提交 93134870 authored 作者: Frederic Bastien's avatar Frederic Bastien

flake8

上级 f92772ed
...@@ -230,7 +230,7 @@ class TestAssertConvShape(unittest.TestCase): ...@@ -230,7 +230,7 @@ class TestAssertConvShape(unittest.TestCase):
class TestAssertShape(unittest.TestCase): class TestAssertShape(unittest.TestCase):
@change_flags([("conv.assert_shape",True)]) @change_flags([("conv.assert_shape", True)])
def test_basic(self): def test_basic(self):
x = tensor.tensor4() x = tensor.tensor4()
s1 = tensor.iscalar() s1 = tensor.iscalar()
...@@ -246,7 +246,7 @@ class TestAssertShape(unittest.TestCase): ...@@ -246,7 +246,7 @@ class TestAssertShape(unittest.TestCase):
assert_raises(AssertionError, f, v, 0, 7) assert_raises(AssertionError, f, v, 0, 7)
assert_raises(AssertionError, f, v, 7, 7) assert_raises(AssertionError, f, v, 7, 7)
@change_flags([("conv.assert_shape",True)]) @change_flags([("conv.assert_shape", True)])
def test_shape_check_conv2d(self): def test_shape_check_conv2d(self):
input = tensor.tensor4() input = tensor.tensor4()
filters = tensor.tensor4() filters = tensor.tensor4()
...@@ -264,7 +264,7 @@ class TestAssertShape(unittest.TestCase): ...@@ -264,7 +264,7 @@ class TestAssertShape(unittest.TestCase):
numpy.zeros((3, 5, 7, 11), dtype='float32'), numpy.zeros((3, 5, 7, 11), dtype='float32'),
numpy.zeros((7, 5, 2, 2), dtype='float32')) numpy.zeros((7, 5, 2, 2), dtype='float32'))
@change_flags([("conv.assert_shape",True)]) @change_flags([("conv.assert_shape", True)])
def test_shape_check_conv3d(self): def test_shape_check_conv3d(self):
input = tensor.tensor5() input = tensor.tensor5()
filters = tensor.tensor5() filters = tensor.tensor5()
...@@ -282,7 +282,7 @@ class TestAssertShape(unittest.TestCase): ...@@ -282,7 +282,7 @@ class TestAssertShape(unittest.TestCase):
numpy.zeros((3, 5, 7, 11, 13), dtype='float32'), numpy.zeros((3, 5, 7, 11, 13), dtype='float32'),
numpy.zeros((7, 5, 2, 2, 2), dtype='float32')) numpy.zeros((7, 5, 2, 2, 2), dtype='float32'))
@change_flags([("conv.assert_shape",True)]) @change_flags([("conv.assert_shape", True)])
def test_shape_check_conv2d_grad_wrt_inputs(self): def test_shape_check_conv2d_grad_wrt_inputs(self):
output_grad = tensor.tensor4() output_grad = tensor.tensor4()
filters = tensor.tensor4() filters = tensor.tensor4()
...@@ -296,7 +296,7 @@ class TestAssertShape(unittest.TestCase): ...@@ -296,7 +296,7 @@ class TestAssertShape(unittest.TestCase):
numpy.zeros((3, 6, 5, 9), dtype='float32'), numpy.zeros((3, 6, 5, 9), dtype='float32'),
numpy.zeros((7, 6, 3, 3), dtype='float32')) numpy.zeros((7, 6, 3, 3), dtype='float32'))
@change_flags([("conv.assert_shape",True)]) @change_flags([("conv.assert_shape", True)])
def test_shape_check_conv3d_grad_wrt_inputs(self): def test_shape_check_conv3d_grad_wrt_inputs(self):
output_grad = tensor.tensor5() output_grad = tensor.tensor5()
filters = tensor.tensor5() filters = tensor.tensor5()
...@@ -310,7 +310,7 @@ class TestAssertShape(unittest.TestCase): ...@@ -310,7 +310,7 @@ class TestAssertShape(unittest.TestCase):
numpy.zeros((3, 6, 5, 9, 11), dtype='float32'), numpy.zeros((3, 6, 5, 9, 11), dtype='float32'),
numpy.zeros((7, 6, 3, 3, 3), dtype='float32')) numpy.zeros((7, 6, 3, 3, 3), dtype='float32'))
@change_flags([("conv.assert_shape",True)]) @change_flags([("conv.assert_shape", True)])
def test_shape_check_conv2d_grad_wrt_weights(self): def test_shape_check_conv2d_grad_wrt_weights(self):
input = tensor.tensor4() input = tensor.tensor4()
output_grad = tensor.tensor4() output_grad = tensor.tensor4()
...@@ -324,7 +324,7 @@ class TestAssertShape(unittest.TestCase): ...@@ -324,7 +324,7 @@ class TestAssertShape(unittest.TestCase):
numpy.zeros((3, 6, 7, 11), dtype='float32'), numpy.zeros((3, 6, 7, 11), dtype='float32'),
numpy.zeros((3, 7, 5, 9), dtype='float32')) numpy.zeros((3, 7, 5, 9), dtype='float32'))
@change_flags([("conv.assert_shape",True)]) @change_flags([("conv.assert_shape", True)])
def test_shape_check_conv3d_grad_wrt_weights(self): def test_shape_check_conv3d_grad_wrt_weights(self):
input = tensor.tensor5() input = tensor.tensor5()
output_grad = tensor.tensor5() output_grad = tensor.tensor5()
......
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