero = numpy.array(0, dtype=oz_dtype).ctypes
            handle = cudnn.get_handle()
            gx = xp.empty_like(x[0])
            gx_cube = gx.reshape(gx.shape[:2] + (-1, 1))
            desc = cudnn.create_tensor_descriptor(gx_cube)
            libcudnn.softmaxBackward(
                handle, _algorithm, _mode, one.data, desc.value,
                self.y.data.ptr, desc.value, gy[0].data.ptr, zero.data,
                desc.value, gx.data.ptr)
        else:
            gx = gy[0] - xp.exp(self.y) * gy[0].sum(axis=1, keepdims=True)

        return gx,