Fix: handle _action_masks buffer in single-task scenarios (#67 )

update readme + dockerfile
only instantiate termination pred head if episodic=true
2025-05-19 20:12:12 -07:00 · 2025-05-13 14:51:16 -07:00 · 2025-05-02 16:51:24 -07:00 · 2025-05-02 16:24:02 -07:00 · 2025-04-15 16:32:15 -07:00 · 2025-04-15 15:55:05 -07:00
460 changed files with 36209 additions and 1070 deletions
--- a/README.md
+++ b/README.md
@@ -2,23 +2,30 @@

 Official implementation of

-[TD-MPC2: Scalable, Robust World Models for Continuous Control](https://nicklashansen.github.io/td-mpc2) by
+[TD-MPC2: Scalable, Robust World Models for Continuous Control](https://www.tdmpc2.com) by

-[Nicklas Hansen](https://nicklashansen.github.io/), [Hao Su](https://cseweb.ucsd.edu/~haosu/)\*, [Xiaolong Wang](https://xiaolonw.github.io/)\* (UC San Diego)</br>
+[Nicklas Hansen](https://nicklashansen.github.io), [Hao Su](https://cseweb.ucsd.edu/~haosu)\*, [Xiaolong Wang](https://xiaolonw.github.io)\* (UC San Diego)</br>

 <img src="assets/0.gif" width="12.5%"><img src="assets/1.gif" width="12.5%"><img src="assets/2.gif" width="12.5%"><img src="assets/3.gif" width="12.5%"><img src="assets/4.gif" width="12.5%"><img src="assets/5.gif" width="12.5%"><img src="assets/6.gif" width="12.5%"><img src="assets/7.gif" width="12.5%"></br>

-[[Website]](https://nicklashansen.github.io/td-mpc2) [[Paper]](https://arxiv.org/abs/2310.16828) [[Models]](https://nicklashansen.github.io/td-mpc2/models)  [[Dataset]](https://nicklashansen.github.io/td-mpc2/dataset)
+[[Website]](https://www.tdmpc2.com) [[Paper]](https://arxiv.org/abs/2310.16828) [[Models]](https://www.tdmpc2.com/models)  [[Dataset]](https://www.tdmpc2.com/dataset)

 ----

+**Announcement (Apr 2025): support for episodic tasks!**
+
+We have added support for episodic RL (tasks with terminations) in the latest release. This functionality can be enabled with `episodic=true` but remains disabled by default to ensure reproducibility of results across releases.
+
+----
+
+
 ## Overview

 TD-MPC**2** is a scalable, robust model-based reinforcement learning algorithm. It compares favorably to existing model-free and model-based methods across **104** continuous control tasks spanning multiple domains, with a *single* set of hyperparameters (*right*). We further demonstrate the scalability of TD-MPC**2** by training a single 317M parameter agent to perform **80** tasks across multiple domains, embodiments, and action spaces (*left*). 

 <img src="assets/8.png" width="100%" style="max-width: 640px"><br/>

-This repository contains code for training and evaluating both single-task online RL and multi-task offline RL TD-MPC**2** agents. We additionally open-source **300+** [model checkpoints](https://nicklashansen.github.io/td-mpc2/models) (including 12 multi-task models) across 4 task domains: [DMControl](https://arxiv.org/abs/1801.00690), [Meta-World](https://meta-world.github.io/), [ManiSkill2](https://maniskill2.github.io/), and [MyoSuite](https://sites.google.com/view/myosuite), as well as our [30-task and 80-task datasets](https://nicklashansen.github.io/td-mpc2/dataset) used to train the multi-task models. Our codebase supports both state and pixel observations. We hope that this repository will serve as a useful community resource for future research on model-based RL.
+This repository contains code for training and evaluating both single-task online RL and multi-task offline RL TD-MPC**2** agents. We additionally open-source **300+** [model checkpoints](https://www.tdmpc2.com/models) (including 12 multi-task models) across 4 task domains: [DMControl](https://arxiv.org/abs/1801.00690), [Meta-World](https://meta-world.github.io/), [ManiSkill2](https://maniskill2.github.io/), and [MyoSuite](https://sites.google.com/view/myosuite), as well as our [30-task and 80-task datasets](https://www.tdmpc2.com/dataset) used to train the multi-task models. Our codebase supports both state and pixel observations. We hope that this repository will serve as a useful community resource for future research on model-based RL.

 ----

@@ -29,17 +36,18 @@ You will need a machine with a GPU and at least 12 GB of RAM for single-task onl
 We provide a `Dockerfile` for easy installation. You can build the docker image by running

 ```
-cd docker && docker build . -t <user>/tdmpc2:0.1.0
+cd docker && docker build . -t <user>/tdmpc2:1.0.1
 ```

-If you prefer to install dependencies manually, start by installing dependencies via `conda` by running one of the following commands:
+This docker image contains all dependencies needed for running DMControl. We also provide a pre-built docker image [here](https://hub.docker.com/repository/docker/nicklashansen/tdmpc2/tags/1.0.1/sha256-b07d4e04d4b28ffd9a63ac18ec1541950e874bb51d276c7d09b36135f170dd93).
+
+If you prefer to use `conda` rather than docker, start by running the following command:

 ```
 conda env create -f docker/environment.yaml
-conda env create -f docker/environment_minimal.yaml
 ```

-The `environment.yaml` file installs dependencies required for all environments, whereas `environment_minimal.yaml` only installs dependencies for training on DMControl tasks.
+The `docker/environment.yaml` file installs dependencies required for training on DMControl tasks. Other domains can be installed by following the instructions in `docker/environment.yaml`.

 If you want to run ManiSkill2, you will additionally need to download and link the necessary assets by running

@@ -53,19 +61,19 @@ which downloads assets to `./data`. You may move these assets to any location. T
 export MS2_ASSET_DIR=<path>/<to>/<data>
 ```

-and restart your terminal. Meta-World additionally requires MuJoCo 2.1.0. We host the unrestricted MuJoCo 2.1.0 license (courtesy of Google DeepMind) at [https://www.tdmpc2.com/files/mjkey.txt](https://www.tdmpc2.com/files/mjkey.txt). You can download the license by running
+and restart your terminal. Note that Meta-World requires MuJoCo 2.1.0 and `gym==0.21.0` which is becoming increasingly difficult to install. We host the unrestricted MuJoCo 2.1.0 license (courtesy of Google DeepMind) at [https://www.tdmpc2.com/files/mjkey.txt](https://www.tdmpc2.com/files/mjkey.txt). You can download the license by running

 ```
 wget https://www.tdmpc2.com/files/mjkey.txt -O ~/.mujoco/mjkey.txt
 ```

-See `docker/Dockerfile` for installation instructions if you do not already have MuJoCo 2.1.0 installed. MyoSuite requires `gym==0.13.0` which is incompatible with Meta-World and ManiSkill2. Install separately with `pip install myosuite` if desired. Depending on your existing system packages, you may need to install other dependencies. See `docker/Dockerfile` for a list of recommended system packages.
+Depending on your existing system packages, you may need to install other dependencies. See `docker/Dockerfile` for a list of recommended system packages.

 ----

 ## Supported tasks

-This codebase currently supports **104** continuous control tasks from **DMControl**, **Meta-World**, **ManiSkill2**, and **MyoSuite**. Specifically, it supports 39 tasks from DMControl (including 11 custom tasks), 50 tasks from Meta-World, 5 tasks from ManiSkill2, and 10 tasks from MyoSuite, and covers all tasks used in the paper. See below table for expected name formatting for each task domain:
+This codebase provides support for all **104** continuous control tasks from **DMControl**, **Meta-World**, **ManiSkill2**, and **MyoSuite** used in our paper. Specifically, it supports 39 tasks from DMControl (including 11 custom tasks), 50 tasks from Meta-World, 5 tasks from ManiSkill2, and 10 tasks from MyoSuite, and covers all tasks used in the paper. See below table for expected name formatting for each task domain:

 | domain | task
 | --- | --- |
@@ -78,9 +86,9 @@ This codebase currently supports **104** continuous control tasks from **DMContr
 | myosuite  | myo-key-turn
 | myosuite  | myo-key-turn-hard

-which can be run by specifying the `task` argument for `evaluation.py`. Multi-task training and evaluation is specified by setting `task=mt80` or `task=mt30` for the 80-task and 30-task sets, respectively.
+which can be run by specifying the `task` argument for `evaluation.py`. Multi-task training and evaluation is specified by setting `task=mt80` or `task=mt30` for the 80-task and 30-task sets, respectively. While you generally do not need to access the underlying task IDs or embeddings during training or evaluation of our multi-task models, the mapping from task name to task embedding used in our work can be found [here](https://github.com/nicklashansen/tdmpc2/blob/7ec6bc83a82a5188ca3faddc59aea83f430ab570/tdmpc2/common/__init__.py#L26). As of April 2025, our codebase also provides basic support for other MuJoCo/Box2d Gymnasium tasks; refer to the `envs` directory for a list of tasks. It should be relatively straightforward to add support for custom tasks by following the examples in `envs`.

-**As of Dec 27, 2023 the TD-MPC2 codebase also supports pixel observations for DMControl tasks**; use argument `obs=rgb` if you wish to train visual policies.
+**Note:** we also provide support for image observations in the DMControl tasks. Use argument `obs=rgb` if you wish to train visual policies.


 ## Example usage
@@ -112,22 +120,27 @@ $ python train.py task=walker-walk obs=rgb

 We recommend using default hyperparameters for single-task online RL, including the default model size of 5M parameters (`model_size=5`). Multi-task offline RL benefits from a larger model size, but larger models are also increasingly costly to train and evaluate. Available arguments are `model_size={1, 5, 19, 48, 317}`. See `config.yaml` for a full list of arguments.

-**As of Jan 7, 2024 the TD-MPC2 codebase also supports multi-GPU training for multi-task offline RL experiments**; use branch `distributed` and argument `world_size=N` to train on `N` GPUs. We cannot guarantee that distributed training will yield the same results, but they appear to be similar based on our limited testing.
-
 ----

 ## Citation

-If you find our work useful, please consider citing the paper as follows:
+If you find our work useful, please consider citing our paper as follows:

 ```
-@misc{hansen2023tdmpc2,
-	title={TD-MPC2: Scalable, Robust World Models for Continuous Control}, 
-	author={Nicklas Hansen and Hao Su and Xiaolong Wang},
-	year={2023},
-	eprint={2310.16828},
-	archivePrefix={arXiv},
-	primaryClass={cs.LG}
+@inproceedings{hansen2024tdmpc2,
+  title={TD-MPC2: Scalable, Robust World Models for Continuous Control}, 
+  author={Nicklas Hansen and Hao Su and Xiaolong Wang},
+  booktitle={International Conference on Learning Representations (ICLR)},
+  year={2024}
+}
+```
+as well as the original TD-MPC paper:
+```
+@inproceedings{hansen2022tdmpc,
+  title={Temporal Difference Learning for Model Predictive Control},
+  author={Nicklas Hansen and Xiaolong Wang and Hao Su},
+  booktitle={International Conference on Machine Learning (ICML)},
+  year={2022}
 }
 ```

--- a/datasets/download_mt30.sh
+++ b/datasets/download_mt30.sh
@@ -0,0 +1 @@
+for i in {0..3}; do wget https://huggingface.co/datasets/nicklashansen/tdmpc2/resolve/main/mt30/chunk_${i}.pt?download=true && mv chunk_${i}.pt'?download=true' chunk_${i}.pt; done
--- a/datasets/download_mt80.sh
+++ b/datasets/download_mt80.sh
@@ -0,0 +1 @@
+for i in {0..19}; do wget https://huggingface.co/datasets/nicklashansen/tdmpc2/resolve/main/mt80/chunk_${i}.pt?download=true && mv chunk_${i}.pt'?download=true' chunk_${i}.pt; done
--- a/docker/Dockerfile
+++ b/docker/Dockerfile
@@ -1,59 +1,49 @@
 ##########################################
 # Dockerfile for TD-MPC2                 #
-# TD-MPC2 Anonymous Authors, 2023 (c)    #
+# Nicklas Hansen, 2023 (c)               #
+# https://www.tdmpc2.com                 #
 # -------------------------------------- #
-# Instructions:                          #
-# docker build . -t <user>/tdmpc2:0.1.0  #
-# docker push <user>/tdmpc2:0.1.0        #
+# Build instructions:                    #
+# docker build . -t <user>/tdmpc2:1.0.1  #
+# docker push <user>/tdmpc2:1.0.1        #
+# -------------------------------------- #
+# Run:                                   #
+# docker run -i \                        #
+#   -v <path>/<to>/tdmpc2:/tdmpc2 \      #
+#   --gpus all \                         #
+#   -t <user>/tdmpc2:1.0.1 \             #
+#   /bin/bash                            #
 ##########################################

 # base image
-FROM nvidia/cudagl:11.3.1-devel-ubuntu20.04
+FROM pytorch/pytorch:2.5.1-cuda12.4-cudnn9-runtime
 ENV DEBIAN_FRONTEND=noninteractive

 # packages
 RUN apt-get -y update && \
-    apt-get install -y --no-install-recommends build-essential git nano rsync vim tree curl \
-    wget unzip htop tmux xvfb patchelf ca-certificates bash-completion libjpeg-dev libpng-dev \
-    ffmpeg cmake swig libssl-dev libcurl4-openssl-dev libopenmpi-dev python3-dev zlib1g-dev \
-    qtbase5-dev qtdeclarative5-dev libglib2.0-0 libglu1-mesa-dev libgl1-mesa-dev libvulkan1 \
-    libgl1-mesa-glx libosmesa6 libosmesa6-dev libglew-dev mesa-utils && \
+    apt-get install -y --no-install-recommends build-essential git nano rsync vim tree curl wget \
+    swig ffmpeg unzip htop tmux xvfb ca-certificates bash-completion libjpeg-dev libpng-dev \
+    libssl-dev libcurl4-openssl-dev libopenmpi-dev zlib1g-dev qtbase5-dev qtdeclarative5-dev \
+    libglib2.0-0 libglu1-mesa-dev libgl1-mesa-dev libvulkan1 libgl1-mesa-glx libosmesa6 \
+    libosmesa6-dev libglew-dev mesa-utils && \
    apt-get clean && \
    apt-get autoremove -y && \
    rm -rf /var/lib/apt/lists/* && \
    mkdir /root/.ssh

-# miniconda
-RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh && \
-    /bin/bash ~/miniconda.sh -b -p /opt/conda && \
-    rm ~/miniconda.sh && \
-    . /opt/conda/etc/profile.d/conda.sh && \
-    conda init && \
-    conda clean -ya
-ENV PATH /opt/conda/bin:$PATH
-SHELL ["/bin/bash", "-c"]
-
 # conda environment
 COPY nvidia_icd.json /usr/share/vulkan/icd.d/nvidia_icd.json
 COPY environment.yaml /root
-RUN conda env update -n base -f /root/environment.yaml && \
+RUN conda update conda && \
+    conda env update -n base -f /root/environment.yaml && \
    rm /root/environment.yaml && \
-    cd /root && \
-    python -m mani_skill2.utils.download_asset all -y && \
    conda clean -ya && \
-    pip cache purge
+    pip cache purge && \
+    conda init
+SHELL ["/bin/bash", "-c"]
+RUN echo "cd /root" >> /root/.bashrc
+# image does not include metaworld, maniskill, myosuite
+# these can be installed separately; see environment.yaml for details

-# environment variables
-ENV MUJOCO_GL egl
-ENV MS2_ASSET_DIR /root/data
-ENV LD_LIBRARY_PATH /root/.mujoco/mujoco210/bin:${LD_LIBRARY_PATH}
-
-# mujoco (required for metaworld)
-RUN mkdir -p /root/.mujoco && \
-    wget https://www.tdmpc2.com/files/mjkey.txt && \
-    wget https://github.com/deepmind/mujoco/releases/download/2.1.0/mujoco210-linux-x86_64.tar.gz && \
-    tar -xzf mujoco210-linux-x86_64.tar.gz && \
-    rm mujoco210-linux-x86_64.tar.gz && \
-    mv mujoco210 /root/.mujoco/mujoco210 && \
-    mv mjkey.txt /root/.mujoco/mjkey.txt && \
-    python -c "import mujoco_py"
+# success!
+RUN echo "Successfully built TD-MPC2 Docker image!"
--- a/docker/environment.yaml
+++ b/docker/environment.yaml
@@ -5,49 +5,57 @@ channels:
  - conda-forge
  - defaults
 dependencies:
-  - python=3.9.0
-  - pytorch
-  - torchvision
-  - cudatoolkit=11.7
-  - glew
-  - glib
-  - pip==21
+  - glew=2.2.0
+  - glib=2.78.4
+  - pip=24.0
+  - python=3.9
+  - pytorch=2.6.0.dev20241112
+  - pytorch-cuda=12.4
+  - torchvision=0.15.2
  - pip:
-    - absl-py
-    - glfw
-    - kornia
-    - termcolor
-    - gym==0.21.0
-    - moviepy
-    - ffmpeg
-    - imageio
-    - imageio-ffmpeg
-    - omegaconf
-    - hydra-core
-    - hydra-submitit-launcher
-    - submitit
-    - pandas
-    - patchelf
-    - protobuf
-    - tqdm
-    - transforms3d
-    - joblib
-    - opencv-python
-    - opencv-contrib-python
-    - filelock
-    - sapien==2.2.1
-    - mani-skill2==0.4.1
-    - trimesh
-    - open3d
-    - setuptools==65.5.0
-    - "cython<3"
-    - mujoco==2.3.1
-    - mujoco-py==2.1.2.14
-    - dm-control
-    - pillow
-    - pyquaternion
-    - git+https://github.com/Farama-Foundation/Metaworld.git@04be337a12305e393c0caf0cbf5ec7755c7c8feb
-    # - myosuite # MyoSuite requires gym==0.13.0 which conflicts with Meta-World & ManiSkill2, install separately if needed
-    - tensordict-nightly
-    - torchrl-nightly
-    - wandb
+    - dm-control==1.0.16
+    - glfw==2.7.0
+    - gymnasium==0.29.1
+    - ffmpeg==1.4
+    - imageio==2.34.1
+    - imageio-ffmpeg==0.4.9
+    - h5py==3.11.0
+    - hydra-core==1.3.2
+    - hydra-submitit-launcher==1.2.0
+    - submitit==1.5.1
+    - omegaconf==2.3.0
+    - moviepy==1.0.3
+    - mujoco==3.1.2
+    - numpy==1.24.4
+    - tensordict-nightly==2025.1.1
+    - torchrl-nightly==2025.1.1
+    - kornia==0.7.2
+    - termcolor==2.4.0
+    - tqdm==4.66.4
+    - pandas==2.0.3
+    - wandb==0.17.4
+    ####################
+    # Gym:
+    # (unmaintained but required for maniskill2/meta-world)
+    # - "cython<3"
+    # - wheel==0.38.0
+    # - setuptools==65.5.0
+    # - mujoco==2.3.1
+    # - mujoco-py==2.1.2.14
+    # - gym==0.21.0
+    ####################
+    # ManiSkill2:
+    # (requires gym==0.21.0 which occasionally breaks)
+    # - mani-skill2==0.4.1
+    ####################
+    # Meta-World:
+    # (requires gym==0.21.0 which occasionally breaks)
+    # - git+https://github.com/Farama-Foundation/Metaworld.git@04be337a12305e393c0caf0cbf5ec7755c7c8feb
+    ####################
+    # MyoSuite:
+    # - myosuite
+    ####################
+    # Classic MuJoCo/Box2d:
+    # - swig
+    # - gymnasium[box2d]
+    ####################
--- a/docker/environment_minimal.yaml
+++ b/docker/environment_minimal.yaml
@@ -1,39 +0,0 @@
-name: tdmpc2
-channels:
-  - pytorch-nightly
-  - nvidia
-  - conda-forge
-  - defaults
-dependencies:
-  - python=3.9.0
-  - pytorch
-  - torchvision
-  - cudatoolkit=11.7
-  - glew
-  - glib
-  - pip==21
-  - pip:
-    - absl-py
-    - glfw
-    - kornia
-    - termcolor
-    - gym==0.21.0
-    - moviepy
-    - ffmpeg
-    - imageio
-    - imageio-ffmpeg
-    - omegaconf
-    - hydra-core
-    - hydra-submitit-launcher
-    - submitit
-    - pandas
-    - patchelf
-    - protobuf
-    - tqdm
-    - setuptools==65.5.0
-    - "cython<3"
-    - dm-control
-    - pillow
-    - tensordict-nightly
-    - torchrl-nightly
-    - wandb
--- a/results/dreamerv3/acrobot-swingup.csv
+++ b/results/dreamerv3/acrobot-swingup.csv
@@ -0,0 +1,120 @@
+step,reward,seed
+0,0.3,3
+100000,85.3,3
+200000,110.7,3
+300000,230.7,3
+400000,259.4,3
+500000,316.0,3
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+0,3.6,2
+100000,91.7,2
+200000,245.2,2
+300000,257.1,2
+400000,305.4,2
+500000,360.6,2
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+1000000,342.8,2
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+1800000,362.9,2
+1900000,352.7,2
+2000000,369.8,2
+2100000,326.1,2
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+2300000,377.6,2
+2400000,364.8,2
+2500000,331.6,2
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+2800000,391.8,2
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+3000000,378.2,2
+3100000,331.9,2
+3200000,315.5,2
+3300000,367.1,2
+3400000,354.2,2
+3500000,316.5,2
+3600000,362.0,2
+3700000,344.0,2
+3800000,369.0,2
+0,0.5,1
+100000,126.8,1
+200000,177.2,1
+300000,207.9,1
+400000,237.6,1
+500000,289.0,1
+600000,322.0,1
+700000,319.4,1
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+3500000,335.2,1
+3600000,369.9,1
+3700000,422.8,1
+3800000,409.7,1
+3900000,386.4,1
--- a/results/dreamerv3/cartpole-balance-sparse.csv
+++ b/results/dreamerv3/cartpole-balance-sparse.csv
@@ -0,0 +1,119 @@
+step,reward,seed
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--- a/results/dreamerv3/cartpole-balance.csv
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--- a/results/dreamerv3/cartpole-swingup-sparse.csv
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--- a/results/dreamerv3/cartpole-swingup.csv
+++ b/results/dreamerv3/cartpole-swingup.csv
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--- a/results/dreamerv3/cheetah-jump.csv
+++ b/results/dreamerv3/cheetah-jump.csv
@@ -0,0 +1,114 @@
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--- a/results/dreamerv3/cheetah-run-back.csv
+++ b/results/dreamerv3/cheetah-run-back.csv
@@ -0,0 +1,116 @@
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--- a/results/dreamerv3/cheetah-run-backwards.csv
+++ b/results/dreamerv3/cheetah-run-backwards.csv
@@ -0,0 +1,114 @@
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--- a/results/dreamerv3/cheetah-run-front.csv
+++ b/results/dreamerv3/cheetah-run-front.csv
@@ -0,0 +1,115 @@
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--- a/results/dreamerv3/cheetah-run.csv
+++ b/results/dreamerv3/cheetah-run.csv
@@ -0,0 +1,116 @@
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--- a/results/dreamerv3/cup-catch.csv
+++ b/results/dreamerv3/cup-catch.csv
@@ -0,0 +1,117 @@
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--- a/results/dreamerv3/cup-spin.csv
+++ b/results/dreamerv3/cup-spin.csv
@@ -0,0 +1,113 @@
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--- a/results/dreamerv3/dog-run.csv
+++ b/results/dreamerv3/dog-run.csv
@@ -0,0 +1,155 @@
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--- a/results/dreamerv3/dog-stand.csv
+++ b/results/dreamerv3/dog-stand.csv
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--- a/results/dreamerv3/dog-trot.csv
+++ b/results/dreamerv3/dog-trot.csv
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--- a/results/dreamerv3/dog-walk.csv
+++ b/results/dreamerv3/dog-walk.csv
@@ -0,0 +1,148 @@
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--- a/results/dreamerv3/finger-spin.csv
+++ b/results/dreamerv3/finger-spin.csv
@@ -0,0 +1,119 @@
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--- a/results/dreamerv3/finger-turn-easy.csv
+++ b/results/dreamerv3/finger-turn-easy.csv
@@ -0,0 +1,116 @@
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--- a/results/dreamerv3/finger-turn-hard.csv
+++ b/results/dreamerv3/finger-turn-hard.csv
@@ -0,0 +1,118 @@
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--- a/results/dreamerv3/fish-swim.csv
+++ b/results/dreamerv3/fish-swim.csv
@@ -0,0 +1,117 @@
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--- a/results/dreamerv3/hopper-hop-backwards.csv
+++ b/results/dreamerv3/hopper-hop-backwards.csv
@@ -0,0 +1,114 @@
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--- a/results/dreamerv3/hopper-hop.csv
+++ b/results/dreamerv3/hopper-hop.csv
@@ -0,0 +1,116 @@
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--- a/results/dreamerv3/hopper-stand.csv
+++ b/results/dreamerv3/hopper-stand.csv
@@ -0,0 +1,114 @@
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--- a/results/dreamerv3/humanoid-run.csv
+++ b/results/dreamerv3/humanoid-run.csv
@@ -0,0 +1,149 @@
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--- a/results/dreamerv3/humanoid-stand.csv
+++ b/results/dreamerv3/humanoid-stand.csv
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--- a/results/dreamerv3/humanoid-walk.csv
+++ b/results/dreamerv3/humanoid-walk.csv
@@ -0,0 +1,162 @@
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--- a/results/dreamerv3/lift-cube.csv
+++ b/results/dreamerv3/lift-cube.csv
@@ -0,0 +1,114 @@
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--- a/results/dreamerv3/mw-assembly.csv
+++ b/results/dreamerv3/mw-assembly.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-basketball.csv
+++ b/results/dreamerv3/mw-basketball.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-bin-picking.csv
+++ b/results/dreamerv3/mw-bin-picking.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-box-close.csv
+++ b/results/dreamerv3/mw-box-close.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-button-press-topdown-wall.csv
+++ b/results/dreamerv3/mw-button-press-topdown-wall.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-button-press-topdown.csv
+++ b/results/dreamerv3/mw-button-press-topdown.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-button-press-wall.csv
+++ b/results/dreamerv3/mw-button-press-wall.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-button-press.csv
+++ b/results/dreamerv3/mw-button-press.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-coffee-button.csv
+++ b/results/dreamerv3/mw-coffee-button.csv
@@ -0,0 +1,61 @@
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--- a/results/dreamerv3/mw-coffee-pull.csv
+++ b/results/dreamerv3/mw-coffee-pull.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-coffee-push.csv
+++ b/results/dreamerv3/mw-coffee-push.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-dial-turn.csv
+++ b/results/dreamerv3/mw-dial-turn.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-disassemble.csv
+++ b/results/dreamerv3/mw-disassemble.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-door-close.csv
+++ b/results/dreamerv3/mw-door-close.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-door-lock.csv
+++ b/results/dreamerv3/mw-door-lock.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-door-open.csv
+++ b/results/dreamerv3/mw-door-open.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-door-unlock.csv
+++ b/results/dreamerv3/mw-door-unlock.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-drawer-close.csv
+++ b/results/dreamerv3/mw-drawer-close.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-drawer-open.csv
+++ b/results/dreamerv3/mw-drawer-open.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-faucet-close.csv
+++ b/results/dreamerv3/mw-faucet-close.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-faucet-open.csv
+++ b/results/dreamerv3/mw-faucet-open.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-hammer.csv
+++ b/results/dreamerv3/mw-hammer.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-hand-insert.csv
+++ b/results/dreamerv3/mw-hand-insert.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-handle-press-side.csv
+++ b/results/dreamerv3/mw-handle-press-side.csv
@@ -0,0 +1,62 @@
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--- a/results/dreamerv3/mw-handle-press.csv
+++ b/results/dreamerv3/mw-handle-press.csv
@@ -0,0 +1,62 @@
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--- a/results/dreamerv3/mw-handle-pull-side.csv
+++ b/results/dreamerv3/mw-handle-pull-side.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-handle-pull.csv
+++ b/results/dreamerv3/mw-handle-pull.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-lever-pull.csv
+++ b/results/dreamerv3/mw-lever-pull.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-peg-insert-side.csv
+++ b/results/dreamerv3/mw-peg-insert-side.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-peg-unplug-side.csv
+++ b/results/dreamerv3/mw-peg-unplug-side.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-pick-out-of-hole.csv
+++ b/results/dreamerv3/mw-pick-out-of-hole.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-pick-place-wall.csv
+++ b/results/dreamerv3/mw-pick-place-wall.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-pick-place.csv
+++ b/results/dreamerv3/mw-pick-place.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-plate-slide-back-side.csv
+++ b/results/dreamerv3/mw-plate-slide-back-side.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-plate-slide-back.csv
+++ b/results/dreamerv3/mw-plate-slide-back.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-plate-slide-side.csv
+++ b/results/dreamerv3/mw-plate-slide-side.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-plate-slide.csv
+++ b/results/dreamerv3/mw-plate-slide.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-push-back.csv
+++ b/results/dreamerv3/mw-push-back.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-push-wall.csv
+++ b/results/dreamerv3/mw-push-wall.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-push.csv
+++ b/results/dreamerv3/mw-push.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-reach-wall.csv
+++ b/results/dreamerv3/mw-reach-wall.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-reach.csv
+++ b/results/dreamerv3/mw-reach.csv
@@ -0,0 +1,47 @@
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--- a/results/dreamerv3/mw-shelf-place.csv
+++ b/results/dreamerv3/mw-shelf-place.csv
@@ -0,0 +1,47 @@
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--- a/results/dreamerv3/mw-soccer.csv
+++ b/results/dreamerv3/mw-soccer.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-stick-pull.csv
+++ b/results/dreamerv3/mw-stick-pull.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-stick-push.csv
+++ b/results/dreamerv3/mw-stick-push.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-sweep-into.csv
+++ b/results/dreamerv3/mw-sweep-into.csv
@@ -0,0 +1,63 @@
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--- a/results/dreamerv3/mw-sweep.csv
+++ b/results/dreamerv3/mw-sweep.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/mw-window-close.csv
+++ b/results/dreamerv3/mw-window-close.csv
@@ -0,0 +1,64 @@
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--- a/results/dreamerv3/myo-hand-key-turn-hard.csv
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--- a/results/dreamerv3/myo-hand-key-turn.csv
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--- a/results/dreamerv3/myo-hand-obj-hold-hard.csv
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--- a/results/dreamerv3/myo-hand-obj-hold.csv
+++ b/results/dreamerv3/myo-hand-obj-hold.csv
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--- a/results/dreamerv3/myo-hand-pen-twirl-hard.csv
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--- a/results/dreamerv3/myo-hand-pen-twirl.csv
+++ b/results/dreamerv3/myo-hand-pen-twirl.csv
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--- a/results/dreamerv3/myo-hand-reach-hard.csv
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--- a/results/dreamerv3/myo-hand-reach.csv
+++ b/results/dreamerv3/myo-hand-reach.csv
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--- a/results/dreamerv3/pendulum-spin.csv
+++ b/results/dreamerv3/pendulum-spin.csv
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--- a/results/dreamerv3/pendulum-swingup.csv
+++ b/results/dreamerv3/pendulum-swingup.csv
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--- a/results/dreamerv3/pick-cube.csv
+++ b/results/dreamerv3/pick-cube.csv
@@ -0,0 +1,115 @@
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--- a/results/dreamerv3/pick-ycb.csv
+++ b/results/dreamerv3/pick-ycb.csv
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--- a/results/dreamerv3/quadruped-run.csv
+++ b/results/dreamerv3/quadruped-run.csv
@@ -0,0 +1,116 @@
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--- a/results/dreamerv3/quadruped-walk.csv
+++ b/results/dreamerv3/quadruped-walk.csv
@@ -0,0 +1,117 @@
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--- a/results/dreamerv3/reacher-easy.csv
+++ b/results/dreamerv3/reacher-easy.csv
@@ -0,0 +1,113 @@
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--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Sue Hyun Park	8bbc14ebab	Fix: handle _action_masks buffer in single-task scenarios (#67 )	2025-05-19 20:12:12 -07:00
Nicklas Hansen	7992fa193e	update readme + dockerfile	2025-05-13 14:51:16 -07:00
Nicklas Hansen	7ec6bc83a8	only instantiate termination pred head if episodic=true	2025-05-02 16:51:24 -07:00
Nicklas Hansen	38b31a5d72	only instantiate termination pred head if episodic=true	2025-05-02 16:24:02 -07:00
Nicklas Hansen	7942e9082b	update readme + clean up	2025-04-15 16:32:15 -07:00
Nicklas Hansen	eece80123d	full support for episodic rl	2025-04-15 15:55:05 -07:00
Nicklas Hansen	38f853efc4	clean up	2025-04-15 10:16:02 -07:00
Nicklas Hansen	62be41ab58	experimental changes to termination prediction	2025-04-10 00:32:13 -07:00
Nicklas Hansen	c95b755655	add walker2d	2025-04-09 15:55:57 -07:00
Nicklas Hansen	81eb17068e	QoL improvements to termination signal debugging	2025-04-08 19:15:31 -07:00
Nicklas Hansen	add30b5a74	merge main into branch + fix termination in td-targets	2025-04-08 12:40:10 -07:00
Nicklas Hansen	0a914570dc	fix multitask model api conversion	2025-02-27 16:25:21 -08:00
Nicklas Hansen	55bde9745f	update torchrl version	2025-02-05 16:46:34 -08:00
Nicklas Hansen	5ced6dfeb4	auto-convert old checkpoints to new format	2025-02-05 16:26:19 -08:00
Nicklas Hansen	dddc226d25	partial fix to loading checkpoints	2025-01-21 00:10:53 -08:00
Vincent Moens	ae4238946f	Conversion tools for state-dicts (#55 ) * init * init * amend	2025-01-20 15:49:36 -08:00
Nicklas Hansen	a19f91c0b5	enable torch.compile for offline rl + rgb inputs	2024-12-25 12:22:39 -08:00
Nicklas Hansen	e452ca7539	factor pi outputs	2024-12-25 12:08:07 -08:00
Nicklas Hansen	db1865334e	refactor pi outputs	2024-12-25 12:02:33 -08:00
Nicklas Hansen	804f9b3949	refactor pi outputs	2024-12-24 03:05:00 -08:00
Nicklas Hansen	66f8c21f58	cache buffer values in offline training	2024-12-19 09:40:04 -08:00
Nicklas Hansen	9cac7c5775	faster offline data loading	2024-12-19 06:52:31 -08:00
Nicklas Hansen	df8a465c8e	update offline trainer to use new torch.load api	2024-12-10 16:30:05 -08:00
Nicklas Hansen	2e27fbb6f4	partial fix for loading old checkpoints	2024-12-10 16:04:27 -08:00
Nicklas Hansen	6117bc427d	simplify dmcontrol wrappers + upgrade to gymnasium==0.29.1	2024-12-10 15:16:34 -08:00
Nicklas Hansen	32fc2bdf93	refactor policy	2024-12-03 12:22:02 -08:00
Nicklas Hansen	0a79c8bd38	update Dockerfile + environment.yaml	2024-11-28 11:35:15 -08:00
Nicklas Hansen	1bfbcb7794	Merge pull request #49 from nicklashansen/speedups Speedups	2024-11-10 12:33:32 -08:00
Nicklas Hansen	0c3fcc4619	update readme	2024-11-10 12:32:57 -08:00
Nicklas Hansen	fb07cdac3f	update compile print	2024-11-10 12:27:24 -08:00
Nicklas Hansen	c694d286f0	add assertion for compile=true compatibility	2024-11-10 12:25:43 -08:00
Nicklas Hansen	1a77207646	support newest version of myosuite	2024-11-04 15:15:40 -08:00
Nicklas Hansen	b7725e74a5	move cfg conversion to parser.py	2024-10-31 14:52:59 -07:00
Nicklas Hansen	d477619f8d	Merge branch 'speedups' of github.com:nicklashansen/tdmpc2 into speedups	2024-10-27 14:24:39 -07:00
Nicklas Hansen	c1dd0c0338	minor QoL improvements in offline pipeline	2024-10-27 14:24:19 -07:00
Nicklas Hansen	c0d3faac77	Merge pull request #48 from vmoens/patch-1 Use torch.compiler.cudagraph_mark_step_begin() in eval	2024-10-27 14:22:51 -07:00
Vincent Moens	3b5f67592c	Update offline_trainer.py	2024-10-26 00:33:27 +01:00
Vincent Moens	fad0d1be03	Use torch.compiler.cudagraph_mark_step_begin() in eval	2024-10-26 00:32:16 +01:00
Nicklas Hansen	836547d76f	fix eval index + clean up	2024-10-21 14:49:21 -07:00
Nicklas Hansen	970792e2b6	clean up prints	2024-10-18 15:31:25 -07:00
Nicklas Hansen	c3a912e10d	Merge pull request #46 from vmoens/cudagraphs [WIP,Feature] Add cudagraphs and compile option	2024-10-18 09:35:33 -07:00
Nicklas Hansen	38eb46df04	Merge branch 'cudagraphs' of https://github.com/vmoens/tdmpc2 into cudagraphs	2024-10-17 14:57:32 -07:00
vmoens	8b731819a6	merged commits	2024-10-08 10:24:02 -07:00
Nicklas Hansen	a7890b6985	add more results	2024-10-06 21:11:38 -07:00
vmoens	603b67ce66	merged commits	2024-10-03 16:09:48 +01:00
Nicklas Hansen	88095e7899	add more results	2024-08-30 11:28:02 -07:00
Nicklas Hansen	3789fcd5b8	update pinned torchrl version	2024-07-02 10:12:06 -07:00
Nicklas Hansen	d51feb0e9f	Update README.md	2024-07-02 10:12:06 -07:00
Nicklas Hansen	2dc668ecaf	reduce # wandb calls	2024-07-02 10:12:06 -07:00
Nicklas Hansen	39be86fc52	update dockerfile	2024-07-02 10:12:06 -07:00
Nicklas Hansen	f0af4b6b27	update dockerfile + pin all versions	2024-07-02 10:12:06 -07:00
Nicklas Hansen	a2d9d0c8ff	minor fix in print	2024-07-02 10:12:06 -07:00
Nicklas Hansen	ab43880945	migrate to slicebuffer from torchrl-nightly	2024-07-02 10:12:06 -07:00
Nicklas Hansen	5f6fadec0f	update pinned torchrl version	2024-03-27 12:51:40 -07:00
Nicklas Hansen	57158282b4	Merge branch 'main' of github.com:nicklashansen/tdmpc2 into main	2024-02-02 15:56:56 -08:00
Nicklas Hansen	718966c28d	reduce # wandb calls	2024-02-02 15:56:54 -08:00
Nicklas Hansen	01cdf0f799	Update README.md	2024-01-24 21:43:20 -08:00
Nicklas Hansen	02b18a48b1	update dockerfile	2024-01-22 17:37:31 -08:00
Nicklas Hansen	e8f1ed6785	update dockerfile + pin all versions	2024-01-21 21:21:44 -08:00
Nicklas Hansen	8b6fe61bed	minor fix in print	2024-01-11 18:19:08 -08:00
Nicklas Hansen	aa9c6f33f5	migrate to slicebuffer from torchrl-nightly	2024-01-10 19:53:30 -08:00
Nicklas Hansen	ff02f41e73	fix	2024-01-08 17:18:22 -08:00
Nicklas Hansen	e86c343a67	Merge branch 'episodic-rl' of github.com:nicklashansen/tdmpc2 into episodic-rl	2024-01-08 10:55:10 -08:00
Nicklas Hansen	cc62c4c9ce	init	2024-01-08 10:51:27 -08:00
Nicklas Hansen	fabf01a5ec	solves episodic variant of cartpole-balance-sparse	2024-01-07 19:28:41 -08:00
Nicklas Hansen	26c72119cd	init	2024-01-07 18:16:33 -08:00
				`@@ -0,0 +1 @@`
				`for i in {0..3}; do wget https://huggingface.co/datasets/nicklashansen/tdmpc2/resolve/main/mt30/chunk_${i}.pt?download=true && mv chunk_${i}.pt'?download=true' chunk_${i}.pt; done`
				`@@ -0,0 +1 @@`
				`for i in {0..19}; do wget https://huggingface.co/datasets/nicklashansen/tdmpc2/resolve/main/mt80/chunk_${i}.pt?download=true && mv chunk_${i}.pt'?download=true' chunk_${i}.pt; done`