diff options
Diffstat (limited to 'tensorflow/python/framework/tensor_util_test.py')
| -rw-r--r-- | tensorflow/python/framework/tensor_util_test.py | 28 |
1 files changed, 14 insertions, 14 deletions
diff --git a/tensorflow/python/framework/tensor_util_test.py b/tensorflow/python/framework/tensor_util_test.py index dfefc27f99..5eb5230404 100644 --- a/tensorflow/python/framework/tensor_util_test.py +++ b/tensorflow/python/framework/tensor_util_test.py @@ -18,8 +18,8 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function -import numpy as np import sys +import numpy as np from tensorflow.python.framework import constant_op from tensorflow.python.framework import dtypes @@ -49,7 +49,7 @@ 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(""" dtype: DT_FLOAT tensor_shape { dim { size: 3 } } tensor_content: "A \000\000A\240\000\000A\360\000\000" @@ -67,7 +67,7 @@ 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(""" dtype: DT_FLOAT tensor_shape { dim { size: 3 } } tensor_content: "A \000\000A\240\000\000A\360\000\000" @@ -85,7 +85,7 @@ 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(""" dtype: DT_FLOAT tensor_shape { dim { size: 3 } } tensor_content: "A \000\000A\240\000\000A\360\000\000" @@ -104,7 +104,7 @@ 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(""" dtype: DT_FLOAT tensor_shape { dim { size: 3 } } tensor_content: "A \000\000A\240\000\000A\360\000\000" @@ -122,7 +122,7 @@ 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(""" dtype: DT_FLOAT tensor_shape { dim { size: 1 } dim { size: 3 } } tensor_content: "A \000\000A\240\000\000A\360\000\000" @@ -140,7 +140,7 @@ 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(""" dtype: DT_FLOAT tensor_shape { dim { size: 3 } dim { size: 1 } } tensor_content: "A \000\000A\240\000\000A\360\000\000" @@ -168,7 +168,7 @@ 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(""" 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" @@ -259,7 +259,7 @@ 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(""" 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(" @@ -329,7 +329,7 @@ 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(""" 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" @@ -347,7 +347,7 @@ 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(""" 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" @@ -368,7 +368,7 @@ class TensorUtilTest(test.TestCase): t = tensor_util.make_tensor_proto(data, dtype=dtypes.qint32) if sys.byteorder == "big": - self.assertProtoEquals(""" + self.assertProtoEquals(""" dtype: DT_QINT32 tensor_shape { dim { size: 3 } } tensor_content: "\000\000\000\025\000\000\000\026\000\000\000\027" @@ -405,7 +405,7 @@ class TensorUtilTest(test.TestCase): t = tensor_util.make_tensor_proto(data, dtype=dtypes.quint16) if sys.byteorder == "big": - self.assertProtoEquals(""" + self.assertProtoEquals(""" dtype: DT_QUINT16 tensor_shape { dim { size: 3 } } tensor_content: "\000\025\000\026\000\027" @@ -422,7 +422,7 @@ class TensorUtilTest(test.TestCase): t = tensor_util.make_tensor_proto(data, dtype=dtypes.qint16) if sys.byteorder == "big": - self.assertProtoEquals(""" + self.assertProtoEquals(""" dtype: DT_QINT16 tensor_shape { dim { size: 3 } } tensor_content: "\000\025\000\026\000\027" |