File size: 6,049 Bytes
5405dcd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 |
diff --git a/data/envs/metaworld/generate_dataset.py b/data/envs/metaworld/generate_dataset.py
index dc51b4f..ed99a4a 100644
--- a/data/envs/metaworld/generate_dataset.py
+++ b/data/envs/metaworld/generate_dataset.py
@@ -4,7 +4,9 @@ from typing import Dict, Optional
import gym
import metaworld
import numpy as np
+import pandas as pd
import torch
+from datasets import Dataset
from huggingface_hub import HfApi, repocard, upload_folder
from sample_factory.algo.learning.learner import Learner
from sample_factory.algo.sampling.batched_sampling import preprocess_actions
@@ -12,11 +14,7 @@ from sample_factory.algo.utils.action_distributions import argmax_actions
from sample_factory.algo.utils.env_info import extract_env_info
from sample_factory.algo.utils.make_env import make_env_func_batched
from sample_factory.algo.utils.rl_utils import make_dones, prepare_and_normalize_obs
-from sample_factory.cfg.arguments import (
- load_from_checkpoint,
- parse_full_cfg,
- parse_sf_args,
-)
+from sample_factory.cfg.arguments import load_from_checkpoint, parse_full_cfg, parse_sf_args
from sample_factory.envs.env_utils import register_env
from sample_factory.model.actor_critic import create_actor_critic
from sample_factory.model.model_utils import get_rnn_size
@@ -165,10 +163,8 @@ def create_dataset(cfg: Config):
# Create dataset
dataset_size = 100_000
dataset = {
- "observations": np.zeros(
- (dataset_size, *env.observation_space["obs"].shape), dtype=env.observation_space["obs"].dtype
- ),
- "actions": np.zeros((dataset_size, *env.action_space.shape), env.action_space.dtype),
+ "observations": np.zeros((dataset_size, *env.observation_space["obs"].shape), dtype=np.float32),
+ "actions": np.zeros((dataset_size, *env.action_space.shape), np.float32),
"dones": np.zeros((dataset_size,), bool),
"rewards": np.zeros((dataset_size,), np.float32),
}
@@ -206,6 +202,13 @@ def create_dataset(cfg: Config):
env.close()
+ # Convert dict of numpy array to pandas dataframe
+# dataset = Dataset.from_dict(dataset)
+# dataset.create_config_id
+ # Set the card of the dataset
+# dataset.card = f""""""
+# dataset.push_to_hub("qgallouedec/prj_gia_dataset_metaworld_assembly_v2_1111_demo")
+
# Save dataset
repo_path = f"{cfg.train_dir}/datasets/{cfg.experiment}"
os.makedirs(repo_path, exist_ok=True)
diff --git a/data/envs/metaworld/generate_dataset_all.sh b/data/envs/metaworld/generate_dataset_all.sh
index 802bf5c..3cc4f97 100755
--- a/data/envs/metaworld/generate_dataset_all.sh
+++ b/data/envs/metaworld/generate_dataset_all.sh
@@ -1,34 +1,6 @@
#!/bin/bash
ENVS=(
- assembly
- basketball
- bin-picking
- box-close
- button-press-topdown
- button-press-topdown-wall
- button-press
- button-press-wall
- coffee-button
- coffee-pull
- coffee-push
- dial-turn
- disassemble
- door-close
- door-lock
- door-open
- door-unlock
- drawer-close
- drawer-open
- faucet-close
- faucet-open
- hammer
- hand-insert
- handle-press-side
- handle-press
- handle-pull-side
- handle-pull
- lever-pull
peg-insert-side
peg-unplug-side
pick-out-of-hole
@@ -40,19 +12,8 @@ ENVS=(
plate-slide
push-back
push
- push-wall
- reach
- reach-wall
- shelf-place
- soccer
- stick-pull
- stick-push
- sweep-into
- sweep
- window-close
- window-open
)
for ENV in "${ENVS[@]}"; do
- python generate_dataset.py --env $ENV-v2 --experiment $ENV-v2 --train_dir=./train_dir
+ python generate_dataset.py --env $ENV-v2 --experiment $ENV-v2 --train_dir=./train_dir
done
diff --git a/data/envs/metaworld/train_all.sh b/data/envs/metaworld/train_all.sh
index dbf328a..1237f2c 100755
--- a/data/envs/metaworld/train_all.sh
+++ b/data/envs/metaworld/train_all.sh
@@ -1,48 +1,48 @@
#!/bin/bash
ENVS=(
- assembly
- basketball
- bin-picking
- box-close
- button-press-topdown
- button-press-topdown-wall
- button-press
- button-press-wall
- coffee-button
- coffee-pull
- coffee-push
- dial-turn
- disassemble
- door-close
- door-lock
- door-open
- door-unlock
- drawer-close
- drawer-open
- faucet-close
- faucet-open
- hammer
- hand-insert
- handle-press-side
- handle-press
- handle-pull-side
- handle-pull
- lever-pull
- peg-insert-side
- peg-unplug-side
- pick-out-of-hole
- pick-place
- pick-place-wall
- plate-slide-back-side
- plate-slide-back
- plate-slide-side
- plate-slide
- push-back
- push
- push-wall
- reach
- reach-wall
+# assembly
+# basketball
+# bin-picking
+# box-close
+# button-press-topdown
+# button-press-topdown-wall
+# button-press
+# button-press-wall
+# coffee-button
+# coffee-pull
+# coffee-push
+# dial-turn
+# disassemble
+# door-close
+# door-lock
+# door-open
+# door-unlock
+# drawer-close
+# drawer-open
+# faucet-close
+# faucet-open
+# hammer
+# hand-insert
+# handle-press-side
+# handle-press
+# handle-pull-side
+# handle-pull
+# lever-pull
+# peg-insert-side
+# peg-unplug-side
+# pick-out-of-hole
+# pick-place
+# pick-place-wall
+# plate-slide-back-side
+# plate-slide-back
+# plate-slide-side
+# plate-slide
+# push-back
+# push
+# push-wall
+# reach
+# reach-wall
shelf-place
soccer
stick-pull
@@ -55,4 +55,5 @@ ENVS=(
for ENV in "${ENVS[@]}"; do
python train.py --env $ENV-v2 --experiment $ENV-v2 --with_wandb True --wandb_user qgallouedec --wandb_project sample_facotry_metaworld
+ python enjoy.py --algo=APPO --env $ENV-v2 --experiment $ENV-v2 --train_dir=./train_dir --max_num_episodes=10 --push_to_hub --hf_repository=qgallouedec/sample-factory-$ENV-v2 --save_video --no_render --enjoy_script=enjoy --train_script=train --load_checkpoint_kind best
done
|