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

tests/gof/test_graph_opt_caching.py

 import os
 import numpy as np
 import theano
-import theano.tensor as T
+import theano.tensor as tt
 
 floatX = "float32"
 
@@ -17,18 +17,18 @@ def test_graph_opt_caching():
     default = theano.config.cache_optimizations
     try:
         theano.config.cache_optimizations = True
-        a = T.fmatrix("a")
-        b = T.fmatrix("b")
+        a = tt.fmatrix("a")
+        b = tt.fmatrix("b")
         c = theano.shared(np.ones((10, 10), dtype=floatX))
         d = theano.shared(np.ones((10, 10), dtype=floatX))
-        e = T.sum(T.sum(T.sum(a ** 2 + b) + c) + d)
+        e = tt.sum(tt.sum(tt.sum(a ** 2 + b) + c) + d)
         f1 = theano.function([a, b], e, mode=mode)
 
-        m = T.fmatrix("x1")
-        n = T.fmatrix("x2")
+        m = tt.fmatrix("x1")
+        n = tt.fmatrix("x2")
         p = theano.shared(np.ones((10, 10), dtype=floatX))
         q = theano.shared(np.ones((10, 10), dtype=floatX))
-        j = T.sum(T.sum(T.sum(m ** 2 + n) + p) + q)
+        j = tt.sum(tt.sum(tt.sum(m ** 2 + n) + p) + q)
         f2 = theano.function([m, n], j, mode=mode)
 
         in1 = np.ones((10, 10), dtype=floatX)

tests/gof/test_lazy.py

@@ -7,7 +7,7 @@ from theano.gof.op import PureOp
 from theano.gof import Apply, generic
 from theano import function, Mode
 from theano.ifelse import ifelse
-import theano.tensor as T
+import theano.tensor as tt
 
 
 class IfElseIfElseIf(PureOp):
@@ -104,7 +104,7 @@ class NotImplementedOp(PureOp):
 
 
 def test_ifelse():
-    a = T.scalar()
+    a = tt.scalar()
     b = generic()
     c = generic()
 
@@ -143,17 +143,17 @@ def more_complex_test():
     notimpl = NotImplementedOp()
     ifelseifelseif = IfElseIfElseIf()
 
-    x1 = T.scalar("x1")
-    x2 = T.scalar("x2")
-    c1 = T.scalar("c1")
-    c2 = T.scalar("c2")
+    x1 = tt.scalar("x1")
+    x2 = tt.scalar("x2")
+    c1 = tt.scalar("c1")
+    c2 = tt.scalar("c2")
     t1 = ifelse(c1, x1, notimpl(x2))
     t1.name = "t1"
     t2 = t1 * 10
     t2.name = "t2"
     t3 = ifelse(c2, t2, x1 + t1)
     t3.name = "t3"
-    t4 = ifelseifelseif(T.eq(x1, x2), x1, T.eq(x1, 5), x2, c2, t3, t3 + 0.5)
+    t4 = ifelseifelseif(tt.eq(x1, x2), x1, tt.eq(x1, 5), x2, c2, t3, t3 + 0.5)
     t4.name = "t4"
 
     f = function([c1, c2, x1, x2], t4, mode=Mode(linker="vm", optimizer="fast_run"))

tests/gof/test_opt.py

+import theano.tensor as tt
+
 from theano.gof.type import Type
 from theano.gof.graph import Variable, Apply, Constant
 from theano.gof.op import Op
@@ -16,8 +18,6 @@ from theano.gof.opt import (
 )
 from theano.gof.fg import FunctionGraph
 
-from theano import tensor as T
-
 
 def as_variable(x):
     if not isinstance(x, Variable):
@@ -385,9 +385,9 @@ class TestMergeOptimizer:
 
     def est_one_assert_merge(self):
         # Merge two nodes, one has assert, the other not.
-        x1 = T.matrix("x1")
-        x2 = T.matrix("x2")
-        e = T.dot(x1, x2) + T.dot(T.opt.assert_op(x1, (x1 > x2).all()), x2)
+        x1 = tt.matrix("x1")
+        x2 = tt.matrix("x2")
+        e = tt.dot(x1, x2) + tt.dot(tt.opt.assert_op(x1, (x1 > x2).all()), x2)
         g = FunctionGraph([x1, x2], [e])
         MergeOptimizer().optimize(g)
         strg = theano.printing.debugprint(g, file="str")
@@ -407,10 +407,10 @@ class TestMergeOptimizer:
     def test_both_assert_merge_identical(self):
         # Merge two nodes, both have assert on the same node
         # with the same conditions.
-        x1 = T.matrix("x1")
-        x2 = T.matrix("x2")
-        e = T.dot(T.opt.assert_op(x1, (x1 > x2).all()), x2) + T.dot(
-            T.opt.assert_op(x1, (x1 > x2).all()), x2
+        x1 = tt.matrix("x1")
+        x2 = tt.matrix("x2")
+        e = tt.dot(tt.opt.assert_op(x1, (x1 > x2).all()), x2) + tt.dot(
+            tt.opt.assert_op(x1, (x1 > x2).all()), x2
         )
         g = FunctionGraph([x1, x2], [e])
         MergeOptimizer().optimize(g)
@@ -432,11 +432,11 @@ class TestMergeOptimizer:
     def est_both_assert_merge_1(self):
         # Merge two nodes, both have assert on the same node
         # with different conditions.
-        x1 = T.matrix("x1")
-        x2 = T.matrix("x2")
-        x3 = T.matrix("x3")
-        e = T.dot(T.opt.assert_op(x1, (x1 > x3).all()), x2) + T.dot(
-            T.opt.assert_op(x1, (x1 > x2).all()), x2
+        x1 = tt.matrix("x1")
+        x2 = tt.matrix("x2")
+        x3 = tt.matrix("x3")
+        e = tt.dot(tt.opt.assert_op(x1, (x1 > x3).all()), x2) + tt.dot(
+            tt.opt.assert_op(x1, (x1 > x2).all()), x2
         )
         g = FunctionGraph([x1, x2, x3], [e])
         MergeOptimizer().optimize(g)
@@ -476,11 +476,11 @@ class TestMergeOptimizer:
 
     def est_both_assert_merge_2(self):
         # Merge two nodes, both have assert on different node
-        x1 = T.matrix("x1")
-        x2 = T.matrix("x2")
-        x3 = T.matrix("x3")
-        e = T.dot(T.opt.assert_op(x1, (x1 > x3).all()), x2) + T.dot(
-            x1, T.opt.assert_op(x2, (x2 > x3).all())
+        x1 = tt.matrix("x1")
+        x2 = tt.matrix("x2")
+        x3 = tt.matrix("x3")
+        e = tt.dot(tt.opt.assert_op(x1, (x1 > x3).all()), x2) + tt.dot(
+            x1, tt.opt.assert_op(x2, (x2 > x3).all())
         )
         g = FunctionGraph([x1, x2, x3], [e])
         MergeOptimizer().optimize(g)
@@ -506,11 +506,11 @@ class TestMergeOptimizer:
 
     def est_both_assert_merge_2_reverse(self):
         # Test case "test_both_assert_merge_2" but in reverse order
-        x1 = T.matrix("x1")
-        x2 = T.matrix("x2")
-        x3 = T.matrix("x3")
-        e = T.dot(x1, T.opt.assert_op(x2, (x2 > x3).all())) + T.dot(
-            T.opt.assert_op(x1, (x1 > x3).all()), x2
+        x1 = tt.matrix("x1")
+        x2 = tt.matrix("x2")
+        x3 = tt.matrix("x3")
+        e = tt.dot(x1, tt.opt.assert_op(x2, (x2 > x3).all())) + tt.dot(
+            tt.opt.assert_op(x1, (x1 > x3).all()), x2
         )
         g = FunctionGraph([x1, x2, x3], [e])
         MergeOptimizer().optimize(g)
@@ -610,18 +610,16 @@ class TestEquilibrium(object):
 
 
 def test_pre_constant_merge_slice():
-    ms = theano.tensor.type_other.MakeSlice()(1)
+    ms = tt.type_other.MakeSlice()(1)
     pre_constant_merge([ms])
-    const_slice = theano.tensor.type_other.SliceConstant(
-        type=theano.tensor.type_other.slicetype, data=slice(1, None, 2)
-    )
-    adv = theano.tensor.subtensor.AdvancedSubtensor()(
-        theano.tensor.matrix(), [2, 3], const_slice
+    const_slice = tt.type_other.SliceConstant(
+        type=tt.type_other.slicetype, data=slice(1, None, 2)
     )
+    adv = tt.subtensor.AdvancedSubtensor()(tt.matrix(), [2, 3], const_slice)
     pre_constant_merge(adv)
 
-    cst = pre_greedy_local_optimizer([theano.tensor.opt.constant_folding], ms)
-    assert isinstance(cst, theano.tensor.type_other.SliceConstant)
+    cst = pre_greedy_local_optimizer([tt.opt.constant_folding], ms)
+    assert isinstance(cst, tt.type_other.SliceConstant)
 
     # Make sure constant of slice signature is hashable.
     hash(cst.signature())