dbad8809bf
* Release mo dev guide refactoring (#3266) * Updated MO extension guide * Minor change and adding svg images * Added additional information about operation extractors. Fixed links and markdown issues * Added missing file with information about Caffe Python layers and image for MO transformations dependencies graph * Added section with common graph transformations attributes and diagram with anchor transformations. Added list of available front phase transformations * Added description of front-phase transformations except the scope-defined and points defined. Removed legacy document and examples for such transformations. * Added sections about node name pattern defined front phase transformations. Copy-pasted the old one for the points defined front transformation * Added description of the rest of front transformations and and all middle and back phase transformations * Refactored Legacy_Mode_for_Caffe_Custom_Layers and updated the Customize_Model_Optimizer with information about extractors order * Added TOC for the MO Dev guide document and updated SVG images with PNG ones * Fixed broken link. Removed redundant image * Fixed broken links * Added information about attributes 'run_not_recursively', 'force_clean_up' and 'force_shape_inference' of the transformation * Code review comments * Added a section about `Port`s * Extended Ports description with examples * Added information about Connections * Updated MO README.md and removed a lot of redundant and misleading information * Updates to the Customize_Model_Optimizer.md * More updates to the Customize_Model_Optimizer.md * Final updates for the Customize_Model_Optimizer.md * Fixed some broken links * More fixed links * Refactored Custom Layers Guide: removed legacy and incorrect text, added up-to-date. * Draft implementation of the Custom layer guide example for the MO part * Fixed broken links using #. Change layer->operation in extensibility documents * Updated Custom operation guide with IE part * Fixed broken links and minor updates to the Custom Operations Guide * Updating links * Layer->Operation * Moved FFTOp implementation to the template extension * Update the CMake for template_extension to build the FFT op conditionally * Fixed template extension compilation * Fixed CMake for template extension * Fixed broken snippet * Added mri_demo script and updated documentation * One more compilation error fix * Added missing header for a demo file * Added reference to OpenCV * Fixed unit test for the template extension * Fixed typos in the template extension * Fixed compilation of template extension for case when ONNX importer is disabled Co-authored-by: Alexander Zhogov <alexander.zhogov@intel.com>
35 lines
967 B
C++
35 lines
967 B
C++
// Copyright (C) 2020 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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//! [fft_op:implementation]
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#include "fft_op.hpp"
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using namespace TemplateExtension;
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constexpr ngraph::NodeTypeInfo FFTOp::type_info;
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FFTOp::FFTOp(const ngraph::Output<ngraph::Node>& inp, bool _inverse) : Op({inp}) {
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constructor_validate_and_infer_types();
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inverse = _inverse;
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}
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void FFTOp::validate_and_infer_types() {
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auto outShape = get_input_partial_shape(0);
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set_output_type(0, get_input_element_type(0), outShape);
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}
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std::shared_ptr<ngraph::Node> FFTOp::clone_with_new_inputs(const ngraph::OutputVector &new_args) const {
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if (new_args.size() != 1) {
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throw ngraph::ngraph_error("Incorrect number of new arguments");
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}
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return std::make_shared<FFTOp>(new_args.at(0), inverse);
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}
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bool FFTOp::visit_attributes(ngraph::AttributeVisitor &visitor) {
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visitor.on_attribute("inverse", inverse);
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return true;
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}
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//! [fft_op:implementation]
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