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mindspore.ops.ExtractVolumePatches

class mindspore.ops.ExtractVolumePatches(kernel_size, strides, padding)

Extract patches from input and put them in the “depth” output dimension.

Parameters

• kernel_size (Union[int, tuple[int], list[int]]) – A list of ints which’s length is 3 or 5. The size of the sliding window for each dimension of input. Must be: [1, 1, k_d, k_h, k_w] or [k_d, k_h, k_w]. If k_d = k_h = k_w, you can enter an integer.

• strides (Union[int, tuple[int], list[int]]) – A list of ints which’s length is 3 or 5. How far the centers of two consecutive patches are in input. Must be: [1, 1, s_d, s_h, s_w] or [s_d, s_h, s_w]. If s_d = s_h = s_w, you can enter an integer.

• padding (str) – A string from: “SAME”, “VALID”. The type of padding algorithm to use.

Inputs:

• input_x (Tensor) - A Tensor. 5-D Tensor with shape $(x_n,x_c,x_d,x_h,x_w)$.

Outputs:

Tensor, has the same type as input. If padding is VALID, the shape is $(x_n,k_d\ast k_h\ast k_w\ast x_c,1+(x_d-k_d)/s_d,1+(x_h-k_h)/s_h,1+(x_w-k_w)/s_w)$; if padding is SAME, the shape is $(x_n,k_d\ast k_h\ast k_w\ast x_c,(x_d+s_d-1)/s_d,(x_h+s_h-1)/s_h,(x_w+s_w-1)/s_w)$.

Raises

• TypeError – If kernel_size or strides is not a list, a tuple or an int.

• TypeError – If input_x is not a tensor.

• TypeError – If padding is not str.

• ValueError – If the length of kernel_size is neither 3 nor 5 and kernel_size is not an integer.

• ValueError – If the length of strides is neither 3 nor 5 and strides is not an integer.

• ValueError – If padding is neither “VALID” nor “SAME”.

• ValueError – If elements of kernel_size or strides are not positive integer.

• ValueError – If input_x is not a tensor in dimension 5.

• ValueError – If input_x’s shape has zero.

• ValueError – If one of kernel_size or strides’ first two numbers is not 1.

• ValueError – If padding = “VALID” and input - kernel_size is less than 0 in d, h or w dimension.

• ValueError – If padding = “SAME” and $padding\mathrm{\_}needed=((input\mathrm{\_}x+strides-1)/strides-1)\ast strides+kernel\mathrm{\_}size-input$ is less than 0 in d, h or w dimension.

• ValueError – If x_h is not 1 or x_w is not 1 and x_w + padding_needed - k_w - s_w is less than 0.

• ValueError – If x_d * x_h * x_w is greater than 2048.

Supported Platforms:

Ascend CPU

Examples

>>> kernel_size = (1, 1, 2, 2, 2)
>>> strides = (1, 1, 1, 1, 1)
>>> padding = "VALID"
>>> input_x = P.Reshape()(Tensor(np.arange(1, 28), mstype.float16), (1, 1, 3, 3, 3))
>>> output_y = P.ExtractVolumePatches(kernel_size, strides, padding)(input_x)
>>> print(output_y.shape)
(1, 8, 2, 2, 2)