Open HarukiOgawa1 opened 1 month ago
HarukiOgawa1
commented
1 month ago 参考に従って環境のCUDA versionは以下である．
gymuser@HayashibaraLab-ML3:/gymworkspace/IsaacGymEnvs/isaacgymenvs$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Sun_Aug_15_21:14:11_PDT_2021
Cuda compilation tools, release 11.4, V11.4.120
Build cuda_11.4.r11.4/compiler.30300941_0以下は /gymworkspace/IsaacGymEnvs/isaacgymnvs$ python3 train.py task=Ant を実行したら出てきたターミナル画面（長いです）．
gymuser@HayashibaraLab-ML3:/gymworkspace/IsaacGymEnvs/isaacgymenvs$ python3 train.py task=Ant
/home/gymuser/.local/lib/python3.8/site-packages/hydra/_internal/hydra.py:119: UserWarning: Future Hydra versions will no longer change working directory at job runtime by default.
See https://hydra.cc/docs/1.2/upgrades/1.1_to_1.2/changes_to_job_working_dir/ for more information.
ret = run_job(
Importing module 'gym_38' (/gymworkspace/isaacgym/python/isaacgym/_bindings/linux-x86_64/gym_38.so)
Setting GYM_USD_PLUG_INFO_PATH to /gymworkspace/isaacgym/python/isaacgym/_bindings/linux-x86_64/usd/plugInfo.json
PyTorch version 1.10.0a0+3fd9dcf
Device count 2
/gymworkspace/isaacgym/python/isaacgym/_bindings/src/gymtorch
Using /home/gymuser/.cache/torch_extensions/py38_cu114 as PyTorch extensions root...
Emitting ninja build file /home/gymuser/.cache/torch_extensions/py38_cu114/gymtorch/build.ninja...
Building extension module gymtorch...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
ninja: no work to do.
Loading extension module gymtorch...
2024-05-26 12:31:35,152 - INFO - logger - logger initialized
/gymworkspace/IsaacGymEnvs/isaacgymenvs/tasks/amp/poselib/poselib/core/rotation3d.py:222: DeprecationWarning: invalid escape sequence \*
"""
Error: FBX library failed to load - importing FBX data will not succeed. Message: No module named 'fbx'
FBX tools must be installed from https://help.autodesk.com/view/FBX/2020/ENU/?guid=FBX_Developer_Help_scripting_with_python_fbx_installing_python_fbx_html
/gymworkspace/isaacgym/python/isaacgym/torch_utils.py:135: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
def get_axis_params(value, axis_idx, x_value=0., dtype=np.float, n_dims=3):
/home/gymuser/.local/lib/python3.8/site-packages/networkx/classes/graph.py:23: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
from collections import Mapping
/home/gymuser/.local/lib/python3.8/site-packages/networkx/classes/reportviews.py:95: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
from collections import Mapping, Set, Iterable
/home/gymuser/.local/lib/python3.8/site-packages/networkx/readwrite/graphml.py:346: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
(np.int, "int"), (np.int8, "int"),
task:
name: Ant
physics_engine: physx
env:
numEnvs: 4096
envSpacing: 5
episodeLength: 1000
enableDebugVis: False
clipActions: 1.0
powerScale: 1.0
controlFrequencyInv: 1
headingWeight: 0.5
upWeight: 0.1
actionsCost: 0.005
energyCost: 0.05
dofVelocityScale: 0.2
contactForceScale: 0.1
jointsAtLimitCost: 0.1
deathCost: -2.0
terminationHeight: 0.31
plane:
staticFriction: 1.0
dynamicFriction: 1.0
restitution: 0.0
asset:
assetFileName: mjcf/nv_ant.xml
enableCameraSensors: False
sim:
dt: 0.0166
substeps: 2
up_axis: z
use_gpu_pipeline: True
gravity: [0.0, 0.0, -9.81]
physx:
num_threads: 4
solver_type: 1
use_gpu: True
num_position_iterations: 4
num_velocity_iterations: 0
contact_offset: 0.02
rest_offset: 0.0
bounce_threshold_velocity: 0.2
max_depenetration_velocity: 10.0
default_buffer_size_multiplier: 5.0
max_gpu_contact_pairs: 8388608
num_subscenes: 4
contact_collection: 0
task:
randomize: False
randomization_params:
frequency: 600
observations:
range: [0, 0.002]
operation: additive
distribution: gaussian
actions:
range: [0.0, 0.02]
operation: additive
distribution: gaussian
actor_params:
ant:
color: True
rigid_body_properties:
mass:
range: [0.5, 1.5]
operation: scaling
distribution: uniform
setup_only: True
dof_properties:
damping:
range: [0.5, 1.5]
operation: scaling
distribution: uniform
stiffness:
range: [0.5, 1.5]
operation: scaling
distribution: uniform
lower:
range: [0, 0.01]
operation: additive
distribution: gaussian
upper:
range: [0, 0.01]
operation: additive
distribution: gaussian
train:
params:
seed: 42
algo:
name: a2c_continuous
model:
name: continuous_a2c_logstd
network:
name: actor_critic
separate: False
space:
continuous:
mu_activation: None
sigma_activation: None
mu_init:
name: default
sigma_init:
name: const_initializer
val: 0
fixed_sigma: True
mlp:
units: [256, 128, 64]
activation: elu
d2rl: False
initializer:
name: default
regularizer:
name: None
load_checkpoint: False
load_path:
config:
name: Ant
full_experiment_name: Ant
env_name: rlgpu
multi_gpu: False
ppo: True
mixed_precision: True
normalize_input: True
normalize_value: True
value_bootstrap: True
num_actors: 4096
reward_shaper:
scale_value: 0.01
normalize_advantage: True
gamma: 0.99
tau: 0.95
learning_rate: 0.0003
lr_schedule: adaptive
schedule_type: legacy
kl_threshold: 0.008
score_to_win: 20000
max_epochs: 500
save_best_after: 200
save_frequency: 50
grad_norm: 1.0
entropy_coef: 0.0
truncate_grads: False
e_clip: 0.2
horizon_length: 16
minibatch_size: 32768
mini_epochs: 4
critic_coef: 2
clip_value: True
seq_len: 4
bounds_loss_coef: 0.0001
pbt:
enabled: False
task_name: Ant
experiment:
num_envs:
seed: 42
torch_deterministic: False
max_iterations:
physics_engine: physx
pipeline: gpu
sim_device: cuda:0
rl_device: cuda:0
graphics_device_id: 0
num_threads: 4
solver_type: 1
num_subscenes: 4
test: False
checkpoint:
sigma:
multi_gpu: False
wandb_activate: False
wandb_group:
wandb_name: Ant
wandb_entity:
wandb_project: isaacgymenvs
wandb_tags: []
wandb_logcode_dir:
capture_video: False
capture_video_freq: 1464
capture_video_len: 100
force_render: True
headless: False
Setting seed: 42
Using rl_device: cuda:0
Using sim_device: cuda:0
{'name': 'Ant', 'full_experiment_name': None, 'env_name': 'rlgpu', 'multi_gpu': False, 'ppo': True, 'mixed_precision': True, 'normalize_input': True, 'normalize_value': True, 'value_bootstrap': True, 'num_actors': 4096, 'reward_shaper': {'scale_value': 0.01}, 'normalize_advantage': True, 'gamma': 0.99, 'tau': 0.95, 'learning_rate': 0.0003, 'lr_schedule': 'adaptive', 'schedule_type': 'legacy', 'kl_threshold': 0.008, 'score_to_win': 20000, 'max_epochs': 500, 'save_best_after': 200, 'save_frequency': 50, 'grad_norm': 1.0, 'entropy_coef': 0.0, 'truncate_grads': False, 'e_clip': 0.2, 'horizon_length': 16, 'minibatch_size': 32768, 'mini_epochs': 4, 'critic_coef': 2, 'clip_value': True, 'seq_len': 4, 'bounds_loss_coef': 0.0001, 'device': 'cuda:0', 'population_based_training': False, 'pbt_idx': None}
self.seed = 42
Error executing job with overrides: ['task=Ant']
Traceback (most recent call last):
File "train.py", line 206, in launch_rlg_hydra
os.makedirs(experiment_dir, exist_ok=True)
File "/opt/conda/lib/python3.8/os.py", line 223, in makedirs
mkdir(name, mode)
PermissionError: [Errno 13] Permission denied: 'runs/Ant_26-12-31-35'
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
gymuser@HayashibaraLab-ML3:/gymworkspace/IsaacGymEnvs/isaacgymenvs$
DockerでIsaac Gymを環境構築する記録（メモ） 実行環境
以下を参考に行う． https://valinux.hatenablog.com/entry/20240111