create_dl_layer_dropoutT_create_dl_layer_dropoutCreateDlLayerDropoutCreateDlLayerDropoutcreate_dl_layer_dropout (Operator)
Name
create_dl_layer_dropoutT_create_dl_layer_dropoutCreateDlLayerDropoutCreateDlLayerDropoutcreate_dl_layer_dropout — Create a DropOut layer.
Signature
void CreateDlLayerDropout(const HTuple& DLLayerInput, const HTuple& LayerName, const HTuple& Probability, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* DLLayerDropOut)
HDlLayer HDlLayer::CreateDlLayerDropout(const HString& LayerName, double Probability, const HTuple& GenParamName, const HTuple& GenParamValue) const
HDlLayer HDlLayer::CreateDlLayerDropout(const HString& LayerName, double Probability, const HString& GenParamName, const HString& GenParamValue) const
HDlLayer HDlLayer::CreateDlLayerDropout(const char* LayerName, double Probability, const char* GenParamName, const char* GenParamValue) const
HDlLayer HDlLayer::CreateDlLayerDropout(const wchar_t* LayerName, double Probability, const wchar_t* GenParamName, const wchar_t* GenParamValue) const
(
Windows only)
static void HOperatorSet.CreateDlLayerDropout(HTuple DLLayerInput, HTuple layerName, HTuple probability, HTuple genParamName, HTuple genParamValue, out HTuple DLLayerDropOut)
HDlLayer HDlLayer.CreateDlLayerDropout(string layerName, double probability, HTuple genParamName, HTuple genParamValue)
HDlLayer HDlLayer.CreateDlLayerDropout(string layerName, double probability, string genParamName, string genParamValue)
Description
The operator create_dl_layer_dropoutcreate_dl_layer_dropoutCreateDlLayerDropoutCreateDlLayerDropoutcreate_dl_layer_dropout creates a DropOut layer with
probability ProbabilityProbabilityProbabilityprobabilityprobability and returns the handle DLLayerDropOutDLLayerDropOutDLLayerDropOutDLLayerDropOutdllayer_drop_out.
The parameter DLLayerInputDLLayerInputDLLayerInputDLLayerInputdllayer_input determines the feeding input layer and
expects the layer handle as value.
The parameter LayerNameLayerNameLayerNamelayerNamelayer_name sets an individual layer name.
Note that if creating a model using create_dl_modelcreate_dl_modelCreateDlModelCreateDlModelcreate_dl_model each layer of
the created network must have a unique name.
During training, activations within DLLayerInputDLLayerInputDLLayerInputDLLayerInputdllayer_input are set to zero
with probability ProbabilityProbabilityProbabilityprobabilityprobability. All other activations are rescaled
with (1 - ProbabilityProbabilityProbabilityprobabilityprobability).
The following generic parameters GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and the corresponding
values GenParamValueGenParamValueGenParamValuegenParamValuegen_param_value are supported:
- 'is_inference_output'"is_inference_output""is_inference_output""is_inference_output""is_inference_output":
-
Determines whether apply_dl_modelapply_dl_modelApplyDlModelApplyDlModelapply_dl_model will include the output of this
layer in the dictionary DLResultBatchDLResultBatchDLResultBatchDLResultBatchdlresult_batch even without specifying this
layer in OutputsOutputsOutputsoutputsoutputs ('true'"true""true""true""true") or not ('false'"false""false""false""false").
Default: 'false'"false""false""false""false"
Certain parameters of layers created using this operator
create_dl_layer_dropoutcreate_dl_layer_dropoutCreateDlLayerDropoutCreateDlLayerDropoutcreate_dl_layer_dropout can be set and retrieved using
further operators.
The following tables give an overview, which parameters can be set
using set_dl_model_layer_paramset_dl_model_layer_paramSetDlModelLayerParamSetDlModelLayerParamset_dl_model_layer_param and which ones can be retrieved
using get_dl_model_layer_paramget_dl_model_layer_paramGetDlModelLayerParamGetDlModelLayerParamget_dl_model_layer_param or get_dl_layer_paramget_dl_layer_paramGetDlLayerParamGetDlLayerParamget_dl_layer_param. Note, the
operators set_dl_model_layer_paramset_dl_model_layer_paramSetDlModelLayerParamSetDlModelLayerParamset_dl_model_layer_param and get_dl_model_layer_paramget_dl_model_layer_paramGetDlModelLayerParamGetDlModelLayerParamget_dl_model_layer_param
require a model created by create_dl_modelcreate_dl_modelCreateDlModelCreateDlModelcreate_dl_model.
|
Generic Layer Parameters |
set |
get |
|
'is_inference_output'"is_inference_output""is_inference_output""is_inference_output""is_inference_output" |
x |
x
|
|
'num_trainable_params'"num_trainable_params""num_trainable_params""num_trainable_params""num_trainable_params" |
|
x
|
Execution Information
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
Parameters
DLLayerInputDLLayerInputDLLayerInputDLLayerInputdllayer_input (input_control) dl_layer → HDlLayer, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
Feeding layer.
LayerNameLayerNameLayerNamelayerNamelayer_name (input_control) string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
Name of the output layer.
ProbabilityProbabilityProbabilityprobabilityprobability (input_control) number → HTuplefloatHTupleHtuple (real) (double) (double) (double)
Probability.
Default:
0.5
GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (input_control) attribute.name(-array) → HTupleMaybeSequence[str]HTupleHtuple (string) (string) (HString) (char*)
Generic input parameter names.
Default:
[]
List of values:
'is_inference_output'"is_inference_output""is_inference_output""is_inference_output""is_inference_output"
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)
Generic input parameter values.
Default:
[]
Suggested values:
'true'"true""true""true""true", 'false'"false""false""false""false"
DLLayerDropOutDLLayerDropOutDLLayerDropOutDLLayerDropOutdllayer_drop_out (output_control) dl_layer → HDlLayer, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
DropOut layer.
Module
Deep Learning Training