Merge pull request #101 from brandonwillard/refactor-tests

.github/workflows/test.yml

@@ -70,8 +70,8 @@ jobs:
         float32: [0]
         part:
           - "tests --ignore=tests/tensor --ignore=tests/sparse --ignore=tests/tensor/nnet"
-          - "tests/tensor tests/sparse --ignore=tests/tensor/test_basic.py --ignore=tests/tensor/test_elemwise.py --ignore=tests/tensor/test_opt.py --ignore=tests/tensor/nnet"
-          - "tests/tensor/test_basic.py"
+          - "tests/tensor tests/sparse --ignore=tests/tensor/test_basic.py --ignore=tests/tensor/test_basic_scipy.py --ignore=tests/tensor/test_inplace.py --ignore=tests/tensor/test_elemwise.py --ignore=tests/tensor/test_opt.py --ignore=tests/tensor/nnet"
+          - "tests/tensor/test_basic.py tests/tensor/test_basic_scipy.py tests/tensor/test_inplace.py"
           - "tests/tensor/test_elemwise.py tests/tensor/test_opt.py"
           - "tests/tensor/nnet --ignore-glob='*/test_abstract_conv.py'"
           - "tests/tensor/nnet/test_abstract_conv.py"

.gitignore

@@ -40,3 +40,4 @@ Theano.suo
 .ropeproject
 core
 .idea
+/htmlcov/

doc/extending/unittest.txt

@@ -425,7 +425,7 @@ verify that the op generates the proper output, that the gradient is
 valid, that the Op fails in known/expected ways. Because so much of
 this is common, two helper functions exists to make your lives easier:
 ``makeTester`` and ``makeBroadcastTester`` (defined in module
-``tests.tensor.test_basic``).
+``tests.tensor.utils``).
 
 Here is an example of ``makeTester`` generating testcases for the Dot
 product op:
@@ -435,7 +435,7 @@ product op:
     from numpy import dot
     from numpy.random import rand
 
-    from tests.tensor.test_basic import makeTester
+    from tests.tensor.utils import makeTester
 
     TestDot = makeTester(name = 'DotTester',
                          op = dot,

setup.cfg

@@ -5,6 +5,7 @@ max-line-length = 88
 per-file-ignores =
     **/__init__.py:F401,E402,F403
     theano/sparse/sandbox/sp2.py:F401
+    tests/tensor/test_basic_scipy.py:E402
     tests/sparse/test_basic.py:E402
     tests/sparse/test_opt.py:E402
     tests/sparse/test_sp2.py:E402

tests/gpuarray/test_basic_ops.py

-import pytest
-
-
-pygpu = pytest.importorskip("pygpu")
-gpuarray = pygpu.gpuarray
 import numpy as np
+import pytest
 
 import theano
 import theano.tensor as tt
+
+# Don't import test classes otherwise they get tested as part of the file
 from tests import unittest_tools as utt
 from tests.gpuarray.config import mode_with_gpu, mode_without_gpu, test_ctx_name
 from tests.tensor.test_basic import (
@@ -14,9 +12,8 @@ from tests.tensor.test_basic import (
     TestComparison,
     TestJoinAndSplit,
     TestReshape,
-    rand,
-    safe_make_node,
 )
+from tests.tensor.utils import rand, safe_make_node
 from theano.gpuarray.basic_ops import (
     GpuAlloc,
     GpuAllocEmpty,
@@ -35,13 +32,14 @@ from theano.gpuarray.basic_ops import (
 )
 from theano.gpuarray.elemwise import GpuDimShuffle, GpuElemwise
 from theano.gpuarray.subtensor import GpuSubtensor
-
-# Don't import test classes otherwise they get tested as part of the file
 from theano.gpuarray.type import GpuArrayType, get_context, gpuarray_shared_constructor
 from theano.tensor import TensorType
 from theano.tensor.basic import alloc
 
 
+pygpu = pytest.importorskip("pygpu")
+gpuarray = pygpu.gpuarray
+
 utt.seed_rng()
 rng = np.random.RandomState(seed=utt.fetch_seed())
 

tests/gpuarray/test_linalg.py

@@ -397,7 +397,7 @@ class TestMagma:
         fn = theano.function([A], gpu_matrix_inverse(A), mode=mode_with_gpu)
         N = 1000
         test_rng = np.random.RandomState(seed=1)
-        # Copied from tests.tensor.test_basic.rand.
+        # Copied from tests.tensor.utils.rand.
         A_val = test_rng.rand(N, N).astype("float32") * 2 - 1
         A_val_inv = fn(A_val)
         utt.assert_allclose(np.eye(N), np.dot(A_val_inv, A_val), atol=1e-2)

tests/gpuarray/test_opt.py

@@ -4,10 +4,10 @@ import pytest
 import theano
 import theano.gpuarray
 import theano.tensor.slinalg as slinalg
-from tests import test_ifelse
 from tests import unittest_tools as utt
 from tests.gpuarray.config import mode_with_gpu, mode_without_gpu, test_ctx_name
-from tests.tensor import test_basic
+from tests.tensor.test_basic import TestSpecifyShape
+from tests.test_ifelse import TestIfelse
 from theano import tensor
 from theano.breakpoint import PdbBreakpoint
 from theano.gof.opt import check_stack_trace
@@ -312,12 +312,12 @@ def test_rebroadcast():
     assert _check_stack_trace(f)
 
 
-class TestSpecifyShape(test_basic.TestSpecifyShape):
+class TestSpecifyShape(TestSpecifyShape):
     mode = mode_with_gpu
     input_type = GpuArrayType
 
 
-class TestGpuIfelse(test_ifelse.TestIfelse):
+class TestGpuIfelse(TestIfelse):
     mode = mode_with_gpu
 
     @staticmethod

tests/scalar/test_basic.py

@@ -69,58 +69,21 @@ from theano.scalar.basic import (
 )
 
 
-def inputs():
-    return floats("xyz")
-
-
-class TestScalarOps:
-    def test_straightforward(self):
-        x, y, z = inputs()
-        e = mul(add(x, y), div_proxy(x, y))
-        g = FunctionGraph([x, y], [e])
-        fn = gof.DualLinker().accept(g).make_function()
-        assert fn(1.0, 2.0) == 1.5
-
-    # This test is moved to tests.tensor.test_basic.py:test_mod
-    # We move it their as under ubuntu the c_extract call of theano.scalar
-    # call PyInt_check and it fail under some os. If work in other case.
-    # As we use theano.scalar normally, but we use theano.tensor.scalar
-    # that is not important. Also this make the theano fct fail at call time
-    # so this is not a silent bug.
-    # --> This is why it is purposely named 'tes_mod' instead of 'test_mod'.
-    def tes_mod(self):
-        # We add this test as not all language and C implementation give the same
-        # sign to the result. This check that the c_code of `Mod` is implemented
-        # as Python. That is what we want.
-
-        x, y = ints("xy")
-        fn = gof.DualLinker().accept(FunctionGraph([x, y], [x % y])).make_function()
-        for a, b in (
-            (0, 1),
-            (1, 1),
-            (0, -1),
-            (1, -1),
-            (-1, -1),
-            (1, 2),
-            (-1, 2),
-            (1, -2),
-            (-1, -2),
-            (5, 3),
-            (-5, 3),
-            (5, -3),
-            (-5, -3),
-        ):
-            assert fn(a, b) == a % b, (a,)
-
-
-def has_f16(comp):
-    if any(v.type == float16 for v in comp.fgraph.variables):
-        return True
-    return False
+def test_mul_add_div_proxy():
+    x, y, z = floats("xyz")
+    e = mul(add(x, y), div_proxy(x, y))
+    g = FunctionGraph([x, y], [e])
+    fn = gof.DualLinker().accept(g).make_function()
+    assert fn(1.0, 2.0) == 1.5
 
 
 class TestComposite:
     def test_composite_clone_float32(self):
+        def has_f16(comp):
+            if any(v.type == float16 for v in comp.fgraph.variables):
+                return True
+            return False
+
         w = int8()
         x = float16()
         y = float32()
@@ -153,7 +116,7 @@ class TestComposite:
         assert not has_f16(nc)
 
     def test_straightforward(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         e = mul(add(x, y), div_proxy(x, y))
         C = Composite([x, y], [e])
         c = C.make_node(x, y)
@@ -164,7 +127,7 @@ class TestComposite:
 
     def test_flatten(self):
         # Test that we flatten multiple Composite.
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         C = Composite([x, y], [x + y])
         CC = Composite([x, y], [C(x * y, y)])
         assert not isinstance(CC.outputs[0].owner.op, Composite)
@@ -175,7 +138,7 @@ class TestComposite:
         assert isinstance(CC.outputs[0].owner.op, Composite)
 
     def test_with_constants(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         e = mul(add(70.0, y), div_proxy(x, y))
         C = Composite([x, y], [e])
         c = C.make_node(x, y)
@@ -186,7 +149,7 @@ class TestComposite:
         assert fn(1.0, 2.0) == 36.0
 
     def test_many_outputs(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         e0 = x + y + z
         e1 = x + y * z
         e2 = x / y
@@ -243,37 +206,37 @@ class TestComposite:
 
 class TestLogical:
     def test_gt(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         fn = gof.DualLinker().accept(FunctionGraph([x, y], [x > y])).make_function()
         for a, b in ((3.0, 9), (3, 0.9), (3, 3)):
             assert fn(a, b) == (a > b)
 
     def test_lt(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         fn = gof.DualLinker().accept(FunctionGraph([x, y], [x < y])).make_function()
         for a, b in ((3.0, 9), (3, 0.9), (3, 3)):
             assert fn(a, b) == (a < b)
 
     def test_le(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         fn = gof.DualLinker().accept(FunctionGraph([x, y], [x <= y])).make_function()
         for a, b in ((3.0, 9), (3, 0.9), (3, 3)):
             assert fn(a, b) == (a <= b)
 
     def test_ge(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         fn = gof.DualLinker().accept(FunctionGraph([x, y], [x >= y])).make_function()
         for a, b in ((3.0, 9), (3, 0.9), (3, 3)):
             assert fn(a, b) == (a >= b)
 
     def test_eq(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         fn = gof.DualLinker().accept(FunctionGraph([x, y], [eq(x, y)])).make_function()
         for a, b in ((3.0, 9), (3, 0.9), (3, 3)):
             assert fn(a, b) == (a == b)
 
     def test_neq(self):
-        x, y, z = inputs()
+        x, y, z = floats("xyz")
         fn = gof.DualLinker().accept(FunctionGraph([x, y], [neq(x, y)])).make_function()
         for a, b in ((3.0, 9), (3, 0.9), (3, 3)):
             assert fn(a, b) == (a != b)
@@ -424,36 +387,33 @@ class TestUpgradeToFloat:
             self._test_binary(binary_op, x_range, y_range)
 
 
-class TestComplexMod:
+def test_mod_complex_fail():
     # Make sure % fails on complex numbers.
-
-    def test_fail(self):
-        x = complex64()
-        y = int32()
-        with pytest.raises(ComplexError):
-            x % y
-
-
-class TestDiv:
-    def test_0(self):
-        a = int8()
-        b = int32()
-        c = complex64()
-        d = float64()
-        f = float32()
-
-        assert isinstance((a // b).owner.op, IntDiv)
-        assert isinstance((b // a).owner.op, IntDiv)
-        assert isinstance((b / d).owner.op, TrueDiv)
-        assert isinstance((b / f).owner.op, TrueDiv)
-        assert isinstance((f / a).owner.op, TrueDiv)
-        assert isinstance((d / b).owner.op, TrueDiv)
-        assert isinstance((d / f).owner.op, TrueDiv)
-        assert isinstance((f / c).owner.op, TrueDiv)
-        assert isinstance((a / c).owner.op, TrueDiv)
-
-
-def TestGradGt():
+    x = complex64()
+    y = int32()
+    with pytest.raises(ComplexError):
+        x % y
+
+
+def test_div_types():
+    a = int8()
+    b = int32()
+    c = complex64()
+    d = float64()
+    f = float32()
+
+    assert isinstance((a // b).owner.op, IntDiv)
+    assert isinstance((b // a).owner.op, IntDiv)
+    assert isinstance((b / d).owner.op, TrueDiv)
+    assert isinstance((b / f).owner.op, TrueDiv)
+    assert isinstance((f / a).owner.op, TrueDiv)
+    assert isinstance((d / b).owner.op, TrueDiv)
+    assert isinstance((d / f).owner.op, TrueDiv)
+    assert isinstance((f / c).owner.op, TrueDiv)
+    assert isinstance((a / c).owner.op, TrueDiv)
+
+
+def test_grad_gt():
     x = float32(name="x")
     y = float32(name="y")
     z = x > y
@@ -461,7 +421,7 @@ def TestGradGt():
     assert g.eval({y: 1.0}) == 0.0
 
 
-def TestGradSwitch():
+def test_grad_switch():
 
     # This is a code snippet from the mailing list
     # It caused an assert to be raised due to the
@@ -477,7 +437,7 @@ def TestGradSwitch():
     theano.gradient.grad(l, x)
 
 
-def TestGradIdentity():
+def test_grad_identity():
     # Check that the grad method of Identity correctly handles int dytpes
     x = theano.tensor.imatrix("x")
     # tensor_copy is Elemwise{Identity}
@@ -486,7 +446,7 @@ def TestGradIdentity():
     theano.gradient.grad(l, x)
 
 
-def TestGradInrange():
+def test_grad_inrange():
     for bound_definition in [(True, True), (False, False)]:
         # Instantiate op, and then take the gradient
         op = InRange(*bound_definition)
@@ -512,7 +472,7 @@ def TestGradInrange():
         utt.assert_allclose(f(7, 1, 5), [0, 0, 0])
 
 
-def TestGradAbs():
+def test_grad_abs():
     a = theano.tensor.fscalar("a")
     b = theano.tensor.nnet.relu(a)
     c = theano.grad(b, a)
@@ -523,11 +483,7 @@ def TestGradAbs():
     assert ret == 0.5, ret
 
 
-# Testing of Composite is done in tensor/tests/test_opt.py
-# in test_fusion, TestCompositeCodegen
-
-
-def TestConstant():
+def test_constant():
     c = constant(2, name="a")
     assert c.name == "a"
     assert c.dtype == "int8"

tests/tensor/nnet/test_nnet.py

@@ -4,7 +4,7 @@ import pytest
 import theano
 import theano.tensor as tt
 from tests import unittest_tools as utt
-from tests.tensor.test_basic import (
+from tests.tensor.utils import (
     _good_broadcast_unary_normal_float_no_complex,
     check_floatX,
     makeBroadcastTester,

tests/tensor/nnet/test_sigm.py

@@ -3,7 +3,7 @@ import numpy as np
 import theano
 import theano.tensor as tt
 from tests import unittest_tools as utt
-from tests.tensor.test_basic import (
+from tests.tensor.utils import (
     _good_broadcast_unary_normal_no_complex,
     check_floatX,
     copymod,

tests/tensor/test_blas.py

@@ -22,8 +22,9 @@ import theano
 import theano.tensor as tt
 import theano.tensor.blas_scipy
 from tests import unittest_tools
-from tests.tensor.test_basic import as_tensor_variable, compile, inplace, inplace_func
+from tests.tensor.utils import inplace_func
 from theano import In, config, shared
+from theano.tensor import as_tensor_variable, inplace
 from theano.tensor.blas import (
     Dot22,
     Dot22Scalar,
@@ -109,7 +110,7 @@ class TestGemm:
                 f = inplace_func(
                     [tz, ta, tx, ty, tb],
                     gemm_inplace(tz, ta, tx, ty, tb),
-                    mode=compile.Mode(optimizer=None, linker=l),
+                    mode=theano.compile.Mode(optimizer=None, linker=l),
                 )
                 f(z, a, x, y, b)
                 z_after = self._gemm(z_orig, a, x, y, b)
@@ -274,12 +275,12 @@ class TestGemm:
             tz, ta, tx, ty, tb = [shared(p) for p in (z, a, x, y, b)]
 
             # f = inplace_func([tz,ta,tx,ty,tb], gemm_inplace(tz,ta,tx,ty,tb),
-            #                 mode = compile.Mode(optimizer = None, linker=l))
+            #                 mode = theano.compile.Mode(optimizer = None, linker=l))
             # f(z, a, x, y, b)
             f = inplace_func(
                 [],
                 gemm_inplace(tz, ta, tx, ty, tb),
-                mode=compile.Mode(optimizer=None, linker=l),
+                mode=theano.compile.Mode(optimizer=None, linker=l),
             )
             f()
             unittest_tools.assert_allclose(z_after, tz.get_value(borrow=True))
@@ -336,7 +337,7 @@ class TestGemm:
                 f_i = inplace_func(
                     [],
                     gemm_inplace(tz[:, :, i], ta, tx[:, :, i], ty[:, :, i], tb),
-                    mode=compile.Mode(optimizer=None, linker=l),
+                    mode=theano.compile.Mode(optimizer=None, linker=l),
                 )
                 for j in range(3):
                     # tz will not _always_ be overwritten,
@@ -355,7 +356,7 @@ class TestGemm:
                     [],
                     tz_i,
                     updates=[(tz, tt.set_subtensor(tz[:, :, i], tz_i))],
-                    mode=compile.Mode(optimizer=None, linker=l),
+                    mode=theano.compile.Mode(optimizer=None, linker=l),
                 )
                 for j in range(3):
                     g_i()
@@ -612,7 +613,7 @@ def just_gemm(i, o, ishapes=None, max_graphlen=0, expected_nb_gemm=1):
     g = inplace_func(
         i,
         o,
-        mode=compile.Mode(linker="py", optimizer=None),
+        mode=theano.compile.Mode(linker="py", optimizer=None),
         allow_input_downcast=True,
         on_unused_input="ignore",
     )
@@ -701,7 +702,7 @@ def test_gemm_opt_double_gemm():
     g = inplace_func(
         i,
         o,
-        mode=compile.Mode(linker="py", optimizer=None),
+        mode=theano.compile.Mode(linker="py", optimizer=None),
         on_unused_input="ignore",
     )
 

tests/tensor/test_subtensor.py

@@ -10,7 +10,7 @@ import theano
 import theano.scalar as scal
 import theano.tensor as tt
 from tests import unittest_tools as utt
-from tests.tensor.test_basic import inplace_func, rand, randint_ranged
+from tests.tensor.utils import inplace_func, rand, randint_ranged
 from theano import change_flags, config
 from theano.compile import DeepCopyOp
 from theano.gof.op import get_test_value

tests/typed_list/test_opt.py

@@ -3,19 +3,12 @@ import numpy as np
 import theano
 import theano.tensor as tt
 import theano.typed_list
+from tests.tensor.utils import rand_ranged
 from theano import In
 from theano.typed_list.basic import Append, Extend, Insert, Remove, Reverse
 from theano.typed_list.type import TypedListType
 
 
-# took from tensors/tests/test_basic.py
-def rand_ranged_matrix(minimum, maximum, shape):
-    return np.asarray(
-        np.random.rand(*shape) * (maximum - minimum) + minimum,
-        dtype=theano.config.floatX,
-    )
-
-
 class TestInplace:
     def test_reverse_inplace(self):
         mySymbolicMatricesList = TypedListType(
@@ -32,9 +25,9 @@ class TestInplace:
         )
         assert f.maker.fgraph.toposort()[0].op.inplace
 
-        x = rand_ranged_matrix(-1000, 1000, [100, 101])
+        x = rand_ranged(-1000, 1000, [100, 101])
 
-        y = rand_ranged_matrix(-1000, 1000, [100, 101])
+        y = rand_ranged(-1000, 1000, [100, 101])
 
         assert np.array_equal(f([x, y]), [y, x])
 
@@ -56,9 +49,9 @@ class TestInplace:
         )
         assert f.maker.fgraph.toposort()[0].op.inplace
 
-        x = rand_ranged_matrix(-1000, 1000, [100, 101])
+        x = rand_ranged(-1000, 1000, [100, 101])
 
-        y = rand_ranged_matrix(-1000, 1000, [100, 101])
+        y = rand_ranged(-1000, 1000, [100, 101])
 
         assert np.array_equal(f([x], y), [x, y])
 
@@ -83,9 +76,9 @@ class TestInplace:
         )
         assert f.maker.fgraph.toposort()[0].op.inplace
 
-        x = rand_ranged_matrix(-1000, 1000, [100, 101])
+        x = rand_ranged(-1000, 1000, [100, 101])
 
-        y = rand_ranged_matrix(-1000, 1000, [100, 101])
+        y = rand_ranged(-1000, 1000, [100, 101])
 
         assert np.array_equal(f([x], [y]), [x, y])
 
@@ -111,9 +104,9 @@ class TestInplace:
         )
         assert f.maker.fgraph.toposort()[0].op.inplace
 
-        x = rand_ranged_matrix(-1000, 1000, [100, 101])
+        x = rand_ranged(-1000, 1000, [100, 101])
 
-        y = rand_ranged_matrix(-1000, 1000, [100, 101])
+        y = rand_ranged(-1000, 1000, [100, 101])
 
         assert np.array_equal(f([x], np.asarray(1, dtype="int64"), y), [x, y])
 
@@ -135,9 +128,9 @@ class TestInplace:
         )
         assert f.maker.fgraph.toposort()[0].op.inplace
 
-        x = rand_ranged_matrix(-1000, 1000, [100, 101])
+        x = rand_ranged(-1000, 1000, [100, 101])
 
-        y = rand_ranged_matrix(-1000, 1000, [100, 101])
+        y = rand_ranged(-1000, 1000, [100, 101])
 
         assert np.array_equal(f([x, y], y), [x])