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提交 23460ad2 authored 作者: Brandon T. Willard's avatar Brandon T. Willard
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Convert remaining exception tests to pytest format

上级 6e8c2b92
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正在显示 包含 230 行增加 和 449 行删除
theano/compile/tests/test_debugmode.py
浏览文件 @ 23460ad2
......@@ -8,7 +8,6 @@ from six import reraise
from theano import config
from theano import gof
import theano
from theano.compat import exc_message
from theano.compile import debugmode
import theano.tensor
from theano.tests import unittest_tools as utt
......@@ -214,14 +213,10 @@ def test_badthunkoutput():
if not theano.config.cxx:
pytest.skip("G++ not available, so we need to skip this test.")
try:
with pytest.raises(debugmode.BadThunkOutput) as einfo:
f_inconsistent([1.0, 2.0, 3.0], [2, 3, 4])
except debugmode.BadThunkOutput as e:
# print repr(e)
assert e.r.owner.op is inconsistent
return # TEST PASS
assert False # an error should have been detected
assert einfo.value.r.owner.op is inconsistent
def test_badoptimization():
......@@ -240,15 +235,11 @@ def test_badoptimization():
f = theano.function([a, b], a + b, mode=debugmode.DebugMode(optimizer=opt))
try:
with pytest.raises(debugmode.BadOptimization) as einfo:
f(
[1.0, 2.0, 3.0], [2, 3, 4],
)
except debugmode.BadOptimization as e:
assert str(e.reason) == "insert_broken_add"
return # TEST PASS
assert False
assert str(einfo.value.reason) == "insert_broken_add"
def test_badoptimization_opt_err():
......@@ -283,17 +274,15 @@ def test_badoptimization_opt_err():
b = theano.tensor.dvector()
f = theano.function([a, b], a + b, mode=debugmode.DebugMode(optimizer=opt))
try:
with pytest.raises(ValueError, match=r"insert_bigger_b_add"):
f(
[1.0, 2.0, 3.0], [2, 3, 4],
)
except ValueError as e:
assert "insert_bigger_b_add" in exc_message(e)
else:
assert False
# Test that opt that do an illegal change still get the error from gof.
try:
with pytest.raises(
theano.gof.toolbox.BadOptimization, match=r"insert_bad_dtype"
) as einfo:
with theano.change_flags(on_opt_error="raise"):
f2 = theano.function(
[a, b],
......@@ -303,20 +292,14 @@ def test_badoptimization_opt_err():
f2(
[1.0, 2.0, 3.0], [2, 3, 4],
)
except theano.gof.toolbox.BadOptimization as e:
assert "insert_bad_dtype" in str(e)
# Test that we can reraise the error with an extended message
try:
new_e = e.__class__("TTT" + str(e))
exc_type, exc_value, exc_trace = sys.exc_info()
exc_value = new_e
reraise(e.__class__, exc_value, exc_trace)
except theano.gof.toolbox.BadOptimization:
pass
else:
assert False
else:
assert False
# Test that we can reraise the error with an extended message
with pytest.raises(theano.gof.toolbox.BadOptimization):
e = einfo.value
new_e = e.__class__("TTT" + str(e))
exc_type, exc_value, exc_trace = sys.exc_info()
exc_value = new_e
reraise(e.__class__, exc_value, exc_trace)
def test_stochasticoptimization():
......@@ -340,7 +323,7 @@ def test_stochasticoptimization():
a = theano.tensor.dvector()
b = theano.tensor.dvector()
try:
with pytest.raises(debugmode.StochasticOrder):
theano.function(
[a, b],
theano.tensor.add(a, b),
......@@ -350,9 +333,6 @@ def test_stochasticoptimization():
stability_patience=max(2, config.DebugMode.patience),
),
)
except debugmode.StochasticOrder:
return # TEST PASS
assert False
def test_just_c_code():
......@@ -379,11 +359,8 @@ def test_baddestroymap():
y = theano.tensor.dvector()
f = theano.function([x, y], BadAdd()(x, y), mode="DEBUG_MODE")
try:
with pytest.raises(debugmode.BadDestroyMap):
f([1, 2], [3, 4])
assert False # failed to raise error
except debugmode.BadDestroyMap:
pass
def test_baddestroymap_c():
......@@ -391,11 +368,8 @@ def test_baddestroymap_c():
pytest.skip("G++ not available, so we need to skip this test.")
x = theano.tensor.dvector()
f = theano.function([x], wb2i(x), mode=debugmode.DebugMode(check_py_code=False))
try:
with pytest.raises(debugmode.BadDestroyMap):
assert np.all(f([1, 2]) == [2, 4])
assert False # failed to raise error
except debugmode.BadDestroyMap:
pass
class TestViewMap:
......@@ -423,21 +397,15 @@ class TestViewMap:
x = theano.tensor.dvector()
y = theano.tensor.dvector()
f = theano.function([x, y], self.BadAddRef()(x, y), mode="DEBUG_MODE")
try:
with pytest.raises(debugmode.BadViewMap):
f([1, 2], [3, 4])
assert False # failed to raise error
except debugmode.BadViewMap:
return
def test_badviewmap_slice(self):
x = theano.tensor.dvector()
y = theano.tensor.dvector()
f = theano.function([x, y], self.BadAddSlice()(x, y), mode="DEBUG_MODE")
try:
with pytest.raises(debugmode.BadViewMap):
f([1, 2], [3, 4])
assert False # failed to raise error
except debugmode.BadViewMap:
return
def test_goodviewmap(self):
goodop = self.BadAddRef()
......@@ -445,22 +413,16 @@ class TestViewMap:
x = theano.tensor.dvector()
y = theano.tensor.dvector()
f = theano.function([x, y], goodop(x, y), mode="DEBUG_MODE")
try:
f([1, 5, 1], [3, 4, 2, 1, 4])
return
except debugmode.BadViewMap:
assert False # failed to raise error
# Shouldn't raise an error
f([1, 5, 1], [3, 4, 2, 1, 4])
def test_badviewmap_c(self):
if not theano.config.cxx:
pytest.skip("G++ not available, so we need to skip this test.")
pytest.skip("C++ not available, so we need to skip this test.")
x = theano.tensor.dvector()
f = theano.function([x], wb1i(x), mode=debugmode.DebugMode(check_py_code=False))
try:
with pytest.raises(debugmode.BadViewMap):
f([1, 2])
assert False # failed to raise error
except debugmode.BadViewMap:
pass
def test_aliased_outputs_ok(self):
# here aliased outputs is ok because they are both aliased to an input
......@@ -563,12 +525,8 @@ class TestViewMap:
out = bad_xy0 * 2 + bad_xy1 * 2
f = theano.function([x, y], out, mode="DEBUG_MODE")
try:
with pytest.raises(debugmode.BadViewMap):
f([1, 2, 3, 4], [5, 6, 7, 8])
assert False # DebugMode should have caught the error
except debugmode.BadViewMap:
# print e
pass
# the situation can be rescued by picking one of the inputs and
# pretending that it is aliased to both the outputs.
......
theano/gof/tests/test_cc.py
浏览文件 @ 23460ad2
......@@ -365,14 +365,11 @@ def test_duallinker_mismatch():
# (purposely) wrong
assert PerformLinker().accept(g).make_function()(1.0, 2.0, 3.0) == -10.0
try:
with pytest.raises(MyExc):
# this runs OpWiseCLinker and PerformLinker in parallel and feeds
# variables of matching operations to _my_checker to verify that they
# are the same.
fn(1.0, 2.0, 3.0)
raise Exception("An exception should have been raised here!")
except MyExc:
pass
################################
......@@ -407,12 +404,8 @@ def test_c_fail_error():
e = add_fail(mul(x, y), mul(y, z))
lnk = OpWiseCLinker().accept(Env([y, z], [e]))
fn = lnk.make_function()
try:
with pytest.raises(RuntimeError):
fn(1.5, 3.0)
except RuntimeError:
print("Yay, TEST PASSED")
return # test passed
assert 0 # test failed
def test_shared_input_output():
......
theano/gof/tests/test_destroyhandler.py
浏览文件 @ 23460ad2
from __future__ import absolute_import, print_function, division
import pytest
from six.moves import xrange
from theano.gof.type import Type
......@@ -137,26 +138,6 @@ class FailureWatch:
self.failures += 1
def consistent(g):
# print "Testing consistent:", g
try:
assert g.consistent()
except AssertionError:
print("Test failed! The graph was marked as NOT consistent.")
raise
# print "Test OK"
def inconsistent(g):
# print "Testing NOT consistent:", g
try:
assert not g.consistent()
except AssertionError:
print("Test failed! The graph was marked as consistent.")
raise
# print "Test OK"
#################
# Test protocol #
#################
......@@ -166,7 +147,7 @@ def test_misc():
x, y, z = inputs()
e = transpose_view(transpose_view(transpose_view(transpose_view(x))))
g = Env([x, y, z], [e])
consistent(g)
assert g.consistent()
PatternOptimizer((transpose_view, (transpose_view, "x")), "x").optimize(g)
assert str(g) == "[x]"
new_e = add(x, y)
......@@ -174,7 +155,7 @@ def test_misc():
assert str(g) == "[Add(x, y)]"
g.replace(new_e, dot(add_in_place(x, y), transpose_view(x)))
assert str(g) == "[Dot(AddInPlace(x, y), TransposeView(x))]"
inconsistent(g)
assert not g.consistent()
######################
......@@ -190,15 +171,15 @@ def test_aliased_inputs_replacement():
sx = sigmoid(x)
e = add_in_place(x, tv)
g = Env([x, y], [e], False)
inconsistent(g)
assert not g.consistent()
g.replace(tv, sx)
consistent(g)
assert g.consistent()
g.replace(sx, tv)
inconsistent(g)
assert not g.consistent()
g.replace(tv, tvv)
inconsistent(g)
assert not g.consistent()
g.replace(tv, sx)
consistent(g)
assert g.consistent()
def test_indestructible():
......@@ -209,9 +190,9 @@ def test_indestructible():
assert x.tag.indestructible
e = add_in_place(x, y)
g = Env([x, y, z], [e], False)
inconsistent(g)
assert not g.consistent()
g.replace_validate(e, add(x, y))
consistent(g)
assert g.consistent()
@assertFailure_fast
......@@ -220,9 +201,9 @@ def test_usage_loop_through_views_2():
e0 = transpose_view(transpose_view(sigmoid(x)))
e = dot(add_in_place(x, y), transpose_view(e0))
g = Env([x, y, z], [e])
consistent(g) # because sigmoid can do the copy
assert g.consistent() # because sigmoid can do the copy
g.replace(e0, x)
inconsistent(g) # we cut off the path to the sigmoid
assert not g.consistent() # we cut off the path to the sigmoid
@assertFailure_fast
......@@ -232,29 +213,23 @@ def test_destroyers_loop():
e1 = add(x, y)
e2 = add(y, x)
g = Env([x, y, z], [e1, e2])
consistent(g)
assert g.consistent()
g.replace_validate(e1, add_in_place(x, y))
consistent(g)
try:
assert g.consistent()
with pytest.raises(InconsistencyError):
g.replace_validate(e2, add_in_place(y, x))
raise Exception("Shouldn't have reached this point.")
except InconsistencyError:
pass
consistent(g)
assert g.consistent()
x, y, z = inputs()
e1 = add(x, y)
e2 = add(y, x)
g = Env([x, y, z], [e1, e2])
consistent(g)
assert g.consistent()
g.replace_validate(e2, add_in_place(y, x))
consistent(g)
try:
assert g.consistent()
with pytest.raises(InconsistencyError):
g.replace_validate(e1, add_in_place(x, y))
raise Exception("Shouldn't have reached this point.")
except InconsistencyError:
pass
consistent(g)
assert g.consistent()
########
......@@ -266,14 +241,14 @@ def test_aliased_inputs():
x, y, z = inputs()
e = add_in_place(x, x)
g = Env([x], [e], False)
inconsistent(g)
assert not g.consistent()
def test_aliased_inputs2():
x, y, z = inputs()
e = add_in_place(x, transpose_view(x))
g = Env([x], [e], False)
inconsistent(g)
assert not g.consistent()
@assertFailure_fast
......@@ -281,14 +256,14 @@ def test_aliased_inputs_tolerate():
x, y, z = inputs()
e = add_in_place_2(x, x)
g = Env([x], [e], False)
consistent(g)
assert g.consistent()
def test_aliased_inputs_tolerate2():
x, y, z = inputs()
e = add_in_place_2(x, transpose_view(x))
g = Env([x], [e], False)
inconsistent(g)
assert not g.consistent()
@assertFailure_fast
......@@ -296,7 +271,7 @@ def test_same_aliased_inputs_ignored():
x, y, z = inputs()
e = add_in_place_3(x, x)
g = Env([x], [e], False)
consistent(g)
assert g.consistent()
@assertFailure_fast
......@@ -304,7 +279,7 @@ def test_different_aliased_inputs_ignored():
x, y, z = inputs()
e = add_in_place_3(x, transpose_view(x))
g = Env([x], [e], False)
consistent(g)
assert g.consistent()
# warning - don't run this because it would produce the wrong answer
# add_in_place_3 is actually not correct when aliasing of inputs
# is ignored.
......@@ -316,9 +291,9 @@ def test_indestructible_through_views():
tv = transpose_view(x)
e = add_in_place(tv, y)
g = Env([x, y, z], [e], False)
inconsistent(g)
assert not g.consistent()
g.replace_validate(tv, sigmoid(x))
consistent(g)
assert g.consistent()
def test_indirect():
......@@ -326,12 +301,12 @@ def test_indirect():
e0 = add_in_place(x, y)
e = dot(sigmoid(e0), transpose_view(x))
g = Env([x, y, z], [e], False)
inconsistent(g)
assert not g.consistent()
new_e0 = add(x, y)
g.replace(e0, new_e0)
consistent(g)
assert g.consistent()
g.replace(new_e0, add_in_place(x, y))
inconsistent(g)
assert not g.consistent()
@assertFailure_fast
......@@ -340,10 +315,10 @@ def test_indirect_2():
e0 = transpose_view(x)
e = dot(sigmoid(add_in_place(x, y)), e0)
g = Env([x, y, z], [e], False)
inconsistent(g)
assert not g.consistent()
new_e0 = add(e0, y)
g.replace(e0, new_e0)
consistent(g)
assert g.consistent()
@assertFailure_fast
......@@ -351,17 +326,14 @@ def test_long_destroyers_loop():
x, y, z = inputs()
e = dot(dot(add_in_place(x, y), add_in_place(y, z)), add(z, x))
g = Env([x, y, z], [e])
consistent(g)
assert g.consistent()
OpSubOptimizer(add, add_in_place).optimize(g)
consistent(g)
assert g.consistent()
# we don't want to see that!
assert str(g) != "[Dot(Dot(AddInPlace(x, y), AddInPlace(y, z)), AddInPlace(z, x))]"
e2 = dot(dot(add_in_place(x, y), add_in_place(y, z)), add_in_place(z, x))
try:
with pytest.raises(InconsistencyError):
Env(*graph.clone([x, y, z], [e2]))
raise Exception("Shouldn't have reached this point.")
except InconsistencyError:
pass
def test_misc_2():
......@@ -369,19 +341,16 @@ def test_misc_2():
tv = transpose_view(x)
e = add_in_place(x, tv)
g = Env([x, y], [e], False)
inconsistent(g)
assert not g.consistent()
g.replace(tv, x)
inconsistent(g)
assert not g.consistent()
def test_multi_destroyers():
x, y, z = inputs()
e = add(add_in_place(x, y), add_in_place(x, y))
try:
with pytest.raises(InconsistencyError):
Env([x, y, z], [e])
raise Exception("Shouldn't have reached this point.")
except InconsistencyError:
pass
@assertFailure_fast
......@@ -389,10 +358,10 @@ def test_multi_destroyers_through_views():
x, y, z = inputs()
e = dot(add(transpose_view(z), y), add(z, x))
g = Env([x, y, z], [e])
consistent(g)
assert g.consistent()
fail = FailureWatch()
OpSubOptimizer(add, add_in_place, fail).optimize(g)
consistent(g)
assert g.consistent()
assert fail.failures == 1 # should have succeeded once and failed once
......@@ -403,18 +372,18 @@ def test_repair_destroy_path():
e3 = add_in_place(e2, y)
e4 = add_in_place(e1, z)
g = Env([x, y, z], [e3, e4], False)
inconsistent(g)
assert not g.consistent()
g.replace(e2, transpose_view(x))
inconsistent(g)
assert not g.consistent()
def test_usage_loop():
x, y, z = inputs()
g = Env([x, y, z], [dot(add_in_place(x, z), x)], False)
inconsistent(g)
assert not g.consistent()
# replace add_in_place with add
OpSubOptimizer(add_in_place, add).optimize(g)
consistent(g)
assert g.consistent()
def test_usage_loop_through_views():
......@@ -422,9 +391,9 @@ def test_usage_loop_through_views():
aip = add_in_place(x, y)
e = dot(aip, transpose_view(x))
g = Env([x, y, z], [e], False)
inconsistent(g)
assert not g.consistent()
g.replace_validate(aip, add(x, z))
consistent(g)
assert g.consistent()
@assertFailure_fast
......@@ -432,10 +401,10 @@ def test_usage_loop_insert_views():
x, y, z = inputs()
e = dot(add_in_place(x, add(y, z)), sigmoid(sigmoid(sigmoid(sigmoid(sigmoid(x))))))
g = Env([x, y, z], [e])
consistent(g)
assert g.consistent()
fail = FailureWatch()
OpSubOptimizer(sigmoid, transpose_view, fail).optimize(g)
consistent(g)
assert g.consistent()
# it must keep one sigmoid in the long sigmoid chain
assert fail.failures == 1
......@@ -445,9 +414,9 @@ def test_value_repl():
sy = sigmoid(y)
e = add_in_place(x, sy)
g = Env([x, y], [e], False)
consistent(g)
assert g.consistent()
g.replace(sy, MyConstant("abc"))
consistent(g)
assert g.consistent()
@change_flags(compute_test_value="off")
......@@ -456,9 +425,9 @@ def test_value_repl_2():
sy = sigmoid(y)
e = add_in_place(x, sy)
g = Env([x, y], [e], False)
consistent(g)
assert g.consistent()
g.replace(sy, transpose_view(MyConstant("abc")))
consistent(g)
assert g.consistent()
@assertFailure_fast
......@@ -475,28 +444,28 @@ def test_multiple_inplace():
# before multiple and then multiple can still run in-place on y
e_2 = dot(y, y)
g = Env([x, y], [e_1, e_2], False)
consistent(g)
assert g.consistent()
# try to work in-place on x/0 and y/1 (this should fail)
fail = FailureWatch()
OpSubOptimizer(multiple, multiple_in_place_0_1, fail).optimize(g)
consistent(g)
assert g.consistent()
assert fail.failures == 1
# try to work in-place on x/0 (this should fail)
fail = FailureWatch()
OpSubOptimizer(multiple, multiple_in_place_0, fail).optimize(g)
consistent(g)
assert g.consistent()
assert fail.failures == 1
# try to work in-place on y/1 (this should succeed)
fail = FailureWatch()
OpSubOptimizer(multiple, multiple_in_place_1, fail).optimize(g)
consistent(g)
assert g.consistent()
assert fail.failures == 0
# try to work in-place on x/0 and y/1 (this should still fail)
fail = FailureWatch()
OpSubOptimizer(multiple_in_place_1, multiple_in_place_0_1, fail).optimize(g)
consistent(g)
assert g.consistent()
assert fail.failures == 1
theano/gof/tests/test_optdb.py
浏览文件 @ 23460ad2
from __future__ import absolute_import, print_function, division
import pytest
from theano.compat import exc_message
from theano.gof.optdb import opt, DB
class TestDB:
def test_0(self):
def test_name_clashes(self):
class Opt(opt.Optimizer): # inheritance buys __hash__
name = "blah"
......@@ -20,35 +20,11 @@ class TestDB:
assert "b" in db
assert "c" in db
try:
with pytest.raises(ValueError, match=r"The name.*"):
db.register("c", Opt()) # name taken
self.fail()
except ValueError as e:
if exc_message(e).startswith("The name"):
pass
else:
raise
except Exception:
self.fail()
try:
with pytest.raises(ValueError, match=r"The name.*"):
db.register("z", Opt()) # name collides with tag
self.fail()
except ValueError as e:
if exc_message(e).startswith("The name"):
pass
else:
raise
except Exception:
self.fail()
try:
with pytest.raises(ValueError, match=r"The tag.*"):
db.register("u", Opt(), "b") # name new but tag collides with name
self.fail()
except ValueError as e:
if exc_message(e).startswith("The tag"):
pass
else:
raise
except Exception:
self.fail()
theano/gpuarray/tests/test_basic_ops.py
浏览文件 @ 23460ad2
......@@ -187,38 +187,31 @@ def makeTester(
raise
for i, (variable, expected) in enumerate(izip(variables, expecteds)):
if (
condition = (
variable.dtype != expected.dtype
or variable.shape != expected.shape
or not TensorType.values_eq_approx(variable, expected)
):
self.fail(
(
"Test %s::%s: Output %s gave the wrong "
"value. With inputs %s, expected %s "
"(dtype %s), got %s (dtype %s)."
% (
self.op,
testname,
i,
inputs,
expected,
expected.dtype,
variable,
variable.dtype,
)
)
)
assert not condition, (
"Test %s::%s: Output %s gave the wrong "
"value. With inputs %s, expected %s "
"(dtype %s), got %s (dtype %s)."
% (
self.op,
testname,
i,
inputs,
expected,
expected.dtype,
variable,
variable.dtype,
)
)
for description, check in iteritems(self.checks):
if not check(inputs, variables):
self.fail(
(
"Test %s::%s: Failed check: %s "
"(inputs were %s, ouputs were %s)"
)
% (self.op, testname, description, inputs, variables)
)
assert check(inputs, variables), (
"Test %s::%s: Failed check: %s " "(inputs were %s, ouputs were %s)"
) % (self.op, testname, description, inputs, variables)
Checker.__name__ = name
if hasattr(Checker, "__qualname__"):
......
theano/tensor/tests/test_basic.py
浏览文件 @ 23460ad2
......@@ -529,42 +529,35 @@ def makeTester(
expecteds = (expecteds,)
for i, (variable, expected) in enumerate(izip(variables, expecteds)):
if (
condition = (
variable.dtype != expected.dtype
or variable.shape != expected.shape
or not np.allclose(variable, expected, atol=eps, rtol=eps)
):
self.fail(
(
"Test %s::%s: Output %s gave the wrong"
" value. With inputs %s, expected %s (dtype %s),"
" got %s (dtype %s). eps=%f"
" np.allclose returns %s %s"
)
% (
self.op,
testname,
i,
inputs,
expected,
expected.dtype,
variable,
variable.dtype,
eps,
np.allclose(variable, expected, atol=eps, rtol=eps),
np.allclose(variable, expected),
)
)
)
assert not condition, (
"Test %s::%s: Output %s gave the wrong"
" value. With inputs %s, expected %s (dtype %s),"
" got %s (dtype %s). eps=%f"
" np.allclose returns %s %s"
) % (
self.op,
testname,
i,
inputs,
expected,
expected.dtype,
variable,
variable.dtype,
eps,
np.allclose(variable, expected, atol=eps, rtol=eps),
np.allclose(variable, expected),
)
for description, check in iteritems(self.checks):
if not check(inputs, variables):
self.fail(
(
"Test %s::%s: Failed check: %s (inputs"
" were %s, outputs were %s)"
)
% (self.op, testname, description, inputs, variables)
)
assert check(inputs, variables), (
"Test %s::%s: Failed check: %s (inputs"
" were %s, outputs were %s)"
) % (self.op, testname, description, inputs, variables)
def test_bad_build(self):
if skip:
......@@ -4080,10 +4073,12 @@ class TestMinMax:
n = as_tensor_variable(data)
assert min(n).dtype == "bool"
i = eval_outputs(min(n))
assert i is False
assert i.ndim == 0
assert not np.any(i)
assert max(n).dtype == "bool"
i = eval_outputs(max(n))
assert i is True
assert i.ndim == 0
assert np.all(i)
def test_basic_allclose():
......@@ -5353,10 +5348,8 @@ class TestDivimpl:
class TestMean:
def test_regression_mean_of_ndarray_failure(self):
try:
tensor.mean(np.zeros(1))
except AttributeError:
self.fail()
# This shouldn't throw an `AttributeError` (or any other, for that matter)
tensor.mean(np.zeros(1))
def test_mean_f16(self):
x = tensor.vector(dtype="float16")
......
theano/tensor/tests/test_blas.py
浏览文件 @ 23460ad2
......@@ -24,8 +24,6 @@ from six.moves import xrange
import theano
import theano.tensor as T
from theano import tensor, In, shared, config
from theano.compat import exc_message # noqa: E401
from theano.printing import pp
from theano.tensor.blas import (
_dot22,
_dot22scalar,
......@@ -128,28 +126,16 @@ class TestGemm:
def test_basic(self):
Gemm.debug = True
try:
with pytest.raises(TypeError, match=Gemm.E_rank):
gemm_no_inplace([1.0], 1.0, [1.0], [1.0], 1.0)
except TypeError as e:
if exc_message(e) is Gemm.E_rank:
return
self.fail()
def test_basic_1(self):
try:
with pytest.raises(TypeError, match=Gemm.E_rank):
self.cmp(1.0, 0.0, 1.0, 1.0, 1.0)
except TypeError as e:
if exc_message(e) is Gemm.E_rank:
return
self.fail()
def test_basic_2(self):
try:
with pytest.raises(TypeError, match=Gemm.E_rank):
self.cmp(2.0, 1.0, [3, 2, 1.0], [[1], [2], [3.0]], 1.0)
except TypeError as e:
assert exc_message(e) == Gemm.E_rank
return
self.fail()
def test_basic_4(self):
self.cmp(self.rand(3, 4), 1.0, self.rand(3, 5), self.rand(5, 4), 0.0)
......@@ -233,45 +219,29 @@ class TestGemm:
def test_destroy_map0(self):
# test that only first input can be overwritten.
Z = as_tensor_variable(self.rand(2, 2))
try:
with pytest.raises(InconsistencyError, match=Gemm.E_z_uniq):
gemm_inplace(Z, 1.0, Z, Z, 1.0)
except InconsistencyError as e:
if exc_message(e) == Gemm.E_z_uniq:
return
self.fail()
def test_destroy_map1(self):
# test that only first input can be overwritten.
Z = as_tensor_variable(self.rand(2, 2))
A = as_tensor_variable(self.rand(2, 2))
try:
with pytest.raises(InconsistencyError, match=Gemm.E_z_uniq):
gemm_inplace(Z, 1.0, A, inplace.transpose_inplace(Z), 1.0)
except InconsistencyError as e:
if exc_message(e) == Gemm.E_z_uniq:
return
self.fail()
def test_destroy_map2(self):
# test that only first input can be overwritten.
Z = as_tensor_variable(self.rand(2, 2))
A = as_tensor_variable(self.rand(2, 2))
try:
with pytest.raises(InconsistencyError, match=Gemm.E_z_uniq):
gemm_inplace(Z, 1.0, inplace.transpose_inplace(Z), A, 1.0)
except InconsistencyError as e:
if exc_message(e) == Gemm.E_z_uniq:
return
self.fail()
def test_destroy_map3(self):
# test that only first input can be overwritten
Z = as_tensor_variable(self.rand(2, 2))
A = as_tensor_variable(self.rand(2, 2))
try:
with pytest.raises(InconsistencyError, match=Gemm.E_z_uniq):
gemm_inplace(Z, 1.0, Z, A, 1.0)
except InconsistencyError as e:
if exc_message(e) == Gemm.E_z_uniq:
return
self.fail()
def test_destroy_map4(self):
# test that dot args can be aliased
......@@ -337,12 +307,8 @@ class TestGemm:
t(C, A[:2, :].T, B[:, :2].T)
t(C.T, A[:2, :].T, B[:, :2].T)
try:
with pytest.raises(ValueError, match=r".*aligned.*"):
t(C.T, A[:2, :], B[:, :2].T)
except ValueError as e:
if exc_message(e).find("aligned") >= 0:
return
self.fail()
def test_non_contiguous(self):
# Like test_transposes but with matrices without any
......@@ -598,7 +564,7 @@ class TestAsScalar:
# Test that it fails on nonscalar variables
a = T.matrix()
assert _as_scalar(a) is None
assert _as_scalar(T.DimShuffle([False, False], [0, "x", 1])(1)) is None
assert _as_scalar(T.DimShuffle([False, False], [0, "x", 1])(a)) is None
class TestRealMatrix:
......@@ -622,61 +588,49 @@ def XYZab():
return T.matrix(), T.matrix(), T.matrix(), T.scalar(), T.scalar()
class Failure(Exception):
pass
def just_gemm(
i, o, ishapes=[(4, 3), (3, 5), (4, 5), (), ()], max_graphlen=0, expected_nb_gemm=1
):
try:
f = inplace_func(
[In(ii, mutable=True, allow_downcast=True) for ii in i],
o,
mode="FAST_RUN",
on_unused_input="ignore",
)
nb_gemm = 0
for node in f.maker.fgraph.apply_nodes:
if isinstance(node.op, T.Dot):
raise Failure("dot not changed to gemm_inplace in graph")
if node.op == _dot22:
raise Failure("_dot22 not changed to gemm_inplace in graph")
if node.op == gemm_inplace:
nb_gemm += 1
assert nb_gemm == expected_nb_gemm, (nb_gemm, expected_nb_gemm)
g = inplace_func(
i,
o,
mode=compile.Mode(linker="py", optimizer=None),
allow_input_downcast=True,
on_unused_input="ignore",
)
for node in g.maker.fgraph.apply_nodes:
if node.op == gemm_inplace:
raise Exception("gemm_inplace in original graph")
graphlen = len(f.maker.fgraph.toposort())
if max_graphlen and (graphlen <= max_graphlen):
# theano.printing.debugprint(f)
assert False, "graphlen=%i>%i" % (graphlen, max_graphlen)
rng = np.random.RandomState(unittest_tools.fetch_seed(234))
r0 = f(*[np.asarray(rng.randn(*sh), config.floatX) for sh in ishapes])
rng = np.random.RandomState(unittest_tools.fetch_seed(234))
r1 = g(*[np.asarray(rng.randn(*sh), config.floatX) for sh in ishapes])
max_abs_err = np.max(np.abs(r0[0] - r1[0]))
eps = 1.0e-8
if config.floatX == "float32":
eps = 1.0e-6
if max_abs_err > eps:
raise Failure(
"GEMM is computing the wrong output. max_rel_err =", max_abs_err
)
except Failure:
for node in f.maker.fgraph.toposort():
print("GRAPH", node)
raise
f = inplace_func(
[In(ii, mutable=True, allow_downcast=True) for ii in i],
o,
mode="FAST_RUN",
on_unused_input="ignore",
)
nb_gemm = 0
for node in f.maker.fgraph.apply_nodes:
assert not isinstance(
node.op, T.Dot
), "_dot22 not changed to gemm_inplace in graph"
assert node.op != _dot22
if node.op == gemm_inplace:
nb_gemm += 1
assert nb_gemm == expected_nb_gemm, (nb_gemm, expected_nb_gemm)
g = inplace_func(
i,
o,
mode=compile.Mode(linker="py", optimizer=None),
allow_input_downcast=True,
on_unused_input="ignore",
)
for node in g.maker.fgraph.apply_nodes:
assert node.op != gemm_inplace, "gemm_inplace in original graph"
graphlen = len(f.maker.fgraph.toposort())
assert not (max_graphlen and (graphlen <= max_graphlen)), "graphlen=%i>%i" % (
graphlen,
max_graphlen,
)
rng = np.random.RandomState(unittest_tools.fetch_seed(234))
r0 = f(*[np.asarray(rng.randn(*sh), config.floatX) for sh in ishapes])
rng = np.random.RandomState(unittest_tools.fetch_seed(234))
r1 = g(*[np.asarray(rng.randn(*sh), config.floatX) for sh in ishapes])
max_abs_err = np.max(np.abs(r0[0] - r1[0]))
eps = 1.0e-8
if config.floatX == "float32":
eps = 1.0e-6
assert max_abs_err <= eps, "GEMM is computing the wrong output. max_rel_err ="
@unittest_tools.assertFailure_fast
......@@ -732,43 +686,28 @@ def test_gemm_opt_double_gemm():
+ gemm_inplace(Z, b, S.T, R.T, T.constant(1.0).astype(config.floatX))
)
]
try:
f = inplace_func(
[In(ii, mutable=True) for ii in i],
o,
mode="FAST_RUN",
on_unused_input="ignore",
)
for node in f.maker.fgraph.apply_nodes:
if isinstance(node.op, T.Dot):
raise Failure("dot in graph")
if node.op == _dot22:
raise Failure("_dot22 in graph")
g = inplace_func(
i,
o,
mode=compile.Mode(linker="py", optimizer=None),
on_unused_input="ignore",
)
# for node in g.maker.fgraph.apply_nodes:
# if node.op == gemm_inplace: raise Failure('gemm_inplace in graph')
rng = np.random.RandomState(unittest_tools.fetch_seed(234))
r0 = f(*[np.asarray(rng.randn(*sh), config.floatX) for sh in ishapes])
rng = np.random.RandomState(unittest_tools.fetch_seed(234))
r1 = g(*[np.asarray(rng.randn(*sh), config.floatX) for sh in ishapes])
max_abs_err = np.max(np.abs(r0[0] - r1[0]))
eps = 1.0e-8
if config.floatX == "float32":
eps = 1.0e-6
if max_abs_err > eps:
raise Failure(
"GEMM is computing the wrong output. max_rel_err =", max_abs_err
)
except Failure:
for node in f.maker.fgraph.toposort():
print("GRAPH", node)
raise
f = inplace_func(
[In(ii, mutable=True) for ii in i],
o,
mode="FAST_RUN",
on_unused_input="ignore",
)
for node in f.maker.fgraph.apply_nodes:
assert not isinstance(node.op, T.Dot)
assert node.op != _dot22
g = inplace_func(
i, o, mode=compile.Mode(linker="py", optimizer=None), on_unused_input="ignore",
)
rng = np.random.RandomState(unittest_tools.fetch_seed(234))
r0 = f(*[np.asarray(rng.randn(*sh), config.floatX) for sh in ishapes])
rng = np.random.RandomState(unittest_tools.fetch_seed(234))
r1 = g(*[np.asarray(rng.randn(*sh), config.floatX) for sh in ishapes])
max_abs_err = np.max(np.abs(r0[0] - r1[0]))
eps = 1.0e-8
if config.floatX == "float32":
eps = 1.0e-6
assert max_abs_err <= eps, "GEMM is computing the wrong output. max_rel_err ="
def test_gemm_canonicalize():
......@@ -954,12 +893,10 @@ def test_gemm_opt_vector_stuff():
u, v = T.vector(), T.vector()
f = inplace_func([a, u, v], a + T.dot(u, v), mode="FAST_RUN")
if gemm_inplace in [n.op for n in f.maker.fgraph.apply_nodes]:
raise Failure("gemm_inplace in graph")
assert gemm_inplace not in [n.op for n in f.maker.fgraph.apply_nodes]
f = inplace_func([a, u, X, Y], a * u + T.dot(X, Y), mode="FAST_RUN")
if gemm_inplace in [n.op for n in f.maker.fgraph.apply_nodes]:
raise Failure("gemm_inplace in graph")
assert gemm_inplace not in [n.op for n in f.maker.fgraph.apply_nodes]
def test_gemm_unrolled():
......@@ -1029,9 +966,7 @@ def test_inplace0():
R, S, c = T.matrix("R"), T.matrix("S"), T.scalar("c")
f = inplace_func([Z, b, R, S], [Z * (Z + b * T.dot(R, S).T)], mode="FAST_RUN")
if gemm_inplace in [n.op for n in f.maker.fgraph.apply_nodes]:
print(pp(f.maker.fgraph.outputs[0]))
raise Failure("gemm_inplace in graph")
assert gemm_inplace not in [n.op for n in f.maker.fgraph.apply_nodes]
assert gemm_no_inplace in [n.op for n in f.maker.fgraph.apply_nodes]
# gemm_inplace should be inserted here, to work in-place on Z*c
......@@ -1040,9 +975,7 @@ def test_inplace0():
[Z * (c * Z + a * T.dot(X, Y) + b * T.dot(R, S).T)],
mode="FAST_RUN",
)
if gemm_inplace not in [n.op for n in f.maker.fgraph.apply_nodes]:
theano.printing.debugprint(f)
raise Failure("no gemm_inplace in graph")
assert gemm_inplace in [n.op for n in f.maker.fgraph.apply_nodes]
def test_inplace1():
......
theano/tensor/tests/test_elemwise.py
浏览文件 @ 23460ad2
......@@ -482,13 +482,8 @@ class TestCAReduce(unittest_tools.InferShapeTester):
% str(scalar_op)
)
if scalar_op in [scalar.maximum, scalar.minimum] and numpy_raised:
try:
out = f(xv)
assert out.dtype == dtype
except ValueError:
pass
else:
self.fail()
with pytest.raises(ValueError):
f(xv)
else:
if test_nan:
try:
......
theano/tensor/tests/test_subtensor.py
浏览文件 @ 23460ad2
......@@ -142,25 +142,15 @@ class TestSubtensor(utt.OptimizationTestMixin):
oldlevel = _logger.level
_logger.setLevel(logging.CRITICAL)
try:
try:
with pytest.raises(IndexError):
self.eval_output_and_check(t)
except IndexError:
return
self.fail()
finally:
_logger.setLevel(oldlevel)
def test_err_subslice(self):
n = self.shared(np.ones(3, dtype=self.dtype))
try:
with pytest.raises(Exception):
n[slice(0, slice(1, 2, None), None)]
except Exception:
# Relax constraint on the type of Exception,
# since this might be handled by AvancedSubtensor
# if e[0] != Subtensor.e_indextype:
# raise
return
self.fail()
def test_ok_range_finite(self):
n = self.shared(np.arange(3, dtype=self.dtype))
......@@ -1095,24 +1085,12 @@ class TestSubtensor(utt.OptimizationTestMixin):
a = fscalar()
b = fscalar()
c = vector()
try:
with pytest.raises(TypeError):
c[a:b]
except NotImplementedError:
self.fail()
except TypeError:
pass
try:
with pytest.raises(TypeError):
c[a:]
except NotImplementedError:
self.fail()
except TypeError:
pass
try:
with pytest.raises(TypeError):
c[:b]
except NotImplementedError:
self.fail()
except TypeError:
pass
@pytest.mark.slow
def test_grad_list(self):
......
theano/tests/test_rop.py
浏览文件 @ 23460ad2
......@@ -77,18 +77,8 @@ class RopLopChecker:
If your op is not differentiable(so you can't define Rop)
test that an error is raised.
"""
raised = False
try:
with pytest.raises(ValueError):
tensor.Rop(y, self.x, self.v)
except ValueError:
raised = True
if not raised:
self.fail(
(
"Op did not raise an error even though the function"
" is not differentiable"
)
)
def check_mat_rop_lop(self, y, out_shape):
"""
......@@ -162,10 +152,13 @@ class RopLopChecker:
v1 = rop_f(vx, vv)
v2 = scan_f(vx, vv)
assert np.allclose(v1, v2), "ROP mismatch: %s %s" % (v1, v2)
known_fail = False
try:
self.check_nondiff_rop(theano.clone(y, replace={self.x: break_op(self.x)}))
except AssertionError:
tensor.Rop(
theano.clone(y, replace={self.x: break_op(self.x)}), self.x, self.v
)
except ValueError:
known_fail = True
# TEST LOP
......
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