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cleanup, remove torch 1.13.1 hack

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This commit is contained in:
Seunghoon Lee
2024-01-30 15:41:21 +09:00
parent 192b9db5b3
commit 88882a38e4
2 changed files with 9 additions and 15 deletions
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launch.py
-6
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@@ -23,12 +23,6 @@ python = sys.executable # used by some extensions to run python
skip_install = False # parsed by some extensions
try:
import torch._dynamo
except ModuleNotFoundError:
sys.modules["torch._dynamo"] = {} # HACK torch 1.13.1 does not have _dynamo. will be removed.
def init_olive():
try:
import olive.workflows # pylint: disable=unused-import
modules/onnx_pipelines.py
+9 -9
View File
@@ -45,7 +45,7 @@ CONVERSION_PASS_UNET = {
}
class OnnxPipelineBase(TorchCompatibleModule, diffusers.DiffusionPipeline, metaclass=ABCMeta):
class PipelineBase(TorchCompatibleModule, diffusers.DiffusionPipeline, metaclass=ABCMeta):
model_type: str
sd_model_hash: str
sd_checkpoint_info: CheckpointInfo
@@ -101,7 +101,7 @@ class OnnxPipelineBase(TorchCompatibleModule, diffusers.DiffusionPipeline, metac
return cls.from_single_file(pretrained_model_name_or_path)
class OnnxRawPipeline(OnnxPipelineBase):
class OnnxRawPipeline(PipelineBase):
config = {}
_is_sdxl: bool
is_refiner: bool
@@ -109,12 +109,12 @@ class OnnxRawPipeline(OnnxPipelineBase):
path: os.PathLike
original_filename: str
constructor: Type[OnnxPipelineBase]
constructor: Type[PipelineBase]
init_dict: Dict[str, Tuple[str]] = {}
scheduler: Any = None # for Img2Img
def __init__(self, constructor: Type[OnnxPipelineBase], path: os.PathLike):
def __init__(self, constructor: Type[PipelineBase], path: os.PathLike):
self._is_sdxl = check_pipeline_sdxl(constructor)
self.from_diffusers_cache = check_diffusers_cache(path)
self.path = path
@@ -512,7 +512,7 @@ def prepare_latents(
return latents
class OnnxStableDiffusionPipeline(diffusers.OnnxStableDiffusionPipeline, OnnxPipelineBase):
class OnnxStableDiffusionPipeline(diffusers.OnnxStableDiffusionPipeline, PipelineBase):
__module__ = 'diffusers'
__name__ = 'OnnxStableDiffusionPipeline'
@@ -672,7 +672,7 @@ class OnnxStableDiffusionPipeline(diffusers.OnnxStableDiffusionPipeline, OnnxPip
return StableDiffusionPipelineOutput(images=image, nsfw_content_detected=has_nsfw_concept)
class OnnxStableDiffusionImg2ImgPipeline(diffusers.OnnxStableDiffusionImg2ImgPipeline, OnnxPipelineBase):
class OnnxStableDiffusionImg2ImgPipeline(diffusers.OnnxStableDiffusionImg2ImgPipeline, PipelineBase):
__module__ = 'diffusers'
__name__ = 'OnnxStableDiffusionImg2ImgPipeline'
@@ -862,7 +862,7 @@ class OnnxStableDiffusionImg2ImgPipeline(diffusers.OnnxStableDiffusionImg2ImgPip
return StableDiffusionPipelineOutput(images=image, nsfw_content_detected=has_nsfw_concept)
class OnnxStableDiffusionInpaintPipeline(diffusers.OnnxStableDiffusionInpaintPipeline, OnnxPipelineBase):
class OnnxStableDiffusionInpaintPipeline(diffusers.OnnxStableDiffusionInpaintPipeline, PipelineBase):
__module__ = 'diffusers'
__name__ = 'OnnxStableDiffusionInpaintPipeline'
@@ -1074,7 +1074,7 @@ class OnnxStableDiffusionInpaintPipeline(diffusers.OnnxStableDiffusionInpaintPip
return StableDiffusionPipelineOutput(images=image, nsfw_content_detected=has_nsfw_concept)
class OnnxStableDiffusionXLPipeline(OnnxPipelineBase, optimum.onnxruntime.ORTStableDiffusionXLPipeline):
class OnnxStableDiffusionXLPipeline(PipelineBase, optimum.onnxruntime.ORTStableDiffusionXLPipeline):
__module__ = 'optimum.onnxruntime.modeling_diffusion'
__name__ = 'ORTStableDiffusionXLPipeline'
@@ -1100,7 +1100,7 @@ class OnnxStableDiffusionXLPipeline(OnnxPipelineBase, optimum.onnxruntime.ORTSta
return prepare_latents(self.scheduler.init_noise_sigma, batch_size, height, width, dtype, generator, latents, num_channels_latents, self.vae_scale_factor)
class OnnxStableDiffusionXLImg2ImgPipeline(OnnxPipelineBase, optimum.onnxruntime.ORTStableDiffusionXLImg2ImgPipeline):
class OnnxStableDiffusionXLImg2ImgPipeline(PipelineBase, optimum.onnxruntime.ORTStableDiffusionXLImg2ImgPipeline):
__module__ = 'optimum.onnxruntime.modeling_diffusion'
__name__ = 'ORTStableDiffusionXLImg2ImgPipeline'