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Chris Elion
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add "the the" to precommit spell check (Unity-Technologies#4059)
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.pre-commit-search-and-replace.yaml

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search: /ML[ -]Agents toolkit/
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replacement: ML-Agents Toolkit
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insensitive: true
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- description: Replace "the the"
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search: /the the/
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replacement: the
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insensitive: true

docs/Installation.md

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order to find it.
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**NOTE:** If you do not see the ML-Agents package listed in the Package Manager
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please follow the the [advanced installation instructions](#advanced-local-installation-for-development) below.
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please follow the [advanced installation instructions](#advanced-local-installation-for-development) below.
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#### Advanced: Local Installation for Development
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docs/Migrating.md

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`RayPerception3d.Perceive()` that was causing the `endOffset` to be used
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incorrectly. However this may produce different behavior from previous
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versions if you use a non-zero `startOffset`. To reproduce the old behavior,
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you should increase the the value of `endOffset` by `startOffset`. You can
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you should increase the value of `endOffset` by `startOffset`. You can
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verify your raycasts are performing as expected in scene view using the debug
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rays.
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- If you use RayPerception3D, replace it with RayPerceptionSensorComponent3D

docs/Training-on-Amazon-Web-Service.md

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Fatal server error:
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(EE) no screens found(EE)
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(EE)
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Please consult the The X.Org Foundation support
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Please consult the X.Org Foundation support
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at http://wiki.x.org
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for help.
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(EE) Please also check the log file at "/var/log/Xorg.0.log" for additional information.

ml-agents/mlagents/trainers/ghost/trainer.py

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)
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)
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# Counts the The number of steps of the ghost policies. Snapshot swapping
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# Counts the number of steps of the ghost policies. Snapshot swapping
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# depends on this counter whereas snapshot saving and team switching depends
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# on the wrapped. This ensures that all teams train for the same number of trainer
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# steps.

ml-agents/mlagents/trainers/sac/trainer.py

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:param training: Whether the trainer is set for training.
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:param load: Whether the model should be loaded.
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:param seed: The seed the model will be initialized with
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:param run_id: The The identifier of the current run
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:param run_id: The identifier of the current run
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"""
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super().__init__(
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brain_name, trainer_settings, training, run_id, reward_buff_cap

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