simplify pre-training dataset, use npz
This commit is contained in:
allenzren
parent
447c8dfd02
commit
8ce0aa1485
@ -57,7 +57,7 @@ export DPPO_DATA_DIR=/path/to/data -->
|
||||
<!-- ``` -->
|
||||
|
||||
Pre-training data for all tasks are pre-processed and can be found at [here](https://drive.google.com/drive/folders/1AXZvNQEKOrp0_jk1VLepKh_oHCg_9e3r?usp=drive_link). Pre-training script will download the data (including normalization statistics) automatically to the data directory.
|
||||
<!-- The data path follows `${DPPO_DATA_DIR}/<benchmark>/<task>/train.npz`, e.g., `${DPPO_DATA_DIR}/gym/hopper-medium-v2/train.pkl`. -->
|
||||
<!-- The data path follows `${DPPO_DATA_DIR}/<benchmark>/<task>/train.npz`, e.g., `${DPPO_DATA_DIR}/gym/hopper-medium-v2/train.npz`. -->
|
||||
|
||||
### Run pre-training with data
|
||||
All the configs can be found under `cfg/<env>/pretrain/`. A new WandB project may be created based on `wandb.project` in the config file; set `wandb=null` in the command line to test without WandB logging.
|
||||
@ -159,7 +159,8 @@ To use DDIM fine-tuning, set `denoising_steps=100` in pre-training and set `mode
|
||||
## Adding your own dataset/environment
|
||||
|
||||
### Pre-training data
|
||||
Pre-training script is at [`agent/pretrain/train_diffusion_agent.py`](agent/pretrain/train_diffusion_agent.py). The pre-training dataset [loader](agent/dataset/sequence.py) assumes a pickle file containing a dictionary of `observations`, `actions`, and `traj_length`, where `observations` and `actions` have the shape of num_episode x max_episode_length x obs_dim/act_dim, and `traj_length` is a 1-D array. One pre-processing example can be found at [`script/process_robomimic_dataset.py`](script/process_robomimic_dataset.py).
|
||||
Pre-training script is at [`agent/pretrain/train_diffusion_agent.py`](agent/pretrain/train_diffusion_agent.py). The pre-training dataset [loader](agent/dataset/sequence.py) assumes a npz file containing numpy arrays `states`, `actions`, `images` (if using pixel) and `traj_length`, where `states` and `actions` have the shape of num_total_steps x obs_dim/act_dim, `images` num_total_steps x C (concatenated if multiple images) x H x W, and `traj_length` is a 1-D array for indexing across num_total_steps.
|
||||
<!-- One pre-processing example can be found at [`script/process_robomimic_dataset.py`](script/process_robomimic_dataset.py). -->
|
||||
|
||||
**Note:** The current implementation does not support loading history observations (only using observation at the current timestep). If needed, you can modify [here](agent/dataset/sequence.py#L130-L131).
|
||||
|
||||
|
||||
@ -1,110 +0,0 @@
|
||||
"""
|
||||
Pre-training data loader. Modified from https://github.com/jannerm/diffuser/blob/main/diffuser/datasets/buffer.py
|
||||
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
|
||||
def atleast_2d(x):
|
||||
if isinstance(x, torch.Tensor):
|
||||
while x.dim() < 2:
|
||||
x = x.unsqueeze(-1)
|
||||
return x
|
||||
else:
|
||||
while x.ndim < 2:
|
||||
x = np.expand_dims(x, axis=-1)
|
||||
return x
|
||||
|
||||
|
||||
class StitchedBuffer:
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
sum_of_path_lengths,
|
||||
device="cpu",
|
||||
):
|
||||
self.sum_of_path_lengths = sum_of_path_lengths
|
||||
if device == "cpu":
|
||||
self._dict = {
|
||||
"path_lengths": np.zeros(sum_of_path_lengths, dtype=int),
|
||||
}
|
||||
else:
|
||||
self._dict = {
|
||||
"path_lengths": torch.zeros(sum_of_path_lengths, dtype=int).to(device),
|
||||
}
|
||||
self._count = 0
|
||||
self.sum_of_path_lengths = sum_of_path_lengths
|
||||
self.device = device
|
||||
|
||||
def __repr__(self):
|
||||
return "Fields:\n" + "\n".join(
|
||||
f" {key}: {val.shape}" for key, val in self.items()
|
||||
)
|
||||
|
||||
def __getitem__(self, key):
|
||||
return self._dict[key]
|
||||
|
||||
def __setitem__(self, key, val):
|
||||
self._dict[key] = val
|
||||
self._add_attributes()
|
||||
|
||||
@property
|
||||
def n_episodes(self):
|
||||
return self._count
|
||||
|
||||
@property
|
||||
def n_steps(self):
|
||||
return sum(self["path_lengths"])
|
||||
|
||||
def _add_keys(self, path):
|
||||
if hasattr(self, "keys"):
|
||||
return
|
||||
self.keys = list(path.keys())
|
||||
|
||||
def _add_attributes(self):
|
||||
"""
|
||||
can access fields with `buffer.observations`
|
||||
instead of `buffer['observations']`
|
||||
"""
|
||||
for key, val in self._dict.items():
|
||||
setattr(self, key, val)
|
||||
|
||||
def items(self):
|
||||
return {k: v for k, v in self._dict.items() if k != "path_lengths"}.items()
|
||||
|
||||
def _allocate(self, key, array):
|
||||
assert key not in self._dict
|
||||
dim = array.shape[1:] # skip batch dimension
|
||||
shape = (self.sum_of_path_lengths, *dim)
|
||||
if self.device == "cpu":
|
||||
self._dict[key] = np.zeros(shape, dtype=np.float32)
|
||||
else:
|
||||
self._dict[key] = torch.zeros(shape, dtype=torch.float32).to(self.device)
|
||||
# print(f'[ utils/mujoco ] Allocated {key} with size {shape}')
|
||||
|
||||
def add_path(self, path):
|
||||
path_length = len(path["observations"])
|
||||
# assert path_length <= self.sum_of_path_lengths
|
||||
|
||||
## if first path added, set keys based on contents
|
||||
self._add_keys(path)
|
||||
|
||||
## add tracked keys in path
|
||||
for key in self.keys:
|
||||
array = atleast_2d(path[key])
|
||||
if key not in self._dict:
|
||||
self._allocate(key, array)
|
||||
self._dict[key][self._count : self._count + path_length] = array
|
||||
|
||||
## record path length
|
||||
self._dict["path_lengths"][
|
||||
self._count : self._count + path_length
|
||||
] = path_length
|
||||
|
||||
## increment path counter
|
||||
self._count += path_length
|
||||
|
||||
def finalize(self):
|
||||
self._add_attributes()
|
||||
@ -8,7 +8,6 @@ No normalization is applied here --- we always normalize the data when pre-proce
|
||||
"""
|
||||
|
||||
from collections import namedtuple
|
||||
from tqdm import tqdm
|
||||
import numpy as np
|
||||
import torch
|
||||
import logging
|
||||
@ -17,11 +16,7 @@ import random
|
||||
|
||||
log = logging.getLogger(__name__)
|
||||
|
||||
from .buffer import StitchedBuffer
|
||||
|
||||
|
||||
Batch = namedtuple("Batch", "trajectories conditions")
|
||||
ValueBatch = namedtuple("ValueBatch", "trajectories conditions values")
|
||||
|
||||
|
||||
class StitchedSequenceDataset(torch.utils.data.Dataset):
|
||||
@ -32,7 +27,7 @@ class StitchedSequenceDataset(torch.utils.data.Dataset):
|
||||
(tuple of) dimension of observation, action, images, etc.
|
||||
|
||||
Example:
|
||||
Observations: [----------traj 1----------][---------traj 2----------] ... [---------traj N----------]
|
||||
states: [----------traj 1----------][---------traj 2----------] ... [---------traj N----------]
|
||||
Episode IDs: [---------- 1 ----------][---------- 2 ---------] ... [---------- N ---------]
|
||||
"""
|
||||
|
||||
@ -43,67 +38,56 @@ class StitchedSequenceDataset(torch.utils.data.Dataset):
|
||||
cond_steps=1,
|
||||
max_n_episodes=10000,
|
||||
use_img=False,
|
||||
device="cpu",
|
||||
device="cuda:0",
|
||||
):
|
||||
self.horizon_steps = horizon_steps
|
||||
self.cond_steps = cond_steps
|
||||
self.device = device
|
||||
self.use_img = use_img
|
||||
|
||||
# Load dataset to device specified
|
||||
if dataset_path.endswith(".npz"):
|
||||
dataset = np.load(dataset_path, allow_pickle=True)
|
||||
dataset = np.load(dataset_path, allow_pickle=False) # only np arrays
|
||||
else:
|
||||
with open(dataset_path, "rb") as f:
|
||||
dataset = pickle.load(f)
|
||||
num_episodes = dataset["observations"].shape[0]
|
||||
|
||||
# Get the sum total of the valid trajectories' lengths
|
||||
traj_lengths = dataset["traj_length"]
|
||||
sum_of_path_lengths = np.sum(traj_lengths)
|
||||
self.sum_of_path_lengths = sum_of_path_lengths
|
||||
|
||||
fields = StitchedBuffer(sum_of_path_lengths, device)
|
||||
for i in tqdm(
|
||||
range(min(max_n_episodes, num_episodes)), desc="Loading trajectories"
|
||||
):
|
||||
traj_length = traj_lengths[i]
|
||||
episode = {
|
||||
"observations": dataset["observations"][i][:traj_length],
|
||||
"actions": dataset["actions"][i][:traj_length],
|
||||
"episode_ids": i * np.ones(traj_length),
|
||||
}
|
||||
if use_img:
|
||||
episode["images"] = dataset["images"][i][:traj_length]
|
||||
for key, val in episode.items():
|
||||
if device == "cpu":
|
||||
episode[key] = val
|
||||
else:
|
||||
# if None array, save as empty tensor
|
||||
if np.all(np.equal(episode[key], None)):
|
||||
episode[key] = torch.empty(episode[key].shape).to(device)
|
||||
else:
|
||||
if key == "images":
|
||||
episode[key] = torch.tensor(val, dtype=torch.uint8).to(
|
||||
device
|
||||
)
|
||||
# (, H, W, C) -> (, C, H, W)
|
||||
episode[key] = episode[key].permute(0, 3, 1, 2)
|
||||
else:
|
||||
episode[key] = torch.tensor(val, dtype=torch.float32).to(
|
||||
device
|
||||
)
|
||||
fields.add_path(episode)
|
||||
fields.finalize()
|
||||
traj_lengths = dataset["traj_lengths"] # 1-D array
|
||||
total_num_steps = np.sum(traj_lengths[:max_n_episodes])
|
||||
|
||||
# Set up indices for sampling
|
||||
self.indices = self.make_indices(traj_lengths, horizon_steps)
|
||||
self.obs_dim = fields.observations.shape[-1]
|
||||
self.action_dim = fields.actions.shape[-1]
|
||||
self.fields = fields
|
||||
self.n_episodes = fields.n_episodes
|
||||
self.path_lengths = fields.path_lengths
|
||||
self.traj_lengths = traj_lengths
|
||||
self.use_img = use_img
|
||||
log.info(fields)
|
||||
|
||||
# Extract states and actions up to max_n_episodes
|
||||
self.states = (
|
||||
torch.from_numpy(dataset["states"][:total_num_steps]).float().to(device)
|
||||
) # (total_num_steps, obs_dim)
|
||||
self.actions = (
|
||||
torch.from_numpy(dataset["actions"][:total_num_steps]).float().to(device)
|
||||
) # (total_num_steps, action_dim)
|
||||
log.info(f"Loaded dataset from {dataset_path}")
|
||||
log.info(f"Number of episodes: {min(max_n_episodes, len(traj_lengths))}")
|
||||
log.info(f"States shape/type: {self.states.shape, self.states.dtype}")
|
||||
log.info(f"Actions shape/type: {self.actions.shape, self.actions.dtype}")
|
||||
if self.use_img:
|
||||
self.images = torch.from_numpy(dataset["images"][:total_num_steps]).to(
|
||||
device
|
||||
) # (total_num_steps, C, H, W)
|
||||
log.info(f"Images shape/type: {self.images.shape, self.images.dtype}")
|
||||
|
||||
def __getitem__(self, idx):
|
||||
start = self.indices[idx]
|
||||
end = start + self.horizon_steps
|
||||
states = self.states[start:end]
|
||||
actions = self.actions[start:end]
|
||||
if self.use_img:
|
||||
images = self.images[start:end]
|
||||
conditions = {
|
||||
1 - self.cond_steps: {"state": states[0], "rgb": images[0]}
|
||||
} # TODO: allow obs history, -1, -2, ...
|
||||
else:
|
||||
conditions = {1 - self.cond_steps: states[0]}
|
||||
batch = Batch(actions, conditions)
|
||||
return batch
|
||||
|
||||
def make_indices(self, traj_lengths, horizon_steps):
|
||||
"""
|
||||
@ -119,44 +103,12 @@ class StitchedSequenceDataset(torch.utils.data.Dataset):
|
||||
return indices
|
||||
|
||||
def set_train_val_split(self, train_split):
|
||||
"""Not doing validation right now"""
|
||||
num_train = int(len(self.indices) * train_split)
|
||||
train_indices = random.sample(self.indices, num_train)
|
||||
val_indices = [i for i in range(len(self.indices)) if i not in train_indices]
|
||||
self.indices = train_indices
|
||||
return val_indices
|
||||
|
||||
def set_indices(self, indices):
|
||||
self.indices = indices
|
||||
|
||||
def get_conditions(self, observations, images=None):
|
||||
"""
|
||||
condition on current observation for planning. Take into account the number of conditioning steps.
|
||||
"""
|
||||
if images is not None:
|
||||
return {
|
||||
1 - self.cond_steps: {"state": observations[0], "rgb": images[0]}
|
||||
} # TODO: allow obs history, -1, -2, ...
|
||||
else:
|
||||
return {1 - self.cond_steps: observations[0]}
|
||||
|
||||
def __len__(self):
|
||||
return len(self.indices)
|
||||
|
||||
def __getitem__(self, idx, eps=1e-4):
|
||||
raise NotImplementedError("Get item defined in subclass.")
|
||||
|
||||
|
||||
class StitchedActionSequenceDataset(StitchedSequenceDataset):
|
||||
"""Only use action trajectory, and then obs_cond for current observation"""
|
||||
|
||||
def __getitem__(self, idx):
|
||||
start = self.indices[idx]
|
||||
end = start + self.horizon_steps
|
||||
observations = self.fields.observations[start:end]
|
||||
actions = self.fields.actions[start:end]
|
||||
images = None
|
||||
if self.use_img:
|
||||
images = self.fields.images[start:end]
|
||||
conditions = self.get_conditions(observations, images)
|
||||
batch = Batch(actions, conditions)
|
||||
return batch
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: avoid_m1_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m1/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m1/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -63,7 +63,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: avoid_m1_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m1/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m1/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: avoid_m1_pre_gmm_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m1/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m1/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: avoid_m2_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m2/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m2/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -63,7 +63,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: avoid_m2_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m2/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m2/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: avoid_m2_pre_gmm_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m2/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m2/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: avoid_m3_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m3/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m3/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -63,7 +63,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: avoid_m3_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m3/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m3/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: avoid_m3_pre_gmm_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m3/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m3/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -65,7 +65,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -67,7 +67,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -65,7 +65,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -66,7 +66,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -65,7 +65,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -67,7 +67,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -65,7 +65,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -66,7 +66,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -65,7 +65,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -66,7 +66,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -65,7 +65,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -66,7 +66,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/furniture-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/furniture/${task}_${randomness}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/gym-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/gym/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/gym/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -64,7 +64,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/gym-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/gym/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/gym/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -64,7 +64,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/gym-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/gym/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/gym/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -64,7 +64,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -61,7 +61,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_img_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -82,7 +82,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
use_img: True
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -64,7 +64,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -53,7 +53,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_img_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -74,7 +74,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
use_img: True
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_transformer_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gmm_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gmm_transformer_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -61,7 +61,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_img_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -82,7 +82,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
use_img: True
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -64,7 +64,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -53,7 +53,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_img_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -74,7 +74,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
use_img: True
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_transformer_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gmm_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gmm_transformer_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -62,7 +62,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_img_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -82,7 +82,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
use_img: True
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -64,7 +64,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -53,7 +53,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_img_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -74,7 +74,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
use_img: True
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_transformer_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gmm_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gmm_transformer_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -61,7 +61,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_mlp_img_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -83,7 +83,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
use_img: True
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_diffusion_agent.TrainDiffusionAgent
|
||||
|
||||
name: ${env}_pre_diffusion_unet_ta${horizon_steps}_td${denoising_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -64,7 +64,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -53,7 +53,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_mlp_img_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}-img/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -75,7 +75,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
use_img: True
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gaussian_transformer_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gmm_mlp_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -55,7 +55,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -7,7 +7,7 @@ _target_: agent.pretrain.train_gaussian_agent.TrainGaussianAgent
|
||||
|
||||
name: ${env}_pre_gmm_transformer_ta${horizon_steps}
|
||||
logdir: ${oc.env:DPPO_LOG_DIR}/robomimic-pretrain/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.pkl
|
||||
train_dataset_path: ${oc.env:DPPO_DATA_DIR}/robomimic/${env}/train.npz
|
||||
|
||||
seed: 42
|
||||
device: cuda:0
|
||||
@ -57,7 +57,7 @@ ema:
|
||||
decay: 0.995
|
||||
|
||||
train_dataset:
|
||||
_target_: agent.dataset.sequence.StitchedActionSequenceDataset
|
||||
_target_: agent.dataset.sequence.StitchedSequenceDataset
|
||||
dataset_path: ${train_dataset_path}
|
||||
horizon_steps: ${horizon_steps}
|
||||
cond_steps: ${cond_steps}
|
||||
|
||||
@ -124,6 +124,9 @@ class VisionDiffusionMLP(nn.Module):
|
||||
else:
|
||||
state = cond["state"]
|
||||
|
||||
# convert rgb to float32 for augmentation
|
||||
rgb = rgb.float()
|
||||
|
||||
# get vit output - pass in two images separately
|
||||
if rgb.shape[1] == 6: # TODO: properly handle multiple images
|
||||
rgb1 = rgb[:, :3]
|
||||
|
||||
Loading…
Reference in New Issue
Block a user