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Documentation update: use concurrency terminology in docstrings and comments
Summary: Updates docstrings and comments from "parallelism" to "concurrency" across orchestration, early stopping, telemetry, runner, adapter, and utility modules. Also includes minor formatting fixes in `orchestrator.py` and `fblearner.py`. No interface, constant, or behavioral changes. Differential Revision: D93771906
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ax/analysis/healthcheck/early_stopping_healthcheck.py

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@@ -95,7 +95,7 @@ def __init__(
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single-objective unconstrained experiments.
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min_savings_threshold: Minimum savings threshold to suggest early
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stopping. Default is 0.1 (10% savings).
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max_pending_trials: Maximum number of pending trials for replay
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max_pending_trials: Maximum number of concurrent trials for replay
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orchestrator. Default is 5.
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auto_early_stopping_config: A string for configuring automated early
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stopping strategy.

ax/core/runner.py

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@@ -81,7 +81,7 @@ def poll_available_capacity(self) -> int:
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artificially force this method to limit capacity; ``Orchestrator`` has other
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limitations in place to limit number of trials running at once,
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like the ``OrchestratorOptions.max_pending_trials`` setting, or
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more granular control in the form of the `max_parallelism`
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more granular control in the form of the `max_concurrency`
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setting in each of the `GenerationStep`s of a `GenerationStrategy`).
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Returns:

ax/early_stopping/experiment_replay.py

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@@ -130,7 +130,7 @@ def estimate_hypothetical_early_stopping_savings(
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Args:
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experiment: The experiment to analyze.
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metric: The metric to use for early stopping replay.
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max_pending_trials: Maximum number of pending trials for the replay
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max_pending_trials: Maximum number of concurrent trials for the replay
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orchestrator. Defaults to 5.
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Returns:

ax/orchestration/orchestrator.py

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@@ -1645,7 +1645,7 @@ def _validate_options(self, options: OrchestratorOptions) -> None:
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)
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def _get_max_pending_trials(self) -> int:
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"""Returns the maximum number of pending trials specified in the options, or
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"""Returns the maximum number of concurrent trials specified in the options, or
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zero, if the failure rate limit has been exceeded at any point during the
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optimization.
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"""
@@ -1690,8 +1690,9 @@ def _prepare_trials(
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max_pending_upper_bound = max_pending_trials - num_pending_trials
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if max_pending_upper_bound < 1:
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self.logger.debug(
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f"`max_pending_trials={max_pending_trials}` and {num_pending_trials} "
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"trials are currently pending; not initiating any additional trials."
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f"`max_pending_trials={max_pending_trials}` and "
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f"{num_pending_trials} trials are currently pending; "
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"not initiating any additional trials."
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)
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return [], []
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n = max_pending_upper_bound if n == -1 else min(max_pending_upper_bound, n)

ax/orchestration/orchestrator_options.py

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@@ -90,7 +90,7 @@ class OrchestratorOptions:
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deployment. The size of the groups will be determined as
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the minimum of ``self.poll_available_capacity()`` and the number
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of generator runs that the generation strategy is able to produce
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without more data or reaching its allowed max paralellism limit.
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without more data or reaching its allowed max concurrency limit.
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debug_log_run_metadata: Whether to log run_metadata for debugging purposes.
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early_stopping_strategy: A ``BaseEarlyStoppingStrategy`` that determines
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whether a trial should be stopped given the current state of

ax/utils/common/complexity_utils.py

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@@ -111,7 +111,7 @@ class OptimizationSummary:
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is True).
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tolerated_trial_failure_rate: Maximum tolerated trial failure rate
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(should be <= 0.9).
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max_pending_trials: Maximum number of pending trials.
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max_pending_trials: Maximum number of concurrent trials.
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min_failed_trials_for_failure_rate_check: Minimum failed trials before
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failure rate is checked.
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non_default_advanced_options: Whether non-default advanced options are set.

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