From 4a98fcec2ef7bf5710c83405bf2f04b34f226875 Mon Sep 17 00:00:00 2001
From: oscarchaufour <101994223+oscarchaufour@users.noreply.github.com>
Date: Tue, 27 Feb 2024 22:09:45 +0100
Subject: [PATCH] update

---
 .gitignore                   | 134 ++++++
 CartPole-v1.zip              | Bin 0 -> 191974 bytes
 README.md                    |   5 +
 a2c_sb3_cartpole.py          |  82 ++--
 images/reinforce_rewards.png | Bin 36534 -> 52983 bytes
 neural_network_model.zip     | Bin 6368 -> 0 bytes
 reinforce_cartpole.py        |   2 +-
 test.ipynb                   | 769 -----------------------------------
 8 files changed, 189 insertions(+), 803 deletions(-)
 create mode 100644 .gitignore
 create mode 100644 CartPole-v1.zip
 delete mode 100644 neural_network_model.zip
 delete mode 100644 test.ipynb

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..a5a8dfa
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,134 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+runs
+wandb
+models
+
+
+# fichier mac
+.DS_Store
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
diff --git a/CartPole-v1.zip b/CartPole-v1.zip
new file mode 100644
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diff --git a/README.md b/README.md
index 29da3e7..1d483f6 100644
--- a/README.md
+++ b/README.md
@@ -6,3 +6,8 @@ Link to the model on the hub :
 
 # REINFORCE
 Plot showing the total reward accross episodes: ![Alt text](images/reinforce_rewards.png)
+
+# A2C trained model 
+Link to the trained model (available on huggingFace): https://huggingface.co/oscarchaufour/a2c-CartPole-v1
+
+
diff --git a/a2c_sb3_cartpole.py b/a2c_sb3_cartpole.py
index d5090b4..9a1a519 100644
--- a/a2c_sb3_cartpole.py
+++ b/a2c_sb3_cartpole.py
@@ -1,53 +1,69 @@
-import gymnasium as gym
+import gym
 import cv2
 from stable_baselines3 import A2C
 from huggingface_sb3 import package_to_hub, push_to_hub
 from gym import envs
 from gymnasium.envs.registration import register
 from tqdm import tqdm
+import matplotlib.pyplot as plt
+import wandb
+from wandb.integration.sb3 import WandbCallback
+from stable_baselines3.common.vec_env import VecVideoRecorder
+import dill
+import zipfile
 
+# Initialize Weights & Biases
+total_timesteps = 10000
+config = {
+    "policy_type": "MlpPolicy",
+    "total_timesteps": total_timesteps,
+    "env_name": "CartPole-v1",
+}
+wandb.login()
+run = wandb.init(
+    project="a2c-cartpole-v1",
+    config=config,
+    sync_tensorboard=True,  # auto-upload sb3's tensorboard metrics
+    monitor_gym=True,  # auto-upload the videos of agents playing the game
+    save_code=True,  # optional
+)
 env_id = "CartPole-v1"
 
 # Register the environment
 register(id=env_id, entry_point='gym.envs.classic_control:CartPoleEnv', max_episode_steps=500)
 
 env = gym.make(env_id)
+# env = VecVideoRecorder(
+#     env,
+#     f"videos/{run.id}",
+#     record_video_trigger=lambda x: x % 2000 == 0,
+#     video_length=200,
+# )
 
-model = A2C("MlpPolicy", env, verbose=1)
-model.learn(total_timesteps=10_000)
+model = A2C("MlpPolicy", env, verbose=1, tensorboard_log=f"runs/{run.id}")
+model.learn(total_timesteps=total_timesteps, callback=WandbCallback(
+        gradient_save_freq=100,
+        model_save_path=f"models/{run.id}"))
+
+
+# Mark the run as public in W&B project settings
+run.finish()
 
 vec_env = model.get_env()
 obs = vec_env.reset()
+
 for i in tqdm(range(1000)):
     action, _state = model.predict(obs, deterministic=True)
     obs, reward, done, info = vec_env.step(action)
-    vec_env.render("human")
-
-
-####### TO BE DONE #######
-    
-# # Serialize the model and save it to a .zip file
-# import pickle
-# import zipfile
-
-# # Step 1: Serialize the model
-# model_bytes = pickle.dumps(model)
-
-# # Step 2: Create a .zip file containing the serialized model
-# zip_filename = env_id + ".zip"
-# with zipfile.ZipFile(zip_filename, 'w') as zipf:
-#     zipf.writestr("model.pkl", model_bytes)
-
-# # Package and push the model to the Hugging Face Hub
-# model_package_id = package_to_hub(model=model, 
-#                                   model_name="a2c-CartPole-v1",
-#                                   model_architecture="a2c",
-#                                   env_id=env_id,
-#                                   eval_env=env,
-#                                   repo_id="oscarchaufour/a2c-CartPole-v1",
-#                                   commit_message="Initial commit of A2C CartPole model")
-
-# # Push the model package to the Hub
-# push_to_hub(repo_id="oscarchaufour/a2c-CartPole-v1",
-#             filename=model_package_id + ".zip",
-#             commit_message="Added A2C CartPole model")
\ No newline at end of file
+    vec_env.render()
+
+def save_model(model, env_id):
+    # Step 1: Serialize the model
+    model_bytes = dill.dumps(model)
+
+    # Step 2: Create a .zip file containing the serialized model
+    zip_filename = env_id + ".zip"
+    with zipfile.ZipFile(zip_filename, 'w') as zipf:
+        zipf.writestr("model.pkl", model_bytes)
+
+
diff --git a/images/reinforce_rewards.png b/images/reinforce_rewards.png
index e76d632e17aa3bc917cd5e2de89c865baaeb0bcf..ad6ae6f4dcc6382e3da610e49588c4b51e50ccbd 100644
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diff --git a/reinforce_cartpole.py b/reinforce_cartpole.py
index bf5d1bb..ec767d8 100644
--- a/reinforce_cartpole.py
+++ b/reinforce_cartpole.py
@@ -95,7 +95,7 @@ def plot_rewards(episodes_rewards):
 
 if __name__ == "__main__":
     # Create the environment
-    env = gym.make("CartPole-v1")
+    env = gym.make("CartPole-v1", render_mode="human")
 
     # Set up the agent
     policy = Policy(
diff --git a/test.ipynb b/test.ipynb
deleted file mode 100644
index 8a16e65..0000000
--- a/test.ipynb
+++ /dev/null
@@ -1,769 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# TD 1 : Hands-On Reinforcement Learning"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Packages download"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Collecting pytorch\n",
-      "  Downloading pytorch-1.0.2.tar.gz (689 bytes)\n",
-      "  Installing build dependencies: started\n",
-      "  Installing build dependencies: finished with status 'done'\n",
-      "  Getting requirements to build wheel: started\n",
-      "  Getting requirements to build wheel: finished with status 'done'\n",
-      "  Installing backend dependencies: started\n",
-      "  Installing backend dependencies: finished with status 'done'\n",
-      "  Preparing metadata (pyproject.toml): started\n",
-      "  Preparing metadata (pyproject.toml): finished with status 'done'\n",
-      "Building wheels for collected packages: pytorch\n",
-      "  Building wheel for pytorch (pyproject.toml): started\n",
-      "  Building wheel for pytorch (pyproject.toml): finished with status 'error'\n",
-      "Failed to build pytorch\n",
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "  error: subprocess-exited-with-error\n",
-      "  \n",
-      "  × Building wheel for pytorch (pyproject.toml) did not run successfully.\n",
-      "  │ exit code: 1\n",
-      "  ╰─> [20 lines of output]\n",
-      "      Traceback (most recent call last):\n",
-      "        File \"c:\\Users\\oscar\\Documents\\GitHub\\mso_3_4-td1\\.venv\\Lib\\site-packages\\pip\\_vendor\\pyproject_hooks\\_in_process\\_in_process.py\", line 353, in <module>\n",
-      "          main()\n",
-      "        File \"c:\\Users\\oscar\\Documents\\GitHub\\mso_3_4-td1\\.venv\\Lib\\site-packages\\pip\\_vendor\\pyproject_hooks\\_in_process\\_in_process.py\", line 335, in main\n",
-      "          json_out['return_val'] = hook(**hook_input['kwargs'])\n",
-      "                                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "        File \"c:\\Users\\oscar\\Documents\\GitHub\\mso_3_4-td1\\.venv\\Lib\\site-packages\\pip\\_vendor\\pyproject_hooks\\_in_process\\_in_process.py\", line 251, in build_wheel\n",
-      "          return _build_backend().build_wheel(wheel_directory, config_settings,\n",
-      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "        File \"C:\\Users\\oscar\\AppData\\Local\\Temp\\pip-build-env-onf33rce\\overlay\\Lib\\site-packages\\setuptools\\build_meta.py\", line 404, in build_wheel\n",
-      "          return self._build_with_temp_dir(\n",
-      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "        File \"C:\\Users\\oscar\\AppData\\Local\\Temp\\pip-build-env-onf33rce\\overlay\\Lib\\site-packages\\setuptools\\build_meta.py\", line 389, in _build_with_temp_dir\n",
-      "          self.run_setup()\n",
-      "        File \"C:\\Users\\oscar\\AppData\\Local\\Temp\\pip-build-env-onf33rce\\overlay\\Lib\\site-packages\\setuptools\\build_meta.py\", line 480, in run_setup\n",
-      "          super(_BuildMetaLegacyBackend, self).run_setup(setup_script=setup_script)\n",
-      "        File \"C:\\Users\\oscar\\AppData\\Local\\Temp\\pip-build-env-onf33rce\\overlay\\Lib\\site-packages\\setuptools\\build_meta.py\", line 311, in run_setup\n",
-      "          exec(code, locals())\n",
-      "        File \"<string>\", line 15, in <module>\n",
-      "      Exception: You tried to install \"pytorch\". The package named for PyTorch is \"torch\"\n",
-      "      [end of output]\n",
-      "  \n",
-      "  note: This error originates from a subprocess, and is likely not a problem with pip.\n",
-      "  ERROR: Failed building wheel for pytorch\n",
-      "ERROR: Could not build wheels for pytorch, which is required to install pyproject.toml-based projects\n"
-     ]
-    }
-   ],
-   "source": [
-    "pip install pytorch"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Collecting gym==0.26.2Note: you may need to restart the kernel to use updated packages.\n",
-      "\n",
-      "  Downloading gym-0.26.2.tar.gz (721 kB)\n",
-      "     ---------------------------------------- 0.0/721.7 kB ? eta -:--:--\n",
-      "     ---- ---------------------------------- 92.2/721.7 kB 2.6 MB/s eta 0:00:01\n",
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-      "     -------------------------------------- 721.7/721.7 kB 2.7 MB/s eta 0:00:00\n",
-      "  Installing build dependencies: started\n",
-      "  Installing build dependencies: finished with status 'done'\n",
-      "  Getting requirements to build wheel: started\n",
-      "  Getting requirements to build wheel: finished with status 'done'\n",
-      "  Installing backend dependencies: started\n",
-      "  Installing backend dependencies: finished with status 'done'\n",
-      "  Preparing metadata (pyproject.toml): started\n",
-      "  Preparing metadata (pyproject.toml): finished with status 'done'\n",
-      "Collecting numpy>=1.18.0 (from gym==0.26.2)\n",
-      "  Downloading numpy-1.26.4-cp311-cp311-win_amd64.whl.metadata (61 kB)\n",
-      "     ---------------------------------------- 0.0/61.0 kB ? eta -:--:--\n",
-      "     --------------------------------- ------ 51.2/61.0 kB 1.3 MB/s eta 0:00:01\n",
-      "     ---------------------------------------- 61.0/61.0 kB 1.1 MB/s eta 0:00:00\n",
-      "Collecting cloudpickle>=1.2.0 (from gym==0.26.2)\n",
-      "  Downloading cloudpickle-3.0.0-py3-none-any.whl.metadata (7.0 kB)\n",
-      "Collecting gym-notices>=0.0.4 (from gym==0.26.2)\n",
-      "  Downloading gym_notices-0.0.8-py3-none-any.whl (3.0 kB)\n",
-      "Downloading cloudpickle-3.0.0-py3-none-any.whl (20 kB)\n",
-      "Downloading numpy-1.26.4-cp311-cp311-win_amd64.whl (15.8 MB)\n",
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-      "Building wheels for collected packages: gym\n",
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-      "  Building wheel for gym (pyproject.toml): finished with status 'done'\n",
-      "  Created wheel for gym: filename=gym-0.26.2-py3-none-any.whl size=827629 sha256=73a686c8633b88e54b0477d643a4d44b9c28378813129811ee402183300c3525\n",
-      "  Stored in directory: c:\\users\\oscar\\appdata\\local\\pip\\cache\\wheels\\1c\\77\\9e\\9af5470201a0b0543937933ee99ba884cd237d2faefe8f4d37\n",
-      "Successfully built gym\n",
-      "Installing collected packages: gym-notices, numpy, cloudpickle, gym\n",
-      "Successfully installed cloudpickle-3.0.0 gym-0.26.2 gym-notices-0.0.8 numpy-1.26.4\n"
-     ]
-    }
-   ],
-   "source": [
-    "pip install gym==0.26.2"
-   ]
-  },
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-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Collecting pyglet==2.0.10\n",
-      "  Downloading pyglet-2.0.10-py3-none-any.whl.metadata (8.5 kB)\n",
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-      "Installing collected packages: pyglet\n",
-      "Successfully installed pyglet-2.0.10\n",
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
-   "source": [
-    "pip install pyglet==2.0.10"
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-  },
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-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
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-     "output_type": "stream",
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-      "Installing collected packages: pygame\n",
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-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
-   "source": [
-    "pip install pygame==2.5.2"
-   ]
-  },
-  {
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-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
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-      "Collecting PyQt5Note: you may need to restart the kernel to use updated packages.\n",
-      "\n",
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-      "Installing collected packages: PyQt5-Qt5, PyQt5-sip, PyQt5\n",
-      "Successfully installed PyQt5-5.15.10 PyQt5-Qt5-5.15.2 PyQt5-sip-12.13.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "pip install PyQt5"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Usage"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import gym\n",
-    "import time\n",
-    "\n",
-    "# Create the environment\n",
-    "env = gym.make(\"CartPole-v1\", render_mode=\"human\")\n",
-    "\n",
-    "# Reset the environment and get the initial observation\n",
-    "observation = env.reset()\n",
-    "\n",
-    "for _ in range(1000):\n",
-    "    # Select a random action from the action space\n",
-    "    action = env.action_space.sample()\n",
-    "    # Apply the action to the environment\n",
-    "    # Returns next observation, reward, done signal (indicating\n",
-    "    # if the episode has ended), and an additional info dictionary\n",
-    "    observation, reward, terminated, truncated, info = env.step(action)\n",
-    "    # Render the environment to visualize the agent's behavior\n",
-    "    env.render()\n",
-    "    if terminated: \n",
-    "        # Terminated before max step\n",
-    "        break\n",
-    "    time.sleep(0.2) # Sleep added to slow down the visualization\n",
-    "\n",
-    "env.close()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Upload model to Hugging Face hub"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'model' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[8], line 3\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mhuggingface_sb3\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m package_to_hub, push_to_hub\n\u001b[1;32m----> 3\u001b[0m package_to_hub(model\u001b[38;5;241m=\u001b[39m\u001b[43mmodel\u001b[49m, \n\u001b[0;32m      4\u001b[0m                 model_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma2c-CartPole-v1\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m      5\u001b[0m                 model_architecture\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma2c\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m      6\u001b[0m                 env_id\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCartPole-v1\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m      7\u001b[0m                 eval_env\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m      8\u001b[0m                 repo_id\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moscarchaufour/a2c-CartPole-v1\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m      9\u001b[0m                 commit_message\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTest commit\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m     11\u001b[0m push_to_hub(repo_id\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moscarchaufour/a2c-CartPole-v1\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     12\u001b[0m             filename\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma2c_sb3_cartpole.zip\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     13\u001b[0m             commit_message\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAdded A2C CartPole model\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
-      "\u001b[1;31mNameError\u001b[0m: name 'model' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "from huggingface_sb3 import package_to_hub, push_to_hub\n",
-    "\n",
-    "package_to_hub(model=model, \n",
-    "                model_name=\"a2c-CartPole-v1\",\n",
-    "                model_architecture=\"a2c\",\n",
-    "                env_id=\"CartPole-v1\",\n",
-    "                eval_env=None,\n",
-    "                repo_id=\"oscarchaufour/a2c-CartPole-v1\",\n",
-    "                commit_message=\"Test commit\")\n",
-    "    \n",
-    "push_to_hub(repo_id=\"oscarchaufour/a2c-CartPole-v1\",\n",
-    "            filename=\"a2c_sb3_cartpole.zip\",\n",
-    "            commit_message=\"Added A2C CartPole model\")\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": ".venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
-- 
GitLab