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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from . import NeuralNetwork
class ComputationalGraph(NeuralNetwork):
"""
A simple neural network that the last layer outputs cost.
def __init__(self, input_dim=0, model=None, input_tensor=None,
cost=None, output=None, blocks=None, input_vars=None, target_vars=None):
Create a basic network.
Parameters:
input_dim - dimension of input variable
model - a short hand to specify the model
config - network configuration
input_tensor - specify the tensor of input if it's special
super(ComputationalGraph, self).__init__(input_dim, input_tensor=input_tensor)
if model:
self.stack(model)
if output:
self.stack(output)
if cost:
self.stack(cost)
if blocks:
self.register(*blocks)
if input_vars:
self.input_variables = [t.tensor for t in input_vars]
if target_vars:
self.target_variables = [t.tensor for t in target_vars]
@property
def cost(self):
return self.output
def test_cost(self):
return self.test_output
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