Intro
Variable
is a way to to define inputs to the network, very much similar to the Input
class in Keras
. However, since we need to perform differentiation and other operations on the network, we cannot just use Input
. Instead, we need to define the inputs of the network through Variable
.
For scientific computations, a Variable
has only a dimension of 1. Therefore, if you need to have a three-dimensional coordinate inputs, you need to define three variables:
from sciann import Variable
x = Variable('x')
y = Variable('y')
z = Variable('z')
This is precisely because we need to perform differentiation with respect to (x, y, z).
Variable
sciann.functionals.variable.Variable(name=None, units=1, tensor=None, dtype=None)
Configures the Variable
object for the network's input.
Arguments
- name: String. Required as derivatives work only with layer names.
- units: Int. Number of feature of input var.
- tensor: Tensorflow
Tensor
. Can be pass as the input path. - dtype: data-type of the network parameters, can be ('float16', 'float32', 'float64').
Raises