Maajid/implement read network #64
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smkarlap
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suryasidd
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Just that one change for the exception. Everything else LGTM. Do we have any other small fixes upcoming that we wan't to add before we send the PR ? |
->Using Core::ReadNetwork() method for reading and creating a CNNNework ->Since OpenVINO™ 2020.4 version, Inference Engine enables reading ONNX models via the Inference Engine Core API and there is no need to use directly the low-level ONNX* Importer API anymore. To read ONNX* models, it's recommended to use the Core::ReadNetwork() method that provide a uniform way to read models from ONNX format. Signed-off-by: MaajidKhan <[email protected]>
-> use InferenceEngine::details::InferenceEngineException to catch the exception for ReadNetwork() Signed-off-by: MaajidKhan <[email protected]>
->The UEP component fails to compile with OpenVINO_2021.1 release version due to indentation error.Indentation is fixed with this commit. Signed-off-by: MaajidKhan <[email protected]>
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sfatimar
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…oft#22603) Add support for softmaxcrossentropy loss. This is already enabled on our ROCm Fork of the MIGraphX EP ### Motivation and Context Adds support for the SoftmaxCrossEntropyLoss operator and removes the filtering of inputs here.
ankitm3k
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…oft#22603) Add support for softmaxcrossentropy loss. This is already enabled on our ROCm Fork of the MIGraphX EP ### Motivation and Context Adds support for the SoftmaxCrossEntropyLoss operator and removes the filtering of inputs here.
ankitm3k
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Dec 11, 2024
…oft#22603) Add support for softmaxcrossentropy loss. This is already enabled on our ROCm Fork of the MIGraphX EP ### Motivation and Context Adds support for the SoftmaxCrossEntropyLoss operator and removes the filtering of inputs here.
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Description:
Using Core::ReadNetwork() method for reading and creating a CNNNework
Motivation and Context
Since OpenVINO™ 2020.4 version, Inference Engine enables reading ONNX models via the Inference Engine Core API and there is no need to use directly the low-level ONNX* Importer API anymore. To read ONNX* models, it's recommended to use the Core::ReadNetwork() method that provide a uniform way to read models from ONNX format.