[quant][graphmode][fx] Change standalone module api#49719
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jerryzh168 wants to merge 2 commits intogh/jerryzh168/525/basefrom
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[quant][graphmode][fx] Change standalone module api#49719jerryzh168 wants to merge 2 commits intogh/jerryzh168/525/basefrom
jerryzh168 wants to merge 2 commits intogh/jerryzh168/525/basefrom
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Summary:
We find there are multiple use cases for standalone module, one use case requires standalone module
to produce a module that takes float Tensor as input and outputs a float Tensor, the other needs to
produce a modulee that takes quantized Tensor as input and outputs a quantized Tensor.
This is similar to `quantized_input_idxs` and `quantized_output_idxs` so we want to nest
prepare_custom_config_dict in the standalone module configuration, for maximum flxibility we also
include qconfig_dict for stand alone module as well in case user needs to have special qconfig_dict for
the standalone module in the future.
Changed from
```python
prepare_custom_config_dict =
{
"standalone_module_name": ["standalone_module"],
"standalone_module_class": [StandaloneModule]
}
```
to
```python
prepare_custom_config_dict =
{
"standalone_module_name": [("standalone_module", qconfig_dict1, prepare_custom_config_dict1)],
"standalone_module_class": [(StandaloneModule, qconfig_dict2, prepare_custom_config_dict2)]
}
```
The entries in the config are:
1. name/module_class
2. optional qconfig_dict, when it is None, we'll use {"": qconfig} where qconfig is the one from parent qconfig_dict
3. optional prepare_custom_config_dict, when it is None, we'll use default value of prepare_custom_config_dict for prepare API (None)
Test Plan:
python test/test_quantization.py TestQuantizeFx.test_standalone_module
Reviewers:
Subscribers:
Tasks:
Tags:
[ghstack-poisoned]
Contributor
💊 CI failures summary and remediationsAs of commit 07eab29 (more details on the Dr. CI page):
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jerryzh168
added a commit
that referenced
this pull request
Dec 22, 2020
Summary:
We find there are multiple use cases for standalone module, one use case requires standalone module
to produce a module that takes float Tensor as input and outputs a float Tensor, the other needs to
produce a modulee that takes quantized Tensor as input and outputs a quantized Tensor.
This is similar to `quantized_input_idxs` and `quantized_output_idxs` so we want to nest
prepare_custom_config_dict in the standalone module configuration, for maximum flxibility we also
include qconfig_dict for stand alone module as well in case user needs to have special qconfig_dict for
the standalone module in the future.
Changed from
```python
prepare_custom_config_dict =
{
"standalone_module_name": ["standalone_module"],
"standalone_module_class": [StandaloneModule]
}
```
to
```python
prepare_custom_config_dict =
{
"standalone_module_name": [("standalone_module", qconfig_dict1, prepare_custom_config_dict1)],
"standalone_module_class": [(StandaloneModule, qconfig_dict2, prepare_custom_config_dict2)]
}
```
The entries in the config are:
1. name/module_class
2. optional qconfig_dict, when it is None, we'll use {"": qconfig} where qconfig is the one from parent qconfig_dict
3. optional prepare_custom_config_dict, when it is None, we'll use default value of prepare_custom_config_dict for prepare API (None)
Test Plan:
python test/test_quantization.py TestQuantizeFx.test_standalone_module
Reviewers:
Subscribers:
Tasks:
Tags:
ghstack-source-id: c5c100b
Pull Request resolved: #49719
vkuzo
reviewed
Dec 22, 2020
| "standalone_module_name": [ | ||
| "submodule.standalone" | ||
| # module_name, qconfig_dict, prepare_custom_config_dict | ||
| ("submodule.standalone", None, None) |
Contributor
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does qconfig_dict == None here means "do not quantize" or "use parent qconfig"?
Contributor
Author
There was a problem hiding this comment.
it means "use parent qconfig"
for "do not quantize": qconfit_dict = {"": None}
| qconfig_dict = {"": default_qconfig} | ||
| config_name = {"standalone_module_name": ["standalone"]} | ||
| config_class = {"standalone_module_class": [StandaloneModule]} | ||
| config_name = {"standalone_module_name": [("standalone", None, None)]} |
Contributor
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Can we also test for selective quantization of inputs/outputs for standalone modules?
Contributor
Author
There was a problem hiding this comment.
yes, it's in the next PR
Contributor
There was a problem hiding this comment.
Sorry, just saw that
raghuramank100
approved these changes
Dec 22, 2020
Summary:
We find there are multiple use cases for standalone module, one use case requires standalone module
to produce a module that takes float Tensor as input and outputs a float Tensor, the other needs to
produce a modulee that takes quantized Tensor as input and outputs a quantized Tensor.
This is similar to `quantized_input_idxs` and `quantized_output_idxs` so we want to nest
prepare_custom_config_dict in the standalone module configuration, for maximum flxibility we also
include qconfig_dict for stand alone module as well in case user needs to have special qconfig_dict for
the standalone module in the future.
Changed from
```python
prepare_custom_config_dict =
{
"standalone_module_name": ["standalone_module"],
"standalone_module_class": [StandaloneModule]
}
```
to
```python
prepare_custom_config_dict =
{
"standalone_module_name": [("standalone_module", qconfig_dict1, prepare_custom_config_dict1)],
"standalone_module_class": [(StandaloneModule, qconfig_dict2, prepare_custom_config_dict2)]
}
```
The entries in the config are:
1. name/module_class
2. optional qconfig_dict, when it is None, we'll use {"": qconfig} where qconfig is the one from parent qconfig_dict
3. optional prepare_custom_config_dict, when it is None, we'll use default value of prepare_custom_config_dict for prepare API (None)
Test Plan:
python test/test_quantization.py TestQuantizeFx.test_standalone_module
Reviewers:
Subscribers:
Tasks:
Tags:
Differential Revision: [D25675704](https://our.internmc.facebook.com/intern/diff/D25675704)
[ghstack-poisoned]
Codecov Report
@@ Coverage Diff @@
## gh/jerryzh168/525/base #49719 +/- ##
==========================================================
- Coverage 80.67% 80.58% -0.09%
==========================================================
Files 1895 1895
Lines 205307 205316 +9
==========================================================
- Hits 165622 165446 -176
- Misses 39685 39870 +185 |
Contributor
|
This pull request has been merged in f474ffa. |
laurentdupin
pushed a commit
to laurentdupin/pytorch
that referenced
this pull request
Apr 24, 2026
Summary: Pull Request resolved: pytorch#49719 We find there are multiple use cases for standalone module, one use case requires standalone module to produce a module that takes float Tensor as input and outputs a float Tensor, the other needs to produce a modulee that takes quantized Tensor as input and outputs a quantized Tensor. This is similar to `quantized_input_idxs` and `quantized_output_idxs` so we want to nest prepare_custom_config_dict in the standalone module configuration, for maximum flxibility we also include qconfig_dict for stand alone module as well in case user needs to have special qconfig_dict for the standalone module in the future. Changed from ```python prepare_custom_config_dict = { "standalone_module_name": ["standalone_module"], "standalone_module_class": [StandaloneModule] } ``` to ```python prepare_custom_config_dict = { "standalone_module_name": [("standalone_module", qconfig_dict1, prepare_custom_config_dict1)], "standalone_module_class": [(StandaloneModule, qconfig_dict2, prepare_custom_config_dict2)] } ``` The entries in the config are: 1. name/module_class 2. optional qconfig_dict, when it is None, we'll use {"": qconfig} where qconfig is the one from parent qconfig_dict 3. optional prepare_custom_config_dict, when it is None, we'll use default value of prepare_custom_config_dict for prepare API (None) Test Plan: python test/test_quantization.py TestQuantizeFx.test_standalone_module Imported from OSS Reviewed By: raghuramank100 Differential Revision: D25675704 fbshipit-source-id: 0889f519a3e55a7a677f0e2db4db9a18d87a93d4
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Stack from ghstack:
Summary:
We find there are multiple use cases for standalone module, one use case requires standalone module
to produce a module that takes float Tensor as input and outputs a float Tensor, the other needs to
produce a modulee that takes quantized Tensor as input and outputs a quantized Tensor.
This is similar to
quantized_input_idxsandquantized_output_idxsso we want to nestprepare_custom_config_dict in the standalone module configuration, for maximum flxibility we also
include qconfig_dict for stand alone module as well in case user needs to have special qconfig_dict for
the standalone module in the future.
Changed from
to
The entries in the config are:
Test Plan:
python test/test_quantization.py TestQuantizeFx.test_standalone_module
Reviewers:
Subscribers:
Tasks:
Tags:
Differential Revision: D25675704