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Segmentation fault in tf.quantization.quantize_and_dequantize #42105

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mijungk opened this issue Aug 6, 2020 · 8 comments · Fixed by #42109
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Segmentation fault in tf.quantization.quantize_and_dequantize #42105

mijungk opened this issue Aug 6, 2020 · 8 comments · Fixed by #42109
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stat:awaiting tensorflower Status - Awaiting response from tensorflower TF 2.2 Issues related to TF 2.2 type:bug Bug

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@mijungk
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mijungk commented Aug 6, 2020

System information

  • Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
  • OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 18.04
  • Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: N/A
  • TensorFlow installed from (source or binary): binary
  • TensorFlow version (use command below): v2.2.0-rc4-8-g2b96f3662b 2.2.0
  • Python version: 3.7.6
  • Bazel version (if compiling from source): N/A
  • GCC/Compiler version (if compiling from source): N/A
  • CUDA/cuDNN version: N/A
  • GPU model and memory: N/A

Describe the current behavior
tf.quantization.quantize_and_dequantize produces a segfault when input is a tensor in any shape of float32 or float64 and axis is specified to a large number.

Describe the expected behavior
No segfault

Standalone code to reproduce the issue

import tensorflow as tf
tf.quantization.quantize_and_dequantize(input=[2.5, 2.5], input_min=[0,0], input_max=[1,1], axis=10)

Other info / logs Include any logs or source code that would be helpful to
diagnose the problem. If including tracebacks, please include the full
traceback. Large logs and files should be attached.
Segmentation fault (core dumped)

@mijungk mijungk added the type:bug Bug label Aug 6, 2020
@Saduf2019 Saduf2019 added stat:awaiting tensorflower Status - Awaiting response from tensorflower TF 2.2 Issues related to TF 2.2 labels Aug 7, 2020
@google-ml-butler
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Are you satisfied with the resolution of your issue?
Yes
No

tensorflow-copybara pushed a commit that referenced this issue Aug 9, 2020
Imported from GitHub PR #42109

Try to fix #42105
Copybara import of the project:

--
0573f8c by bhack <bhack@users.noreply.github.com>:

Check input and axis params

--
3e5a78f by bhack <bhack@users.noreply.github.com>:

Else fix

PiperOrigin-RevId: 325639857
Change-Id: Ifc18bc9686e9ff38839bb0c45fb3ef1d2ad9c208
@geetachavan1 geetachavan1 added this to To do in TensorFlow 2.4.0 via automation Sep 29, 2020
@geetachavan1 geetachavan1 moved this from To do to Done in TensorFlow 2.4.0 Sep 29, 2020
@mihaimaruseac mihaimaruseac reopened this Oct 19, 2020
TensorFlow 2.4.0 automation moved this from Done to To do Oct 19, 2020
@mihaimaruseac
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Reopening since #42109 seems to not be solving this issue (this op is V2, the PR fixes on V1)

@mihaimaruseac mihaimaruseac moved this from To do to In progress in TensorFlow 2.4.0 Oct 19, 2020
TensorFlow 2.4.0 automation moved this from In progress to Done Oct 20, 2020
@google-ml-butler
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Are you satisfied with the resolution of your issue?
Yes
No

copybara-service bot pushed a commit that referenced this issue Oct 20, 2020
The issues have been fixed already and will land in next TF release.

PiperOrigin-RevId: 338160244
Change-Id: Ia275845f970b380331ee8a00b0619f5119730d66
@lvyuqi
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lvyuqi commented Apr 9, 2021

Does the CVE-2020-15265 Vulnerability Affect 1.15.5?

This was referenced Apr 10, 2021
@mihaimaruseac
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Yes, but we no longer patch 1.15. Please update post 2.1

@mgmm13
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mgmm13 commented Sep 2, 2021

Hello, is there any chance that vulnerability fix will be applied in versions like 2.3.4?

@mihaimaruseac
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Hi. Not in 2.3.4, as the 2.3.x has reached end of life.

It is already included in 2.4.0 and later

@mgmm13
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mgmm13 commented Sep 3, 2021

@mihaimaruseac noted on this, thank you for the feedback.

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5 participants