src.model.deeplearn.arch.point_net_pwise_classif

Classes

PointNetPwiseClassif(**kwargs)

class src.model.deeplearn.arch.point_net_pwise_classif.PointNetPwiseClassif(**kwargs)

Author:

Alberto M. Esmoris Pena

A specialization of the PointNet architecture for point-wise classification.

See PointNet.

__init__(**kwargs)

See architecture.PointNet.__init__().

build_hidden(x, **kwargs)

Build the hidden layers of the PointNet neural network for point-wise classification tasks.

See point_net.PointNet.build_hidden().

Parameters:

x (tf.Tensor) – The input layer for the first hidden layer.

Returns:

The last hidden layer.

Return type:

tf.Tensor.

build_output(x, **kwargs)

Build the output layer of a PointNet neural network for point-wise classification tasks.

See architecture.Architecture.build_output().

Parameters:

x (tf.Tensor) – The input for the output layer.

Returns:

The output layer.

Return type:

tf.Tensor

build_features_structuring_layer(x)

Build a features structuring layer to be computed on the features at given layer x.

Parameters:

x (tf.Tensor) – Given layer that has features as output.

Returns:

The built features structuring layer.

Return type:

FeaturesStructuringLayer

prefit_logic_callback(cache_map)

The callback implementing any necessary logic immediately before fitting a PointNetPwiseClassif model.

Parameters:

cache_map – The key-word dictionary containing variables that are guaranteed to live at least during prefit, fit, and postfit.

Returns:

Nothing.

posfit_logic_callback(cache_map)

The callback implementing any necessary logic immediately after fitting a PointNetPwiseClassif model.

Parameters:

cache_map – The key-word dictionary containing variables that are guaranteed to live at least during prefit, fit, and postfit.

Returns:

Nothing.