Public API for tf.keras.internal.legacy.layers namespace.
Modules
experimental module: Public API for tf.keras.internal.legacy.layers.experimental namespace.
Classes
class AveragePooling1D: Average Pooling layer for 1D inputs.
class AveragePooling2D: Average pooling layer for 2D inputs (e.g. images).
class AveragePooling3D: Average pooling layer for 3D inputs (e.g. volumes).
class BatchNormalization: Batch Normalization layer from (Ioffe et al., 2015).
class Conv1D: 1D convolution layer (e.g. temporal convolution).
class Conv2D: 2D convolution layer (e.g. spatial convolution over images).
class Conv2DTranspose: Transposed 2D convolution layer (sometimes called 2D Deconvolution).
class Conv3D: 3D convolution layer (e.g. spatial convolution over volumes).
class Conv3DTranspose: Transposed 3D convolution layer (sometimes called 3D Deconvolution).
class Dense: Densely-connected layer class.
class Dropout: Applies Dropout to the input.
class Flatten: Flattens an input tensor while preserving the batch axis (axis 0).
class InputSpec: Specifies the rank, dtype and shape of every input to a layer.
class Layer: Base layer class.
class MaxPooling1D: Max Pooling layer for 1D inputs.
class MaxPooling2D: Max pooling layer for 2D inputs (e.g. images).
class MaxPooling3D: Max pooling layer for 3D inputs (e.g. volumes).
class SeparableConv1D: Depthwise separable 1D convolution.
class SeparableConv2D: Depthwise separable 2D convolution.
Functions
average_pooling1d(...): Average Pooling layer for 1D inputs.
average_pooling2d(...): Average pooling layer for 2D inputs (e.g. images).
average_pooling3d(...): Average pooling layer for 3D inputs (e.g. volumes).
batch_normalization(...): Functional interface for the batch normalization layer from_config(Ioffe et al., 2015).
conv1d(...): Functional interface for 1D convolution (e.g. temporal convolution).
conv2d(...): Functional interface for the 2D convolution layer.
conv2d_transpose(...): Functional interface for transposed 2D convolution layer.
conv3d(...): Functional interface for the 3D convolution layer.
conv3d_transpose(...): Functional interface for transposed 3D convolution layer.
dense(...): Functional interface for the densely-connected layer.
dropout(...): Applies Dropout to the input.
flatten(...): Flattens an input tensor while preserving the batch axis (axis 0).
max_pooling1d(...): Max Pooling layer for 1D inputs.
max_pooling2d(...): Max pooling layer for 2D inputs (e.g. images).
max_pooling3d(...): Max pooling layer for 3D inputs (e.g.
separable_conv1d(...): Functional interface for the depthwise separable 1D convolution layer.
separable_conv2d(...): Functional interface for the depthwise separable 2D convolution layer.