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save_path: saved_standard_challenging_context32_nocond_cont_cont_all_cont
model:
base_learning_rate: 8.0e-05
target: ldm.models.diffusion.ddpm.LatentDiffusion
params:
linear_start: 0.0015
linear_end: 0.0195
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: image
cond_stage_key: action_
scheduler_sampling_rate: 0.0
hybrid_key: c_concat
image_size: [64, 48]
channels: 3
cond_stage_trainable: false
conditioning_key: hybrid
monitor: val/loss_simple_ema
unet_config:
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
params:
image_size: [64, 48]
in_channels: 166
out_channels: 4
model_channels: 192
attention_resolutions:
- 8
- 4
- 2
num_res_blocks: 2
channel_mult:
- 1
- 2
- 3
- 5
num_head_channels: 32
use_spatial_transformer: false
transformer_depth: 1
first_stage_config:
target: ldm.models.autoencoder.AutoencoderKL
params:
embed_dim: 4
monitor: val/rec_loss
ddconfig:
double_z: true
z_channels: 4
resolution: 256
in_channels: 3
out_ch: 3
ch: 128
ch_mult:
- 1
- 2
- 4
- 4
num_res_blocks: 2
attn_resolutions: []
dropout: 0.0
lossconfig:
target: torch.nn.Identity
cond_stage_config: __is_unconditional__
data:
target: data.data_processing.datasets.DataModule
params:
batch_size: 256
num_workers: 16
wrap: false
shuffle: True
drop_last: True
pin_memory: True
prefetch_factor: 2
persistent_workers: True
train:
target: data.data_processing.datasets.ActionsData
params:
data_csv_path: train_dataset/train_dataset.target_frames.csv
normalization: standard
context_length: 32
#validation:
# target: data.data_processing.datasets.ActionsData
# params:
# data_csv_path: train_dataset/train_dataset_14frames_firstframe_allframes.csv
lightning:
trainer:
benchmark: False
max_epochs: 6400
limit_val_batches: 0
accelerator: gpu
gpus: 1
accumulate_grad_batches: 1
gradient_clip_val: 1
checkpoint_callback: True |