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CS60003-HW3

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Organize ACT models under topic2

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  1. README.md +16 -16
  2. topic2/README.md +156 -0
  3. topic2/act_calvin_ABC_best/pretrained_model/config.json +71 -0
  4. topic2/act_calvin_ABC_best/pretrained_model/model.safetensors +3 -0
  5. topic2/act_calvin_ABC_best/pretrained_model/policy_postprocessor.json +32 -0
  6. topic2/act_calvin_ABC_best/pretrained_model/policy_postprocessor_step_0_unnormalizer_processor.safetensors +3 -0
  7. topic2/act_calvin_ABC_best/pretrained_model/policy_preprocessor.json +64 -0
  8. topic2/act_calvin_ABC_best/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors +3 -0
  9. topic2/act_calvin_ABC_best/pretrained_model/train_config.json +0 -0
  10. topic2/act_calvin_A_best/pretrained_model/config.json +71 -0
  11. topic2/act_calvin_A_best/pretrained_model/model.safetensors +3 -0
  12. topic2/act_calvin_A_best/pretrained_model/policy_postprocessor.json +32 -0
  13. topic2/act_calvin_A_best/pretrained_model/policy_postprocessor_step_0_unnormalizer_processor.safetensors +3 -0
  14. topic2/act_calvin_A_best/pretrained_model/policy_preprocessor.json +64 -0
  15. topic2/act_calvin_A_best/pretrained_model/policy_preprocessor_step_3_normalizer_processor.safetensors +3 -0
  16. topic2/act_calvin_A_best/pretrained_model/train_config.json +4223 -0
  17. topic2/best_model_summary.json +44 -0
README.md CHANGED
@@ -10,21 +10,21 @@ tags:
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  # CS60003-HW3 Model Artifacts
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- This repository stores the trained models and generated 3D assets for both HW3 tasks.
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-
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- ## Task 1: 3DGS and AIGC Asset Fusion
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-
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- - `topic1/weights/`: four packaged checkpoints for object A, Flowers background, DreamFusion object B, and Stable Zero123 object C.
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- - `topic1/assets/`: exported OBJ meshes and sampled PLY point clouds.
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- - `topic1/previews/`: turntable renders, 3DGS renders, and the final fusion preview.
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- - `topic1/model_manifest.json`: training settings, metrics, file sizes, and SHA256 checksums.
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-
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- ## Task 2: LeRobot ACT
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-
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- - `act_calvin_A_best/pretrained_model/`: validation-best A-only ACT policy.
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- - `act_calvin_ABC_best/pretrained_model/`: validation-best A/B/C joint ACT policy.
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- - `best_model_summary.json`: validation and zero-shot D Action L1 metrics.
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-
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- Code and the full report:
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  https://github.com/Zhan-xing-pz/CS60003-HW3
 
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  # CS60003-HW3 Model Artifacts
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+ The model repository mirrors the two-task structure of the GitHub project.
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+
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+ ```text
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+ topic1/
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+ weights/ 3DGS, DreamFusion, and Stable Zero123 checkpoints
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+ assets/ Exported OBJ meshes and PLY point clouds
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+ previews/ 3DGS renders, turntables, and fusion video
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+ model_manifest.json Metrics, sizes, and SHA256 checksums
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+
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+ topic2/
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+ act_calvin_A_best/ Validation-best A-only ACT policy
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+ act_calvin_ABC_best/ Validation-best A/B/C joint ACT policy
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+ best_model_summary.json
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+ ```
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+
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+ Code and full report:
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  https://github.com/Zhan-xing-pz/CS60003-HW3
topic2/README.md ADDED
@@ -0,0 +1,156 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # Topic 2: LeRobot ACT 跨环境泛化
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+
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+ 本目录实现题目二“基于 LeRobot 的 ACT 策略跨环境泛化挑战”。
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+
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+ 实验比较：
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+
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+ - `act_calvin_A`：仅使用 CALVIN 环境 A 训练。
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+ - `act_calvin_ABC`：联合使用环境 A/B/C 训练。
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+
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+ 两个模型使用相同的 ACT 架构和训练超参数，只根据训练域 validation Action L1 选择最佳 checkpoint；环境 D 仅用于最终 zero-shot 评估。
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+
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+ ## 最终设置
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+
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+ | 项目 | 设置 |
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+ |---|---|
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+ | Training Steps | 30000 |
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+ | Batch Size | 64 |
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+ | Learning Rate | 1e-4 |
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+ | Optimizer | AdamW |
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+ | Weight Decay | 1e-6 |
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+ | Loss | L1 imitation loss |
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+ | ACT Chunk Size | 16 |
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+ | Checkpoint Frequency | 1000 steps |
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+ | Validation per Checkpoint | 50 batches |
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+ | Final D Evaluation | 200 batches |
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+
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+ 最终结果：
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+
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+ | 模型 | Best Step | Validation Action L1 | D Zero-shot Action L1 |
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+ |---|---:|---:|---:|
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+ | A-only | 14000 | 0.475544 | 0.496255 |
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+ | A/B/C joint | 27000 | 0.427793 | 0.447098 |
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+
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+ D 的离线数据没有可靠任务完成信号，因此使用 Action L1 作为主要 zero-shot 指标。
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+
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+ ## 目录结构
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+
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+ ```text
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+ configs/ ACT 训练与 smoke test 配置
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+ scripts/ 数据准备、训练、评估与绘图脚本
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+ src/hw3_act/ 核心实现
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+ requirements.txt Python 依赖
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+ environment.yml Conda 环境
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+ outputs/ 本地运行结果，不提交 Git
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+ wandb/ 本地 WandB 记录，不提交 Git
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+ ```
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+
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+ ## 环境
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+
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+ 正式实验使用服务器 Conda 环境：
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+
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+ ```bash
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+ conda activate pz
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+ ```
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+
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+ 新环境可执行：
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+
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+ ```bash
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+ conda env create -f environment.yml
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+ conda activate hw3-act
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+ pip install -r requirements.txt
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+ ```
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+
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+ LeRobot 安装与 ACT 文档：
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+
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+ https://huggingface.co/docs/lerobot/act
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+
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+ ## 数据准备
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+
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+ 数据集：
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+
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+ https://huggingface.co/datasets/huiwon/calvin_task_ABC_D
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+
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+ 在 `topic2/` 目录运行：
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+
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+ ```bash
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+ python scripts/download_calvin.py
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+ python scripts/convert_lerobot_v30.py
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+ python scripts/prepare_data.py \
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+ --dataset-root data/lerobot_v21 \
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+ --output-dir data/splits
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+ ```
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+
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+ 最终使用的数据目录：
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+
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+ ```text
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+ data/lerobot_v21/local/calvin_A
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+ data/lerobot_v21/local/calvin_ABC
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+ data/lerobot_v21/local/calvin_D
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+ ```
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+
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+ ## 训练
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+
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+ ```bash
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+ python scripts/train.py --config configs/act_a_only.yaml
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+ python scripts/train.py --config configs/act_abc.yaml
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+ ```
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+
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+ 服务器可使用：
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+
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+ ```bash
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+ bash scripts/launch_best_training.sh
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+ ```
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+
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+ 训练包装器会：
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+
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+ - 每 1000 steps 评估训练域 validation split。
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+ - 写入 `metrics/checkpoint_valid_metrics.csv`。
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+ - 只维护 `checkpoints/best/pretrained_model`。
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+ - 保留训练日志和可重新生成图表的 CSV。
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+
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+ ## D 环境 Zero-shot 评估
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+
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+ ```bash
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+ python scripts/eval_zero_shot.py \
116
+ --config configs/act_a_only.yaml \
117
+ --checkpoint outputs/act_calvin_A/checkpoints/best/pretrained_model
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+
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+ python scripts/eval_zero_shot.py \
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+ --config configs/act_abc.yaml \
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+ --checkpoint outputs/act_calvin_ABC/checkpoints/best/pretrained_model
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+ ```
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+
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+ 输出：
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+
126
+ ```text
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+ outputs/<run>/metrics/eval_D_summary.csv
128
+ outputs/<run>/metrics/eval_D_episodes.csv
129
+ ```
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+
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+ ## 可视化
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+
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+ ```bash
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+ python scripts/parse_lerobot_log.py --run outputs/act_calvin_A
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+ python scripts/parse_lerobot_log.py --run outputs/act_calvin_ABC
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+
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+ python scripts/plot_metrics.py \
138
+ --runs outputs/act_calvin_A outputs/act_calvin_ABC \
139
+ --output-dir outputs/figures
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+ ```
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+
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+ WandB 项目：
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+
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+ https://wandb.ai/zhanxing-fudan-university-school-of-management/CS60003-HW3-ACT
145
+
146
+ ## 模型权重
147
+
148
+ Hugging Face：
149
+
150
+ ```text
151
+ topic2/act_calvin_A_best/pretrained_model/
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+ topic2/act_calvin_ABC_best/pretrained_model/
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+ topic2/best_model_summary.json
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+ ```
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+
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+ https://huggingface.co/zhanxing/CS60003-HW3/tree/main/topic2
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topic2/best_model_summary.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "repo_id": "zhanxing/CS60003-HW3",
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+ "github": "https://github.com/Zhan-xing-pz/CS60003-HW3",
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+ "models": {
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+ "act_calvin_A_best": {
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+ "training_data": "CALVIN environment A",
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+ "best_step": 14000,
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+ "validation_action_l1": 0.47554418712854385,
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+ "zero_shot_D_action_l1": 0.4962553956359625,
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+ "path_in_repo": "act_calvin_A_best/pretrained_model",
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+ "files": [
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+ "config.json",
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+ "model.safetensors",
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+ "policy_postprocessor.json",
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+ "policy_postprocessor_step_0_unnormalizer_processor.safetensors",
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+ "policy_preprocessor.json",
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+ },
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+ "act_calvin_ABC_best": {
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+ "training_data": "CALVIN environments A/B/C",
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+ "best_step": 27000,
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+ "validation_action_l1": 0.42779327780008314,
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+ "zero_shot_D_action_l1": 0.44709823302924634,
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+ "path_in_repo": "act_calvin_ABC_best/pretrained_model",
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+ "files": [
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+ "config.json",
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+ "model.safetensors",
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+ "policy_postprocessor.json",
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+ "policy_preprocessor.json",
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+ "train_config.json"
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+ "total_size_bytes": 141436058
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+ }
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+ },
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+ "notes": [
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+ "Both folders contain LeRobot pretrained_model artifacts.",
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+ "Environment D has no reliable success signal in the converted offline data; Action L1 is reported instead."
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+ ]
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+ }