mirror of
https://github.com/vladmandic/automatic
synced 2026-09-18 08:44:33 +02:00
@@ -832,7 +832,7 @@ class HunyuanVideoTransformer3DModelPacked(ModelMixin, ConfigMixin, PeftAdapterM
|
||||
clean_latents_4x=None, clean_latent_4x_indices=None
|
||||
):
|
||||
hidden_states = self.gradient_checkpointing_method(self.x_embedder.proj, latents)
|
||||
B, _C, T, H, W = hidden_states.shape
|
||||
B, C, T, H, W = hidden_states.shape
|
||||
|
||||
if latent_indices is None:
|
||||
latent_indices = torch.arange(0, T).unsqueeze(0).expand(B, -1)
|
||||
@@ -897,7 +897,7 @@ class HunyuanVideoTransformer3DModelPacked(ModelMixin, ConfigMixin, PeftAdapterM
|
||||
if attention_kwargs is None:
|
||||
attention_kwargs = {}
|
||||
|
||||
batch_size, _num_channels, num_frames, height, width = hidden_states.shape
|
||||
batch_size, num_channels, num_frames, height, width = hidden_states.shape
|
||||
p, p_t = self.config['patch_size'], self.config['patch_size_t']
|
||||
post_patch_num_frames = num_frames // p_t
|
||||
post_patch_height = height // p
|
||||
|
||||
@@ -18,7 +18,7 @@ torch_linalg_solve = None
|
||||
|
||||
|
||||
def test_solver():
|
||||
from modules import devices
|
||||
from modules import devices, shared
|
||||
try:
|
||||
a = torch.randn(50, 50).to(device=devices.device, dtype=torch.float32)
|
||||
b = torch.randn(50, 2).to(device=devices.device, dtype=torch.float32)
|
||||
|
||||
Reference in New Issue
Block a user