pep8

01_building_expressions/01_scalar.py

@@ -7,20 +7,23 @@
 from theano import function
 raise NotImplementedError("TODO: add any other imports you need")
 
+
 def make_scalar():
     """
     Returns a new Theano scalar.
     """
 
     raise NotImplementedError("TODO: implement this function.")
 
+
 def log(x):
     """
     Returns the logarithm of a Theano scalar x.
     """
 
     raise NotImplementedError("TODO: implement this function.")
 
+
 def add(x, y):
     """
     Adds two theano scalars together and returns the result.
@@ -36,7 +39,7 @@ def add(x, y):
     f = function([a, b], d)
     a = np.cast[a.dtype](1.)
     b = np.cast[b.dtype](2.)
-    actual = f(a,b)
+    actual = f(a, b)
     expected = 1. + np.log(2.)
     assert np.allclose(actual, expected)
     print "SUCCESS!"

01_building_expressions/01_scalar_soln.py

@@ -2,20 +2,23 @@
 from theano import function
 import theano.tensor as T
 
+
 def make_scalar():
     """
     Returns a new Theano scalar.
     """
 
     return T.scalar()
 
+
 def log(x):
     """
     Returns the logarithm of a Theano scalar x.
     """
 
     return T.log(x)
 
+
 def add(x, y):
     """
     Adds two theano scalars together and returns the result.
@@ -31,7 +34,7 @@ def add(x, y):
     f = function([a, b], d)
     a = np.cast[a.dtype](1.)
     b = np.cast[b.dtype](2.)
-    actual = f(a,b)
+    actual = f(a, b)
     expected = 1. + np.log(2.)
     assert np.allclose(actual, expected)
     print "SUCCESS!"

01_building_expressions/02_vector_mat.py

@@ -7,20 +7,23 @@
 from theano import function
 raise NotImplementedError("TODO: add any other imports you need")
 
+
 def make_vector():
     """
     Returns a new Theano vector.
     """
 
     raise NotImplementedError("TODO: implement this function.")
 
+
 def make_matrix():
     """
     Returns a new Theano matrix.
     """
 
     raise NotImplementedError("TODO: implement this function.")
 
+
 def elemwise_mul(a, b):
     """
     a: A theano matrix
@@ -30,6 +33,7 @@ def elemwise_mul(a, b):
 
     raise NotImplementedError("TODO: implement this function.")
 
+
 def matrix_vector_mul(a, b):
     """
     a: A theano matrix

01_building_expressions/02_vector_mat_soln.py

@@ -2,20 +2,23 @@
 from theano import function
 import theano.tensor as T
 
+
 def make_vector():
     """
     Returns a new Theano vector.
     """
 
     return T.vector()
 
+
 def make_matrix():
     """
     Returns a new Theano matrix.
     """
 
     return T.matrix()
 
+
 def elemwise_mul(a, b):
     """
     a: A theano matrix
@@ -25,6 +28,7 @@ def elemwise_mul(a, b):
 
     return a * b
 
+
 def matrix_vector_mul(a, b):
     """
     a: A theano matrix

01_building_expressions/03_tensor.py

@@ -7,6 +7,7 @@
 from theano import function
 raise NotImplementedError("TODO: add any other imports you need")
 
+
 def make_tensor(dim):
     """
     Returns a new Theano tensor with no broadcastable dimensions.
@@ -16,6 +17,7 @@ def make_tensor(dim):
 
     raise NotImplementedError("TODO: implement this function.")
 
+
 def broadcasted_add(a, b):
     """
     a: a 3D theano tensor
@@ -29,6 +31,7 @@ def broadcasted_add(a, b):
 
     raise NotImplementedError("TODO: implement this function.")
 
+
 def partial_max(a):
     """
     a: a 4D theano tensor
@@ -48,7 +51,7 @@ def partial_max(a):
     c = broadcasted_add(a, b)
     d = partial_max(c)
 
-    f = function([a, b,], d)
+    f = function([a, b], d)
 
     rng = np.random.RandomState([1, 2, 3])
     a_value = rng.randn(2, 2, 2).astype(a.dtype)

01_building_expressions/03_tensor_soln.py

@@ -2,6 +2,7 @@
 from theano import function
 import theano.tensor as T
 
+
 def make_tensor(dim):
     """
     Returns a new Theano tensor with no broadcastable dimensions.
@@ -10,6 +11,7 @@ def make_tensor(dim):
 
     return T.TensorType(broadcastable=tuple([False] * dim), dtype='float32')()
 
+
 def broadcasted_add(a, b):
     """
     a: a 3D theano tensor
@@ -23,6 +25,7 @@ def broadcasted_add(a, b):
 
     return a.dimshuffle(2, 'x', 1, 0) + b
 
+
 def partial_max(a):
     """
     a: a 4D theano tensor
@@ -42,7 +45,7 @@ def partial_max(a):
     c = broadcasted_add(a, b)
     d = partial_max(c)
 
-    f = function([a, b,], d)
+    f = function([a, b], d)
 
     rng = np.random.RandomState([1, 2, 3])
     a_value = rng.randn(2, 2, 2).astype(a.dtype)

02_compiling_and_running/01_function.py

@@ -6,6 +6,7 @@
 from theano import tensor as T
 raise NotImplementedError("TODO: add any other imports you need")
 
+
 def evaluate(x, y, expr, x_value, y_value):
     """
     x: A theano variable

02_compiling_and_running/01_function_soln.py

@@ -1,6 +1,7 @@
 from theano import tensor as T
 from theano import function
 
+
 def evaluate(x, y, expr, x_value, y_value):
     """
     x: A theano variable

02_compiling_and_running/02_shared.py

@@ -6,6 +6,7 @@
 import numpy as np
 raise NotImplementedError("TODO: add any other imports you need")
 
+
 def make_shared(shape):
     """
     Returns a theano shared variable containing a tensor of the specified
@@ -14,6 +15,7 @@ def make_shared(shape):
     """
     raise NotImplementedError("TODO: implement the function")
 
+
 def exchange_shared(a, b):
     """
     a: a theano shared variable
@@ -22,6 +24,7 @@ def exchange_shared(a, b):
     """
     raise NotImplementedError("TODO: implement the function")
 
+
 def make_exchange_func(a, b):
     """
     a: a theano shared variable
@@ -34,7 +37,6 @@ def make_exchange_func(a, b):
     raise NotImplementedError("TODO: implement the function")
 
 
-
 if __name__ == "__main__":
     a = make_shared((5, 4, 3))
     assert a.get_value().shape == (5, 4, 3)

02_compiling_and_running/02_shared_soln.py

@@ -3,6 +3,7 @@
 from theano import function
 from theano import shared
 
+
 def make_shared(shape):
     """
     Returns a theano shared variable containing a tensor of the specified
@@ -11,6 +12,7 @@ def make_shared(shape):
     """
     return shared(np.zeros(shape))
 
+
 def exchange_shared(a, b):
     """
     a: a theano shared variable
@@ -21,6 +23,7 @@ def exchange_shared(a, b):
     a.set_value(b.get_value())
     b.set_value(temp)
 
+
 def make_exchange_func(a, b):
     """
     a: a theano shared variable
@@ -38,7 +41,6 @@ def make_exchange_func(a, b):
     return f
 
 
-
 if __name__ == "__main__":
     a = make_shared((5, 4, 3))
     assert a.get_value().shape == (5, 4, 3)

03_modifying/01_grad.py

@@ -5,6 +5,7 @@
 # compute some derivative.
 from theano import tensor as T
 
+
 def grad_sum(x, y, z):
     """
     x: A theano variable
@@ -22,5 +23,5 @@ def grad_sum(x, y, z):
     y = T.scalar()
     z = x + y
     s = grad_sum(x, y, z)
-    assert s.eval({x: 0, y:0}) == 2
+    assert s.eval({x: 0, y: 0}) == 2
     print "SUCCESS!"

03_modifying/01_grad_soln.py

@@ -3,6 +3,7 @@
 #
 from theano import tensor as T
 
+
 def grad_sum(x, y, z):
     """
     x: A theano variable
@@ -14,12 +15,10 @@ def grad_sum(x, y, z):
 
     return sum(T.grad(z, [x, y]))
 
-
-
 if __name__ == "__main__":
     x = T.scalar()
     y = T.scalar()
     z = x + y
     s = grad_sum(x, y, z)
-    assert s.eval({x: 0, y:0}) == 2
+    assert s.eval({x: 0, y: 0}) == 2
     print "SUCCESS!"

03_modifying/02_traverse.py

@@ -8,6 +8,7 @@
 from theano import tensor as T
 raise NotImplementedError("Add any imports you need.")
 
+
 def arg_to_softmax(prob):
     """
     Oh no! Someone has passed you the probability output,

03_modifying/02_traverse_soln.py

@@ -2,6 +2,7 @@
 from theano.gof import Variable
 from theano import tensor as T
 
+
 def arg_to_softmax(prob):
     """
     Oh no! Someone has passed you the probability output,