add concept of repo variant

tests/test_model_probe.py

@@ -3,7 +3,7 @@ from pathlib import Path
 import pytest
 
 from invokeai.backend import BaseModelType
-from invokeai.backend.model_management.model_probe import VaeFolderProbe
+from invokeai.backend.model_manager.probe import VaeFolderProbe
 
 
 @pytest.mark.parametrize(
@@ -20,3 +20,10 @@ def test_get_base_type(vae_path: str, expected_type: BaseModelType, datadir: Pat
     probe = VaeFolderProbe(sd1_vae_path)
     base_type = probe.get_base_type()
     assert base_type == expected_type
+    repo_variant = probe.get_repo_variant()
+    assert repo_variant == 'default'
+
+def test_repo_variant(datadir: Path):
+    probe = VaeFolderProbe(datadir / "vae" / "taesdxl-fp16")
+    repo_variant = probe.get_repo_variant()
+    assert repo_variant == 'fp16'

tests/test_model_probe/vae/taesdxl-fp16/config.json

@@ -0,0 +1,37 @@
+{
+  "_class_name": "AutoencoderTiny",
+  "_diffusers_version": "0.20.0.dev0",
+  "act_fn": "relu",
+  "decoder_block_out_channels": [
+    64,
+    64,
+    64,
+    64
+  ],
+  "encoder_block_out_channels": [
+    64,
+    64,
+    64,
+    64
+  ],
+  "force_upcast": false,
+  "in_channels": 3,
+  "latent_channels": 4,
+  "latent_magnitude": 3,
+  "latent_shift": 0.5,
+  "num_decoder_blocks": [
+    3,
+    3,
+    3,
+    1
+  ],
+  "num_encoder_blocks": [
+    1,
+    3,
+    3,
+    3
+  ],
+  "out_channels": 3,
+  "scaling_factor": 1.0,
+  "upsampling_scaling_factor": 2
+}