theanets.layers.base.Reshape¶
-
class
theanets.layers.base.
Reshape
(name=None, **kwargs)[source]¶ Reshape an input to have different numbers of dimensions.
Parameters: - shape : sequence of int
The desired shape of the output “vectors” for this layer. This should not include the leading axis of the actual shape of the data arrays processed by the graph! For example, to reshape input vectors of length a * b into 2D output “images” use
(a, b)
as the shape—not(batch-size, a, b)
.
Notes
In
theanets
, the leading axis of a data array always runs over the examples in a mini-batch. Since the number of examples in a mini-batch is constant throughout a network graph, this layer always preserves the shape of the leading axis of its inputs.If you want to vectorize a data array, you could do that using
(-1, )
as the shape for this layer. But it’s often easier to read if you use theFlatten
layer type to reshape a layer’s output into a flat vector.Outputs
out
— reshaped inputs
Attributes: - shape : list of int
The desired shape of the output “vectors” for this layer.
-
__init__
(name=None, **kwargs)¶ x.__init__(…) initializes x; see help(type(x)) for signature
Methods
__init__
([name])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. -
transform
(inputs)[source]¶ 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.