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Running
on
T4
File size: 1,352 Bytes
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defaults:
- data: base
- eval_data: base
- override hydra/job_logging: custom-simplest
- _self_
hydra:
run:
dir: ./output/${exp_id}
output_subdir: ${now:%Y-%m-%d_%H-%M-%S}-hydra
enable_email: False
model: small_16k
exp_id: default
debug: False
cudnn_benchmark: True
compile: True
amp: True
weights: null
checkpoint: null
seed: 14159265
num_workers: 10 # per-GPU
pin_memory: False # set to True if your system can handle it, i.e., have enough memory
# NOTE: This DOSE NOT affect the model during inference in any way
# they are just for the dataloader to fill in the missing data in multi-modal loading
# to change the sequence length for the model, see networks.py
data_dim:
text_seq_len: 77
clip_dim: 1024
sync_dim: 768
text_dim: 1024
# ema configuration
ema:
enable: True
sigma_rels: [0.05, 0.1]
update_every: 1
checkpoint_every: 5_000
checkpoint_folder: ${hydra:run.dir}/ema_ckpts
default_output_sigma: 0.05
# sampling
sampling:
mean: 0.0
scale: 1.0
min_sigma: 0.0
method: euler
num_steps: 25
# classifier-free guidance
null_condition_probability: 0.1
cfg_strength: 4.5
# checkpoint paths to external modules
vae_16k_ckpt: ./ext_weights/v1-16.pth
vae_44k_ckpt: ./ext_weights/v1-44.pth
bigvgan_vocoder_ckpt: ./ext_weights/best_netG.pt
synchformer_ckpt: ./ext_weights/synchformer_state_dict.pth |