diff --git a/vllm_omni/diffusion/models/bagel/bagel_transformer.py b/vllm_omni/diffusion/models/bagel/bagel_transformer.py index 7f36c0b69..6ee81a4fd 100644 --- a/vllm_omni/diffusion/models/bagel/bagel_transformer.py +++ b/vllm_omni/diffusion/models/bagel/bagel_transformer.py @@ -714,7 +714,6 @@ class Bagel(torch.nn.Module): return generation_input, newlens, new_rope - @torch.no_grad def forward_cache_update_text( self, past_key_values: NaiveCache, @@ -821,7 +820,6 @@ class Bagel(torch.nn.Module): return generation_input, newlens, new_rope - @torch.no_grad def forward_cache_update_vae( self, vae_model, @@ -946,7 +944,6 @@ class Bagel(torch.nn.Module): return generation_input, newlens, new_rope - @torch.no_grad def forward_cache_update_vit( self, past_key_values: NaiveCache, @@ -1064,7 +1061,6 @@ class Bagel(torch.nn.Module): def prepare_vae_latent(self, curr_kvlens, curr_rope, image_sizes, new_token_ids): return self.prepare_input(curr_kvlens, curr_rope, image_sizes, new_token_ids) - @torch.no_grad def generate_image( self, packed_text_ids: torch.LongTensor, @@ -1121,7 +1117,6 @@ class Bagel(torch.nn.Module): unpacked_latent = x_t.split((packed_seqlens - 2).tolist()) return unpacked_latent - @torch.no_grad def _forward_flow( self, x_t: torch.Tensor, diff --git a/vllm_omni/diffusion/models/flux2_klein/pipeline_flux2_klein.py b/vllm_omni/diffusion/models/flux2_klein/pipeline_flux2_klein.py index ba29e681c..7d1b6578d 100644 --- a/vllm_omni/diffusion/models/flux2_klein/pipeline_flux2_klein.py +++ b/vllm_omni/diffusion/models/flux2_klein/pipeline_flux2_klein.py @@ -644,7 +644,6 @@ class Flux2KleinPipeline(nn.Module, SupportImageInput): def interrupt(self): return self._interrupt - @torch.no_grad() def forward( self, req: OmniDiffusionRequest, diff --git a/vllm_omni/diffusion/models/ovis_image/pipeline_ovis_image.py b/vllm_omni/diffusion/models/ovis_image/pipeline_ovis_image.py index 660338a35..6bf4ca1b5 100644 --- a/vllm_omni/diffusion/models/ovis_image/pipeline_ovis_image.py +++ b/vllm_omni/diffusion/models/ovis_image/pipeline_ovis_image.py @@ -516,7 +516,6 @@ class OvisImagePipeline( def interrupt(self): return self._interrupt - @torch.no_grad() def forward( self, req: OmniDiffusionRequest, diff --git a/vllm_omni/diffusion/models/stable_audio/pipeline_stable_audio.py b/vllm_omni/diffusion/models/stable_audio/pipeline_stable_audio.py index 14516a9bb..c947bd934 100644 --- a/vllm_omni/diffusion/models/stable_audio/pipeline_stable_audio.py +++ b/vllm_omni/diffusion/models/stable_audio/pipeline_stable_audio.py @@ -347,7 +347,6 @@ class StableAudioPipeline(nn.Module, SupportAudioOutput): latents = latents * self.scheduler.init_noise_sigma return latents - @torch.no_grad() def forward( self, req: OmniDiffusionRequest, diff --git a/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2.py b/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2.py index 8ff6271a0..b691cfedb 100644 --- a/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2.py +++ b/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2.py @@ -278,7 +278,6 @@ class Wan22Pipeline(nn.Module): def current_timestep(self): return self._current_timestep - @torch.no_grad() def forward( self, req: OmniDiffusionRequest, diff --git a/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2_i2v.py b/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2_i2v.py index 635da11e6..ed8c0a987 100644 --- a/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2_i2v.py +++ b/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2_i2v.py @@ -254,7 +254,6 @@ class Wan22I2VPipeline(nn.Module, SupportImageInput): image_embeds = self.image_encoder(pixel_values, output_hidden_states=True) return image_embeds.hidden_states[-2] - @torch.no_grad() def forward( self, req: OmniDiffusionRequest, diff --git a/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2_ti2v.py b/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2_ti2v.py index 6c1e39242..b943000cf 100644 --- a/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2_ti2v.py +++ b/vllm_omni/diffusion/models/wan2_2/pipeline_wan2_2_ti2v.py @@ -193,7 +193,6 @@ class Wan22TI2VPipeline(nn.Module, SupportImageInput): def current_timestep(self): return self._current_timestep - @torch.no_grad() def forward( self, req: OmniDiffusionRequest, diff --git a/vllm_omni/diffusion/models/z_image/pipeline_z_image.py b/vllm_omni/diffusion/models/z_image/pipeline_z_image.py index 7d6fb901d..b92d3de88 100644 --- a/vllm_omni/diffusion/models/z_image/pipeline_z_image.py +++ b/vllm_omni/diffusion/models/z_image/pipeline_z_image.py @@ -312,7 +312,6 @@ class ZImagePipeline(nn.Module): def interrupt(self): return self._interrupt - @torch.no_grad() def forward( self, req: OmniDiffusionRequest, diff --git a/vllm_omni/model_executor/models/qwen2_5_omni/qwen2_5_omni_token2wav.py b/vllm_omni/model_executor/models/qwen2_5_omni/qwen2_5_omni_token2wav.py index 1bc68f2a4..c60015c0e 100644 --- a/vllm_omni/model_executor/models/qwen2_5_omni/qwen2_5_omni_token2wav.py +++ b/vllm_omni/model_executor/models/qwen2_5_omni/qwen2_5_omni_token2wav.py @@ -1258,7 +1258,6 @@ class Qwen2_5OmniToken2WavDiTModel(Qwen2_5OmniPreTrainedModel): return output - @torch.no_grad() def sample( self, conditioning_vector, @@ -1333,7 +1332,6 @@ class Qwen2_5OmniToken2WavDiTModel(Qwen2_5OmniPreTrainedModel): generated_mel_spectrogram = generated_waveform.permute(0, 2, 1) return generated_mel_spectrogram - @torch.no_grad() def fast_block_sample( self, conditioning_vector: torch.Tensor,