pytorch

db395425 - [2/n][Compute Meta] support analysis for null flag features

[2/n][Compute Meta] support analysis for null flag features Summary: ## TLDR Support using NaN default value for missing dense features in RawInputProcessor for DPER2. In preparation for subsequent support for null flag features in compute meta. For train_eval this is already supported in DPER3 and we do not plan to support this in DPER2 train eval. ## Overview Intern project plan to support adding dense flags for missing feature values instead of replacing with zero. ## Project plan : https://docs.google.com/document/d/1OsPUTjpJycwxWLCue3Tnb1mx0uDC_2KKWvC1Rwpo2NI/edit?usp=sharing ## Code paths: See https://fb.quip.com/eFXUA0tbDmNw for the call stack for all affected code paths. Test Plan: ## fblearner flow test 1. `flow-cli clone f197867430 --run-as-secure-group ads_personalization_systems --force-build` to build a ephemeral package and start a fblearner flow run (may fail) 2. Clone the new run and change the secure_group to `XXXX` and entitlement to `default` in the UI 3. Adds explicit_null_min_coverage flag 4. Optionally reduce `max_examples` since we only test pass/fail instead of quality. 5. Submit the run to test the change Example: f198538878 ## compare output coverages to daiquery runs 1. Randomly select null flag features from compute meta workflow output 2. Look up the feature id in feature metadata using feature name 3. Check against a daiquery sample of coverage to see if the coverage falls within guidelines. https://www.internalfb.com/intern/daiquery/workspace/275342740223489/192619942076136/ ## Sampled features: GFF_C66_ADS_USER_SUM_84_PAGE_TYPE_RATIO_EVENT_LIKE_IMPRESSION: 15694257 - original feature compute meta coverage: 0.999992 - daiquery feature coverage (10k rows): 0.69588 - null flag compute meta coverage: 0.293409 GFF_R1303_ADS_USER_SUM_7_PAGE_TYPE_COUNTER_CONVERSION: 16051183 - original feature compute meta coverage: 0.949868 - daiquery feature coverage: 0.82241 - null flag compute meta coverage: 0.151687 ## Unit tests: `buck test fblearner/flow/projects/dper/tests/workflows:ads_test` https://www.internalfb.com/intern/testinfra/testconsole/testrun/6192449504303863/ Differential Revision: D22026450 fbshipit-source-id: 46c59d849fa89253f14dc2b035c4c677cd6e3a4c