standalone "Make an embedding file for SD", but non-conventional

Note: this currently does NOT PERFORM AS EXPECTED.
Making an embedding from the word "cat" does not give you consistent images of cats.
It's more like "suggestion of cats".

generate-embedding.py

@@ -0,0 +1,73 @@
+#!/bin/env python
+
+""" Work in progress
+NB: This is COMPLETELY DIFFERENT from "generate-embeddings.py"!!!
+
+
+Plan:
+   Take input for a single word or phrase.
+   Generate a embedding file, "generated.safetensors"
+   Save it out, to "generated.safetensors"
+
+   Note that you can generate an embedding from two words, or even more
+   
+   Note also that apparently there are multiple file formats for embeddings.
+   I only use the simplest of them, in the simplest way.
+"""
+
+
+import sys
+import json
+import torch
+from safetensors.torch import save_file
+from transformers import CLIPProcessor,CLIPModel
+
+import logging
+# Turn off  stupid mesages from CLIPModel.load
+logging.disable(logging.WARNING)
+
+clipsrc="openai/clip-vit-large-patch14"
+processor=None
+model=None
+
+device=torch.device("cuda")
+
+
+def init():
+    global processor
+    global model
+    # Load the processor and model
+    print("loading processor from "+clipsrc,file=sys.stderr)
+    processor = CLIPProcessor.from_pretrained(clipsrc)
+    print("done",file=sys.stderr)
+    print("loading model from "+clipsrc,file=sys.stderr)
+    model = CLIPModel.from_pretrained(clipsrc)
+    print("done",file=sys.stderr)
+
+    model = model.to(device)
+
+def standard_embed_calc(text):
+    inputs = processor(text=text, return_tensors="pt")
+    inputs.to(device)
+    with torch.no_grad():
+        text_features = model.get_text_features(**inputs)
+    embedding = text_features[0]
+    return embedding
+
+
+init()
+
+
+word = input("type a phrase to generate an embedding for: ")
+
+emb = standard_embed_calc(word)
+embs=emb.unsqueeze(0) # stupid matrix magic to make the cat work
+
+print("Shape of result = ",embs.shape)
+output = "generated.safetensors"
+print(f"Saving to {output}...")
+save_file({"emb_params": embs}, output)
+
+
+
+