提交 bd8add03 authored 作者: Frederic's avatar Frederic

pep8

上级 16683490
import os, sys, traceback, warnings import os
import sys
import traceback
import warnings
import numpy import numpy
from nose.plugins.skip import SkipTest from nose.plugins.skip import SkipTest
...@@ -46,34 +49,33 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -46,34 +49,33 @@ class TestComputeTestValue(unittest.TestCase):
theano.config.compute_test_value = 'raise' theano.config.compute_test_value = 'raise'
x = T.matrix('x') x = T.matrix('x')
x.tag.test_value = numpy.random.rand(3,4).astype(config.floatX) x.tag.test_value = numpy.random.rand(3, 4).astype(config.floatX)
y = T.matrix('y') y = T.matrix('y')
y.tag.test_value = numpy.random.rand(4,5).astype(config.floatX) y.tag.test_value = numpy.random.rand(4, 5).astype(config.floatX)
# should work # should work
z = T.dot(x,y) z = T.dot(x, y)
assert hasattr(z.tag, 'test_value') assert hasattr(z.tag, 'test_value')
f = theano.function([x,y], z) f = theano.function([x, y], z)
assert _allclose(f(x.tag.test_value, y.tag.test_value), assert _allclose(f(x.tag.test_value, y.tag.test_value),
z.tag.test_value) z.tag.test_value)
# this test should fail # this test should fail
y.tag.test_value = numpy.random.rand(6,5).astype(config.floatX) y.tag.test_value = numpy.random.rand(6, 5).astype(config.floatX)
self.assertRaises(ValueError, T.dot, x, y) self.assertRaises(ValueError, T.dot, x, y)
finally: finally:
theano.config.compute_test_value = orig_compute_test_value theano.config.compute_test_value = orig_compute_test_value
def test_compute_flag(self): def test_compute_flag(self):
orig_compute_test_value = theano.config.compute_test_value orig_compute_test_value = theano.config.compute_test_value
try: try:
x = T.matrix('x') x = T.matrix('x')
y = T.matrix('y') y = T.matrix('y')
y.tag.test_value = numpy.random.rand(4,5).astype(config.floatX) y.tag.test_value = numpy.random.rand(4, 5).astype(config.floatX)
# should skip computation of test value # should skip computation of test value
theano.config.compute_test_value = 'off' theano.config.compute_test_value = 'off'
z = T.dot(x,y) z = T.dot(x, y)
assert not hasattr(z.tag, 'test_value') assert not hasattr(z.tag, 'test_value')
# should fail when asked by user # should fail when asked by user
...@@ -99,25 +101,25 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -99,25 +101,25 @@ class TestComputeTestValue(unittest.TestCase):
theano.config.compute_test_value = 'raise' theano.config.compute_test_value = 'raise'
x = T.matrix('x') x = T.matrix('x')
x.tag.test_value = numpy.random.rand(3,4).astype(config.floatX) x.tag.test_value = numpy.random.rand(3, 4).astype(config.floatX)
y = T.matrix('y') y = T.matrix('y')
y.tag.test_value = numpy.random.rand(4,5).astype(config.floatX) y.tag.test_value = numpy.random.rand(4, 5).astype(config.floatX)
z = theano.shared(numpy.random.rand(5,6).astype(config.floatX)) z = theano.shared(numpy.random.rand(5, 6).astype(config.floatX))
# should work # should work
out = T.dot(T.dot(x,y), z) out = T.dot(T.dot(x, y), z)
assert hasattr(out.tag, 'test_value') assert hasattr(out.tag, 'test_value')
tf = theano.function([x,y], out) tf = theano.function([x, y], out)
assert _allclose( assert _allclose(
tf(x.tag.test_value, y.tag.test_value), tf(x.tag.test_value, y.tag.test_value),
out.tag.test_value) out.tag.test_value)
def f(x,y,z): def f(x, y, z):
return T.dot(T.dot(x,y),z) return T.dot(T.dot(x, y), z)
# this test should fail # this test should fail
z.set_value(numpy.random.rand(7,6).astype(config.floatX)) z.set_value(numpy.random.rand(7, 6).astype(config.floatX))
self.assertRaises(ValueError, f, x, y, z) self.assertRaises(ValueError, f, x, y, z)
finally: finally:
theano.config.compute_test_value = orig_compute_test_value theano.config.compute_test_value = orig_compute_test_value
...@@ -128,17 +130,18 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -128,17 +130,18 @@ class TestComputeTestValue(unittest.TestCase):
theano.config.compute_test_value = 'raise' theano.config.compute_test_value = 'raise'
x = T.matrix('x') x = T.matrix('x')
x.tag.test_value = numpy.random.rand(3,4).astype(config.floatX) x.tag.test_value = numpy.random.rand(3, 4).astype(config.floatX)
y = theano.shared(numpy.random.rand(4,6).astype(config.floatX), 'y') y = theano.shared(numpy.random.rand(4, 6).astype(config.floatX),
'y')
# should work # should work
z = T.dot(x,y) z = T.dot(x, y)
assert hasattr(z.tag, 'test_value') assert hasattr(z.tag, 'test_value')
f = theano.function([x], z) f = theano.function([x], z)
assert _allclose(f(x.tag.test_value), z.tag.test_value) assert _allclose(f(x.tag.test_value), z.tag.test_value)
# this test should fail # this test should fail
y.set_value(numpy.random.rand(5,6).astype(config.floatX)) y.set_value(numpy.random.rand(5, 6).astype(config.floatX))
self.assertRaises(ValueError, T.dot, x, y) self.assertRaises(ValueError, T.dot, x, y)
finally: finally:
theano.config.compute_test_value = orig_compute_test_value theano.config.compute_test_value = orig_compute_test_value
...@@ -148,17 +151,18 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -148,17 +151,18 @@ class TestComputeTestValue(unittest.TestCase):
try: try:
theano.config.compute_test_value = 'raise' theano.config.compute_test_value = 'raise'
x = numpy.random.rand(2,3).astype(config.floatX) x = numpy.random.rand(2, 3).astype(config.floatX)
y = theano.shared(numpy.random.rand(3,6).astype(config.floatX), 'y') y = theano.shared(numpy.random.rand(3, 6).astype(config.floatX),
'y')
# should work # should work
z = T.dot(x,y) z = T.dot(x, y)
assert hasattr(z.tag, 'test_value') assert hasattr(z.tag, 'test_value')
f = theano.function([], z) f = theano.function([], z)
assert _allclose(f(), z.tag.test_value) assert _allclose(f(), z.tag.test_value)
# this test should fail # this test should fail
x = numpy.random.rand(2,4).astype(config.floatX) x = numpy.random.rand(2, 4).astype(config.floatX)
self.assertRaises(ValueError, T.dot, x, y) self.assertRaises(ValueError, T.dot, x, y)
finally: finally:
theano.config.compute_test_value = orig_compute_test_value theano.config.compute_test_value = orig_compute_test_value
...@@ -168,17 +172,18 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -168,17 +172,18 @@ class TestComputeTestValue(unittest.TestCase):
try: try:
theano.config.compute_test_value = 'raise' theano.config.compute_test_value = 'raise'
x = T.constant(numpy.random.rand(2,3), dtype=config.floatX) x = T.constant(numpy.random.rand(2, 3), dtype=config.floatX)
y = theano.shared(numpy.random.rand(3,6).astype(config.floatX), 'y') y = theano.shared(numpy.random.rand(3, 6).astype(config.floatX),
'y')
# should work # should work
z = T.dot(x,y) z = T.dot(x, y)
assert hasattr(z.tag, 'test_value') assert hasattr(z.tag, 'test_value')
f = theano.function([], z) f = theano.function([], z)
assert _allclose(f(), z.tag.test_value) assert _allclose(f(), z.tag.test_value)
# this test should fail # this test should fail
x = T.constant(numpy.random.rand(2,4), dtype=config.floatX) x = T.constant(numpy.random.rand(2, 4), dtype=config.floatX)
self.assertRaises(ValueError, T.dot, x, y) self.assertRaises(ValueError, T.dot, x, y)
finally: finally:
theano.config.compute_test_value = orig_compute_test_value theano.config.compute_test_value = orig_compute_test_value
...@@ -190,9 +195,9 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -190,9 +195,9 @@ class TestComputeTestValue(unittest.TestCase):
x = T.fmatrix('x') x = T.fmatrix('x')
# Incorrect dtype (float64) for test_value # Incorrect dtype (float64) for test_value
x.tag.test_value = numpy.random.rand(3,4) x.tag.test_value = numpy.random.rand(3, 4)
y = T.dmatrix('y') y = T.dmatrix('y')
y.tag.test_value = numpy.random.rand(4,5) y.tag.test_value = numpy.random.rand(4, 5)
self.assertRaises(TypeError, T.dot, x, y) self.assertRaises(TypeError, T.dot, x, y)
finally: finally:
...@@ -205,9 +210,9 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -205,9 +210,9 @@ class TestComputeTestValue(unittest.TestCase):
try: try:
config.compute_test_value = "raise" config.compute_test_value = "raise"
x = T.matrix() x = T.matrix()
x.tag.test_value = numpy.zeros((2,3), dtype=config.floatX) x.tag.test_value = numpy.zeros((2, 3), dtype=config.floatX)
y = T.matrix() y = T.matrix()
y.tag.test_value = numpy.zeros((2,2), dtype=config.floatX) y.tag.test_value = numpy.zeros((2, 2), dtype=config.floatX)
self.assertRaises(ValueError, x.__mul__, y) self.assertRaises(ValueError, x.__mul__, y)
finally: finally:
theano.config.compute_test_value = orig_compute_test_value theano.config.compute_test_value = orig_compute_test_value
...@@ -250,7 +255,7 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -250,7 +255,7 @@ class TestComputeTestValue(unittest.TestCase):
k = T.iscalar("k") k = T.iscalar("k")
A = T.matrix("A") A = T.matrix("A")
k.tag.test_value = 3 k.tag.test_value = 3
A.tag.test_value = numpy.random.rand(5,3).astype(config.floatX) A.tag.test_value = numpy.random.rand(5, 3).astype(config.floatX)
def fx(prior_result, A): def fx(prior_result, A):
return T.dot(prior_result, A) return T.dot(prior_result, A)
...@@ -286,7 +291,7 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -286,7 +291,7 @@ class TestComputeTestValue(unittest.TestCase):
k = T.iscalar("k") k = T.iscalar("k")
A = T.matrix("A") A = T.matrix("A")
k.tag.test_value = 3 k.tag.test_value = 3
A.tag.test_value = numpy.random.rand(5,3).astype(config.floatX) A.tag.test_value = numpy.random.rand(5, 3).astype(config.floatX)
def fx(prior_result, A): def fx(prior_result, A):
return T.dot(prior_result, A) return T.dot(prior_result, A)
...@@ -338,7 +343,6 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -338,7 +343,6 @@ class TestComputeTestValue(unittest.TestCase):
output, = outputs output, = outputs
output[0] = input + 1 output[0] = input + 1
orig_compute_test_value = theano.config.compute_test_value orig_compute_test_value = theano.config.compute_test_value
try: try:
theano.config.compute_test_value = 'raise' theano.config.compute_test_value = 'raise'
...@@ -349,7 +353,8 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -349,7 +353,8 @@ class TestComputeTestValue(unittest.TestCase):
o = IncOnePython()(i) o = IncOnePython()(i)
# Check that the c_code function is not implemented # Check that the c_code function is not implemented
self.assertRaises((NotImplementedError, utils.MethodNotDefined), self.assertRaises(
(NotImplementedError, utils.MethodNotDefined),
o.owner.op.c_code, o.owner.op.c_code,
o.owner, 'o', ['x'], 'z', {'fail': ''}) o.owner, 'o', ['x'], 'z', {'fail': ''})
...@@ -391,7 +396,8 @@ class TestComputeTestValue(unittest.TestCase): ...@@ -391,7 +396,8 @@ class TestComputeTestValue(unittest.TestCase):
orig_compute_test_value = theano.config.compute_test_value orig_compute_test_value = theano.config.compute_test_value
try: try:
theano.config.compute_test_value = 'raise' theano.config.compute_test_value = 'raise'
init_Mu1 = theano.shared(numpy.zeros((5,),dtype=config.floatX)).dimshuffle('x',0) init_Mu1 = theano.shared(
numpy.zeros((5,), dtype=config.floatX)).dimshuffle('x', 0)
f = theano.function([], outputs=[init_Mu1]) f = theano.function([], outputs=[init_Mu1])
finally: finally:
......
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