Merge changes from github.

Revert #18413. Too many internal test failures due to the name scope change caused by this change.
Revert #18192. Cannot use re2::StringPiece internally. Need alternative for set call. Will pull and clean this up in a separate change.

PiperOrigin-RevId: 197991247

4 files changed, 31 insertions, 21 deletions

diff --git a/tensorflow/python/framework/fast_tensor_util.pyx b/tensorflow/python/framework/fast_tensor_util.pyx
index 19928314ef..17d112a1ec 100644
--- a/tensorflow/python/framework/fast_tensor_util.pyx
+++ b/tensorflow/python/framework/fast_tensor_util.pyx
@@ -7,6 +7,18 @@ cimport numpy as np
 from tensorflow.python.util import compat
 
 
+def AppendFloat16ArrayToTensorProto(
+    # For numpy, npy_half is a typedef for npy_uint16,
+    # see: https://github.com/numpy/numpy/blob/master/doc/source/reference/c-api.coremath.rst#half-precision-functions
+    # Because np.float16_t dosen't exist in cython, we use uint16_t here.
+    # TODO: Use np.float16_t when cython supports it.
+    tensor_proto, np.ndarray[np.uint16_t, ndim=1] nparray):
+  cdef long i, n
+  n = nparray.size
+  for i in range(n):
+    tensor_proto.half_val.append(nparray[i])
+
+
 def AppendFloat32ArrayToTensorProto(
     tensor_proto, np.ndarray[np.float32_t, ndim=1] nparray):
   cdef long i, n
diff --git a/tensorflow/python/framework/ops.py b/tensorflow/python/framework/ops.py
index 80140e4063..9fc8136348 100644
--- a/tensorflow/python/framework/ops.py
+++ b/tensorflow/python/framework/ops.py
@@ -2582,7 +2582,7 @@ def set_shape_and_handle_data_for_outputs(op):
 
   When _USE_C_API = True, this is lazily called when a tensor's shape is first
   requested. Usually this should work automatically, but some edge cases may
-  require manaully calling this first to make sure Tensor._shape_val and
+  require manually calling this first to make sure Tensor._shape_val and
   Tensor._handle_data are set (e.g. manually overriding _handle_data, copying a
   Tensor).
   """
@@ -5426,36 +5426,30 @@ def enable_eager_execution(config=None, device_policy=None,
       in which operations are executed. Note that @{tf.ConfigProto} is also
       used to configure graph execution (via @{tf.Session}) and many options
       within `tf.ConfigProto` are not implemented (or are irrelevant) when
-     eager execution is enabled.
+      eager execution is enabled.
     device_policy: (Optional.) Policy controlling how operations requiring
-     inputs on a specific device (e.g., a GPU 0) handle inputs on a different
-     device  (e.g. GPU 1 or CPU). When set to None, an appropriate value will be
-     picked automatically. The value picked may change between TensorFlow
-     releases.
-     Valid values:
-
+      inputs on a specific device (e.g., a GPU 0) handle inputs on a different
+      device  (e.g. GPU 1 or CPU). When set to None, an appropriate value will be
+      picked automatically. The value picked may change between TensorFlow
+      releases.
+      Valid values:
       - tf.contrib.eager.DEVICE_PLACEMENT_EXPLICIT: raises an error if the
         placement is not correct.
-
       - tf.contrib.eager.DEVICE_PLACEMENT_WARN: copies the tensors which are not
         on the right device but logs a warning.
-
       - tf.contrib.eager.DEVICE_PLACEMENT_SILENT: silently copies the tensors.
         Note that this may hide performance problems as there is no notification
         provided when operations are blocked on the tensor being copied between
         devices.
-
       - tf.contrib.eager.DEVICE_PLACEMENT_SILENT_FOR_INT32: silently copies
         int32 tensors, raising errors on the other ones.
     execution_mode: (Optional.) Policy controlling how operations dispatched are
       actually executed. When set to None, an appropriate value will be picked
       automatically. The value picked may change between TensorFlow releases.
       Valid values:
-
-        - tf.contrib.eager.SYNC: executes each operation synchronously.
-
-        - tf.contrib.eager.ASYNC: executes each operation asynchronously. These
-          operations may return "non-ready" handles.
+      - tf.contrib.eager.SYNC: executes each operation synchronously.
+      - tf.contrib.eager.ASYNC: executes each operation asynchronously. These
+        operations may return "non-ready" handles.
 
   Raises:
     ValueError: If eager execution is enabled after creating/executing a
diff --git a/tensorflow/python/framework/tensor_util.py b/tensorflow/python/framework/tensor_util.py
index 8cf24206ed..ca63efbc84 100644
--- a/tensorflow/python/framework/tensor_util.py
+++ b/tensorflow/python/framework/tensor_util.py
@@ -50,6 +50,13 @@ def SlowAppendFloat16ArrayToTensorProto(tensor_proto, proto_values):
       [ExtractBitsFromFloat16(x) for x in proto_values])
 
 
+def _MediumAppendFloat16ArrayToTensorProto(tensor_proto, proto_values):
+  # TODO: Remove the conversion if cython supports np.float16_t
+  fast_tensor_util.AppendFloat16ArrayToTensorProto(
+      tensor_proto,
+      np.asarray(proto_values, dtype=np.float16).view(np.uint16))
+
+
 def ExtractBitsFromBFloat16(x):
   return np.asscalar(
       np.asarray(x, dtype=dtypes.bfloat16.as_numpy_dtype).view(np.uint16))
@@ -64,11 +71,8 @@ if _FAST_TENSOR_UTIL_AVAILABLE:
   _NP_TO_APPEND_FN = {
       dtypes.bfloat16.as_numpy_dtype:
           SlowAppendBFloat16ArrayToTensorProto,
-      # TODO(sesse): We should have a
-      # fast_tensor_util.AppendFloat16ArrayToTensorProto,
-      # but it seems np.float16_t doesn't exist?
       np.float16:
-          SlowAppendFloat16ArrayToTensorProto,
+          _MediumAppendFloat16ArrayToTensorProto,
       np.float32:
           fast_tensor_util.AppendFloat32ArrayToTensorProto,
       np.float64:
diff --git a/tensorflow/python/framework/test_util.py b/tensorflow/python/framework/test_util.py
index 97cd22e47a..5b01df48fe 100644
--- a/tensorflow/python/framework/test_util.py
+++ b/tensorflow/python/framework/test_util.py
@@ -682,7 +682,7 @@ def run_in_graph_and_eager_modes(__unused__=None,
 
 
   Args:
-    __unused__: Prevents sliently skipping tests.
+    __unused__: Prevents silently skipping tests.
     config: An optional config_pb2.ConfigProto to use to configure the
       session when executing graphs.
     use_gpu: If True, attempt to run as many operations as possible on GPU.