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@ -59,44 +59,39 @@ class TransposeOpMaker : public framework::OpProtoAndCheckerMaker {
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput(
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"X",
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"(Tensor)The input tensor, tensors with rank at most 6 are supported");
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AddOutput("Out", "(Tensor)The output tensor");
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"(Tensor) The input tensor, tensors with rank up to 6 are supported.");
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AddOutput("Out", "(Tensor)The output tensor.");
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AddAttr<std::vector<int>>(
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"axis",
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"(vector<int>)A list of values, and the size of the list should be "
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"the same with the input tensor rank, the tensor will "
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"permute the axes according the the values given");
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"(vector<int>) A list of values, and the size of the list should be "
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"the same with the input tensor rank. This operator permutes the input "
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"tensor's axes according to the values given.");
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AddComment(R"DOC(
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Transpose Operator.
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The input tensor will be permuted according to the axis values given.
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The op functions is similar to how numpy.transpose works in python.
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The input tensor will be permuted according to the axes given.
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The behavior of this operator is similar to how `numpy.transpose` works.
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For example:
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- suppose the input `X` is a 2-D tensor:
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$$
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X = \begin{pmatrix}
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0 &1 &2 \\
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3 &4 &5
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\end{pmatrix}$$
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.. code-block:: text
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the given `axes` is: $[1, 0]$, and $Y$ = transpose($X$, axis)
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input = numpy.arange(6).reshape((2,3))
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then the output $Y$ is:
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the input is:
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$$
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Y = \begin{pmatrix}
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0 &3 \\
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1 &4 \\
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2 &5
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\end{pmatrix}$$
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array([[0, 1, 2],
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[3, 4, 5]])
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given axis is:
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[1, 0]
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output = input.transpose(axis)
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then the output is:
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array([[0, 3],
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[1, 4],
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[2, 5]])
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So, given a input tensor of shape(N, C, H, W) and the axis is {0, 2, 3, 1},
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the output tensor shape will be (N, H, W, C)
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- Given a input tensor with shape $(N, C, H, W)$ and the `axes` is
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$[0, 2, 3, 1]$, then shape of the output tensor will be: $(N, H, W, C)$.
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)DOC");
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}
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