Replace theano.tensor alias T with tt in tests.compile

tests/compile/test_mode.py

 import pytest
 
 import theano
-import theano.tensor as T
+import theano.tensor as tt
 
 from theano.compile.mode import Mode, AddFeatureOptimizer
 from theano.gof.toolbox import NoOutputFromInplace
@@ -11,10 +11,10 @@ from theano.gof.toolbox import NoOutputFromInplace
     not theano.config.cxx, reason="G++ not available, so we need to skip this test."
 )
 def test_no_output_from_implace():
-    x = T.matrix()
-    y = T.matrix()
-    a = T.dot(x, y)
-    b = T.tanh(a)
+    x = tt.matrix()
+    y = tt.matrix()
+    a = tt.dot(x, y)
+    b = tt.tanh(a)
 
     # Ensure that the elemwise op that produces the output is inplace when
     # using a mode that does not include the optimization

tests/compile/test_modes.py

@@ -5,7 +5,7 @@ Test compilation modes
 import copy
 
 import theano
-import theano.tensor as T
+import theano.tensor as tt
 from theano.compile import Mode
 
 
@@ -25,8 +25,8 @@ class TestBunchOfModes:
         modes = predef_modes + [Mode(linker, "fast_run") for linker in linkers]
 
         for mode in modes:
-            x = T.matrix()
-            y = T.vector()
+            x = tt.matrix()
+            y = tt.vector()
             f = theano.function([x, y], x + y, mode=mode)
             # test that it runs something
             f([[1, 2], [3, 4]], [5, 6])

tests/compile/test_nanguardmode.py

@@ -2,23 +2,23 @@
 This test is for testing the NanGuardMode.
 """
 
-
 import logging
 import pytest
 
 import numpy as np
-from theano.compile.nanguardmode import NanGuardMode
 import theano
-import theano.tensor as T
+import theano.tensor as tt
+
+from theano.compile.nanguardmode import NanGuardMode
 
 
 def test_NanGuardMode():
     # Tests if NanGuardMode is working by feeding in numpy.inf and numpy.nans
     # intentionally. A working implementation should be able to capture all
     # the abnormalties.
-    x = T.matrix()
+    x = tt.matrix()
     w = theano.shared(np.random.randn(5, 7).astype(theano.config.floatX))
-    y = T.dot(x, w)
+    y = tt.dot(x, w)
 
     fun = theano.function(
         [x], y, mode=NanGuardMode(nan_is_error=True, inf_is_error=True)
@@ -51,8 +51,8 @@ def test_NanGuardMode():
     nana = np.tile(np.asarray(np.nan).astype(theano.config.floatX), (3, 4, 5))
     biga = np.tile(np.asarray(1e20).astype(theano.config.floatX), (3, 4, 5))
 
-    x = T.tensor3()
-    y = x[:, T.arange(2), T.arange(2), None]
+    x = tt.tensor3()
+    y = x[:, tt.arange(2), tt.arange(2), None]
     fun = theano.function(
         [x], y, mode=NanGuardMode(nan_is_error=True, inf_is_error=True)
     )

tests/compile/test_profiling.py

@@ -4,7 +4,7 @@
 import numpy as np
 
 import theano
-import theano.tensor as T
+import theano.tensor as tt
 
 from six.moves import StringIO
 from theano.ifelse import ifelse
@@ -23,10 +23,10 @@ class TestProfiling:
             theano.config.profile_memory = True
             theano.config.profiling.min_peak_memory = True
 
-            x = [T.fvector("val%i" % i) for i in range(3)]
+            x = [tt.fvector("val%i" % i) for i in range(3)]
 
             z = []
-            z += [T.outer(x[i], x[i + 1]).sum(axis=1) for i in range(len(x) - 1)]
+            z += [tt.outer(x[i], x[i + 1]).sum(axis=1) for i in range(len(x) - 1)]
             z += [x[i] + x[i + 1] for i in range(len(x) - 1)]
 
             p = theano.ProfileStats(False, gpu_checks=False)
@@ -79,10 +79,10 @@ class TestProfiling:
             theano.config.profile = True
             theano.config.profile_memory = True
 
-            a, b = T.scalars("a", "b")
-            x, y = T.scalars("x", "y")
+            a, b = tt.scalars("a", "b")
+            x, y = tt.scalars("x", "y")
 
-            z = ifelse(T.lt(a, b), x * 2, y * 2)
+            z = ifelse(tt.lt(a, b), x * 2, y * 2)
 
             p = theano.ProfileStats(False, gpu_checks=False)