From f06fab5fda989c97acbf6c52bb51397a44958ee5 Mon Sep 17 00:00:00 2001 From: kywch Date: Wed, 1 Nov 2023 23:03:22 -0700 Subject: [PATCH] comments clean up --- evaluate.py | 1 - train.py | 4 ---- 2 files changed, 5 deletions(-) diff --git a/evaluate.py b/evaluate.py index 7204f556..89678748 100644 --- a/evaluate.py +++ b/evaluate.py @@ -112,7 +112,6 @@ def make_policy(envs): # Assign the task to the env tasks = make_task_from_spec(nmmo_env.possible_agents, [select_task] * len(nmmo_env.possible_agents)) - #nmmo_env.reset(make_task_fn=lambda: tasks) nmmo_env.tasks = tasks # this is a hack print("seed:", args.seed, ", task:", nmmo_env.tasks[0].spec_name) diff --git a/train.py b/train.py index fa6da7e0..9f43ea63 100644 --- a/train.py +++ b/train.py @@ -79,7 +79,6 @@ def curriculum_generation_track(trainer, args, use_elm=True): if use_elm: from curriculum_generation import manual_curriculum from curriculum_generation.elm import OpenELMTaskGenerator - AGENT_MODEL_PATH = "" NUM_SEED_TASKS = 20 NUM_NEW_TASKS = 5 ELM_DEBUG = True @@ -87,9 +86,6 @@ def curriculum_generation_track(trainer, args, use_elm=True): task_encoder = TaskEncoder(LLM_CHECKPOINT, manual_curriculum, batch_size=2) task_generator = OpenELMTaskGenerator(manual_curriculum.curriculum, LLM_CHECKPOINT) - # @daveey: We need a baseline checkpoint for this - #load_agent_model(AGENT_MODEL_PATH) - # Generating new tasks and evaluating all candidate training tasks for _ in range(3): # NOTE: adjust NUM_SEED_TASKS to fit your gpu