In [1]:
import numpy as np
import theano
import theano.tensor as T
import theano.d3printing.d3printing as d3p

%load_ext autoreload
%autoreload 2
Couldn't import dot_parser, loading of dot files will not be possible.
In [2]:
# Logistic regression model
num_in = 64**2
num_out = 10
W = theano.shared(np.random.randn(num_in, num_out), name='W', borrow=True)
b = theano.shared(np.random.randn(num_out), name='b', borrow=True)
X = T.dmatrix('X')
y = T.nnet.softmax(X.dot(W) + b)
pred = y > 0.5
In [3]:
d3p.d3print(y, 'logreg_y.html')
The output file is available at logreg_y.html
In [4]:
d3p.d3print(pred, 'logreg_pred.html')
The output file is available at logreg_pred.html