videocrafter / model_adapter_depth_config.yaml
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Create model_adapter_depth_config.yaml
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model:
target: lvdm.models.ddpm3d.T2VAdapterDepth
params:
linear_start: 0.00085
linear_end: 0.012
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: video
cond_stage_key: caption
image_size:
- 32
- 32
video_length: 16
channels: 4
cond_stage_trainable: false
conditioning_key: crossattn
scale_by_std: false
scale_factor: 0.18215
unet_config:
target: lvdm.models.modules.openaimodel3d.UNetModel
params:
image_size: 32
in_channels: 4
out_channels: 4
model_channels: 320
attention_resolutions:
- 4
- 2
- 1
num_res_blocks: 2
channel_mult:
- 1
- 2
- 4
- 4
num_heads: 8
transformer_depth: 1
context_dim: 768
use_checkpoint: true
legacy: false
kernel_size_t: 1
padding_t: 0
temporal_length: 16
use_relative_position: true
first_stage_config:
target: lvdm.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:
target: lvdm.models.modules.condition_modules.FrozenCLIPEmbedder
depth_stage_config:
target: extralibs.midas.api.MiDaSInference
params:
model_type: "dpt_hybrid"
model_path: models/adapter_t2v_depth/dpt_hybrid-midas.pt
adapter_config:
target: lvdm.models.modules.adapter.Adapter
cond_name: depth
params:
cin: 64
channels: [320, 640, 1280, 1280]
nums_rb: 2
ksize: 1
sk: True
use_conv: False