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Printing lines without logging prefix using tf.Print() #12537

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danijar opened this issue Aug 23, 2017 · 1 comment · Fixed by #69149
Closed

Printing lines without logging prefix using tf.Print() #12537

danijar opened this issue Aug 23, 2017 · 1 comment · Fixed by #69149
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stat:contribution welcome Status - Contributions welcome type:feature Feature requests

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@danijar
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danijar commented Aug 23, 2017

Right now, all messages printed via tf.Print() are prefixed by:

<timestamp>: I tensorflow/core/kernels/logging_ops.cc:79]

It would be useful to have a way to print user-friendly output from within the graph. Therefore, suggest adding a parameter for the logging format to tf.Print(), or at least adding a flag that disables the logging prefix.
@danijar danijar added the type:feature Feature requests label Aug 23, 2017
yoon-hyoung added a commit to yoon-hyoung/tensorflow that referenced this issue Aug 24, 2017
@yoon-hyoung
Solution for issue tensorflow#12537
0527b3b 
*print prefix message by flag value
@vrv
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vrv commented Aug 25, 2017

The prefix comes from LOG(INFO) inside the logging_ops kernel. The fix needs to be made at the C++ level, though I don't have a good recommendation as to how.

@aselle aselle added the stat:contribution welcome Status - Contributions welcome label Nov 29, 2017
jzju added a commit to jzju/tensorflow that referenced this issue Dec 7, 2017
@jzju
Fix for tensorflow#12537
28483d3
caisq added a commit that referenced this issue Dec 14, 2017
@caisq
Merge pull request #15173 from JohanJu/master
f9a173a 
Fix for #12537
copybara-service bot pushed a commit that referenced this issue Jun 4, 2024
@sachinmuradi @tensorflower-gardener
PR #12537: [XLA:CPU][oneDNN][BugFix] Add axis support to oneDNN softm…
08075cf 
…ax rewriter

Imported from GitHub PR openxla/xla#12537

This PR fixes :
XLA Issue : openxla/xla#11772
corresponding JAX issue : google/jax#20856

Accuracy fix :
This PR adds support for softmax axis other than -1, previously oneDNN softmax was always executed with axis = -1 (last dimension)
Accuracy issue is observed from JAX 0.4.22 till last release, with current main branch we don't see accuracy issue as the JAX softmax HLO pattern changed (google/jax#20643) and HLO pattern is not re-written to oneDNN softmax. Hence, this PR also adjusts the oneDNN softmax pattern to recognize new HLO pattern and rewrite into oneDNN softmax custom call.
Copybara import of the project:

--
b983bd61044bf52838661057f570e9e218803549 by Sachin Muradi <sachin.muradi@intel.com>:

Add axis support

--
07f7d14aa1f00676b21e8c1f48719fe7e56bcfd2 by Sachin Muradi <sachin.muradi@intel.com>:

address more comments + optional broadcast

Merging this change closes #12537

FUTURE_COPYBARA_INTEGRATE_REVIEW=openxla/xla#12537 from Intel-tensorflow:sachin/softmax-axis de9d6bd36272962faf76077f594649d229bb727a
PiperOrigin-RevId: 640140990
@copybara-service copybara-service bot mentioned this issue Jun 4, 2024
Merged
copybara-service bot pushed a commit that referenced this issue Jun 4, 2024
@sachinmuradi @tensorflower-gardener
PR #12537: [XLA:CPU][oneDNN][BugFix] Add axis support to oneDNN softm…
ec015e3 
…ax rewriter

Imported from GitHub PR openxla/xla#12537

This PR fixes :
XLA Issue : openxla/xla#11772
corresponding JAX issue : google/jax#20856

Accuracy fix :
This PR adds support for softmax axis other than -1, previously oneDNN softmax was always executed with axis = -1 (last dimension)
Accuracy issue is observed from JAX 0.4.22 till last release, with current main branch we don't see accuracy issue as the JAX softmax HLO pattern changed (google/jax#20643) and HLO pattern is not re-written to oneDNN softmax. Hence, this PR also adjusts the oneDNN softmax pattern to recognize new HLO pattern and rewrite into oneDNN softmax custom call.
Copybara import of the project:

--
b983bd61044bf52838661057f570e9e218803549 by Sachin Muradi <sachin.muradi@intel.com>:

Add axis support

--
07f7d14aa1f00676b21e8c1f48719fe7e56bcfd2 by Sachin Muradi <sachin.muradi@intel.com>:

address more comments + optional broadcast

Merging this change closes #12537

FUTURE_COPYBARA_INTEGRATE_REVIEW=openxla/xla#12537 from Intel-tensorflow:sachin/softmax-axis de9d6bd36272962faf76077f594649d229bb727a
PiperOrigin-RevId: 640140990
copybara-service bot pushed a commit that referenced this issue Jun 4, 2024
@sachinmuradi @tensorflower-gardener
PR #12537: [XLA:CPU][oneDNN][BugFix] Add axis support to oneDNN softm…
a800ed0 
…ax rewriter

Imported from GitHub PR openxla/xla#12537

This PR fixes :
XLA Issue : openxla/xla#11772
corresponding JAX issue : google/jax#20856

Accuracy fix :
This PR adds support for softmax axis other than -1, previously oneDNN softmax was always executed with axis = -1 (last dimension)
Accuracy issue is observed from JAX 0.4.22 till last release, with current main branch we don't see accuracy issue as the JAX softmax HLO pattern changed (google/jax#20643) and HLO pattern is not re-written to oneDNN softmax. Hence, this PR also adjusts the oneDNN softmax pattern to recognize new HLO pattern and rewrite into oneDNN softmax custom call.
Copybara import of the project:

--
b983bd61044bf52838661057f570e9e218803549 by Sachin Muradi <sachin.muradi@intel.com>:

Add axis support

--
07f7d14aa1f00676b21e8c1f48719fe7e56bcfd2 by Sachin Muradi <sachin.muradi@intel.com>:

address more comments + optional broadcast

Merging this change closes #12537

Reverts dbf3cd3

FUTURE_COPYBARA_INTEGRATE_REVIEW=openxla/xla#12537 from Intel-tensorflow:sachin/softmax-axis de9d6bd36272962faf76077f594649d229bb727a
PiperOrigin-RevId: 640140990
copybara-service bot pushed a commit that referenced this issue Jun 4, 2024
@sachinmuradi @tensorflower-gardener
PR #12537: [XLA:CPU][oneDNN][BugFix] Add axis support to oneDNN softm…
08d5656 
…ax rewriter

Imported from GitHub PR openxla/xla#12537

This PR fixes :
XLA Issue : openxla/xla#11772
corresponding JAX issue : google/jax#20856

Accuracy fix :
This PR adds support for softmax axis other than -1, previously oneDNN softmax was always executed with axis = -1 (last dimension)
Accuracy issue is observed from JAX 0.4.22 till last release, with current main branch we don't see accuracy issue as the JAX softmax HLO pattern changed (google/jax#20643) and HLO pattern is not re-written to oneDNN softmax. Hence, this PR also adjusts the oneDNN softmax pattern to recognize new HLO pattern and rewrite into oneDNN softmax custom call.
Copybara import of the project:

--
b983bd61044bf52838661057f570e9e218803549 by Sachin Muradi <sachin.muradi@intel.com>:

Add axis support

--
07f7d14aa1f00676b21e8c1f48719fe7e56bcfd2 by Sachin Muradi <sachin.muradi@intel.com>:

address more comments + optional broadcast

Merging this change closes #12537

FUTURE_COPYBARA_INTEGRATE_REVIEW=openxla/xla#12537 from Intel-tensorflow:sachin/softmax-axis de9d6bd36272962faf76077f594649d229bb727a
PiperOrigin-RevId: 639049433
@copybara-service copybara-service bot mentioned this issue Jun 4, 2024
Draft
copybara-service bot pushed a commit that referenced this issue Jun 4, 2024
@sachinmuradi @tensorflower-gardener
PR #12537: [XLA:CPU][oneDNN][BugFix] Add axis support to oneDNN softm…
f8f3735 
…ax rewriter

Imported from GitHub PR openxla/xla#12537

This PR fixes :
XLA Issue : openxla/xla#11772
corresponding JAX issue : google/jax#20856

Accuracy fix :
This PR adds support for softmax axis other than -1, previously oneDNN softmax was always executed with axis = -1 (last dimension)
Accuracy issue is observed from JAX 0.4.22 till last release, with current main branch we don't see accuracy issue as the JAX softmax HLO pattern changed (google/jax#20643) and HLO pattern is not re-written to oneDNN softmax. Hence, this PR also adjusts the oneDNN softmax pattern to recognize new HLO pattern and rewrite into oneDNN softmax custom call.
Copybara import of the project:

--
b983bd61044bf52838661057f570e9e218803549 by Sachin Muradi <sachin.muradi@intel.com>:

Add axis support

--
07f7d14aa1f00676b21e8c1f48719fe7e56bcfd2 by Sachin Muradi <sachin.muradi@intel.com>:

address more comments + optional broadcast

Merging this change closes #12537

PiperOrigin-RevId: 640246750
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