[ao] Added filtered table generation capability to ModelReportVisualizer (#81673)
Summary: This adds the ability to generate and display the collected
statistics in a table format for the ModelReportVisualizer. The output
of this is a dictionary containing two keys, mapping to a tensor stats
table and channel stats table respectively.
The two ways you can filter is by module_fqn, by only including modules
with the `module_fqn_filter` substring, or by feature filter, which only includes
features that contain the `feature_filter` substring.
Expected Use:
```
table_dict = mod_rep_visualizer.generate_filtered_tables()
tensor_table = table_dict[ModelReportVisualizer.TABLE_TENSOR_KEY]
channel_table = table_dict[ModelReportVisualizer.TABLE_CHANNEL_KEY]
```
Headers for the Tensor level info:
```
idx layer_fqn feature_1 feature_2 feature_3 .... feature_n
---- --------- --------- --------- --------- ---------
```
Headers for the channel level info:
```
idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n
---- --------- ------- --------- --------- --------- ---------
```
The reason we split this up into two tables is because with the design
where everything is in one table, it is ambiguous and easy to mix up
whether a tensor level stat is actually tensor level stat or might be a
per channel stat since we would have a row for each channel.
Also changed some of the framework to abstract out the finding of the
tables to the actual visualization to make the API much easier for the
user to digest and parse.
Test Plan: python test/test_quantization.py TestFxModelReportVisualizer.test_generate_table
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81673
Approved by: https://github.com/jerryzh168
