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 — Setzen der Parameterwerte des angegebenen Layers.

Signatur

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)   (Nur Windows)

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

Beschreibung

Der Operator set_dl_model_layer_paramset_dl_model_layer_paramSetDlModelLayerParamSetDlModelLayerParamSetDlModelLayerParamset_dl_model_layer_param setzt den Wert ParamValueParamValueParamValueParamValueparamValueparam_value des Parameters ParamNameParamNameParamNameParamNameparamNameparam_name für einen Layer. Der Layername LayerNameLayerNameLayerNameLayerNamelayerNamelayer_name bezieht sich auf den im Model DLModelHandleDLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle zugeordneten Namen. Die Layernamen können über die Option 'layer_names'"layer_names""layer_names""layer_names""layer_names""layer_names" oder 'summary'"summary""summary""summary""summary""summary" mit get_dl_model_paramget_dl_model_paramGetDlModelParamGetDlModelParamGetDlModelParamget_dl_model_param ausgelesen werden.

Welche generischen und Layer-spezifischen Parameter gesetzt werden können wird in den Einträgen der Operatoren zur Erstellung der Layer (create_dl_layer_*) beschrieben.

Ausführungsinformationen

Parameter

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

Handle des Deep Learning-Modells.

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

Name des Ausgabelayers.

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

Name des gesetzten Parameter.

Defaultwert: []

Werteliste: '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)

Wert des gesetzten Parameter.

Defaultwert: []

Werteliste: '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"

Siehe auch

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

Modul

Foundation. Dieser Operator verwendet dynamische Lizensierung (siehe ``Installation Guide''). Welches der folgenden Module benötigt wird hängt von der Anwendung des Operators ab:
3D Metrology, OCR/OCV, Deep Learning Training