PlaceholderLayer

Layer replacing an unsupported Keras or ONNX layer

PlaceholderLayer is not recommended. Use importNetworkFromTensorFlow or importNetworkFromONNX to import a Keras or ONNX™ network as a dlnetwork object with custom layers.

Description

PlaceholderLayer is a layer that importKerasLayers and importONNXLayers insert into a layer array or layer graph in place of an unsupported Keras or ONNX layer.

Creation

Importing layers from a Keras or ONNX network that has layers that are not supported by Deep Learning Toolbox™ creates PlaceholderLayer objects.

Properties

Name — Layer name

character vector | string scalar

Layer name, specified as a character vector or a string scalar.

Data Types: char | string

Description — Layer description

character vector | string scalar

Layer description, specified as a character vector or a string scalar.

Data Types: char | string

Type — Layer type

character vector | string scalar

Layer type, specified as a character vector or a string scalar.

Data Types: char | string

KerasConfiguration — Keras configuration of layer

structure

Keras configuration of a layer, specified as a structure. The fields of the structure depend on the layer type.

Note

This property only exists if the layer was created when importing a Keras network.

Data Types: struct

ONNXNode — ONNX configuration of layer

structure

ONNX configuration of a layer, specified as a structure. The fields of the structure depend on the layer type.

Note

This property only exists if the layer was created when importing an ONNX network.

Data Types: struct

Weights — Imported weights

structure

Imported weights, specified as a structure.

Data Types: struct

Examples

Find and Explore Placeholder Layers

Specify the Keras network file to import layers from.

modelfile = 'digitsDAGnetwithnoise.h5';

Import the network architecture. The network includes some layer types that are not supported by Deep Learning Toolbox. The importKerasLayers function replaces each unsupported layer with a placeholder layer and returns a warning message.

lgraph = importKerasLayers(modelfile)

Warning: "importKerasLayers" is not recommended and will be removed in a future release. To import TensorFlow-Keras models, save using the SavedModel format and use importNetworkFromTensorFlow function.

Warning: Unable to import some Keras layers, because they are not supported by the Deep Learning Toolbox. They have been replaced by placeholder layers. To find these layers, call the function findPlaceholderLayers on the returned object.

lgraph = 
  LayerGraph with properties:

     InputNames: {'input_1'}
    OutputNames: {'ClassificationLayer_activation_1'}
         Layers: [15x1 nnet.cnn.layer.Layer]
    Connections: [15x2 table]

Display the imported layers of the network. Two placeholder layers replace the Gaussian noise layers in the Keras network.

lgraph.Layers

ans = 
  15x1 Layer array with layers:

     1   'input_1'                            Image Input             28x28x1 images
     2   'conv2d_1'                           2-D Convolution         20 7x7 convolutions with stride [1  1] and padding 'same'
     3   'conv2d_1_relu'                      ReLU                    ReLU
     4   'conv2d_2'                           2-D Convolution         20 3x3 convolutions with stride [1  1] and padding 'same'
     5   'conv2d_2_relu'                      ReLU                    ReLU
     6   'gaussian_noise_1'                   GaussianNoise           Placeholder for "GaussianNoise" Keras layer
     7   'gaussian_noise_2'                   GaussianNoise           Placeholder for "GaussianNoise" Keras layer
     8   'max_pooling2d_1'                    2-D Max Pooling         2x2 max pooling with stride [2  2] and padding 'same'
     9   'max_pooling2d_2'                    2-D Max Pooling         2x2 max pooling with stride [2  2] and padding 'same'
    10   'flatten_1'                          Keras Flatten           Flatten activations into 1-D assuming C-style (row-major) order
    11   'flatten_2'                          Keras Flatten           Flatten activations into 1-D assuming C-style (row-major) order
    12   'concatenate_1'                      Depth concatenation     Depth concatenation of 2 inputs
    13   'dense_1'                            Fully Connected         10 fully connected layer
    14   'activation_1'                       Softmax                 softmax
    15   'ClassificationLayer_activation_1'   Classification Output   crossentropyex

Find the placeholder layers using findPlaceholderLayers. The output argument contains the two placeholder layers that importKerasLayers inserted in place of the Gaussian noise layers of the Keras network.

placeholders = findPlaceholderLayers(lgraph)

placeholders = 
  2x1 PlaceholderLayer array with layers:

     1   'gaussian_noise_1'   GaussianNoise   Placeholder for "GaussianNoise" Keras layer
     2   'gaussian_noise_2'   GaussianNoise   Placeholder for "GaussianNoise" Keras layer

Specify a name for each placeholder layer.

gaussian1 = placeholders(1);
gaussian2 = placeholders(2);

Display the configuration of each placeholder layer.

gaussian1.KerasConfiguration

ans = struct with fields:
        trainable: 1
             name: 'gaussian_noise_1'
           stddev: 1.5000
    inbound_nodes: {{1x1 cell}}

gaussian2.KerasConfiguration

ans = struct with fields:
        trainable: 1
             name: 'gaussian_noise_2'
           stddev: 0.7000
    inbound_nodes: {{1x1 cell}}

Version History

Introduced in R2017b

R2024a: PlaceholderLayer is not recommended

PlaceholderLayer is not recommended. Use importNetworkFromTensorFlow or importNetworkFromONNX to import a Keras or ONNX network as a dlnetwork object with custom layers.