From bdca83b71c0f47628321bafc29056fb2467144db Mon Sep 17 00:00:00 2001
From: Sergei Lebedev <slebedev@google.com>
Date: Fri, 25 Jan 2019 02:52:49 -0800
Subject: [PATCH] Automated rollback of commit
 74a6cca5d867d37e79ec9d780f2c57b926f07a80

PiperOrigin-RevId: 230873931
---
 tensorflow/python/framework/dtypes.py | 119 ++++++++++++++------------
 1 file changed, 65 insertions(+), 54 deletions(-)

diff --git a/tensorflow/python/framework/dtypes.py b/tensorflow/python/framework/dtypes.py
index 574d82ea93e..9d643e041c6 100644
--- a/tensorflow/python/framework/dtypes.py
+++ b/tensorflow/python/framework/dtypes.py
@@ -535,29 +535,47 @@ _np_qint32 = np.dtype([("qint32", np.int32, 1)])
 np_resource = np.dtype([("resource", np.ubyte, 1)])
 
 # Standard mappings between types_pb2.DataType values and numpy.dtypes.
-_NP_TO_TF = frozenset([
-    (np.float16, float16),
-    (np.float32, float32),
-    (np.float64, float64),
-    (np.int32, int32),
-    (np.int64, int64),
-    (np.uint8, uint8),
-    (np.uint16, uint16),
-    (np.uint32, uint32),
-    (np.uint64, uint64),
-    (np.int16, int16),
-    (np.int8, int8),
-    (np.complex64, complex64),
-    (np.complex128, complex128),
-    (np.object_, string),
-    (np.bool_, bool),
-    (_np_qint8, qint8),
-    (_np_quint8, quint8),
-    (_np_qint16, qint16),
-    (_np_quint16, quint16),
-    (_np_qint32, qint32),
-    (_np_bfloat16, bfloat16),
-])
+_NP_TO_TF = {
+    np.float16: float16,
+    np.float32: float32,
+    np.float64: float64,
+    np.int32: int32,
+    np.int64: int64,
+    np.uint8: uint8,
+    np.uint16: uint16,
+    np.uint32: uint32,
+    np.uint64: uint64,
+    np.int16: int16,
+    np.int8: int8,
+    np.complex64: complex64,
+    np.complex128: complex128,
+    np.object_: string,
+    np.string_: string,
+    np.unicode_: string,
+    np.bool_: bool,
+    _np_qint8: qint8,
+    _np_quint8: quint8,
+    _np_qint16: qint16,
+    _np_quint16: quint16,
+    _np_qint32: qint32,
+    _np_bfloat16: bfloat16,
+}
+
+# Map (some) NumPy platform dtypes to TF ones using their fixed-width
+# synonyms. Note that platform dtypes are not always simples aliases,
+# i.e. reference equality is not guaranteed. See e.g. numpy/numpy#9799.
+for pdt in [
+    np.intc,
+    np.uintc,
+    np.int_,
+    np.uint,
+    np.longlong,
+    np.ulonglong,
+]:
+  if pdt not in _NP_TO_TF:
+    _NP_TO_TF[pdt] = next(
+        _NP_TO_TF[dt] for dt in _NP_TO_TF if dt == pdt().dtype)
+
 _TF_TO_NP = {
     types_pb2.DT_HALF:
         np.float16,
@@ -664,6 +682,20 @@ _PYTHON_TO_TF = {
     builtins.object: string
 }
 
+_ANY_TO_TF = {}
+_ANY_TO_TF.update(_INTERN_TABLE)
+_ANY_TO_TF.update(_STRING_TO_TF)
+_ANY_TO_TF.update(_PYTHON_TO_TF)
+_ANY_TO_TF.update(_NP_TO_TF)
+
+# Ensure no collisions.
+assert len(_ANY_TO_TF) == sum(len(d) for d in [
+    _INTERN_TABLE,
+    _STRING_TO_TF,
+    _PYTHON_TO_TF,
+    _NP_TO_TF
+])
+
 
 @tf_export("dtypes.as_dtype", "as_dtype")
 def as_dtype(type_value):
@@ -684,37 +716,16 @@ def as_dtype(type_value):
   if isinstance(type_value, DType):
     return type_value
 
-  try:
-    return _INTERN_TABLE[type_value]
-  except KeyError:
-    pass
-
-  try:
-    return _STRING_TO_TF[type_value]
-  except KeyError:
-    pass
-
-  try:
-    return _PYTHON_TO_TF[type_value]
-  except KeyError:
-    pass
-
   if isinstance(type_value, np.dtype):
-    # The numpy dtype for strings is variable length. We can not compare
-    # dtype with a single constant (np.string does not exist) to decide
-    # dtype is a "string" type. We need to compare the dtype.type to be
-    # sure it's a string type.
-    if type_value.type == np.string_ or type_value.type == np.unicode_:
-      return string
+    try:
+      return _NP_TO_TF[type_value.type]
+    except KeyError:
+      pass
 
-  if isinstance(type_value, (type, np.dtype)):
-    for key, val in _NP_TO_TF:
-      try:
-        if key == type_value:
-          return val
-      except TypeError as e:
-        raise TypeError("Cannot convert {} to a dtype. {}".format(
-            type_value, e))
-
-  raise TypeError("Cannot convert value %r to a TensorFlow DType." % type_value)
+  try:
+    return _ANY_TO_TF[type_value]
+  except KeyError:
+    pass
 
+  raise TypeError(
+      "Cannot convert value %r to a TensorFlow DType." % type_value)