dlpy.layers.Segmentation

class dlpy.layers.Segmentation(name=None, act=None, error=None, target_scale=1.0, src_layers=None, **kwargs)

Segmentation layer

Parameters

namestring, optional

Specifies the name of the layer.

actstring, optional

Specifies the activation function. possible values: [ AUTO, IDENTITY, LOGISTIC, SIGMOID, TANH, RECTIFIER, RELU, SOFPLUS, ELU, LEAKY, FCMP ] default: AUTO

fcmp_actstring, optional

Specifies the FCMP activation function for the layer.

src_layersiterable Layer, optional

Specifies the layers directed to this layer.

heightint, required

Specifies the height of the input data. By default the height is determined automatically when the model training begins.

widthint, required

Specifies the width of the input data. By default the width is determined automatically when the model training begins.

depthint, required

Specifies the depth of the feature maps.

target_scaledouble

Specifies the factor used to scale target values for a segmentation layer.

src_layersiterable Layer, optional

Specifies the layers directed to this layer.

Returns

Segmentation

__init__(name=None, act=None, error=None, target_scale=1.0, src_layers=None, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([name, act, error, target_scale, …])	Initialize self.
count_instances()
format_name([block_num, local_count])	Format the name of the layer
get_number_of_instances()
to_model_params()	Convert the model configuration to CAS action parameters

Attributes

can_be_last_layer
kernel_size
layer_id
num_bias
num_weights
number_of_instances
output_size
rnn_summary	Return a DataFrame containing the layer information for rnn models
summary	Return a DataFrame containing the layer information
type
type_desc
type_label