✨ Support MPS acceleration in OpenCLIP embeddings

Currently, attempting to use OpenCLIP embeddings on a metal performance shader (MPS) device results in the following error:

```
RuntimeError: slow_conv2d_forward_mps: input(device='cpu') and weight(device=mps:0')  must be on the same device in add.
```

These changes fix this error by explicitly moving input tensors to the model device in `OpenCLIPEmbeddingFunction` embedding methods. This provides a significant speedup (~2x on my M1 MacBook Pro) compared to running on CPU.

chromadb/utils/embedding_functions/open_clip_embedding_function.py

@@ -47,6 +47,7 @@ def __init__(
         model, _, preprocess = open_clip.create_model_and_transforms(
             model_name=model_name, pretrained=checkpoint
         )
+        self._device = device
         self._model = model
         self._model.to(device)
         self._preprocess = preprocess
@@ -56,14 +57,16 @@ def _encode_image(self, image: Image) -> Embedding:
         pil_image = self._PILImage.fromarray(image)
         with self._torch.no_grad():
             image_features = self._model.encode_image(
-                self._preprocess(pil_image).unsqueeze(0)
+                self._preprocess(pil_image).unsqueeze(0).to(self._device)
             )
             image_features /= image_features.norm(dim=-1, keepdim=True)
             return cast(Embedding, image_features.squeeze().cpu().numpy())
 
     def _encode_text(self, text: Document) -> Embedding:
         with self._torch.no_grad():
-            text_features = self._model.encode_text(self._tokenizer(text))
+            text_features = self._model.encode_text(
+                self._tokenizer(text).to(self._device)
+            )
             text_features /= text_features.norm(dim=-1, keepdim=True)
             return cast(Embedding, text_features.squeeze().cpu().numpy())