"comment":"\nTranspose Operator.\n\nThe input tensor will be permuted according to the axis values given.\nThe op functions is similar to how numpy.transpose works in python.\n\nFor example: input = numpy.arange(6).reshape((2,3))\nthe input is:\narray([[0, 1, 2],\n [3, 4, 5]])\ngiven axis is: [1, 0]\n\noutput = input.transpose(axis)\nthen the output is:\narray([[0, 3],\n [1, 4],\n [2, 5]])\nSo, given a input tensor of shape(N, C, H, W) and the axis is {0, 2, 3, 1},\nthe output tensor shape will be (N, H, W, C)\n\n",
"comment":"\nTranspose Operator.\n\nThe input tensor will be permuted according to the axis values given.\nThe op functions is similar to how numpy.transpose works in python.\n\nFor example:\n\n .. code-block:: text\n\n input = numpy.arange(6).reshape((2,3))\n\n the input is:\n\n array([[0, 1, 2],\n [3, 4, 5]])\n\n given axis is:\n\n [1, 0]\n\n output = input.transpose(axis)\n\n then the output is:\n\n array([[0, 3],\n [1, 4],\n [2, 5]])\n\nSo, given a input tensor of shape(N, C, H, W) and the axis is {0, 2, 3, 1},\nthe output tensor shape will be (N, H, W, C)\n\n",
