feat(ml): add more search models (#11468)

* update export code

* add uuid glob, sort model names

* add new models to ml, sort names

* add new models to server, sort by dims and name

* typo in name

* update export dependencies

* onnx save function

* format

machine-learning/export/models/mclip.py

@@ -1,3 +1,4 @@
+import os
 import tempfile
 import warnings
 from pathlib import Path
@@ -8,7 +9,6 @@ from transformers import AutoTokenizer
 
 from .openclip import OpenCLIPModelConfig
 from .openclip import to_onnx as openclip_to_onnx
-from .optimize import optimize
 from .util import get_model_path
 
 _MCLIP_TO_OPENCLIP = {
@@ -23,18 +23,20 @@ def to_onnx(
     model_name: str,
     output_dir_visual: Path | str,
     output_dir_textual: Path | str,
-) -> None:
+) -> tuple[Path, Path]:
     textual_path = get_model_path(output_dir_textual)
     with tempfile.TemporaryDirectory() as tmpdir:
-        model = MultilingualCLIP.from_pretrained(model_name, cache_dir=tmpdir)
+        model = MultilingualCLIP.from_pretrained(model_name, cache_dir=os.environ.get("CACHE_DIR", tmpdir))
         AutoTokenizer.from_pretrained(model_name).save_pretrained(output_dir_textual)
 
+        model.eval()
         for param in model.parameters():
             param.requires_grad_(False)
 
         export_text_encoder(model, textual_path)
-        openclip_to_onnx(_MCLIP_TO_OPENCLIP[model_name], output_dir_visual)
-        optimize(textual_path)
+        visual_path, _ = openclip_to_onnx(_MCLIP_TO_OPENCLIP[model_name], output_dir_visual)
+        assert visual_path is not None, "Visual model export failed"
+    return visual_path, textual_path
 
 
 def export_text_encoder(model: MultilingualCLIP, output_path: Path | str) -> None:
@@ -58,10 +60,10 @@ def export_text_encoder(model: MultilingualCLIP, output_path: Path | str) -> Non
             args,
             output_path.as_posix(),
             input_names=["input_ids", "attention_mask"],
-            output_names=["text_embedding"],
+            output_names=["embedding"],
             opset_version=17,
-            dynamic_axes={
-                "input_ids": {0: "batch_size", 1: "sequence_length"},
-                "attention_mask": {0: "batch_size", 1: "sequence_length"},
-            },
+            # dynamic_axes={
+            #     "input_ids": {0: "batch_size", 1: "sequence_length"},
+            #     "attention_mask": {0: "batch_size", 1: "sequence_length"},
+            # },
         )