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create_dl_layer_denseT_create_dl_layer_denseCreateDlLayerDenseCreateDlLayerDensecreate_dl_layer_dense (Operator)

Name

create_dl_layer_denseT_create_dl_layer_denseCreateDlLayerDenseCreateDlLayerDensecreate_dl_layer_dense — Erstellen eines Dense-Layers.

Signatur

create_dl_layer_dense( : : DLLayerInput, LayerName, NumOut, GenParamName, GenParamValue : DLLayerDense)

Herror T_create_dl_layer_dense(const Htuple DLLayerInput, const Htuple LayerName, const Htuple NumOut, const Htuple GenParamName, const Htuple GenParamValue, Htuple* DLLayerDense)

void CreateDlLayerDense(const HTuple& DLLayerInput, const HTuple& LayerName, const HTuple& NumOut, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* DLLayerDense)

HDlLayer HDlLayer::CreateDlLayerDense(const HString& LayerName, Hlong NumOut, const HTuple& GenParamName, const HTuple& GenParamValue) const

HDlLayer HDlLayer::CreateDlLayerDense(const HString& LayerName, Hlong NumOut, const HString& GenParamName, const HString& GenParamValue) const

HDlLayer HDlLayer::CreateDlLayerDense(const char* LayerName, Hlong NumOut, const char* GenParamName, const char* GenParamValue) const

HDlLayer HDlLayer::CreateDlLayerDense(const wchar_t* LayerName, Hlong NumOut, const wchar_t* GenParamName, const wchar_t* GenParamValue) const   ( Nur Windows)

static void HOperatorSet.CreateDlLayerDense(HTuple DLLayerInput, HTuple layerName, HTuple numOut, HTuple genParamName, HTuple genParamValue, out HTuple DLLayerDense)

HDlLayer HDlLayer.CreateDlLayerDense(string layerName, int numOut, HTuple genParamName, HTuple genParamValue)

HDlLayer HDlLayer.CreateDlLayerDense(string layerName, int numOut, string genParamName, string genParamValue)

def create_dl_layer_dense(dllayer_input: HHandle, layer_name: str, num_out: int, gen_param_name: MaybeSequence[str], gen_param_value: MaybeSequence[Union[int, float, str]]) -> HHandle

Beschreibung

Der Operator create_dl_layer_densecreate_dl_layer_denseCreateDlLayerDenseCreateDlLayerDensecreate_dl_layer_dense erzeugt einen Dense- oder Fully-connected Layer (manchmal auch gemm genannt) mit NumOutNumOutNumOutnumOutnum_out Ausgabeneuronen, dessen Handle in DLLayerDenseDLLayerDenseDLLayerDenseDLLayerDensedllayer_dense zurückgegeben wird.

Der Parameter DLLayerInputDLLayerInputDLLayerInputDLLayerInputdllayer_input bestimmt den zuführenden Eingabelayer und erwartet das Layer-Handle als Wert.

Der Parameter LayerNameLayerNameLayerNamelayerNamelayer_name legt einen individuellen Layernamen fest. Es ist zu beachten, dass beim Erstellen eines Modells mit create_dl_modelcreate_dl_modelCreateDlModelCreateDlModelcreate_dl_model jeder Layer des erstellten Netzes einen eindeutigen Namen haben muss.

Die folgenden generischen Parameter GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name und die entsprechenden Werte GenParamValueGenParamValueGenParamValuegenParamValuegen_param_value werden unterstützt:

'bias_filler'"bias_filler""bias_filler""bias_filler""bias_filler":

Siehe create_dl_layer_convolutioncreate_dl_layer_convolutionCreateDlLayerConvolutionCreateDlLayerConvolutioncreate_dl_layer_convolution für eine detaillierte Erklärung dieses Parameters und seiner Werte.

Werteliste: 'xavier'"xavier""xavier""xavier""xavier", 'msra'"msra""msra""msra""msra", 'const'"const""const""const""const".

Default: 'const'"const""const""const""const"

'bias_filler_const_val'"bias_filler_const_val""bias_filler_const_val""bias_filler_const_val""bias_filler_const_val":

Konstanter Wert, wenn 'bias_filler'"bias_filler""bias_filler""bias_filler""bias_filler" = 'const'"const""const""const""const".

Default: 0

'bias_filler_variance_norm'"bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm":

Siehe create_dl_layer_convolutioncreate_dl_layer_convolutionCreateDlLayerConvolutionCreateDlLayerConvolutioncreate_dl_layer_convolution für eine detaillierte Erklärung dieses Parameters und seiner Werte.

Werteliste: 'norm_out'"norm_out""norm_out""norm_out""norm_out", 'norm_in'"norm_in""norm_in""norm_in""norm_in", 'norm_average'"norm_average""norm_average""norm_average""norm_average" oder konstanter Wert (in Kombination mit 'bias_filler'"bias_filler""bias_filler""bias_filler""bias_filler" = 'msra'"msra""msra""msra""msra").

Default: 'norm_out'"norm_out""norm_out""norm_out""norm_out"

'bias_term'"bias_term""bias_term""bias_term""bias_term":

Bestimmt, ob der erzeugte Layer DLLayerDenseDLLayerDenseDLLayerDenseDLLayerDensedllayer_dense einen Bias-Term hat ('true'"true""true""true""true") oder nicht ('false'"false""false""false""false").

Default: 'true'"true""true""true""true"

'is_inference_output'"is_inference_output""is_inference_output""is_inference_output""is_inference_output":

Bestimmt, ob apply_dl_modelapply_dl_modelApplyDlModelApplyDlModelapply_dl_model die Ausgabe dieses Layers im Dictionary DLResultBatchDLResultBatchDLResultBatchDLResultBatchdlresult_batch zurückgibt, auch ohne den Layer in OutputsOutputsOutputsoutputsoutputs anzugeben ('true'"true""true""true""true"), oder nur falls er angegeben wird ('false'"false""false""false""false").

Default: 'false'"false""false""false""false"

'learning_rate_multiplier'"learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier":

Multiplikator für die Lernrate dieses Layers, die beim Training verwendet wird. Wenn 'learning_rate_multiplier'"learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier" auf 0.0 gesetzt ist, wird der Layer beim Training übersprungen.

Default: 1.0

'learning_rate_multiplier_bias'"learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias":

Multiplikator für die Lernrate des Bias-Terms. Die gesamte Bias-Lernrate ist das Produkt aus 'learning_rate_multiplier_bias'"learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias" und 'learning_rate_multiplier'"learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier".

Default: 1.0

'weight_filler'"weight_filler""weight_filler""weight_filler""weight_filler":

Siehe create_dl_layer_convolutioncreate_dl_layer_convolutionCreateDlLayerConvolutionCreateDlLayerConvolutioncreate_dl_layer_convolution für eine detaillierte Erklärung dieses Parameters und seiner Werte.

Werteliste: 'xavier'"xavier""xavier""xavier""xavier", 'msra'"msra""msra""msra""msra", 'const'"const""const""const""const".

Default: 'xavier'"xavier""xavier""xavier""xavier"

'weight_filler_const_val'"weight_filler_const_val""weight_filler_const_val""weight_filler_const_val""weight_filler_const_val":

Siehe create_dl_layer_convolutioncreate_dl_layer_convolutionCreateDlLayerConvolutionCreateDlLayerConvolutioncreate_dl_layer_convolution für eine detaillierte Erklärung dieses Parameters und seiner Werte.

Default: 0.5

'weight_filler_variance_norm'"weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm":

Siehe create_dl_layer_convolutioncreate_dl_layer_convolutionCreateDlLayerConvolutionCreateDlLayerConvolutioncreate_dl_layer_convolution für eine detaillierte Erklärung dieses Parameters und seiner Werte.

Werteliste: 'norm_in'"norm_in""norm_in""norm_in""norm_in", 'norm_out'"norm_out""norm_out""norm_out""norm_out", 'norm_average'"norm_average""norm_average""norm_average""norm_average" oder konstanter Wert (in Kombination mit 'bias_filler'"bias_filler""bias_filler""bias_filler""bias_filler" = 'msra'"msra""msra""msra""msra").

Default: 'norm_in'"norm_in""norm_in""norm_in""norm_in"

Bestimmte Parameter von Layern, die mit create_dl_layer_densecreate_dl_layer_denseCreateDlLayerDenseCreateDlLayerDensecreate_dl_layer_dense erzeugt wurden, können mit weiteren Operatoren gesetzt und abgerufen werden. Die folgenden Tabellen geben einen Überblick, welche Parameter mit set_dl_model_layer_paramset_dl_model_layer_paramSetDlModelLayerParamSetDlModelLayerParamset_dl_model_layer_param gesetzt werden können und welche mit get_dl_model_layer_paramget_dl_model_layer_paramGetDlModelLayerParamGetDlModelLayerParamget_dl_model_layer_param oder get_dl_layer_paramget_dl_layer_paramGetDlLayerParamGetDlLayerParamget_dl_layer_param ausgelesen werden können. Es ist zu beachten, dass die Operatoren set_dl_model_layer_paramset_dl_model_layer_paramSetDlModelLayerParamSetDlModelLayerParamset_dl_model_layer_param und get_dl_model_layer_paramget_dl_model_layer_paramGetDlModelLayerParamGetDlModelLayerParamget_dl_model_layer_param ein Modell benötigen, das mit create_dl_modelcreate_dl_modelCreateDlModelCreateDlModelcreate_dl_model erzeugt wurde.

Layer-Parameter set get
'input_layer'"input_layer""input_layer""input_layer""input_layer" (DLLayerInputDLLayerInputDLLayerInputDLLayerInputdllayer_input) x
'name'"name""name""name""name" (LayerNameLayerNameLayerNamelayerNamelayer_name) x x
'neurons_in'"neurons_in""neurons_in""neurons_in""neurons_in" x
'neurons_out'"neurons_out""neurons_out""neurons_out""neurons_out" (NumOutNumOutNumOutnumOutnum_out) x
'output_layer'"output_layer""output_layer""output_layer""output_layer" (DLLayerDenseDLLayerDenseDLLayerDenseDLLayerDensedllayer_dense) x
'shape'"shape""shape""shape""shape" x
'type'"type""type""type""type" x
Generische Layer-Parameter set get
'bias_filler'"bias_filler""bias_filler""bias_filler""bias_filler" x x
'bias_filler_const_val'"bias_filler_const_val""bias_filler_const_val""bias_filler_const_val""bias_filler_const_val" x x
'bias_filler_variance_norm'"bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm" x x
'bias_term'"bias_term""bias_term""bias_term""bias_term" x
'is_inference_output'"is_inference_output""is_inference_output""is_inference_output""is_inference_output" x x
'learning_rate_multiplier'"learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier""learning_rate_multiplier" x x
'learning_rate_multiplier_bias'"learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias""learning_rate_multiplier_bias" x x
'num_trainable_params'"num_trainable_params""num_trainable_params""num_trainable_params""num_trainable_params" x
'weight_filler'"weight_filler""weight_filler""weight_filler""weight_filler" x x
'weight_filler_const_val'"weight_filler_const_val""weight_filler_const_val""weight_filler_const_val""weight_filler_const_val" x x
'weight_filler_variance_norm'"weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm" x x

Ausführungsinformationen

Parameter

DLLayerInputDLLayerInputDLLayerInputDLLayerInputdllayer_input (input_control)  dl_layer → HDlLayer, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Zuführender Layer.

LayerNameLayerNameLayerNamelayerNamelayer_name (input_control)  string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)

Name des Ausgabelayers.

NumOutNumOutNumOutnumOutnum_out (input_control)  number → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Anzahl Ausgabeneuronen.

Default: 100

GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (input_control)  attribute.name(-array) → HTupleMaybeSequence[str]HTupleHtuple (string) (string) (HString) (char*)

Namen der generischen Eingabeparameter.

Default: []

Werteliste: '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_variance_norm'"bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm""bias_filler_variance_norm", 'bias_term'"bias_term""bias_term""bias_term""bias_term", 'is_inference_output'"is_inference_output""is_inference_output""is_inference_output""is_inference_output", '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", '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_variance_norm'"weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm""weight_filler_variance_norm"

GenParamValueGenParamValueGenParamValuegenParamValuegen_param_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)

Werte der generischen Eingabeparameter.

Default: []

Wertevorschläge: 'xavier'"xavier""xavier""xavier""xavier", 'msra'"msra""msra""msra""msra", 'const'"const""const""const""const", 'nearest_neighbor'"nearest_neighbor""nearest_neighbor""nearest_neighbor""nearest_neighbor", 'bilinear'"bilinear""bilinear""bilinear""bilinear", 'norm_in'"norm_in""norm_in""norm_in""norm_in", 'norm_out'"norm_out""norm_out""norm_out""norm_out", 'norm_average'"norm_average""norm_average""norm_average""norm_average", 'true'"true""true""true""true", 'false'"false""false""false""false", 1.0, 0.9, 0.0

DLLayerDenseDLLayerDenseDLLayerDenseDLLayerDensedllayer_dense (output_control)  dl_layer → HDlLayer, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Dense-Layer.

Modul

Deep Learning Training

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