Move test_basic utilities to utils.py and SciPy tests to test_basic_scipy

.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_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_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/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])
 

tests/typed_list/test_type.py

@@ -3,19 +3,12 @@ import pytest
 
 import theano
 import theano.tensor as tt
-import theano.typed_list
 from tests import unittest_tools as utt
+from tests.tensor.utils import rand_ranged
+from theano.typed_list.basic import TypedListVariable
 from theano.typed_list.type import TypedListType
 
 
-# Taken 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 TestTypedListType:
     def setup_method(self):
         utt.seed_rng()
@@ -70,7 +63,7 @@ class TestTypedListType:
 
         myType = TypedListType(tt.TensorType(theano.config.floatX, (False, False)))
 
-        x = rand_ranged_matrix(-1000, 1000, [100, 100])
+        x = rand_ranged(-1000, 1000, [100, 100])
 
         assert np.array_equal(myType.filter([x]), [x])
 
@@ -88,7 +81,7 @@ class TestTypedListType:
     def test_load_alot(self):
         myType = TypedListType(tt.TensorType(theano.config.floatX, (False, False)))
 
-        x = rand_ranged_matrix(-1000, 1000, [10, 10])
+        x = rand_ranged(-1000, 1000, [10, 10])
         testList = []
         for i in range(10000):
             testList.append(x)
@@ -104,7 +97,7 @@ class TestTypedListType:
 
         myType = TypedListType(myNestedType)
 
-        x = rand_ranged_matrix(-1000, 1000, [100, 100])
+        x = rand_ranged(-1000, 1000, [100, 100])
 
         assert np.array_equal(myType.filter([[x]]), [[x]])
 
@@ -160,4 +153,4 @@ class TestTypedListType:
             tt.TensorType(theano.config.floatX, (False, False))
         )()
 
-        assert isinstance(mySymbolicVariable, theano.typed_list.TypedListVariable)
+        assert isinstance(mySymbolicVariable, TypedListVariable)

theano/gradient.py

@@ -1947,8 +1947,13 @@ class GradientError(Exception):
         self.rel_tol = rel_tol
 
     def __str__(self):
-        # args may have been inserted by e.g. makeTester
-        args_msg = ", ".join(str(a) for a in self.args)
+        if hasattr(self, "args"):
+            # `self.args` may have been inserted by
+            # `tests.tensor.utils.makeTester`
+            args_msg = ", ".join(str(a) for a in self.args)
+        else:
+            args_msg = ""
+
         return """\
 GradientError: numeric gradient and analytic gradient exceed tolerance:
         At position %i of argument %i with shape %s,

theano/scalar/basic_scipy.py

-# Definitions of theano.scalar ops that have their python implementation taken
-# from SciPy. As SciPy is not always available, we treat them separately.
+"""
+`Op`s that have their python implementations taken from SciPy.
+
+As SciPy is not always available, we treat them separately.
+"""
 
 import os