set_dl_model_layer_paramT_set_dl_model_layer_paramSetDlModelLayerParamSetDlModelLayerParamset_dl_model_layer_param (Operator)

Name

set_dl_model_layer_paramT_set_dl_model_layer_paramSetDlModelLayerParamSetDlModelLayerParamset_dl_model_layer_param — Set parameter values of a given layer.

Signature

set_dl_model_layer_param( : : DLModelHandle, LayerName, ParamName, ParamValue : )

Herror T_set_dl_model_layer_param(const Htuple DLModelHandle, const Htuple LayerName, const Htuple ParamName, const Htuple ParamValue)

void SetDlModelLayerParam(const HTuple& DLModelHandle, const HTuple& LayerName, const HTuple& ParamName, const HTuple& ParamValue)

static void HDlLayer::SetDlModelLayerParam(const HDlModel& DLModelHandle, const HString& LayerName, const HString& ParamName, const HTuple& ParamValue)

static void HDlLayer::SetDlModelLayerParam(const HDlModel& DLModelHandle, const HString& LayerName, const HString& ParamName, const HString& ParamValue)

static void HDlLayer::SetDlModelLayerParam(const HDlModel& DLModelHandle, const char* LayerName, const char* ParamName, const char* ParamValue)

static void HDlLayer::SetDlModelLayerParam(const HDlModel& DLModelHandle, const wchar_t* LayerName, const wchar_t* ParamName, const wchar_t* ParamValue)   (Windows only)

static void HOperatorSet.SetDlModelLayerParam(HTuple DLModelHandle, HTuple layerName, HTuple paramName, HTuple paramValue)

static void HDlLayer.SetDlModelLayerParam(HDlModel DLModelHandle, string layerName, string paramName, HTuple paramValue)

static void HDlLayer.SetDlModelLayerParam(HDlModel DLModelHandle, string layerName, string paramName, string paramValue)

def set_dl_model_layer_param(dlmodel_handle: HHandle, layer_name: str, param_name: str, param_value: MaybeSequence[Union[int, float, str]]) -> None

Description

The operator set_dl_model_layer_paramset_dl_model_layer_paramSetDlModelLayerParamSetDlModelLayerParamSetDlModelLayerParamset_dl_model_layer_param sets the value ParamValueParamValueParamValueParamValueparamValueparam_value of the parameter ParamNameParamNameParamNameParamNameparamNameparam_name for a layer. The layer is referred to by its name LayerNameLayerNameLayerNameLayerNamelayerNamelayer_name in the model DLModelHandleDLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle. You can retrieve the layer names using get_dl_model_paramget_dl_model_paramGetDlModelParamGetDlModelParamGetDlModelParamget_dl_model_param with its option 'layer_names'"layer_names""layer_names""layer_names""layer_names""layer_names" or 'summary'"summary""summary""summary""summary""summary".

Which generic and layer-specific parameters can be set is described in the entries of the operators (create_dl_layer_*), which are used for creating the layer.

Execution Information

Parameters

DLModelHandleDLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle (input_control)  dl_model HDlModel, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Deep learning model.

LayerNameLayerNameLayerNameLayerNamelayerNamelayer_name (input_control)  string HTuplestrHTupleHtuple (string) (string) (HString) (char*)

Name of the output layer.

ParamNameParamNameParamNameParamNameparamNameparam_name (input_control)  attribute.name HTuplestrHTupleHtuple (string) (string) (HString) (char*)

Name of the set parameter.

Default value: []

List of values: 'bias_filler'"bias_filler""bias_filler""bias_filler""bias_filler""bias_filler", 'bias_filler_const_val'"bias_filler_const_val""bias_filler_const_val""bias_filler_const_val""bias_filler_const_val""bias_filler_const_val", 'bias_filler_variance_norm'"bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm", 'is_inference_output'"is_inference_output""is_inference_output""is_inference_output""is_inference_output""is_inference_output", 'leaky_relu_alpha'"leaky_relu_alpha""leaky_relu_alpha""leaky_relu_alpha""leaky_relu_alpha""leaky_relu_alpha", 'learning_rate_multiplier'"learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier", 'learning_rate_multiplier_bias'"learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias", 'name'"name""name""name""name""name", 'upper_bound'"upper_bound""upper_bound""upper_bound""upper_bound""upper_bound", 'weight_filler'"weight_filler""weight_filler""weight_filler""weight_filler""weight_filler", 'weight_filler_const_val'"weight_filler_const_val""weight_filler_const_val""weight_filler_const_val""weight_filler_const_val""weight_filler_const_val", 'weight_filler_variance_norm'"weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm"

ParamValueParamValueParamValueParamValueparamValueparam_value (input_control)  attribute.value(-array) HTupleMaybeSequence[Union[int, float, str]]HTupleHtuple (string / integer / real) (string / int / long / double) (HString / Hlong / double) (char* / Hlong / double)

Value of the set parameter.

Default value: []

List of values: 'const'"const""const""const""const""const", 'false'"false""false""false""false""false", 'msra'"msra""msra""msra""msra""msra", 'norm_average'"norm_average""norm_average""norm_average""norm_average""norm_average", 'norm_in'"norm_in""norm_in""norm_in""norm_in""norm_in", 'norm_out'"norm_out""norm_out""norm_out""norm_out""norm_out", 'true'"true""true""true""true""true", 'xavier'"xavier""xavier""xavier""xavier""xavier"

See also

set_dl_model_paramset_dl_model_paramSetDlModelParamSetDlModelParamSetDlModelParamset_dl_model_param, get_dl_model_paramget_dl_model_paramGetDlModelParamGetDlModelParamGetDlModelParamget_dl_model_param, get_dl_model_layer_paramget_dl_model_layer_paramGetDlModelLayerParamGetDlModelLayerParamGetDlModelLayerParamget_dl_model_layer_param

Module

Foundation. This operator uses dynamic licensing (see the ``Installation Guide''). Which of the following modules is required depends on the specific usage of the operator:
3D Metrology, OCR/OCV, Deep Learning Training