Fix performance on resnet50 quantized models (#7670)
* Fix performance on resnet50 quantized models LP transformations won't work on the model unless the last 4 inputs to FakeQuantize are constants. In order to meet that requirement, we need to perform constant folding for those inputs in QuantizeLinear ONNX operator. Ticket: 65375 * fix "Cannot find blob with name: y" exception during onnx_model_quant_conv_linear * remove linking with onnx_ngraph_frontend * fix exclude path
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@@ -66,6 +66,11 @@ ov_model_convert("${CMAKE_CURRENT_SOURCE_DIR}/ngraph/test"
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"${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/test_model_zoo/ngraph"
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onnx_out_files)
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set(rel_path "inference-engine/tests/functional/plugin/shared/models")
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ov_model_convert("${OpenVINO_SOURCE_DIR}/${rel_path}"
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"${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/test_model_zoo/func_tests/models"
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ft_out_files)
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set(rel_path "inference-engine/tests/functional/inference_engine/onnx_reader")
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ov_model_convert("${OpenVINO_SOURCE_DIR}/${rel_path}"
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"${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/test_model_zoo/onnx_reader"
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@@ -116,6 +121,7 @@ if(ENABLE_TESTS)
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endif()
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add_custom_target(test_model_zoo DEPENDS ${onnx_out_files}
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${ft_out_files}
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${ie_onnx_out_files}
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${ie_serialize_out_files}
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${ie_onnx_import_out_files})
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