Replace theano.tensor alias T with tt in tests

tests/test_breakpoint.py

 import numpy as np
 
 import theano
-import theano.tensor as T
+import theano.tensor as tt
 
 from theano.breakpoint import PdbBreakpoint
 
@@ -14,15 +14,15 @@ class TestPdbBreakpoint(utt.InferShapeTester):
 
         # Sample computation that involves tensors with different numbers
         # of dimensions
-        self.input1 = T.fmatrix()
-        self.input2 = T.fscalar()
-        self.output = T.dot(
+        self.input1 = tt.fmatrix()
+        self.input2 = tt.fscalar()
+        self.output = tt.dot(
             (self.input1 - self.input2), (self.input1 - self.input2).transpose()
         )
 
         # Declare the conditional breakpoint
         self.breakpointOp = PdbBreakpoint("Sum of output too high")
-        self.condition = T.gt(self.output.sum(), 1000)
+        self.condition = tt.gt(self.output.sum(), 1000)
         (
             self.monitored_input1,
             self.monitored_input2,
@@ -47,8 +47,8 @@ class TestPdbBreakpoint(utt.InferShapeTester):
         input2_value = 10.0
 
         grads = [
-            T.grad(self.monitored_input1.sum(), self.input1),
-            T.grad(self.monitored_input2.sum(), self.input2),
+            tt.grad(self.monitored_input1.sum(), self.input1),
+            tt.grad(self.monitored_input2.sum(), self.input2),
         ]
 
         # Add self.monitored_input1 as an output to the Theano function to

tests/test_dictionary_output.py

 import theano
-import theano.tensor as T
+import theano.tensor as tt
 
 
-class dictionary_output_checker:
+class TestDictionaryOutput:
     def test_output_dictionary(self):
         # Tests that theano.function works when outputs is a dictionary
 
-        x = T.scalar()
+        x = tt.scalar()
         f = theano.function([x], outputs={"a": x, "c": x * 2, "b": x * 3, "1": x * 4})
 
         outputs = f(10.0)
@@ -19,8 +19,8 @@ class dictionary_output_checker:
     def test_input_named_variables(self):
         # Tests that named variables work when outputs is a dictionary
 
-        x = T.scalar("x")
-        y = T.scalar("y")
+        x = tt.scalar("x")
+        y = tt.scalar("y")
 
         f = theano.function([x, y], outputs={"a": x + y, "b": x * y})
 
@@ -31,11 +31,11 @@ class dictionary_output_checker:
     def test_output_order_sorted(self):
         # Tests that the output keys are sorted correctly.
 
-        x = T.scalar("x")
-        y = T.scalar("y")
-        z = T.scalar("z")
-        e1 = T.scalar("1")
-        e2 = T.scalar("2")
+        x = tt.scalar("x")
+        y = tt.scalar("y")
+        z = tt.scalar("z")
+        e1 = tt.scalar("1")
+        e2 = tt.scalar("2")
 
         f = theano.function(
             [x, y, z, e1, e2], outputs={"x": x, "y": y, "z": z, "1": e1, "2": e2}
@@ -51,16 +51,16 @@ class dictionary_output_checker:
         # Tests that one can compose two theano functions when the outputs are
         # provided in a dictionary.
 
-        x = T.scalar("x")
-        y = T.scalar("y")
+        x = tt.scalar("x")
+        y = tt.scalar("y")
 
         a = x + y
         b = x * y
 
         f = theano.function([x, y], outputs={"a": a, "b": b})
 
-        a = T.scalar("a")
-        b = T.scalar("b")
+        a = tt.scalar("a")
+        b = tt.scalar("b")
 
         l = a + b
         r = a * b
@@ -75,7 +75,7 @@ class dictionary_output_checker:
     def test_output_list_still_works(self):
         # Test that theano.function works if outputs is a list.
 
-        x = T.scalar("x")
+        x = tt.scalar("x")
 
         f = theano.function([x], outputs=[x * 3, x * 2, x * 4, x])
 
@@ -89,7 +89,7 @@ class dictionary_output_checker:
     def test_debug_mode_dict(self):
         # Tests that debug mode works where outputs is a dictionary.
 
-        x = T.scalar("x")
+        x = tt.scalar("x")
 
         f = theano.function(
             [x], outputs={"1": x, "2": 2 * x, "3": 3 * x}, mode="DEBUG_MODE"
@@ -104,7 +104,7 @@ class dictionary_output_checker:
     def test_debug_mode_list(self):
         # Tests that debug mode works where the outputs argument is a list.
 
-        x = T.scalar("x")
+        x = tt.scalar("x")
 
         f = theano.function([x], outputs=[x, 2 * x, 3 * x], mode="DEBUG_MODE")
 
@@ -118,7 +118,7 @@ class dictionary_output_checker:
         # Tests that an exception is thrown if a non-string key is used in
         # the outputs dictionary.
 
-        x = T.scalar("x")
+        x = tt.scalar("x")
         try:
             theano.function([x], outputs={1.0: x})
             raise Exception("Did not throw exception with 1.0 as only key")

tests/test_pickle_unpickle_theano_fn.py

@@ -12,11 +12,12 @@ The config option is in configdefaults.py
 
 This note is written by Li Yao.
 """
-from collections import OrderedDict
 import numpy as np
 import six.moves.cPickle as pickle
 import theano
-import theano.tensor as T
+import theano.tensor as tt
+
+from collections import OrderedDict
 
 floatX = "float32"
 
@@ -25,11 +26,11 @@ def test_pickle_unpickle_with_reoptimization():
     mode = theano.config.mode
     if mode in ["DEBUG_MODE", "DebugMode"]:
         mode = "FAST_RUN"
-    x1 = T.fmatrix("x1")
-    x2 = T.fmatrix("x2")
+    x1 = tt.fmatrix("x1")
+    x2 = tt.fmatrix("x2")
     x3 = theano.shared(np.ones((10, 10), dtype=floatX))
     x4 = theano.shared(np.ones((10, 10), dtype=floatX))
-    y = T.sum(T.sum(T.sum(x1 ** 2 + x2) + x3) + x4)
+    y = tt.sum(tt.sum(tt.sum(x1 ** 2 + x2) + x3) + x4)
 
     updates = OrderedDict()
     updates[x3] = x3 + 1
@@ -57,11 +58,11 @@ def test_pickle_unpickle_without_reoptimization():
     mode = theano.config.mode
     if mode in ["DEBUG_MODE", "DebugMode"]:
         mode = "FAST_RUN"
-    x1 = T.fmatrix("x1")
-    x2 = T.fmatrix("x2")
+    x1 = tt.fmatrix("x1")
+    x2 = tt.fmatrix("x2")
     x3 = theano.shared(np.ones((10, 10), dtype=floatX))
     x4 = theano.shared(np.ones((10, 10), dtype=floatX))
-    y = T.sum(T.sum(T.sum(x1 ** 2 + x2) + x3) + x4)
+    y = tt.sum(tt.sum(tt.sum(x1 ** 2 + x2) + x3) + x4)
 
     updates = OrderedDict()
     updates[x3] = x3 + 1

tests/test_updates.py

 import pytest
 import theano
-import theano.tensor as T
+import theano.tensor as tt
 
 from theano.updates import OrderedUpdates
 
@@ -21,7 +21,7 @@ class TestIfelse:
         with pytest.raises(TypeError):
             up.__setitem__(5, 7)
         with pytest.raises(TypeError):
-            up.__setitem__(T.vector(), 7)
+            up.__setitem__(tt.vector(), 7)
 
         up[theano.shared(88)] = 7
 

tests/unittest_tools.py

@@ -6,7 +6,7 @@ import pytest
 import numpy as np
 
 import theano
-import theano.tensor as T
+import theano.tensor as tt
 
 from functools import wraps
 from copy import copy, deepcopy
@@ -79,7 +79,7 @@ def verify_grad(op, pt, n_tests=2, rng=None, *args, **kwargs):
     if rng is None:
         seed_rng()
         rng = np.random
-    T.verify_grad(op, pt, n_tests, rng, *args, **kwargs)
+    tt.verify_grad(op, pt, n_tests, rng, *args, **kwargs)
 
 
 #
@@ -92,7 +92,7 @@ def verify_grad(op, pt, n_tests=2, rng=None, *args, **kwargs):
 #     print e.analytic_grad
 #     raise
 #
-verify_grad.E_grad = T.verify_grad.E_grad
+verify_grad.E_grad = tt.verify_grad.E_grad
 
 
 # A helpful class to check random values close to the boundaries
@@ -155,7 +155,7 @@ class OptimizationTestMixin(object):
 class OpContractTestMixin(object):
     # self.ops should be a list of instantiations of an Op class to test.
     # self.other_op should be an op which is different from every op
-    other_op = T.add
+    other_op = tt.add
 
     def copy(self, x):
         return copy(x)
@@ -296,7 +296,7 @@ class WrongValue(Exception):
 
 
 def assert_allclose(expected, value, rtol=None, atol=None):
-    if not T.basic._allclose(expected, value, rtol, atol):
+    if not tt.basic._allclose(expected, value, rtol, atol):
         raise WrongValue(expected, value, rtol, atol)