Operator Reference

create_dl_layer_identityT_create_dl_layer_identityCreateDlLayerIdentityCreateDlLayerIdentitycreate_dl_layer_identity (Operator)

create_dl_layer_identityT_create_dl_layer_identityCreateDlLayerIdentityCreateDlLayerIdentitycreate_dl_layer_identity — Create an identity layer.

Signature

create_dl_layer_identity( : : DLLayerInput, LayerName, GenParamName, GenParamValue : DLLayerIdentity)

Description

The operator create_dl_layer_identitycreate_dl_layer_identityCreateDlLayerIdentityCreateDlLayerIdentitycreate_dl_layer_identity creates an identity layer whose handle is returned in DLLayerIdentityDLLayerIdentityDLLayerIdentityDLLayerIdentitydllayer_identity.

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.

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_identitycreate_dl_layer_identityCreateDlLayerIdentityCreateDlLayerIdentitycreate_dl_layer_identity 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.

Layer Parameters	`set`	`get`
'input_layer'"input_layer""input_layer""input_layer""input_layer" (`DLLayerInputDLLayerInputDLLayerInputDLLayerInputdllayer_input`)		`x`
'name'"name""name""name""name" (`LayerNameLayerNameLayerNamelayerNamelayer_name`)	`x`	`x`
'output_layer'"output_layer""output_layer""output_layer""output_layer" (`DLLayerIdentityDLLayerIdentityDLLayerIdentityDLLayerIdentitydllayer_identity`)		`x`
'shape'"shape""shape""shape""shape"		`x`
'type'"type""type""type""type"		`x`

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 → (handle)

Feeding layer.

LayerNameLayerNameLayerNamelayerNamelayer_name (input_control) string → (string)

Name of the output layer.

GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (input_control) attribute.name(-array) → (string)

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) → (string / integer / real)

Generic input parameter values.

Default: []

Suggested values: 'true'"true""true""true""true", 'false'"false""false""false""false"

DLLayerIdentityDLLayerIdentityDLLayerIdentityDLLayerIdentitydllayer_identity (output_control) dl_layer → (handle)

Identity layer.

Example (HDevelop)

* Create a model that concatinates the output of a convolution layer.
create_dl_layer_input ('input', [10,10,3], [], [], DLLayerInput)
create_dl_layer_convolution (DLLayerInput, 'conv', 3, 1, 1, 8, 1, 'none', \
                            'none', [], [], DLLayerConvolution)
* Using the same layer multiple times as input does not work, so make a copy.
create_dl_layer_identity (DLLayerConvolution, 'conv_copy', [], [], \
                          DLLayerIdentity)
create_dl_layer_concat ([DLLayerConvolution, DLLayerIdentity], 'concat', \
                        'depth', [], [], DLLayerConcat)
create_dl_model (DLLayerConcat, DLModelHandle)

Possible Successors

create_dl_layer_elementwisecreate_dl_layer_elementwiseCreateDlLayerElementwiseCreateDlLayerElementwisecreate_dl_layer_elementwise, create_dl_layer_concatcreate_dl_layer_concatCreateDlLayerConcatCreateDlLayerConcatcreate_dl_layer_concat

Module

Deep Learning Professional

Operators