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Summary Add a complete OTG traffic generation backend as an alternative to the existing Keysight restpy-based Ixia integration. This enables TAAC to drive traffic via the open-source snappi/ixia-c stack ...
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Summary Batch of OSS-mode improvements developed and validated against real Ixia hardware in our lab. Three areas: 1. VP4 thrift client factory — dependency-injected client factory so FbossSwitch can ...
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Summary: D109061377 relaxed MultiObjectiveOptimizationConfig validation so that, in multi-objective optimization, an outcome constraint can be placed on an objective metric (e.g. flops = 42 while minimizing ...
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Two unrelated OSS-compat fixes for the public slice. 1. Move EBB conveyor TestConfig aggregation out of the package __init__ taac/routing/ebb/ebb_bgp_plus_plus_test_config/ebb_bgp_plus_plus_conveyor/__init__.py ...
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The internal and external repositories are out of sync. This Pull Request attempts to brings them back in sync by patching the GitHub repository. Please carefully review this patch. You must disable ShipIt ...
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The internal and external repositories are out of sync. This Pull Request attempts to brings them back in sync by patching the GitHub repository. Please carefully review this patch. You must disable ShipIt ...
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Summary: Implements the feature requested in https://github.com/facebook/Ax/issues/4688: a fit_tracking_metrics option on the high-level Client.configure_generation_strategy API, so users can disable modeling ...
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Summary: Migrates fbcode/ax from Pyre to Pyrefly by removing the root python.set_pyrefly(False) opt-out so the tree inherits set_pyrefly(True) from the fbcode root default. Pre-existing type errors are ...
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Summary: Summary Adds a log_scale: bool | None = None field to ChoiceParameterConfig and pipes it through parameter_from_config to the underlying ChoiceParameter. This is the Ax-side change for T276435081, ...
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Summary: In multi-objective optimization, the acquisition function can exploit asymmetric model uncertainty by proposing points that are extreme in easy-to-predict objectives (e.g., very small model size) ...
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