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metadata_root: "./data/dataset/metadata/dataset_root.json"
log_directory: "./log/latent_diffusion"
project: "audioldm"
precision: "high"
variables:
sampling_rate: &sampling_rate 16000
mel_bins: &mel_bins 64
latent_embed_dim: &latent_embed_dim 8
latent_t_size: &latent_t_size 256 # TODO might need to change
latent_f_size: &latent_f_size 16
in_channels: &unet_in_channels 8
optimize_ddpm_parameter: &optimize_ddpm_parameter true
optimize_gpt: &optimize_gpt true
warmup_steps: &warmup_steps 2000
data:
train: ["audiocaps"]
val: "audiocaps"
test: "audiocaps"
class_label_indices: "audioset_eval_subset"
dataloader_add_ons: ["waveform_rs_48k"]
step:
validation_every_n_epochs: 15
save_checkpoint_every_n_steps: 5000
# limit_val_batches: 2
max_steps: 800000
save_top_k: 1
preprocessing:
audio:
sampling_rate: *sampling_rate
max_wav_value: 32768.0
duration: 10.24
stft:
filter_length: 1024
hop_length: 160
win_length: 1024
mel:
n_mel_channels: *mel_bins
mel_fmin: 0
mel_fmax: 8000
augmentation:
mixup: 0.0
model:
base_learning_rate: 8.0e-06
target: audioldm_train.modules.latent_encoder.autoencoder.AutoencoderKL
params:
# reload_from_ckpt: "data/checkpoints/vae_mel_16k_64bins.ckpt"
sampling_rate: *sampling_rate
batchsize: 4
monitor: val/rec_loss
image_key: fbank
subband: 1
embed_dim: *latent_embed_dim
time_shuffle: 1
lossconfig:
target: audioldm_train.losses.LPIPSWithDiscriminator
params:
disc_start: 50001
kl_weight: 1000.0
disc_weight: 0.5
disc_in_channels: 1
ddconfig:
double_z: true
mel_bins: *mel_bins # The frequency bins of mel spectrogram
z_channels: 8
resolution: 256
downsample_time: false
in_channels: 1
out_ch: 1
ch: 128
ch_mult:
- 1
- 2
- 4
num_res_blocks: 2
attn_resolutions: []
dropout: 0.0
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