theanets.layers.base.Input

class theanets.layers.base.Input(name='in', ndim=2, sparse=False, **kwargs)

A layer that receives external input data.

Input layers are responsible for the Theano variables that represent input to a network. The name of the layer is passed along to the symbolic Theano input variable.

Input layers essentially add only noise to the input data (if desired), but otherwise reproduce their inputs exactly.

Parameters:

ndim : int, optional

Number of dimensions required to store the input data for this layer. If a shape tuple is given, this defaults to 1 + len(shape); otherwise, this defaults to 2, i.e., (num-examples, num-variables).

sparse : bool or str, optional

If this is 'csr' or 'csc', then the inputs to the loss will be stored as sparse matrices in the CSR or CSC format (respectively). If this is True, sparse input will be enabled in CSR format. By default this is False, which means inputs are dense.

Raises:

AssertionError :

If sparse is enabled and ndim is not 2.

__init__(name='in', ndim=2, sparse=False, **kwargs)

x.__init__(…) initializes x; see help(type(x)) for signature

Methods

__init__([name, ndim, sparse])	x.__init__(…) initializes x; see help(type(x)) for signature
add_bias(name, size[, mean, std])	Helper method to create a new bias vector.
add_weights(name, nin, nout[, mean, std, …])	Helper method to create a new weight matrix.
bind(graph[, reset, initialize])	Bind this layer into a computation graph.
connect(inputs)	Create Theano variables representing the outputs of this layer.
find(key)	Get a shared variable for a parameter by name.
full_name(name)	Return a fully-scoped name for the given layer output.
log()	Log some information about this layer.
log_params()	Log information about this layer’s parameters.
resolve_inputs(layers)	Resolve the names of inputs for this layer into shape tuples.
resolve_outputs()	Resolve the names of outputs for this layer into shape tuples.
setup()	Set up the parameters and initial values for this layer.
to_spec()	Create a specification dictionary for this layer.
transform(inputs)	Transform the inputs for this layer into an output for the layer.

Attributes

input_name	Name of layer input (for layers with one input).
input_shape	Shape of layer input (for layers with one input).
input_size	Size of layer input (for layers with one input).
output_name	Full name of the default output for this layer.
output_shape	Shape of default output from this layer.
output_size	Number of “neurons” in this layer’s default output.
params	A list of all parameters in this layer.

log()

Log some information about this layer.

resolve_inputs(layers)

Resolve the names of inputs for this layer into shape tuples.

Parameters:

layers : list of Layer

A list of the layers that are available for resolving inputs.

Raises:

theanets.util.ConfigurationError :

If an input cannot be resolved.

resolve_outputs()

Resolve the names of outputs for this layer into shape tuples.

transform(inputs)

Transform the inputs for this layer into an output for the layer.

Parameters:

inputs : dict of Theano expressions

Symbolic inputs to this layer, given as a dictionary mapping string names to Theano expressions. See Layer.connect().

Returns:

output : Theano expression

The output for this layer is the same as the input.

updates : list

An empty updates list.