ef45b5da8d
* Doc Migration from Gitlab (#1289) * doc migration * fix * Update FakeQuantize_1.md * Update performance_benchmarks.md * Updates graphs for FPGA * Update performance_benchmarks.md * Change DL Workbench structure (#1) * Changed DL Workbench structure * Fixed tags * fixes * Update ie_docs.xml * Update performance_benchmarks_faq.md * Fixes in DL Workbench layout * Fixes for CVS-31290 * [DL Workbench] Minor correction * Fix for CVS-30955 * Added nGraph deprecation notice as requested by Zoe * fix broken links in api doxy layouts * CVS-31131 fixes * Additional fixes * Fixed POT TOC * Update PAC_Configure.md PAC DCP 1.2.1 install guide. * Update inference_engine_intro.md * fix broken link * Update opset.md * fix * added opset4 to layout * added new opsets to layout, set labels for them * Update VisionAcceleratorFPGA_Configure.md Updated from 2020.3 to 2020.4 Co-authored-by: domi2000 <domi2000@users.noreply.github.com>
2.5 KiB
2.5 KiB
Transpose
Versioned name: Transpose-1
Category: Data movement
Short description: Transpose operation reorders the input tensor dimensions.
Attributes:
No attributes available.
Inputs:
- 1: "arg" - the tensor to be transposed. A tensor of type T1. Required.
- 2: "input_order" - the permutation to apply to the axes of the input shape. Must be a vector of element T2 type, with shape [n], where n is the rank of "arg". The tensor's value must contain every integer in the range [0,n-1]. If an empty list is specified [] then the axes will be inverted. A tensor of type T2. Required.
Outputs:
- 1: A tensor with shape and type matching 1st tensor.
Types
- T1: arbitrary supported type.
- T2: any integer type.
Detailed description:
Transpose operation reorders the input tensor dimensions. Source indexes and destination indexes are bound by the formula: \f[ output[i(order[0]), i(order[1]), ..., i(order[N-1])] = input[i(0), i(1), ..., i(N-1)], where i(j) in range 0..(input.shape[j]-1). \f]
Examples
Example 1
<layer ... type="Transpose">
<input>
<port id="0">
<dim>2</dim>
<dim>3</dim>
<dim>4</dim>
</port>
<port id="1">
<dim>3</dim> <!-- [2, 0, 1] -->
</port>
</input>
<output>
<port id="2">
<dim>4</dim>
<dim>2</dim>
<dim>3</dim>
</port>
</output>
</layer>
Example 2: input_order in not specified
<layer ... type="Transpose">
<input>
<port id="0">
<dim>2</dim>
<dim>3</dim>
<dim>4</dim>
</port>
</input>
<output> <!-- input_order = [2, 1, 0] if input_order is not set -->
<port id="1">
<dim>4</dim>
<dim>3</dim>
<dim>2</dim>
</port>
</output>
</layer>
Example 3: input_order = empty_list []
<layer ... type="Transpose">
<input>
<port id="0">
<dim>2</dim>
<dim>3</dim>
<dim>4</dim>
</port>
<port id="1">
<dim>0</dim> <!-- input_order = [2, 1, 0] if input_order is empty list -->
</port>
</input>
<output>
<port id="2">
<dim>4</dim>
<dim>3</dim>
<dim>2</dim>
</port>
</output>
</layer>