Exports tf.experimental.numpy.enable_numpy_behavior, and unbreaks tf-numpy guide.

PiperOrigin-RevId: 358529149
Change-Id: I533f9bce385480cdbd17492cf21130fab5d00328

tensorflow/python/framework/ops.py

@@ -391,9 +391,10 @@ class Tensor(internal.NativeObject, core_tf_types.Tensor):
                 "tolist", "data"}:
       # TODO(wangpeng): Export the enable_numpy_behavior knob
       raise AttributeError("""
+        '{}' object has no attribute '{}'.
         If you are looking for numpy-related methods, please run the following:
         import tensorflow.python.ops.numpy_ops.np_config
-        np_config.enable_numpy_behavior()""")
+        np_config.enable_numpy_behavior()""".format(type(self).__name__, name))
     self.__getattribute__(name)
 
   @staticmethod

tensorflow/python/ops/numpy_ops/__init__.py

@@ -175,6 +175,7 @@ from tensorflow.python.ops.numpy_ops import np_utils
 # pylint: disable=wildcard-import
 from tensorflow.python.ops.numpy_ops.np_array_ops import *
 from tensorflow.python.ops.numpy_ops.np_arrays import ndarray
+from tensorflow.python.ops.numpy_ops.np_config import *
 from tensorflow.python.ops.numpy_ops.np_dtypes import *
 from tensorflow.python.ops.numpy_ops.np_math_ops import *
 # pylint: enable=wildcard-import

tensorflow/python/ops/numpy_ops/np_config.py

@@ -20,18 +20,29 @@ from __future__ import print_function
 
 from tensorflow.python.framework import ops
 from tensorflow.python.ops.numpy_ops import np_dtypes
+from tensorflow.python.ops.numpy_ops import np_export
 from tensorflow.python.ops.numpy_ops import np_math_ops
 
 
+@np_export.np_export("experimental_enable_numpy_behavior")
 def enable_numpy_behavior(prefer_float32=False):
   """Enable NumPy behavior on Tensors.
 
-  Includes addition of methods, type promotion on operator overloads and
-  support for NumPy-style slicing.
+  Enabling NumPy behavior has three effects:
+  * It adds to `tf.Tensor` some common NumPy methods such as `T`,
+    `reshape` and `ravel`.
+  * It changes dtype promotion in `tf.Tensor` operators to be
+    compatible with NumPy. For example,
+    `tf.ones([], tf.int32) + tf.ones([], tf.float32)` used to throw a
+    "dtype incompatible" error, but after this it will return a
+    float64 tensor (obeying NumPy's promotion rules).
+  * It enhances `tf.Tensor`'s indexing capability to be on par with
+    [NumPy's](https://numpy.org/doc/stable/reference/arrays.indexing.html).
 
   Args:
-    prefer_float32: Whether to allow type inference to use float32, or use
-    float64 similar to NumPy.
+    prefer_float32: Controls whether dtype inference will use float32
+    for Python floats, or float64 (the default and the
+    NumPy-compatible behavior).
   """
   ops.enable_numpy_style_type_promotion()
   ops.enable_numpy_style_slicing()

third_party/py/numpy/tf_numpy_api/tensorflow.experimental.numpy.pbtxt

@@ -388,6 +388,10 @@ tf_module {
     name: "expand_dims"
     argspec: "args=[\'a\', \'axis\'], varargs=None, keywords=None, defaults=None"
   }
+  member_method {
+    name: "experimental_enable_numpy_behavior"
+    argspec: "args=[\'prefer_float32\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
   member_method {
     name: "expm1"
     argspec: "args=[\'x\'], varargs=None, keywords=None, defaults=None"