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olive fix mat1 mat2 mismatch

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This commit is contained in:
Seunghoon Lee
2024-02-02 16:17:59 +09:00
parent 69599f01e5
commit df7564a01f
1 changed files with 43 additions and 52 deletions
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modules/onnx_impl/pipelines.py
+43 -52
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@@ -139,13 +139,7 @@ class OnnxRawPipeline(PipelineBase):
pipeline.scheduler = self.scheduler
return pipeline
def convert(self, submodels: List[str], in_dir: os.PathLike):
out_dir = os.path.join(shared.opts.onnx_cached_models_path, self.original_filename)
if (self.from_diffusers_cache and check_cache_onnx(self.path)):
return self.path
if os.path.isdir(out_dir): # if model is ONNX format or had already converted.
return out_dir
def convert(self, submodels: List[str], in_dir: os.PathLike, out_dir: os.PathLike):
shutil.rmtree("cache", ignore_errors=True)
shutil.rmtree("footprints", ignore_errors=True)
@@ -211,19 +205,10 @@ class OnnxRawPipeline(PipelineBase):
with open(os.path.join(out_dir, "model_index.json"), 'w', encoding="utf-8") as file:
json.dump(model_index, file)
return out_dir
def run_olive(self, submodels: List[str], in_dir: os.PathLike):
def run_olive(self, submodels: List[str], in_dir: os.PathLike, out_dir: os.PathLike):
if not shared.cmd_opts.debug:
ort.set_default_logger_severity(4)
out_dir = os.path.join(shared.opts.onnx_cached_models_path, f"{self.original_filename}-{config.width}w-{config.height}h")
if os.path.isdir(out_dir): # already optimized (cached)
return out_dir
if not shared.opts.olive_cache_optimized:
out_dir = shared.opts.onnx_temp_dir
try:
from olive.model import ONNXModel # olive-ai==0.4.0
except ImportError:
@@ -326,8 +311,6 @@ class OnnxRawPipeline(PipelineBase):
with open(os.path.join(out_dir, "model_index.json"), 'w', encoding="utf-8") as file:
json.dump(model_index, file)
return out_dir
def preprocess(self, p: StableDiffusionProcessing):
disable_classifier_free_guidance = p.cfg_scale < 0.01
@@ -347,27 +330,32 @@ class OnnxRawPipeline(PipelineBase):
config.cross_attention_dim = 2048
config.time_ids_size = 6
else:
config.cross_attention_dim = 256 + p.height
config.cross_attention_dim = 768
config.time_ids_size = 5
if not disable_classifier_free_guidance and "turbo" in str(self.path).lower():
log.warning("ONNX: It looks like you are trying to run a Turbo model with CFG Scale, which will lead to 'size mismatch' or 'unexpected parameter' error.")
try:
converted_dir = self.convert(
(SUBMODELS_SDXL_REFINER if self.is_refiner else SUBMODELS_SDXL) if self._is_sdxl else SUBMODELS_SD,
self.path if os.path.isdir(self.path) else shared.opts.onnx_temp_dir
)
except Exception as e:
log.error(f"ONNX: Failed to convert model: model='{self.original_filename}', error={e}")
shutil.rmtree(shared.opts.onnx_temp_dir, ignore_errors=True)
shutil.rmtree(os.path.join(shared.opts.onnx_cached_models_path, self.original_filename), ignore_errors=True)
return
out_dir = os.path.join(shared.opts.onnx_cached_models_path, self.original_filename)
if (self.from_diffusers_cache and check_cache_onnx(self.path)): # if model is ONNX format or had already converted, skip conversion.
out_dir = self.path
elif not os.path.isdir(out_dir):
try:
self.convert(
(SUBMODELS_SDXL_REFINER if self.is_refiner else SUBMODELS_SDXL) if self._is_sdxl else SUBMODELS_SD,
self.path if os.path.isdir(self.path) else shared.opts.onnx_temp_dir,
out_dir,
)
except Exception as e:
log.error(f"ONNX: Failed to convert model: model='{self.original_filename}', error={e}")
shutil.rmtree(shared.opts.onnx_temp_dir, ignore_errors=True)
shutil.rmtree(out_dir, ignore_errors=True)
return
kwargs = {
"provider": get_provider(),
}
out_dir = converted_dir
in_dir = out_dir
if shared.opts.cuda_compile_backend == "olive-ai":
if run_olive_workflow is None:
@@ -391,34 +379,37 @@ class OnnxRawPipeline(PipelineBase):
else:
log.warning("Olive implementation is experimental. It contains potentially an issue and is subject to change at any time.")
in_dir = converted_dir
out_dir = os.path.join(shared.opts.onnx_cached_models_path, f"{self.original_filename}-{config.width}w-{config.height}h")
if not os.path.isdir(out_dir): # check the model is already optimized (cached)
if not shared.opts.olive_cache_optimized:
out_dir = shared.opts.onnx_temp_dir
if p.width != p.height:
log.warning("Olive: Different width and height are detected. The quality of the result is not guaranteed.")
if p.width != p.height:
log.warning("Olive: Different width and height are detected. The quality of the result is not guaranteed.")
if shared.opts.olive_static_dims:
sess_options = DynamicSessionOptions()
sess_options.enable_static_dims({
"is_sdxl": self._is_sdxl,
"is_refiner": self.is_refiner,
if shared.opts.olive_static_dims:
sess_options = DynamicSessionOptions()
sess_options.enable_static_dims({
"is_sdxl": self._is_sdxl,
"is_refiner": self.is_refiner,
"hidden_batch_size": p.batch_size if disable_classifier_free_guidance else p.batch_size * 2,
"height": p.height,
"width": p.width,
})
kwargs["sess_options"] = sess_options
"hidden_batch_size": p.batch_size if disable_classifier_free_guidance else p.batch_size * 2,
"height": p.height,
"width": p.width,
})
kwargs["sess_options"] = sess_options
try:
out_dir = self.run_olive(submodels_for_olive, in_dir)
except Exception as e:
log.error(f"Olive: Failed to run olive passes: model='{self.original_filename}', error={e}")
shutil.rmtree(shared.opts.onnx_temp_dir, ignore_errors=True)
shutil.rmtree(os.path.join(shared.opts.onnx_cached_models_path, self.original_filename), ignore_errors=True)
try:
self.run_olive(submodels_for_olive, in_dir, out_dir)
except Exception as e:
log.error(f"Olive: Failed to run olive passes: model='{self.original_filename}', error={e}")
shutil.rmtree(shared.opts.onnx_temp_dir, ignore_errors=True)
shutil.rmtree(out_dir, ignore_errors=True)
pipeline = self.derive_properties(load_pipeline(self.constructor, out_dir, **kwargs))
if not shared.opts.onnx_cache_converted:
shutil.rmtree(converted_dir)
if not shared.opts.onnx_cache_converted and in_dir != self.path:
shutil.rmtree(in_dir)
shutil.rmtree(shared.opts.onnx_temp_dir, ignore_errors=True)
return pipeline