Package mdp :: Package hinet :: Class SameInputLayer

Class SameInputLayer

SameInputLayer is a layer were all nodes receive the full input.

So instead of splitting the input according to node dimensions, all nodes
receive the complete input data.

Instance Methods

[hide private]

__init__(self, nodes, dtype=None)
Setup the layer with the given list of nodes.

_execute(self, x, *args, **kwargs)
Process the data through the internal nodes.

_pre_execution_checks(self, x)
Make sure that output_dim is set and then perform nromal checks.

_train(self, x, *args, **kwargs)
Perform single training step by training the internal nodes.

execute(self, x, *args, **kwargs)
Process the data through the internal nodes.

train(self, x, *args, **kwargs)
Perform single training step by training the internal nodes.

Inherited from unreachable.newobject: __long__, __native__, __nonzero__, __unicode__, next

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __subclasshook__

Inherited from Layer

__contains__(self, item)

__getitem__(self, key)

__iter__(self)

__len__(self)

_check_props(self, dtype)
Check the compatibility of the properties of the internal nodes.

_get_output_dim_from_nodes(self)
Calculate the output_dim from the nodes and return it.

_get_supported_dtypes(self)
Return the list of dtypes supported by this node.

_get_train_seq(self)
Return the train sequence.

_inverse(self, x, *args, **kwargs)
Combine the inverse of all the internal nodes.

_set_dtype(self, t)

_stop_training(self, *args, **kwargs)
Stop training of the internal nodes.

inverse(self, x, *args, **kwargs)
Combine the inverse of all the internal nodes.

is_trainable(self)
Return True if the node can be trained, False otherwise.

stop_training(self, *args, **kwargs)
Stop training of the internal nodes.

Inherited from Node

__add__(self, other)

__call__(self, x, *args, **kwargs)
Calling an instance of Node is equivalent to calling its execute method.

__repr__(self)
repr(x)

__str__(self)
str(x)

_check_input(self, x)

_check_output(self, y)

_check_train_args(self, x, *args, **kwargs)

_if_training_stop_training(self)

_pre_inversion_checks(self, y)
This method contains all pre-inversion checks.

_refcast(self, x)
Helper function to cast arrays to the internal dtype.

_set_input_dim(self, n)

_set_output_dim(self, n)

copy(self, protocol=None)
Return a deep copy of the node.

get_current_train_phase(self)
Return the index of the current training phase.

get_dtype(self)
Return dtype.

get_input_dim(self)
Return input dimensions.

get_output_dim(self)
Return output dimensions.

get_remaining_train_phase(self)
Return the number of training phases still to accomplish.

get_supported_dtypes(self)
Return dtypes supported by the node as a list of numpy.dtype objects.

has_multiple_training_phases(self)
Return True if the node has multiple training phases.

is_training(self)
Return True if the node is in the training phase, False otherwise.

save(self, filename, protocol=-1)
Save a pickled serialization of the node to filename. If filename is None, return a string.

set_dtype(self, t)
Set internal structures' dtype.

set_input_dim(self, n)
Set input dimensions.

set_output_dim(self, n)
Set output dimensions.

Static Methods

[hide private]

is_invertible()
Return True if the node can be inverted, False otherwise.

Properties

[hide private]

Inherited from object: __class__

Inherited from Node

_train_seq
List of tuples:

dtype
dtype

input_dim
Input dimensions

output_dim
Output dimensions

supported_dtypes
Supported dtypes

Method Details

[hide private]

init(self, nodes, dtype=None)
(Constructor)

Setup the layer with the given list of nodes.

The input dimensions for the nodes must all be equal, the output
dimensions can differ (but must be set as well for simplicity reasons).

Keyword arguments:
nodes -- List of the nodes to be used.

Overrides: object.__init__

_execute(self, x, *args, **kwargs)

Process the data through the internal nodes.

Overrides: Node._execute

_pre_execution_checks(self, x)

Make sure that output_dim is set and then perform nromal checks.

Overrides: Node._pre_execution_checks

_train(self, x, *args, **kwargs)

Perform single training step by training the internal nodes.

Overrides: Node._train

execute(self, x, *args, **kwargs)

Process the data through the internal nodes.

Overrides: Node.execute

is_invertible()
Static Method

Return True if the node can be inverted, False otherwise.

Overrides: Node.is_invertible: (inherited documentation)

train(self, x, *args, **kwargs)

Perform single training step by training the internal nodes.

Overrides: Node.train

Class SameInputLayer

__init__(self, nodes, dtype=None) (Constructor)

_execute(self, x, *args, **kwargs)

_pre_execution_checks(self, x)

_train(self, x, *args, **kwargs)

execute(self, x, *args, **kwargs)

is_invertible() Static Method

train(self, x, *args, **kwargs)

init(self, nodes, dtype=None)
(Constructor)

is_invertible()
Static Method