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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2022/01/10 14:55:37 UTC
[GitHub] [incubator-mxnet] bgawrych opened a new pull request #20813: Add quantization API doc and oneDNN to migration guide
bgawrych opened a new pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813
## Description ##
Migration guide:
Quantization API:
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[GitHub] [incubator-mxnet] bgawrych commented on a change in pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on a change in pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#discussion_r793737572
##########
File path: docs/python_docs/python/tutorials/getting-started/gluon_migration_guide.md
##########
@@ -432,6 +432,67 @@ A new module called `mxnet.gluon.probability` has been introduced in Gluon 2.0.
3. [Transformation](https://github.com/apache/incubator-mxnet/tree/master/python/mxnet/gluon/probability/transformation): implement invertible transformation with computable log det jacobians.
+## oneDNN Integration
+### Operator Fusion
+In versions 1.x of MXNet pattern fusion in execution graph was enabled by default when using MXNet built with oneDNN library support and could have been disabled by setting 'MXNET_SUBGRAPH_BACKEND' environment flag to `None`. MXNet 2.0 introduced changes in forward inference flow which led to refactor of fusion mechanism. To fuse model in MXNet 2.0 there are two requirements:
+
+ - the model must be defined as a subclass of HybridBlock or Symbol
+
+ - the model must have specific operator patterns which can be fused
+
+Both HybridBlock and Symbol classes provide API to easily run fusion of operators. All we have to do is to add single line of code running fusion passes on our model:
Review comment:
```suggestion
Both HybridBlock and Symbol classes provide API to easily run fusion of operators. Adding only one line of code is needed to run fusion passes on model:
```
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[GitHub] [incubator-mxnet] bartekkuncer commented on a change in pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bartekkuncer commented on a change in pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#discussion_r787586914
##########
File path: docs/python_docs/python/tutorials/getting-started/gluon_migration_guide.md
##########
@@ -432,6 +432,67 @@ A new module called `mxnet.gluon.probability` has been introduced in Gluon 2.0.
3. [Transformation](https://github.com/apache/incubator-mxnet/tree/master/python/mxnet/gluon/probability/transformation): implement invertible transformation with computable log det jacobians.
+## oneDNN Integration
+### Operator Fusion
+In versions 1.x of MXNet pattern fusion in execution graph was enabled by default when using MXNet built with oneDNN library support and could have been disabled by setting 'MXNET_SUBGRAPH_BACKEND' environment flag to `None`. MXNet 2.0 introduced changes in forward inference flow which led to refactor of fusion mechanism. To fuse model in MXNet 2.0 there are two requirements:
+
+ - the model must be defined as a subclass of HybridBlock or Symbol
+
+ - the model must have specific operator patterns which can be fused
Review comment:
```suggestion
- the model must have specific operator patterns which can be fused.
```
##########
File path: docs/python_docs/python/tutorials/getting-started/gluon_migration_guide.md
##########
@@ -432,6 +432,67 @@ A new module called `mxnet.gluon.probability` has been introduced in Gluon 2.0.
3. [Transformation](https://github.com/apache/incubator-mxnet/tree/master/python/mxnet/gluon/probability/transformation): implement invertible transformation with computable log det jacobians.
+## oneDNN Integration
+### Operator Fusion
+In versions 1.x of MXNet pattern fusion in execution graph was enabled by default when using MXNet built with oneDNN library support and could have been disabled by setting 'MXNET_SUBGRAPH_BACKEND' environment flag to `None`. MXNet 2.0 introduced changes in forward inference flow which led to refactor of fusion mechanism. To fuse model in MXNet 2.0 there are two requirements:
+
+ - the model must be defined as a subclass of HybridBlock or Symbol
+
+ - the model must have specific operator patterns which can be fused
+
+Both HybridBlock and Symbol classes provide API to easily run fusion of operators. All we have to do is to add single line of code running fusion passes on our model:
Review comment:
Only sentence written in first person.
##########
File path: python/mxnet/contrib/quantization.py
##########
@@ -174,15 +174,16 @@ def __init__(self):
def collect(self, name, op_name, arr):
"""Function which is registered to Block as monitor callback. Names of layers
requiring calibration are stored in `self.include_layers` variable.
- Parameters
- ----------
- name : str
- Node name from which collected data comes from
- op_name : str
- Operator name from which collected data comes from. Single operator
- can have multiple inputs/ouputs nodes - each should have different name
- arr : NDArray
- NDArray containing data of monitored node
+
+ Parameters
+ ----------
+ name : str
+ Node name from which collected data comes from
+ op_name : str
+ Operator name from which collected data comes from. Single operator
+ can have multiple inputs/ouputs nodes - each should have different name
Review comment:
```suggestion
can have multiple input/ouput nodes - each should have different name.
```
##########
File path: python/mxnet/contrib/quantization.py
##########
@@ -174,15 +174,16 @@ def __init__(self):
def collect(self, name, op_name, arr):
"""Function which is registered to Block as monitor callback. Names of layers
requiring calibration are stored in `self.include_layers` variable.
- Parameters
- ----------
- name : str
- Node name from which collected data comes from
- op_name : str
- Operator name from which collected data comes from. Single operator
- can have multiple inputs/ouputs nodes - each should have different name
- arr : NDArray
- NDArray containing data of monitored node
+
+ Parameters
+ ----------
+ name : str
+ Node name from which collected data comes from
Review comment:
```suggestion
Node name from which collected data comes from.
```
##########
File path: python/mxnet/contrib/quantization.py
##########
@@ -174,15 +174,16 @@ def __init__(self):
def collect(self, name, op_name, arr):
"""Function which is registered to Block as monitor callback. Names of layers
requiring calibration are stored in `self.include_layers` variable.
- Parameters
- ----------
- name : str
- Node name from which collected data comes from
- op_name : str
- Operator name from which collected data comes from. Single operator
- can have multiple inputs/ouputs nodes - each should have different name
- arr : NDArray
- NDArray containing data of monitored node
+
+ Parameters
+ ----------
+ name : str
+ Node name from which collected data comes from
+ op_name : str
+ Operator name from which collected data comes from. Single operator
+ can have multiple inputs/ouputs nodes - each should have different name
+ arr : NDArray
+ NDArray containing data of monitored node
Review comment:
```suggestion
NDArray containing data of monitored node.
```
##########
File path: docs/python_docs/python/tutorials/getting-started/gluon_migration_guide.md
##########
@@ -432,6 +432,67 @@ A new module called `mxnet.gluon.probability` has been introduced in Gluon 2.0.
3. [Transformation](https://github.com/apache/incubator-mxnet/tree/master/python/mxnet/gluon/probability/transformation): implement invertible transformation with computable log det jacobians.
+## oneDNN Integration
+### Operator Fusion
+In versions 1.x of MXNet pattern fusion in execution graph was enabled by default when using MXNet built with oneDNN library support and could have been disabled by setting 'MXNET_SUBGRAPH_BACKEND' environment flag to `None`. MXNet 2.0 introduced changes in forward inference flow which led to refactor of fusion mechanism. To fuse model in MXNet 2.0 there are two requirements:
+
+ - the model must be defined as a subclass of HybridBlock or Symbol
Review comment:
```suggestion
- the model must be defined as a subclass of HybridBlock or Symbol,
```
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[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
mxnet-bot commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1025592438
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[GitHub] [incubator-mxnet] bgawrych commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1024052074
@mxnet-bot run ci [windows-gpu, unix-cpu]
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[GitHub] [incubator-mxnet] bgawrych commented on a change in pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on a change in pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#discussion_r793737572
##########
File path: docs/python_docs/python/tutorials/getting-started/gluon_migration_guide.md
##########
@@ -432,6 +432,67 @@ A new module called `mxnet.gluon.probability` has been introduced in Gluon 2.0.
3. [Transformation](https://github.com/apache/incubator-mxnet/tree/master/python/mxnet/gluon/probability/transformation): implement invertible transformation with computable log det jacobians.
+## oneDNN Integration
+### Operator Fusion
+In versions 1.x of MXNet pattern fusion in execution graph was enabled by default when using MXNet built with oneDNN library support and could have been disabled by setting 'MXNET_SUBGRAPH_BACKEND' environment flag to `None`. MXNet 2.0 introduced changes in forward inference flow which led to refactor of fusion mechanism. To fuse model in MXNet 2.0 there are two requirements:
+
+ - the model must be defined as a subclass of HybridBlock or Symbol
+
+ - the model must have specific operator patterns which can be fused
+
+Both HybridBlock and Symbol classes provide API to easily run fusion of operators. All we have to do is to add single line of code running fusion passes on our model:
Review comment:
```suggestion
Both HybridBlock and Symbol classes provide API to easily run fusion of operators. Adding only single line of code is needed to run fusion passes on model:
```
--
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[GitHub] [incubator-mxnet] bgawrych commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1025455454
@mxnet-bot run ci [unix-cpu]
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[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
mxnet-bot commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1008951086
Hey @bgawrych , Thanks for submitting the PR
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[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1025455474
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[GitHub] [incubator-mxnet] bgawrych commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1011152750
@mxnet-bot run ci [windows-gpu]
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[GitHub] [incubator-mxnet] bgawrych commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1012009943
@mxnet-bot run ci [windows-gpu]
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[GitHub] [incubator-mxnet] bgawrych commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1025592352
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[GitHub] [incubator-mxnet] szha merged pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
szha merged pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813
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[GitHub] [incubator-mxnet] bgawrych commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1010704486
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[GitHub] [incubator-mxnet] bgawrych commented on pull request #20813: Add quantization API doc and oneDNN to migration guide
Posted by GitBox <gi...@apache.org>.
bgawrych commented on pull request #20813:
URL: https://github.com/apache/incubator-mxnet/pull/20813#issuecomment-1015207204
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