fix(api): only use optimum's fp16 mode for SDXL export when torch fp1…

…6 is enabled

api/onnx_web/convert/__main__.py

@@ -599,7 +599,7 @@ def main(args=None) -> int:
     logger.info("CLI arguments: %s", args)
 
     server = ConversionContext.from_environ()
-    server.half = args.half or "onnx-fp16" in server.optimizations
+    server.half = args.half or server.has_optimization("onnx-fp16")
     server.opset = args.opset
     server.token = args.token
     logger.info(

api/onnx_web/convert/diffusion/diffusion_xl.py

@@ -81,7 +81,7 @@ def convert_diffusion_diffusers_xl(
         output=dest_path,
         task="stable-diffusion-xl",
         device=device,
-        fp16=conversion.half,
+        fp16=conversion.has_optimization("torch-fp16"), # optimum's fp16 mode only works on CUDA or ROCm
         framework="pt",
     )
 

api/onnx_web/diffusers/load.py

@@ -563,45 +563,45 @@ def optimize_pipeline(
     pipe: StableDiffusionPipeline,
 ) -> None:
     if (
-        "diffusers-attention-slicing" in server.optimizations
-        or "diffusers-attention-slicing-auto" in server.optimizations
+        server.has_optimization("diffusers-attention-slicing")
+        or server.has_optimization("diffusers-attention-slicing-auto")
     ):
         logger.debug("enabling auto attention slicing on SD pipeline")
         try:
             pipe.enable_attention_slicing(slice_size="auto")
         except Exception as e:
             logger.warning("error while enabling auto attention slicing: %s", e)
 
-    if "diffusers-attention-slicing-max" in server.optimizations:
+    if server.has_optimization("diffusers-attention-slicing-max"):
         logger.debug("enabling max attention slicing on SD pipeline")
         try:
             pipe.enable_attention_slicing(slice_size="max")
         except Exception as e:
             logger.warning("error while enabling max attention slicing: %s", e)
 
-    if "diffusers-vae-slicing" in server.optimizations:
+    if server.has_optimization("diffusers-vae-slicing"):
         logger.debug("enabling VAE slicing on SD pipeline")
         try:
             pipe.enable_vae_slicing()
         except Exception as e:
             logger.warning("error while enabling VAE slicing: %s", e)
 
-    if "diffusers-cpu-offload-sequential" in server.optimizations:
+    if server.has_optimization("diffusers-cpu-offload-sequential"):
         logger.debug("enabling sequential CPU offload on SD pipeline")
         try:
             pipe.enable_sequential_cpu_offload()
         except Exception as e:
             logger.warning("error while enabling sequential CPU offload: %s", e)
 
-    elif "diffusers-cpu-offload-model" in server.optimizations:
+    elif server.has_optimization("diffusers-cpu-offload-model"):
         # TODO: check for accelerate
         logger.debug("enabling model CPU offload on SD pipeline")
         try:
             pipe.enable_model_cpu_offload()
         except Exception as e:
             logger.warning("error while enabling model CPU offload: %s", e)
 
-    if "diffusers-memory-efficient-attention" in server.optimizations:
+    if server.has_optimization("diffusers-memory-efficient-attention"):
         # TODO: check for xformers
         logger.debug("enabling memory efficient attention for SD pipeline")
         try:

api/onnx_web/server/context.py

@@ -129,8 +129,11 @@ def from_environ(cls):
     def has_feature(self, flag: str) -> bool:
         return flag in self.feature_flags
 
+    def has_optimization(self, opt: str) -> bool:
+        return opt in self.optimizations
+
     def torch_dtype(self):
-        if "torch-fp16" in self.optimizations:
+        if self.has_optimization("torch-fp16"):
             return torch.float16
         else:
             return torch.float32