Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62685
Adds a `ref_node_target_type` field to hold the string type
of the base node. This is needed because in some cases
the previous node does not match ref_node (if we have observers,
or if we are logging inputs), and it is useful to know the type
of ref_node.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs
```
Imported from OSS
Reviewed By: hx89
Differential Revision: D30082947
fbshipit-source-id: 98ded7b25a5d8d5ea820e0ef62c3799b65c3fc77
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62333
We incorrectly ignored any custom relationships the user specified
in the `extract_weights` API. Fixing this and adding a test case.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_user_defined_function
```
Imported from OSS
Reviewed By: hx89
Differential Revision: D29963502
fbshipit-source-id: 33ce3d4df1acb6298b6c7dcb6674015c8d14bdf4
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62038
Updates the logic to extract weights from nodes to use a
direct mapping from type to weight extraction function.
This is needed for a future PR which will allow users to
specify custom weight extraction functions for user defined
types.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs
python test/test_quantization.py TestFXNumericSuiteCoreAPIsModels
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D29853627
fbshipit-source-id: 3ef90ef4bd7b28f6316c0af215a2bd3ff8a2aeca
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61377
Both the quantization tracer and the NS tracer record
`_node_name_to_scope`, which contains the mapping from
node name to FQN.
This PR adds the FQN information to the NS results, so that it is
more convenient for users to attribute a NS result to the corresponding
module in their model.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_extract_weights_fqn
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_match_activations_fqn
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_shadow_activations_fqn
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D29600349
fbshipit-source-id: df489e03daff97dd380f59c83ffdc2b0012a0a53
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61323
Before this PR, all observers and fake quants were silently removed
when adding loggers with NS. This is problematic for QAT models because
we need the fake quants to run in order to properly capture intermediate
outputs.
This PR fixes the issue by preserving the observers throughout
the passes which add loggers. In detail:
* for each quantization module or fusion, add additional patterns with that fusion and an observer/fake_quant at the end
* remove the places in the logger model creation code which removed observers
* add unit testing that QAT numerics do not change after adding loggers
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_loggers_preserve_qat_numerics
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_shadow_loggers_preserve_qat_numerics
```
Imported from OSS
Reviewed By: hx89
Differential Revision: D29600351
fbshipit-source-id: 5f25118b79eb47860c49bca882de6a8eae7a4456
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60305
Adjusts the NS for FX weight and activation extraction APIs
to require a model name, and rekeys the results of these APIs
to use the node names of the specified model as layer keys.
For example, before
```
// API call
results = ns.extract_logger_info(
model_a, model_b, ns.OutputLogger)
// results
{'base_op_1_0': {'node_output':
{'model_a': [{'ref_node_name': 'linear1', ...}]}}}
```
and after
```
// API call
results = ns.extract_logger_info(
model_a, model_b, ns.OutputLogger, 'model_b_name')
// results
// note: instead of `base_op_1_0`, the layer is named `linear1`
{'linear1': {'node_output':
{'model_a': [{'ref_node_name': 'linear1', ...}]}}}
```
Note: we cannot use these names while collecting data because
node names are not guaranteed to be consistent across graphs.
This is why we only rekey as the very last step.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_layer_names
```
Imported from OSS
Reviewed By: hx89
Differential Revision: D29243045
fbshipit-source-id: d39ecdfdd18b07291e3ecefed2ede287b100b7d0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60103
Adds internal logging for NS for FX API usage.
Test Plan: CI
Reviewed By: jerryzh168
Differential Revision: D29166710
fbshipit-source-id: 2a1bf2f6038b0c6c5945b57b2db2de25c585a04a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57171
No logic change, just moving the mapping to a file where
the other mappings are.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D28077978
fbshipit-source-id: 4049d6a498156a5dffe3a03d2f4abc79da7bf907
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57026
Adds a config option to skip matching classes by class type
and functions by function type.
This is useful when users make custom modules which return
types other than tensors. With the current implementation of
Logger, these are not scriptable.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_user_module_scriptable
```
Reviewed By: jerryzh168
Differential Revision: D28030093
Pulled By: vkuzo
fbshipit-source-id: 71dc54dd935d2071c4b017260ea2a1e5c2298bfe
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57025
Adds the ability to log unshadowed inputs of binary ops such as `add`
and `mul`, when indices 0, 1, or 0 and 1 are tensors.
Note: making shadowing support this is saved for a future PR.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_add_mul_inputs_activations
```
Reviewed By: jerryzh168
Differential Revision: D28030098
Pulled By: vkuzo
fbshipit-source-id: fd46760faac153975cd7688e70c44991ec1d5dff
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57022
Allows usage of user functions in NS shadow APIs. We expose the
i/o mapping to the user APIs, and thread them throughout the code.
Note: the format of the mapping is currently not the best. Saving
improving that for a future PR.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_user_defined_function
```
Reviewed By: jerryzh168
Differential Revision: D28030095
Pulled By: vkuzo
fbshipit-source-id: 2863312362223ad276437e2aeeec4a3f71b691c7
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56493
Adds a config option to skip matching classes by class type
and functions by function type.
This is useful when users make custom modules which return
types other than tensors. With the current implementation of
Logger, these are not scriptable.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_user_module_scriptable
```
needs more testing before land
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D27886107
fbshipit-source-id: ec92c4f7ab7141021bc022f07b3b558b42bbb986
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56408
Adds the ability to log unshadowed inputs of binary ops such as `add`
and `mul`, when indices 0, 1, or 0 and 1 are tensors.
Note: making shadowing support this is saved for a future PR.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_add_mul_inputs_activations
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D27864296
fbshipit-source-id: 3cbeb728297aa192d1ea17e815299709fd9db056
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56301
Allows usage of user functions in NS shadow APIs. We expose the
i/o mapping to the user APIs, and thread them throughout the code.
Note: the format of the mapping is currently not the best. Saving
improving that for a future PR.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_user_defined_function
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D27833189
fbshipit-source-id: dac418e294d1c9b204efbf4071d5cc12a9e784c0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56292
Adds hooks for specifying user defined functions to NS weight and
unshadowed activation APIs.
Adding it to shadowed activation APIs will be a bit more work, upcoming
in a separate PR.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_user_defined_function
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D27830409
fbshipit-source-id: 6bbddc3062c0b3e412a3147244795319c0785a92
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55505
This necessary to add support in NS for QAT modules, to avoid
duplicating logic between NSTracer and QuantizationTracer.
The eng work to expose the custom module and class names to
the user will be in a future PR.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs
python test/test_quantization.py TestFXNumericSuiteCoreAPIsModels
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D27650407
fbshipit-source-id: 431f47c5353b41c11371c5efa79657bfd085459a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55287
Adds support for extracting weights from F.conv2d and F.conv3d.
F.conv1d and the fused variants are saved for future PRs.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_extract_weights_conv_fun
```
Imported from OSS
Reviewed By: hx89
Differential Revision: D27575424
fbshipit-source-id: e945912d7d0ab320f47cab30d00d60ddb7497158
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55060
Removes the previous iteration of Numeric Suite for FX graph mode
quantization, and moves the current iteration into the top level
file.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs
python test/test_quantization.py TestFXGraphMatcher
```
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D27467725
fbshipit-source-id: 4c22b5a3221857231f9f59cf6d2908820e6a7f12
