def print_graph(func):
for i, node in enumerate(func.maker.env.toposort()):
print i, node
# Last node should be the output
print i, pprint(node.outputs[0])
def print_graph(func):
for i, node in enumerate(func.maker.env.toposort()):
print i, node
# Last node should be the output
print i, pprint(node.outputs[0])
import theano
import theano.tensor as T
x = T.scalar()
y = 3*(x**2) + 1
theano.pprint(y)
theano.printing.debugprint(y)
print y.eval({x: 2})
f = theano.function([x], y)
print f(2)
X = T.vector()
X = T.matrix()
X = T.tensor3()
X = T.tensor4()
h2 = T.dot(h1, W2.T)
# compile and call the actual function
f = theano.function([x], h2)
f(numpy.random.rand(5, 10))
"""
"""
import theano.tensor as tt
x = tt.vector('x')
y = tt.vector('y')
s = tt.sum(x**2 + tt.sin(y))
print s
theano.pprint(s)
#theano.ProfileMode.provided_optimizer=fast_compile #None
x = T.vector()
y = T.vector()
z = x + x
z = z + y
f = theano.function([x, y], z)
#theano.pprint(f)
#theano.printing.debugprint(f) 可以输出他的参数类型
f(np.ones((2,)), np.ones((3,)))
import theano
import theano.tensor as T
x = T.scalar()
y = 3 * (x**2) + 1
theano.pprint(y)
theano.printing.debugprint(y)
print y.eval({x: 2})
f = theano.function([x], y)
print f(2)
X = T.vector()
X = T.matrix()
X = T.tensor3()
X = T.tensor4()
import theano
from theano import printing
import theano.tensor as T
import numpy as np
print(T.scalar())
print(T.iscalar())
print(T.fscalar())
print(T.dscalar())
x = T.matrix('x')
y = T.matrix('y')
z = x + y
print(z)
print(theano.pprint(z))
print(printing.debugprint(z))
print(theano.pp(z))
print(z.eval({x: [[1, 2], [1, 3]], y: [[1, 0], [3, 4]]}))
addition = theano.function([x, y], [z])
print(addition([[1, 2], [1, 3]], [[1, 0], [3, 4]]))
print(printing.debugprint(addition))
print(addition(np.ones((2, 2), dtype=theano.config.floatX), np.zeros((2, 2), dtype=theano.config.floatX)))
a = T.zeros((2, 3))
print(a.eval())
b = T.identity_like(a)
print(b.eval())
c = T.arange(10)
print(c.eval())
print(c.ndim)
print(c.dtype)
def __repr__(self):
return theano.pprint(self.Y)
