SiaNet.Model.Layers Namespace
Classes
Class | Description | |
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Activation |
Applies an activation function to an output.
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AvgPool1D |
Average pooling for temporal data.
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AvgPool2D |
Average pooling operation for spatial data.
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AvgPool3D |
Average pooling operation for 3D data (spatial or spatio-temporal).
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BatchNorm |
Batch normalization layer (Ioffe and Szegedy, 2014). Normalize the activations of the previous layer at each batch, i.e.applies a transformation that maintains the mean activation close to 0 and the activation standard deviation close to 1.
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Conv1D |
1D convolution layer (e.g. temporal convolution). This layer creates a convolution kernel that is convolved with the layer input over a single spatial (or temporal) dimension to produce a tensor of outputs. If use_bias is True, a bias vector is created and added to the outputs. Finally, if activation is not None, it is applied to the outputs as well.
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Conv2D |
2D convolution layer (e.g. spatial convolution over images). This layer creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs. If use_bias is True, a bias vector is created and added to the outputs. Finally, if activation is not None, it is applied to the outputs as well.
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Conv3D |
3D convolution layer (e.g. spatial convolution over volumes). This layer creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs. If use_bias is True, a bias vector is created and added to the outputs. Finally, if activation is not None, it is applied to the outputs as well.
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Dense |
Dense implements the operation: output = activation(dot(input, kernel) + bias) where activation is the element-wise activation function passed as the activation argument, kernel is a weights matrix created by the layer, and bias is a bias vector created by the layer (only applicable if use_bias is True).
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Dropout |
Dropout consists in randomly setting a fraction rate of input units to 0 at each update during training time, which helps prevent overfitting.
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GlobalAvgPool1D |
Global average pooling operation for temporal data.
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GlobalAvgPool2D |
Global average pooling operation for spatial data.
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GlobalAvgPool3D |
Global average pooling operation for 3D data (spatial or spatio-temporal).
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GlobalMaxPool1D |
Global max pooling operation for temporal data.
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GlobalMaxPool2D |
Global max pooling operation for spatial data.
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GlobalMaxPool3D |
Global max pooling 3D data (spatial or spatio-temporal).
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MaxPool1D |
Max pooling operation for temporal data.
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MaxPool2D |
Max pooling operation for spatial data.
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MaxPool3D |
Max pooling operation for 3D data (spatial or spatio-temporal).
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