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get_dl_model_layerGetDlModelLayerGetDlModelLayerget_dl_model_layerT_get_dl_model_layer🔗

Short description🔗

get_dl_model_layerGetDlModelLayerGetDlModelLayerget_dl_model_layerT_get_dl_model_layer — Create a deep copy of the layers and all of their graph ancestors in a given deep learning model.

Signature🔗

get_dl_model_layer( dl_model DLModelHandle, string LayerNames, out dl_layer DLLayers )void GetDlModelLayer( const HTuple& DLModelHandle, const HTuple& LayerNames, HTuple* DLLayers )static void HOperatorSet.GetDlModelLayer( HTuple DLModelHandle, HTuple layerNames, out HTuple DLLayers )def get_dl_model_layer( dlmodel_handle: HHandle, layer_names: MaybeSequence[str] ) -> Sequence[HHandle]

def get_dl_model_layer_s( dlmodel_handle: HHandle, layer_names: MaybeSequence[str] ) -> HHandleHerror T_get_dl_model_layer( const Htuple DLModelHandle, const Htuple LayerNames, Htuple* DLLayers )

static HDlLayerArray HDlLayer::GetDlModelLayer( const HDlModel& DLModelHandle, const HTuple& LayerNames )

void HDlLayer::GetDlModelLayer( const HDlModel& DLModelHandle, const HString& LayerNames )

void HDlLayer::GetDlModelLayer( const HDlModel& DLModelHandle, const char* LayerNames )

void HDlLayer::GetDlModelLayer( const HDlModel& DLModelHandle, const wchar_t* LayerNames ) (Windows only)

HDlLayerArray HDlModel::GetDlModelLayer( const HTuple& LayerNames ) const

HDlLayer HDlModel::GetDlModelLayer( const HString& LayerNames ) const

HDlLayer HDlModel::GetDlModelLayer( const char* LayerNames ) const

HDlLayer HDlModel::GetDlModelLayer( const wchar_t* LayerNames ) const (Windows only)

static HDlLayer[] HDlLayer.GetDlModelLayer( HDlModel DLModelHandle, HTuple layerNames )

void HDlLayer.GetDlModelLayer( HDlModel DLModelHandle, string layerNames )

HDlLayer[] HDlModel.GetDlModelLayer( HTuple layerNames )

HDlLayer HDlModel.GetDlModelLayer( string layerNames )

Description🔗

The operator get_dl_model_layerGetDlModelLayer creates a deep copy of every layer named in LayerNameslayerNameslayer_names and all their graph ancestors in the deep learning model DLModelHandleDLModelHandledlmodel_handle. You can retrieve the unique layer names using get_dl_model_paramGetDlModelParam with its option 'summary'"summary".

You might use the output layers returned in DLLayersDLLayersdllayers as inputs to the create_dl_layer_* and create_dl_modelCreateDlModel operators in order to create novel model architectures based on existing models.

If you want to get multiple layers of a single model, these layers have to be specified as a LayerNameslayerNameslayer_names tuple in a single call to get_dl_model_layerGetDlModelLayer. Doing so, you avoid multiple deep copies of graph ancestors that are potentially shared by the layers.

Example:

 
get_dl_model_layer(DLModelHandleOrig, ['layer_name_3', 'layer_name_6'], DLLayersOutput)GetDlModelLayer(DLModelHandleOrig, ["layer_name_3", "layer_name_6"], DLLayersOutput)GetDlModelLayer(DLModelHandleOrig, ["layer_name_3", "layer_name_6"], DLLayersOutput)get_dl_model_layer(DLModelHandleOrig, ["layer_name_3", "layer_name_6"], DLLayersOutput)get_dl_model_layer(DLModelHandleOrig, ["layer_name_3", "layer_name_6"], DLLayersOutput)
create_dl_model([DLLayersOutput], DLModelHandle)CreateDlModel([DLLayersOutput], DLModelHandle)CreateDlModel([DLLayersOutput], DLModelHandle)create_dl_model([DLLayersOutput], DLModelHandle)create_dl_model([DLLayersOutput], DLModelHandle)

Please note, that the output layers are copies. They contain the same weights and settings as in the given input model but they are unique copies. You cannot alter the existing model by changing the output layers.

Execution information🔗

Execution information
  • Multithreading type: reentrant (runs in parallel with non-exclusive operators).

  • Multithreading scope: global (may be called from any thread).

  • Processed without parallelization.

This operator returns a handle. Note that the state of an instance of this handle type may be changed by specific operators even though the handle is used as an input parameter by those operators.

Parameters🔗

DLModelHandleDLModelHandledlmodel_handle (input_control) dl_model → (handle)HTuple (HHandle)HDlModel, HTuple (IntPtr)HHandleHtuple (handle)

Deep learning model.

LayerNameslayerNameslayer_names (input_control) string(-array) → (string)HTuple (HString)HTuple (string)MaybeSequence[str]Htuple (char*)

Names of the layers to be copied.

DLLayersDLLayersdllayers (output_control) dl_layer(-array) → (handle)HTuple (HHandle)HDlLayer, HTuple (IntPtr)Sequence[HHandle]Htuple (handle)

Copies of layers and all of their ancestors.

Combinations with other operators🔗

Combinations

Possible predecessors

read_dl_modelReadDlModel

Possible successors

create_dl_modelCreateDlModel, create_dl_layer_activationCreateDlLayerActivation, create_dl_layer_batch_normalizationCreateDlLayerBatchNormalization, create_dl_layer_class_id_conversionCreateDlLayerClassIdConversion, create_dl_layer_class_id_conversionCreateDlLayerClassIdConversion, create_dl_layer_concatCreateDlLayerConcat, create_dl_layer_convolutionCreateDlLayerConvolution, create_dl_layer_denseCreateDlLayerDense, create_dl_layer_depth_maxCreateDlLayerDepthMax, create_dl_layer_dropoutCreateDlLayerDropout, create_dl_layer_elementwiseCreateDlLayerElementwise, create_dl_layer_loss_cross_entropyCreateDlLayerLossCrossEntropy, create_dl_layer_loss_ctcCreateDlLayerLossCtc, create_dl_layer_loss_distanceCreateDlLayerLossDistance, create_dl_layer_loss_focalCreateDlLayerLossFocal, create_dl_layer_loss_huberCreateDlLayerLossHuber, create_dl_layer_lrnCreateDlLayerLrn, create_dl_layer_poolingCreateDlLayerPooling, create_dl_layer_reduceCreateDlLayerReduce, create_dl_layer_reshapeCreateDlLayerReshape, create_dl_layer_softmaxCreateDlLayerSoftmax, create_dl_layer_transposed_convolutionCreateDlLayerTransposedConvolution, create_dl_layer_zoom_factorCreateDlLayerZoomFactor, create_dl_layer_zoom_sizeCreateDlLayerZoomSize, create_dl_layer_zoom_to_layer_sizeCreateDlLayerZoomToLayerSize

Module🔗

Deep Learning Professional