# Network input¶

class lasagne.layers.InputLayer(shape, input_var=None, name=None, **kwargs)[source]

This layer holds a symbolic variable that represents a network input. A variable can be specified when the layer is instantiated, else it is created.

Parameters: shape : tuple of int or None elements The shape of the input. Any element can be None to indicate that the size of that dimension is not fixed at compile time. input_var : Theano symbolic variable or None (default: None) A variable representing a network input. If it is not provided, a variable will be created. ValueError If the dimension of input_var is not equal to len(shape)

Notes

The first dimension usually indicates the batch size. If you specify it, Theano may apply more optimizations while compiling the training or prediction function, but the compiled function will not accept data of a different batch size at runtime. To compile for a variable batch size, set the first shape element to None instead.

Examples

>>> from lasagne.layers import InputLayer
>>> l_in = InputLayer((100, 20))