fix(api): allow SDXL VAE in any supported tensor format, ensure new S…

…DXL models get hash file

api/onnx_web/convert/diffusion/diffusion_xl.py

@@ -10,7 +10,7 @@
 from optimum.exporters.onnx import main_export
 
 from ...constants import ONNX_MODEL
-from ..utils import ConversionContext
+from ..utils import RESOLVE_FORMATS, ConversionContext, check_ext
 
 logger = getLogger(__name__)
 
@@ -42,13 +42,14 @@ def convert_diffusion_diffusers_xl(
         "converting Stable Diffusion XL model %s: %s -> %s/", name, source, dest_path
     )
 
-    if "hash" in model and not path.exists(model_hash):
-        logger.info("ONNX model does not have hash file, adding one")
-        with open(model_hash, "w") as f:
-            f.write(model["hash"])
-
     if path.exists(dest_path) and path.exists(model_index):
         logger.info("ONNX model already exists, skipping conversion")
+
+        if "hash" in model and not path.exists(model_hash):
+            logger.info("ONNX model does not have hash file, adding one")
+            with open(model_hash, "w") as f:
+                f.write(model["hash"])
+
         return (False, dest_path)
 
     # safetensors -> diffusers directory with torch models
@@ -63,7 +64,7 @@ def convert_diffusion_diffusers_xl(
 
     if replace_vae is not None:
         vae_path = path.join(conversion.model_path, replace_vae)
-        if replace_vae.endswith(".safetensors"):
+        if check_ext(replace_vae, RESOLVE_FORMATS):
             pipeline.vae = AutoencoderKL.from_single_file(vae_path)
         else:
             pipeline.vae = AutoencoderKL.from_pretrained(vae_path)
@@ -80,6 +81,11 @@ def convert_diffusion_diffusers_xl(
         framework="pt",
     )
 
+    if "hash" in model:
+        logger.debug("adding hash file to ONNX model")
+        with open(model_hash, "w") as f:
+            f.write(model["hash"])
+
     if conversion.half:
         unet_path = path.join(dest_path, "unet", ONNX_MODEL)
         infer_shapes_path(unet_path)