DepthToSpace - 1 vs 11¶
DepthToSpace1 → DepthToSpace11
RENAMED
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@@ -1 +1 @@
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1
1
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DepthToSpace rearranges (permutes) data from depth into blocks of spatial data.
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2
2
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This is the reverse transformation of SpaceToDepth. More specifically, this op outputs a copy of
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3
3
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the input tensor where values from the depth dimension are moved in spatial blocks to the height
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4
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-
and width dimensions.
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4
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and width dimensions. By default, mode = DCR.
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5
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In the DCR mode, elements along the depth dimension from the input tensor are rearranged in the
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6
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following order: depth, column, and then row. The output y is computed from the input x as below:
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7
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8
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b, c, h, w = x.shape
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9
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10
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tmp = np.reshape(x, [b, blocksize, blocksize, c // (blocksize**2), h, w])
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11
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12
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tmp = np.transpose(tmp, [0, 3, 4, 1, 5, 2])
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13
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14
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y = np.reshape(tmp, [b, c // (blocksize**2), h * blocksize, w * blocksize])
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15
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16
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In the CRD mode, elements along the depth dimension from the input tensor are rearranged in the
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17
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following order: column, row, and the depth. The output y is computed from the input x as below:
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18
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b, c, h, w = x.shape
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20
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tmp = np.reshape(x, [b, c // (blocksize ** 2), blocksize, blocksize, h, w])
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tmp = np.transpose(tmp, [0, 1, 4, 2, 5, 3])
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y = np.reshape(tmp, [b, c // (blocksize ** 2), h * blocksize, w * blocksize])
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5
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**Attributes**
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* **blocksize** (required):
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7
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Blocks of [blocksize, blocksize] are moved.
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* **mode**:
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DCR (default) for depth-column-row order re-arrangement. Use CRD for
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31
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column-row-depth order.
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8
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**Inputs**
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9
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* **input** (heterogeneous) - **T**:
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10
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Input tensor of [N,C,H,W], where N is the batch axis, C is the
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11
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channel or depth, H is the height and W is the width.
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12
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**Outputs**
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13
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* **output** (heterogeneous) - **T**:
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14
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Output tensor of [N, C/(blocksize * blocksize), H * blocksize, W *
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blocksize].
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16
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**Type Constraints**
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* **T** in (
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tensor(bool),
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tensor(complex128),
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tensor(complex64),
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tensor(double),
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tensor(float),
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tensor(float16),
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tensor(int16),
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tensor(int32),
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tensor(int64),
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tensor(int8),
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tensor(string),
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tensor(uint16),
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tensor(uint32),
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tensor(uint64),
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tensor(uint8)
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):
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Constrain input and output types to all tensor types.
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