Module: tf.compat.v1.layers

Public API for tf.layers namespace.

Modules

experimental module: Public API for tf.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 layer (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.