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提交 60ad703d authored 作者: lamblin's avatar lamblin
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Merge pull request #1106 from nouiz/err_msg2

Add utt.assert_allclose that raise a more informative error.
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doc/tutorial/extending_theano.txt
浏览文件 @ 60ad703d
......@@ -211,8 +211,14 @@ returns the right answer. If you detect an error, you must raise an
inp = numpy.asarray(numpy.random.rand(5, 4), dtype=config.floatX)
out = f(inp)
# Compare the result computed to the expected value.
assert numpy.allclose(inp * 2, out)
utt.assert_allclose(inp * 2, out)
We call ``utt.assert_allclose(expected_value, value)`` to compare
NumPy ndarray.This raise an error message with more information. Also,
the default tolerance can be changed with the Theano flags
``config.tensor.cmp_sloppy`` that take values in 0, 1 and 2. The
defaul value do the most strict comparison, 1 and 2 make less strict
comparison.
Testing the infer_shape
-----------------------
......
theano/compile/debugmode.py
浏览文件 @ 60ad703d
......@@ -171,7 +171,8 @@ class BadThunkOutput(DebugModeError):
of the exception"""
sio = StringIO()
print >> sio, "BadThunkOutput"
print >> sio, " variable :", self.r
print >> sio, " Apply :", self.r.owner
print >> sio, " op :", self.offending_op()
print >> sio, " Outputs Type:", self.r.type
print >> sio, " Outputs Shape:", getattr(self.val1, 'shape', None)
print >> sio, " Outputs Strides:", getattr(self.val1, 'strides', None)
......@@ -180,60 +181,15 @@ class BadThunkOutput(DebugModeError):
for val in self.inputs_val]
print >> sio, " Inputs Strides:", [getattr(val, 'strides', None)
for val in self.inputs_val]
print >> sio, " Apply :", self.r.owner
print >> sio, " Bad Variable:", self.r
print >> sio, " thunk1 :", self.thunk1
print >> sio, " thunk2 :", self.thunk2
print >> sio, " val1 :", self.val1
print >> sio, " val2 :", self.val2
print >> sio, " op :", self.offending_op()
try:
ssio = StringIO()
print >> ssio, " Value 1 : shape, dtype, strides, min, max, n_inf, n_nan:",
print >> ssio, self.val1.shape,
print >> ssio, self.val1.dtype,
print >> ssio, self.val1.strides,
print >> ssio, self.val1.min(),
print >> ssio, self.val1.max(),
print >> ssio, numpy.isinf(self.val1).sum(),
print >> ssio, numpy.isnan(self.val1).sum(),
# only if all succeeds to we add anything to sio
print >> sio, ssio.getvalue()
except Exception:
pass
try:
ssio = StringIO()
print >> ssio, " Value 2 : shape, dtype, strides, min, max, n_inf, n_nan:",
print >> ssio, self.val2.shape,
print >> ssio, self.val2.dtype,
print >> ssio, self.val2.strides,
print >> ssio, self.val2.min(),
print >> ssio, self.val2.max(),
print >> ssio, numpy.isinf(self.val2).sum(),
print >> ssio, numpy.isnan(self.val2).sum(),
# only if all succeeds to we add anything to sio
print >> sio, ssio.getvalue()
except Exception:
pass
try:
ov = numpy.asarray(self.val1)
nv = numpy.asarray(self.val2)
ssio = StringIO()
absdiff = numpy.absolute(nv - ov)
print >> ssio, " Max Abs Diff: ", numpy.max(absdiff)
print >> ssio, " Mean Abs Diff: ", numpy.mean(absdiff)
print >> ssio, " Median Abs Diff: ", numpy.median(absdiff)
print >> ssio, " Std Abs Diff: ", numpy.std(absdiff)
reldiff = numpy.absolute(nv - ov) / (numpy.absolute(nv) +
numpy.absolute(ov))
print >> ssio, " Max Rel Diff: ", numpy.max(reldiff)
print >> ssio, " Mean Rel Diff: ", numpy.mean(reldiff)
print >> ssio, " Median Rel Diff: ", numpy.median(reldiff)
print >> ssio, " Std Rel Diff: ", numpy.std(reldiff)
# only if all succeeds to we add anything to sio
print >> sio, ssio.getvalue()
except Exception:
pass
return sio.getvalue()
#Don't import it at the top of the file to prevent circular import.
utt = theano.tests.unittest_tools
print >> sio, utt.str_diagnostic(self.val1, self.val2, None, None)
ret = sio.getvalue()
return ret
class BadOptimization(DebugModeError):
......
theano/sparse/tests/test_basic.py
浏览文件 @ 60ad703d
......@@ -48,7 +48,6 @@ from theano.sparse import (
from theano.sparse.opt import (StructuredDotCSC, UsmmCscDense, CSMGradC)
from theano.tests import unittest_tools as utt
from theano.tensor.basic import _allclose
def as_sparse_format(data, format):
......@@ -886,7 +885,7 @@ class test_structureddot(unittest.TestCase):
scipy_result = spmat * mat
assert theano_result.shape == scipy_result.shape
assert theano_result.dtype == scipy_result.dtype
assert _allclose(theano_result, scipy_result)
utt.assert_allclose(scipy_result, theano_result)
def test_opt_unpack(self):
#
......@@ -999,7 +998,7 @@ class test_structureddot(unittest.TestCase):
# fail if Theano is slower than scipy by more than a certain amount
overhead_tol = 0.003 # seconds overall
overhead_rtol = 1.2 # times as long
self.assertTrue(numpy.allclose(theano_result, scipy_result))
utt.assert_allclose(scipy_result, theano_result)
if not theano.config.mode in ["DebugMode", "DEBUG_MODE"]:
self.assertFalse(theano_time > overhead_rtol * scipy_time +
overhead_tol)
......@@ -1035,7 +1034,7 @@ class test_structureddot(unittest.TestCase):
# print 'scipy took', scipy_time
overhead_tol = 0.002 # seconds
overhead_rtol = 1.1 # times as long
self.assertTrue(numpy.allclose(theano_result, scipy_result))
utt.assert_allclose(scipy_result, theano_result)
if (not theano.config.mode in ["DebugMode", "DEBUG_MODE"] and
theano.config.cxx):
self.assertFalse(theano_time > overhead_rtol * scipy_time +
......@@ -1075,7 +1074,7 @@ class DotTests(utt.InferShapeTester):
f_a = theano.function([x, y], theano.sparse.dot(x, y))
f_b = lambda x, y: x * y
assert _allclose(f_a(x_v, y_v), f_b(x_v, y_v))
utt.assert_allclose(f_a(x_v, y_v), f_b(x_v, y_v))
# Test infer_shape
self._compile_and_check([x, y], [theano.sparse.dot(x, y)],
......@@ -1094,7 +1093,7 @@ class DotTests(utt.InferShapeTester):
f_a = theano.function([x, y], theano.sparse.dot(x, y))
f_b = lambda x, y: x * y
assert _allclose(f_a(x_v, y_v), f_b(x_v, y_v))
utt.assert_allclose(f_a(x_v, y_v), f_b(x_v, y_v))
# Test infer_shape
self._compile_and_check([x, y], [theano.sparse.dot(x, y)],
......@@ -1117,12 +1116,12 @@ class DotTests(utt.InferShapeTester):
x = theano.sparse.SparseType(format=x_f, dtype=d1)('x')
y = theano.sparse.SparseType(format=x_f, dtype=d2)('x')
f_a = theano.function([x, y], theano.sparse.dot(x, y))
f_b = lambda x, y: x * y
f_a = lambda x, y: x * y
f_b = theano.function([x, y], theano.sparse.dot(x, y))
vx = getattr(self, 'x_' + x_f).astype(d1)
vy = getattr(self, 'y_' + y_f).astype(d2)
assert _allclose(f_a(vx, vy), f_b(vx, vy).toarray())
utt.assert_allclose(f_a(vx, vy).toarray(), f_b(vx, vy))
# Test infer_shape
f_a = theano.function([x, y], theano.sparse.dot(x, y).shape)
......@@ -1150,7 +1149,7 @@ class DotTests(utt.InferShapeTester):
a_val = scipy.sparse.csr_matrix(random_lil((5, 3), 'float32', 5))
d_theano = f(a_val)
d_numpy = a_val * b.get_value()
assert numpy.allclose(d_theano, d_numpy)
utt.assert_allclose(d_numpy, d_theano)
def test_int32_dtype(self):
# Reported on the theano-user mailing-list:
......@@ -1256,7 +1255,7 @@ class UsmmTests(unittest.TestCase):
theano.tensor.basic.float64_atol = orig_atol
theano.tensor.basic.float64_rtol = orig_rtol
assert _allclose(f_a_out, f_b_out, rtol=1e-5), (f_a_out, f_b_out)
utt.assert_allclose(f_a_out, f_b_out, rtol=1e-5)
topo = f_a.maker.fgraph.toposort()
up = theano.scalar.upcast(dtype1, dtype2, dtype3, dtype4)
......@@ -1492,7 +1491,7 @@ class ColScaleCSCTester(utt.InferShapeTester):
expected = x * s
assert tested.format == format
assert numpy.allclose(tested.toarray(), expected)
utt.assert_allclose(expected, tested.toarray())
def test_infer_shape(self):
for format, cls in [('csc', sparse.ColScaleCSC),
......@@ -1533,7 +1532,7 @@ class RowScaleCSCTester(utt.InferShapeTester):
expected = x * s
assert tested.format == format
assert numpy.allclose(tested.toarray(), expected)
utt.assert_allclose(expected, tested.toarray())
def test_infer_shape(self):
for format, cls in [('csc', sparse.RowScaleCSC),
......@@ -1579,7 +1578,7 @@ class SpSumTester(utt.InferShapeTester):
f = theano.function(variable, self.op(variable[0], axis=axis))
tested = f(*data)
expected = data[0].todense().sum(axis).ravel()
assert numpy.allclose(tested, expected)
utt.assert_allclose(expected, tested)
def test_infer_shape(self):
for format in sparse.sparse_formats:
......@@ -1621,7 +1620,7 @@ class DiagTester(utt.InferShapeTester):
tested = f(*data)
expected = data[0].toarray().diagonal()
assert numpy.allclose(tested, expected)
utt.assert_allclose(expected, tested)
def test_infer_shape(self):
for format in sparse.sparse_formats:
......@@ -1659,7 +1658,7 @@ class SquareDiagonalTester(utt.InferShapeTester):
tested = f(*data).toarray()
expected = numpy.diag(*data)
assert numpy.allclose(tested, expected)
utt.assert_allclose(expected, tested)
assert tested.dtype == expected.dtype
assert tested.shape == expected.shape
......@@ -1701,7 +1700,7 @@ class EnsureSortedIndicesTester(utt.InferShapeTester):
tested = f(*data).toarray()
expected = data[0].sorted_indices().toarray()
assert numpy.allclose(tested, expected)
utt.assert_allclose(expected, tested)
def test_infer_shape(self):
for format in sparse.sparse_formats:
......@@ -1744,7 +1743,7 @@ class CleanTester(utt.InferShapeTester):
tested = tested.toarray()
expected = expected.toarray()
assert numpy.allclose(tested, expected)
utt.assert_allclose(expected, tested)
def test_grad(self):
for format in sparse.sparse_formats:
......@@ -2048,9 +2047,9 @@ class CastTester(utt.InferShapeTester):
t_cls = t_cls.toarray()
t_prop = t_prop.toarray()
assert numpy.allclose(t_func, expected)
assert numpy.allclose(t_cls, expected)
assert numpy.allclose(t_prop, expected)
utt.assert_allclose(expected, t_func)
utt.assert_allclose(expected, t_cls)
utt.assert_allclose(expected, t_prop)
def test_infer_shape(self):
for format in sparse.sparse_formats:
......@@ -2120,7 +2119,7 @@ class _HVStackTester(utt.InferShapeTester):
format=out_f,
dtype=dtype)
assert numpy.allclose(tested.toarray(), expected.toarray())
utt.assert_allclose(expected.toarray(), tested.toarray())
assert tested.format == expected.format
assert tested.dtype == expected.dtype
......@@ -2191,7 +2190,7 @@ class AddSSDataTester(utt.InferShapeTester):
tested = f(*self.a[format])
expected = 2 * self.a[format][0]
assert numpy.allclose(tested.toarray(), expected.toarray())
utt.assert_allclose(expected.toarray(), tested.toarray())
assert tested.format == expected.format
assert tested.dtype == expected.dtype
......@@ -2286,7 +2285,7 @@ def elemwise_checker(op, expected_f, gap=None, test_dtypes=None,
tested = tested.toarray()
try:
assert numpy.allclose(tested, expected)
utt.assert_allclose(expected, tested)
except AssertionError:
raise AssertionError(self.__name__)
......@@ -2348,7 +2347,7 @@ def elemwise_checker(op, expected_f, gap=None, test_dtypes=None,
tested = tested.toarray()
try:
assert numpy.allclose(tested, expected, rtol=1e-2)
utt.assert_allclose(tested, expected, rtol=1e-2)
except AssertionError:
raise AssertionError(self.__name__)
......@@ -2578,7 +2577,7 @@ class MulSVTester(unittest.TestCase):
out = f(spmat, mat)
assert numpy.allclose(out.toarray(), spmat.toarray() * mat)
utt.assert_allclose(spmat.toarray() * mat, out.toarray())
class StructuredAddSVTester(unittest.TestCase):
......@@ -2615,8 +2614,8 @@ class StructuredAddSVTester(unittest.TestCase):
out = f(spmat, mat)
assert numpy.allclose(out.toarray(),
spones.multiply(spmat + mat))
utt.assert_allclose(spones.multiply(spmat + mat),
out.toarray())
class SamplingDotTester(utt.InferShapeTester):
......@@ -2645,7 +2644,7 @@ class SamplingDotTester(utt.InferShapeTester):
x, y, p = self.a
expected = p.multiply(numpy.dot(x, y.T))
assert numpy.allclose(tested.toarray(), expected)
utt.assert_allclose(expected, tested.toarray())
assert tested.format == 'csr'
assert tested.dtype == expected.dtype
......
theano/tensor/basic.py
浏览文件 @ 60ad703d
......@@ -474,6 +474,8 @@ else:
def _allclose(a, b, rtol=None, atol=None):
a = numpy.asarray(a)
b = numpy.asarray(b)
narrow = 'float32', 'complex64'
if (str(a.dtype) in narrow) or (str(b.dtype) in narrow):
atol_ = float32_atol
......
theano/tests/unittest_tools.py
浏览文件 @ 60ad703d
from copy import copy, deepcopy
import logging
from StringIO import StringIO
import sys
import unittest
......@@ -239,3 +240,94 @@ class InferShapeTester(unittest.TestCase):
numeric_shapes = shapes_function(*numeric_inputs)
for out, shape in zip(numeric_outputs, numeric_shapes):
assert numpy.all(out.shape == shape)
def str_diagnostic(expected, value, rtol, atol):
"""Return a pretty multiline string representating the cause
of the exception"""
sio = StringIO()
try:
ssio = StringIO()
print >> ssio, " : shape, dtype, strides, min, max, n_inf, n_nan:"
print >> ssio, " Expected :",
print >> ssio, expected.shape,
print >> ssio, expected.dtype,
print >> ssio, expected.strides,
print >> ssio, expected.min(),
print >> ssio, expected.max(),
print >> ssio, numpy.isinf(expected).sum(),
print >> ssio, numpy.isnan(expected).sum(),
# only if all succeeds to we add anything to sio
print >> sio, ssio.getvalue()
except Exception:
pass
try:
ssio = StringIO()
print >> ssio, " Value :",
print >> ssio, value.shape,
print >> ssio, value.dtype,
print >> ssio, value.strides,
print >> ssio, value.min(),
print >> ssio, value.max(),
print >> ssio, numpy.isinf(value).sum(),
print >> ssio, numpy.isnan(value).sum(),
# only if all succeeds to we add anything to sio
print >> sio, ssio.getvalue()
except Exception:
pass
print >> sio, " expected :", expected
print >> sio, " value :", value
try:
ov = numpy.asarray(expected)
nv = numpy.asarray(value)
ssio = StringIO()
absdiff = numpy.absolute(nv - ov)
print >> ssio, " Max Abs Diff: ", numpy.max(absdiff)
print >> ssio, " Mean Abs Diff: ", numpy.mean(absdiff)
print >> ssio, " Median Abs Diff: ", numpy.median(absdiff)
print >> ssio, " Std Abs Diff: ", numpy.std(absdiff)
reldiff = numpy.absolute(nv - ov) / (numpy.absolute(nv) +
numpy.absolute(ov))
print >> ssio, " Max Rel Diff: ", numpy.max(reldiff)
print >> ssio, " Mean Rel Diff: ", numpy.mean(reldiff)
print >> ssio, " Median Rel Diff: ", numpy.median(reldiff)
print >> ssio, " Std Rel Diff: ", numpy.std(reldiff)
# only if all succeeds to we add anything to sio
print >> sio, ssio.getvalue()
except Exception:
pass
#Use the same formula as in _allclose to find the tolerance used
narrow = 'float32', 'complex64'
if ((str(expected.dtype) in narrow) or
(str(value.dtype) in narrow)):
atol_ = T.basic.float32_atol
rtol_ = T.basic.float32_rtol
else:
atol_ = T.basic.float64_atol
rtol_ = T.basic.float64_rtol
if rtol is not None:
rtol_ = rtol
if atol is not None:
atol_ = atol
print >> sio, " rtol, atol:", rtol_, atol_
return sio.getvalue()
class WrongValue(Exception):
def __init__(self, expected_val, val, rtol, atol):
self.val1 = expected_val
self.val2 = val
self.rtol = rtol
self.atol = atol
def __str__(self):
s = "WrongValue\n"
return s + str_diagnostic(self.val1, self.val2, self.rtol, self.atol)
def assert_allclose(val1, val2, rtol=None, atol=None):
if not T.basic._allclose(val1, val2, rtol, atol):
raise WrongValue(val1, val2, rtol, atol)
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