diff --git a/tensorflow/python/framework/tensor_util.py b/tensorflow/python/framework/tensor_util.py
index 84788fbbbcc..cd5af835269 100644
--- a/tensorflow/python/framework/tensor_util.py
+++ b/tensorflow/python/framework/tensor_util.py
@@ -628,6 +628,10 @@ def MakeNdarray(tensor):
values = np.fromiter(tensor.int_val, dtype=dtype)
elif tensor_dtype == dtypes.int64:
values = np.fromiter(tensor.int64_val, dtype=dtype)
+ elif tensor_dtype == dtypes.uint32:
+ values = np.fromiter(tensor.uint32_val, dtype=dtype)
+ elif tensor_dtype == dtypes.uint64:
+ values = np.fromiter(tensor.uint64_val, dtype=dtype)
elif tensor_dtype == dtypes.complex64:
it = iter(tensor.scomplex_val)
values = np.array([complex(x[0], x[1]) for x in zip(it, it)], dtype=dtype)
diff --git a/tensorflow/python/framework/tensor_util_test.py b/tensorflow/python/framework/tensor_util_test.py
index ef61be76634..bc269f5f27c 100644
--- a/tensorflow/python/framework/tensor_util_test.py
+++ b/tensorflow/python/framework/tensor_util_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
import contextlib
import sys
+from absl.testing import parameterized
import numpy as np
from tensorflow.python.framework import constant_op
@@ -41,7 +42,7 @@ from tensorflow.python.platform import test
@test_util.run_all_in_graph_and_eager_modes
-class TensorUtilTest(test.TestCase):
+class TensorUtilTest(test.TestCase, parameterized.TestCase):
def testFloat(self):
value = 10.0
@@ -318,38 +319,42 @@ class TensorUtilTest(test.TestCase):
self.assertEqual(np.int32, a.dtype)
self.assertAllClose(np.array([[10, 20], [30, 40]], dtype=np.int32), a)
- def testIntTypes(self):
- for dtype, nptype in [(dtypes.int32, np.int32),
- (dtypes.uint8, np.uint8),
- (dtypes.uint16, np.uint16),
- (dtypes.int16, np.int16),
- (dtypes.int8, np.int8)]:
- # Test with array.
- t = tensor_util.make_tensor_proto([10, 20, 30], dtype=dtype)
- self.assertEqual(dtype, t.dtype)
- self.assertProtoEquals("dim { size: 3 }", t.tensor_shape)
- a = tensor_util.MakeNdarray(t)
- self.assertEqual(nptype, a.dtype)
- self.assertAllClose(np.array([10, 20, 30], dtype=nptype), a)
- # Test with ndarray.
- t = tensor_util.make_tensor_proto(np.array([10, 20, 30], dtype=nptype))
- self.assertEqual(dtype, t.dtype)
- self.assertProtoEquals("dim { size: 3 }", t.tensor_shape)
- a = tensor_util.MakeNdarray(t)
- self.assertEqual(nptype, a.dtype)
- self.assertAllClose(np.array([10, 20, 30], dtype=nptype), a)
+ @parameterized.named_parameters(
+ ("_int8", dtypes.int8, np.int8), ("_int16", dtypes.int16, np.int16),
+ ("_int32", dtypes.int32, np.int32), ("_int64", dtypes.int64, np.int64),
+ ("_uint8", dtypes.uint8, np.uint8), ("_uint16", dtypes.uint16, np.uint16),
+ ("_uint32", dtypes.uint32, np.uint32),
+ ("_uint64", dtypes.uint64, np.uint64))
+ def testIntTypes(self, dtype, nptype):
+ # Test with array.
+ t = tensor_util.make_tensor_proto([10, 20, 30], dtype=dtype)
+ self.assertEqual(dtype, t.dtype)
+ self.assertProtoEquals("dim { size: 3 }", t.tensor_shape)
+ a = tensor_util.MakeNdarray(t)
+ self.assertEqual(nptype, a.dtype)
+ self.assertAllClose(np.array([10, 20, 30], dtype=nptype), a)
+ # Test with ndarray.
+ t = tensor_util.make_tensor_proto(np.array([10, 20, 30], dtype=nptype))
+ self.assertEqual(dtype, t.dtype)
+ self.assertProtoEquals("dim { size: 3 }", t.tensor_shape)
+ a = tensor_util.MakeNdarray(t)
+ self.assertEqual(nptype, a.dtype)
+ self.assertAllClose(np.array([10, 20, 30], dtype=nptype), a)
- def testIntTypesWithImplicitRepeat(self):
- for dtype, nptype in [(dtypes.int64, np.int64), (dtypes.int32, np.int32),
- (dtypes.uint8, np.uint8), (dtypes.uint16, np.uint16),
- (dtypes.int16, np.int16), (dtypes.int8, np.int8)]:
- self.assertAllEqual(
- np.array([[10, 11, 12, 12], [12, 12, 12, 12], [12, 12, 12, 12]],
- dtype=nptype),
- tensor_util.MakeNdarray(
- tensor_util.make_tensor_proto([10, 11, 12],
- shape=[3, 4],
- dtype=dtype)))
+ @parameterized.named_parameters(
+ ("_int8", dtypes.int8, np.int8), ("_int16", dtypes.int16, np.int16),
+ ("_int32", dtypes.int32, np.int32), ("_int64", dtypes.int64, np.int64),
+ ("_uint8", dtypes.uint8, np.uint8), ("_uint16", dtypes.uint16, np.uint16),
+ ("_uint32", dtypes.uint32, np.uint32),
+ ("_uint64", dtypes.uint64, np.uint64))
+ def testIntTypesWithImplicitRepeat(self, dtype, nptype):
+ self.assertAllEqual(
+ np.array([[10, 11, 12, 12], [12, 12, 12, 12], [12, 12, 12, 12]],
+ dtype=nptype),
+ tensor_util.MakeNdarray(
+ tensor_util.make_tensor_proto([10, 11, 12],
+ shape=[3, 4],
+ dtype=dtype)))
def testIntMixedWithDimension(self):
# Github issue: 11974
@@ -362,53 +367,73 @@ class TensorUtilTest(test.TestCase):
self.assertEqual(nptype, a.dtype)
self.assertAllClose(np.array([10, 20, 30], dtype=nptype), a)
- def testLong(self):
- t = tensor_util.make_tensor_proto(10, dtype=dtypes.int64)
- self.assertProtoEquals("""
- dtype: DT_INT64
+ @parameterized.named_parameters(
+ ("_int64", dtypes.int64, np.int64, "DT_INT64", "int64_val"),
+ ("_uint64", dtypes.uint64, np.uint64, "DT_UINT64", "uint64_val"))
+ def testLong(self, dtype, nptype, proto_dtype, proto_value_name):
+ t = tensor_util.make_tensor_proto(10, dtype=dtype)
+ self.assertProtoEquals(
+ """
+ dtype: %s
tensor_shape {}
- int64_val: 10
- """, t)
+ %s: 10
+ """ % (proto_dtype, proto_value_name), t)
a = tensor_util.MakeNdarray(t)
- self.assertEqual(np.int64, a.dtype)
- self.assertAllClose(np.array(10, dtype=np.int64), a)
+ self.assertEqual(nptype, a.dtype)
+ self.assertAllClose(np.array(10, dtype=nptype), a)
- def testLongN(self):
- t = tensor_util.make_tensor_proto(
- [10, 20, 30], shape=[1, 3], dtype=dtypes.int64)
+ @parameterized.named_parameters(
+ ("_int64", dtypes.int64, np.int64, "DT_INT64"),
+ ("_uint64", dtypes.uint64, np.uint64, "DT_UINT64"))
+ def testLongN(self, dtype, nptype, proto_dtype):
+ t = tensor_util.make_tensor_proto([10, 20, 30], shape=[1, 3], dtype=dtype)
if sys.byteorder == "big":
- self.assertProtoEquals(r"""
- dtype: DT_INT64
+ # pylint: disable=line-too-long
+ self.assertProtoEquals(
+ r"""
+ dtype: %s
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"
- """, t)
+ """ % proto_dtype, t)
+ # pylint: enable=line-too-long
else:
- self.assertProtoEquals(r"""
- dtype: DT_INT64
+ # pylint: disable=line-too-long
+ self.assertProtoEquals(
+ r"""
+ dtype: %s
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"
- """, t)
+ """ % proto_dtype, t)
+ # pylint: enable=line-too-long
a = tensor_util.MakeNdarray(t)
- self.assertEqual(np.int64, a.dtype)
- self.assertAllClose(np.array([[10, 20, 30]], dtype=np.int64), a)
+ self.assertEqual(nptype, a.dtype)
+ self.assertAllClose(np.array([[10, 20, 30]], dtype=nptype), a)
- def testLongNpArray(self):
- t = tensor_util.make_tensor_proto(np.array([10, 20, 30]))
+ @parameterized.named_parameters(("_int64", np.int64, "DT_INT64"),
+ ("_uint64", np.uint64, "DT_UINT64"))
+ def testLongNpArray(self, nptype, proto_dtype):
+ t = tensor_util.make_tensor_proto(np.array([10, 20, 30], dtype=nptype))
if sys.byteorder == "big":
- self.assertProtoEquals(r"""
- dtype: DT_INT64
+ # pylint: disable=line-too-long
+ self.assertProtoEquals(
+ r"""
+ dtype: %s
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"
- """, t)
+ """ % proto_dtype, t)
+ # pylint: enable=line-too-long
else:
- self.assertProtoEquals(r"""
- dtype: DT_INT64
+ # pylint: disable=line-too-long
+ self.assertProtoEquals(
+ r"""
+ dtype: %s
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"
- """, t)
+ """ % proto_dtype, t)
+ # pylint: enable=line-too-long
a = tensor_util.MakeNdarray(t)
- self.assertEqual(np.int64, a.dtype)
- self.assertAllClose(np.array([10, 20, 30], dtype=np.int64), a)
+ self.assertEqual(nptype, a.dtype)
+ self.assertAllClose(np.array([10, 20, 30], dtype=nptype), a)
def testQuantizedTypes(self):
# Test with array.