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-rw-r--r--tensorflow/python/framework/tensor_util_test.py72
1 files changed, 36 insertions, 36 deletions
diff --git a/tensorflow/python/framework/tensor_util_test.py b/tensorflow/python/framework/tensor_util_test.py
index d6edc13643..395cf43b3f 100644
--- a/tensorflow/python/framework/tensor_util_test.py
+++ b/tensorflow/python/framework/tensor_util_test.py
@@ -50,13 +50,13 @@ class TensorUtilTest(test.TestCase):
def testFloatN(self):
t = tensor_util.make_tensor_proto([10.0, 20.0, 30.0])
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "A \000\000A\240\000\000A\360\000\000"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "\000\000 A\000\000\240A\000\000\360A"
@@ -68,13 +68,13 @@ class TensorUtilTest(test.TestCase):
def testFloatTyped(self):
t = tensor_util.make_tensor_proto([10.0, 20.0, 30.0], dtype=dtypes.float32)
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "A \000\000A\240\000\000A\360\000\000"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "\000\000 A\000\000\240A\000\000\360A"
@@ -86,13 +86,13 @@ class TensorUtilTest(test.TestCase):
def testFloatTypeCoerce(self):
t = tensor_util.make_tensor_proto([10, 20, 30], dtype=dtypes.float32)
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "A \000\000A\240\000\000A\360\000\000"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "\000\000 A\000\000\240A\000\000\360A"
@@ -105,13 +105,13 @@ class TensorUtilTest(test.TestCase):
arr = np.asarray([10, 20, 30], dtype="int")
t = tensor_util.make_tensor_proto(arr, dtype=dtypes.float32)
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "A \000\000A\240\000\000A\360\000\000"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "\000\000 A\000\000\240A\000\000\360A"
@@ -123,13 +123,13 @@ class TensorUtilTest(test.TestCase):
def testFloatSizes(self):
t = tensor_util.make_tensor_proto([10.0, 20.0, 30.0], shape=[1, 3])
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 1 } dim { size: 3 } }
tensor_content: "A \000\000A\240\000\000A\360\000\000"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 1 } dim { size: 3 } }
tensor_content: "\000\000 A\000\000\240A\000\000\360A"
@@ -141,13 +141,13 @@ class TensorUtilTest(test.TestCase):
def testFloatSizes2(self):
t = tensor_util.make_tensor_proto([10.0, 20.0, 30.0], shape=[3, 1])
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } dim { size: 1 } }
tensor_content: "A \000\000A\240\000\000A\360\000\000"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } dim { size: 1 } }
tensor_content: "\000\000 A\000\000\240A\000\000\360A"
@@ -169,13 +169,13 @@ class TensorUtilTest(test.TestCase):
t = tensor_util.make_tensor_proto(
np.array([[10.0, 20.0, 30.0]], dtype=np.float64))
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_DOUBLE
tensor_shape { dim { size: 1 } dim { size: 3 } }
tensor_content: "@$\000\000\000\000\000\000@4\000\000\000\000\000\000@>\000\000\000\000\000\000"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_DOUBLE
tensor_shape { dim { size: 1 } dim { size: 3 } }
tensor_content: "\000\000\000\000\000\000$@\000\000\000\000\000\0004@\000\000\000\000\000\000>@"
@@ -206,13 +206,13 @@ class TensorUtilTest(test.TestCase):
self.assertEquals(np.float32, a.dtype)
self.assertAllClose(np.array([5.0, 20.0, 30.0], dtype=np.float32), a)
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "A \000\000A\240\000\000A\360\000\000"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_FLOAT
tensor_shape { dim { size: 3 } }
tensor_content: "\000\000 A\000\000\240A\000\000\360A"
@@ -299,16 +299,16 @@ class TensorUtilTest(test.TestCase):
def testIntNDefaultType(self):
t = tensor_util.make_tensor_proto([10, 20, 30, 40], shape=[2, 2])
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_INT32
tensor_shape { dim { size: 2 } dim { size: 2 } }
- tensor_content: "\000\000\000\\n\000\000\000\024\000\000\000\036\000\000\000("
+ tensor_content: "\000\000\000\n\000\000\000\024\000\000\000\036\000\000\000("
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_INT32
tensor_shape { dim { size: 2 } dim { size: 2 } }
- tensor_content: "\\n\000\000\000\024\000\000\000\036\000\000\000(\000\000\000"
+ tensor_content: "\n\000\000\000\024\000\000\000\036\000\000\000(\000\000\000"
""", t)
a = tensor_util.MakeNdarray(t)
self.assertEquals(np.int32, a.dtype)
@@ -380,16 +380,16 @@ class TensorUtilTest(test.TestCase):
t = tensor_util.make_tensor_proto(
[10, 20, 30], shape=[1, 3], dtype=dtypes.int64)
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_INT64
tensor_shape { dim { size: 1 } dim { size: 3 } }
- tensor_content: "\000\000\000\000\000\000\000\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036"
+ tensor_content: "\000\000\000\000\000\000\000\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_INT64
tensor_shape { dim { size: 1 } dim { size: 3 } }
- tensor_content: "\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036\000\000\000\000\000\000\000"
+ tensor_content: "\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036\000\000\000\000\000\000\000"
""", t)
a = tensor_util.MakeNdarray(t)
self.assertEquals(np.int64, a.dtype)
@@ -398,16 +398,16 @@ class TensorUtilTest(test.TestCase):
def testLongNpArray(self):
t = tensor_util.make_tensor_proto(np.array([10, 20, 30]))
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_INT64
tensor_shape { dim { size: 3 } }
- tensor_content: "\000\000\000\000\000\000\000\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036"
+ tensor_content: "\000\000\000\000\000\000\000\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_INT64
tensor_shape { dim { size: 3 } }
- tensor_content: "\\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036\000\000\000\000\000\000\000"
+ tensor_content: "\n\000\000\000\000\000\000\000\024\000\000\000\000\000\000\000\036\000\000\000\000\000\000\000"
""", t)
a = tensor_util.MakeNdarray(t)
self.assertEquals(np.int64, a.dtype)
@@ -419,13 +419,13 @@ class TensorUtilTest(test.TestCase):
t = tensor_util.make_tensor_proto(data, dtype=dtypes.qint32)
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_QINT32
tensor_shape { dim { size: 3 } }
tensor_content: "\000\000\000\025\000\000\000\026\000\000\000\027"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_QINT32
tensor_shape { dim { size: 3 } }
tensor_content: "\025\000\000\000\026\000\000\000\027\000\000\000"
@@ -435,7 +435,7 @@ class TensorUtilTest(test.TestCase):
self.assertAllEqual(np.array(data, dtype=a.dtype), a)
t = tensor_util.make_tensor_proto(data, dtype=dtypes.quint8)
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_QUINT8
tensor_shape { dim { size: 3 } }
tensor_content: "\025\026\027"
@@ -445,7 +445,7 @@ class TensorUtilTest(test.TestCase):
self.assertAllEqual(np.array(data, dtype=a.dtype), a)
t = tensor_util.make_tensor_proto(data, dtype=dtypes.qint8)
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_QINT8
tensor_shape { dim { size: 3 } }
tensor_content: "\025\026\027"
@@ -456,13 +456,13 @@ class TensorUtilTest(test.TestCase):
t = tensor_util.make_tensor_proto(data, dtype=dtypes.quint16)
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_QUINT16
tensor_shape { dim { size: 3 } }
tensor_content: "\000\025\000\026\000\027"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_QUINT16
tensor_shape { dim { size: 3 } }
tensor_content: "\025\000\026\000\027\000"
@@ -473,13 +473,13 @@ class TensorUtilTest(test.TestCase):
t = tensor_util.make_tensor_proto(data, dtype=dtypes.qint16)
if sys.byteorder == "big":
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_QINT16
tensor_shape { dim { size: 3 } }
tensor_content: "\000\025\000\026\000\027"
""", t)
else:
- self.assertProtoEquals("""
+ self.assertProtoEquals(r"""
dtype: DT_QINT16
tensor_shape { dim { size: 3 } }
tensor_content: "\025\000\026\000\027\000"
generated by cgit v1.2.3 (git 2.39.1) at 2024-06-04 16:43:48 +0000