From bf63af8828efde25666711e0d096e1c7af7f3094 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Mon, 5 Oct 2020 04:03:55 -0700
Subject: [PATCH] Bug fix in `tf.print()` with `OrderedDict` where if an
`OrderedDict` didn't have the keys sorted, the keys and values were not being
printed in accordance with their correct mapping.
PiperOrigin-RevId: 335386269
Change-Id: I3c546b40530e863e4f7f7b93ff183f1f3ff43acc
---
RELEASE.md | 8 +++++++-
tensorflow/python/ops/logging_ops.py | 16 +++++++++++++++-
2 files changed, 22 insertions(+), 2 deletions(-)
diff --git a/RELEASE.md b/RELEASE.md
index 3e8cb4d4382..6d25950f29e 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -1,4 +1,4 @@
-# Release 2.4.0
+h# Release 2.4.0
<INSERT SMALL BLURB ABOUT RELEASE FOCUS AREA AND POTENTIAL TOOLCHAIN CHANGES>
@@ -300,6 +300,12 @@
* Add parameter allow_mixed_precision_on_unconverted_ops to
TrtConversionParams.
+* `tf.print`:
+
+ * Bug fix in `tf.print()` with `OrderedDict` where if an `OrderedDict`
+ didn't have the keys sorted, the keys and values were not being printed
+ in accordance with their correct mapping.
+
* Other:
* We have replaced uses of "whitelist" and "blacklist" with "allowlist"
diff --git a/tensorflow/python/ops/logging_ops.py b/tensorflow/python/ops/logging_ops.py
index 02fce277690..96e24d04362 100644
--- a/tensorflow/python/ops/logging_ops.py
+++ b/tensorflow/python/ops/logging_ops.py
@@ -18,6 +18,7 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
+import collections as py_collections
import os
import pprint
import random
@@ -305,8 +306,21 @@ def print_v2(*inputs, **kwargs):
# printed input.
templates = []
tensors = []
+ # If an input to the print function is of type `OrderedDict`, sort its
+ # elements by the keys for consistency with the ordering of `nest.flatten`.
+ # This is not needed for `dict` types because `pprint.pformat()` takes care
+ # of printing the template in a sorted fashion.
+ inputs_ordered_dicts_sorted = []
+ for input_ in inputs:
+ if isinstance(input_, py_collections.OrderedDict):
+ inputs_ordered_dicts_sorted.append(
+ py_collections.OrderedDict(sorted(input_.items())))
+ else:
+ inputs_ordered_dicts_sorted.append(input_)
tensor_free_structure = nest.map_structure(
- lambda x: "" if tensor_util.is_tensor(x) else x, inputs)
+ lambda x: "" if tensor_util.is_tensor(x) else x,
+ inputs_ordered_dicts_sorted)
+
tensor_free_template = " ".join(
pprint.pformat(x) for x in tensor_free_structure)
placeholder = _generate_placeholder_string(tensor_free_template)