pymoose.predictors.neural_network_predictor module#

class pymoose.predictors.neural_network_predictor.Activation(value)[source]#

Bases: enum.Enum

An enumeration.

IDENTITY = 1#
RELU = 4#
SIGMOID = 2#
SOFTMAX = 3#
class pymoose.predictors.neural_network_predictor.NeuralNetwork(weights, biases, activations)[source]#

Bases: pymoose.predictors.predictor.Predictor

activation_fn(z, i)[source]#
apply_layer(input, i, fixedpoint_dtype)[source]#
classmethod from_onnx(model_proto)[source]#
predictor_fn(x, fixedpoint_dtype)[source]#