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add torch_xla support in pipeline_stable_audio.py #10109

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Merged
merged 2 commits into from Dec 4, 2024
Merged

add torch_xla support in pipeline_stable_audio.py #10109

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8a878cc
Update pipeline_stable_audio.py
Dec 4, 2024
fa64a0d
Merge branch 'main' into main
Dec 4, 2024
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10 changes: 10 additions & 0 deletions src/diffusers/pipelines/stable_audio/pipeline_stable_audio.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,13 +26,20 @@
from ...models.embeddings import get_1d_rotary_pos_embed
from ...schedulers import EDMDPMSolverMultistepScheduler
from ...utils import (
is_torch_xla_available,
logging,
replace_example_docstring,
)
from ...utils.torch_utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
from .modeling_stable_audio import StableAudioProjectionModel

if is_torch_xla_available():
import torch_xla.core.xla_model as xm

XLA_AVAILABLE = True
else:
XLA_AVAILABLE = False

logger = logging.get_logger(__name__) # pylint: disable=invalid-name

Expand Down Expand Up @@ -725,6 +732,9 @@ def __call__(
if callback is not None and i % callback_steps == 0:
step_idx = i // getattr(self.scheduler, "order", 1)
callback(step_idx, t, latents)

if XLA_AVAILABLE:
xm.mark_step()

# 9. Post-processing
if not output_type == "latent":
Expand Down