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6acf609 |
--- theano/compile/mode.py.orig 2019-01-15 14:13:57.000000000 -0700
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6acf609 |
+++ theano/compile/mode.py 2019-08-22 13:25:25.024334947 -0600
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6acf609 |
@@ -261,7 +261,7 @@ class Mode(object):
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6acf609 |
def __init__(self, linker=None, optimizer='default'):
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6acf609 |
if linker is None:
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6acf609 |
linker = config.linker
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6acf609 |
- if optimizer is 'default':
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6acf609 |
+ if optimizer == 'default':
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6acf609 |
optimizer = config.optimizer
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6acf609 |
Mode.__setstate__(self, (linker, optimizer))
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6acf609 |
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6acf609 |
--- theano/gof/opt.py.orig 2019-01-15 14:13:57.000000000 -0700
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6acf609 |
+++ theano/gof/opt.py 2019-08-22 14:06:43.820896086 -0600
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6acf609 |
@@ -1284,7 +1284,7 @@ def local_optimizer(tracks, inplace=Fals
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6acf609 |
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6acf609 |
"""
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6acf609 |
if tracks is not None:
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6acf609 |
- if len(tracks) is 0:
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6acf609 |
+ if len(tracks) == 0:
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raise ValueError("Use None instead of an empty list to apply to all nodes.", f.__module__, f.__name__)
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6acf609 |
for t in tracks:
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6acf609 |
if not (isinstance(t, op.Op) or issubclass(t, op.PureOp)):
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6acf609 |
--- theano/gof/tests/test_link.py.orig 2019-01-15 14:13:57.000000000 -0700
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6acf609 |
+++ theano/gof/tests/test_link.py 2019-08-22 16:29:02.294513027 -0600
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6acf609 |
@@ -113,7 +113,7 @@ class TestPerformLinker(unittest.TestCas
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6acf609 |
def test_input_output_same(self):
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6acf609 |
x, y, z = inputs()
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6acf609 |
fn = perform_linker(FunctionGraph([x], [x])).make_function()
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6acf609 |
- assert 1.0 is fn(1.0)
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6acf609 |
+ assert 1.0 == fn(1.0)
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6acf609 |
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6acf609 |
def test_input_dependency0(self):
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6acf609 |
x, y, z = inputs()
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6acf609 |
--- theano/tensor/nnet/bn.py.orig 2019-01-15 14:13:57.000000000 -0700
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6acf609 |
+++ theano/tensor/nnet/bn.py 2019-08-22 13:35:49.109305914 -0600
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6acf609 |
@@ -642,7 +642,7 @@ class AbstractBatchNormTrainGrad(Op):
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6acf609 |
# some inputs should be disconnected
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6acf609 |
results = [g_wrt_x, g_wrt_dy, g_wrt_scale, g_wrt_x_mean, g_wrt_x_invstd,
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6acf609 |
theano.gradient.DisconnectedType()()]
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6acf609 |
- return [theano.gradient.DisconnectedType()() if r is 0 else r
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6acf609 |
+ return [theano.gradient.DisconnectedType()() if r == 0 else r
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6acf609 |
for r in results]
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6acf609 |
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6acf609 |
def connection_pattern(self, node):
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6acf609 |
--- theano/tensor/nnet/tests/test_conv.py.orig 2019-01-15 14:13:57.000000000 -0700
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6acf609 |
+++ theano/tensor/nnet/tests/test_conv.py 2019-08-22 16:29:51.149656121 -0600
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6acf609 |
@@ -95,7 +95,7 @@ class TestConv2D(utt.InferShapeTester):
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6acf609 |
# REFERENCE IMPLEMENTATION
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6acf609 |
s = 1.
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6acf609 |
orig_image_data = image_data
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6acf609 |
- if border_mode is not 'full':
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6acf609 |
+ if border_mode != 'full':
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6acf609 |
s = -1.
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6acf609 |
out_shape2d = np.array(N_image_shape[-2:]) +\
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6acf609 |
s * np.array(N_filter_shape[-2:]) - s
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6acf609 |
--- theano/tests/test_determinism.py.orig 2019-01-15 14:13:57.000000000 -0700
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6acf609 |
+++ theano/tests/test_determinism.py 2019-08-22 16:31:03.119393791 -0600
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6acf609 |
@@ -57,7 +57,7 @@ def test_determinism_1():
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6acf609 |
updates.append((s, val))
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6acf609 |
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6acf609 |
for var in theano.gof.graph.ancestors(update for _, update in updates):
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6acf609 |
- if var.name is not None and var.name is not 'b':
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6acf609 |
+ if var.name is not None and var.name != 'b':
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6acf609 |
if var.name[0] != 's' or len(var.name) != 2:
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6acf609 |
var.name = None
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6acf609 |
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