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simplify pre-training dataset, use npz

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allenzren
2024-09-08 17:52:16 -04:00
parent 447c8dfd02
commit 8ce0aa1485
66 changed files with 170 additions and 324 deletions
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cfg/furniture/pretrain/lamp_med/pre_diffusion_mlp.yaml
+2 -2
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@@ -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}
cfg/furniture/pretrain/lamp_med/pre_diffusion_unet.yaml
+2 -2
View File
@@ -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}
cfg/furniture/pretrain/lamp_med/pre_gaussian_mlp.yaml
+2 -2
View File
@@ -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}