fix(docs): add conversion error to user guide (#404)

docs/converted-readme.md

@@ -4,6 +4,9 @@ This is a copy of MODEL TITLE converted to the ONNX format for use with tools th
 https://github.com/ssube/onnx-web. If you have questions about using this model, please see
 https://github.com/ssube/onnx-web/blob/main/docs/user-guide.md#pre-converted-models.
 
+FP16 WARNING: This model has been converted to FP16 format and will not run correctly on the CPU platform. If you are
+using the CPU platform, please use the FP32 model instead.
+
 As a derivative of MODEL TITLE, the model files that came with this README are licensed under the terms of TODO. A copy
 of the license was included in the archive. Please make sure to read and follow the terms before you use this model or
 redistribute these files.
@@ -12,6 +15,13 @@ If you are the author of this model and have questions about ONNX models or woul
 distribution or moved to another site, please contact ssube on https://github.com/ssube/onnx-web/issues or
 https://discord.gg/7CdQmutGuw.
 
+## Adding models
+
+Extract the entire ZIP archive into the models folder of your onnx-web installation and restart the server or click the
+Restart Workers button in the web UI and then refresh the page.
+
+Please see https://github.com/ssube/onnx-web/blob/main/docs/user-guide.md#adding-your-own-models for more details.
+
 ## Folder structure
 
 - cnet
@@ -32,12 +42,4 @@ https://discord.gg/7CdQmutGuw.
   - UNet model
 - vae_decoder
   - VAE decoder model
-- vae_encoder
-  - VAE encoder model
-
-## Adding models
-
-Extract the entire ZIP archive into the models folder of your onnx-web installation and restart the server or click the
-Restart Workers button in the web UI and then refresh the page.
-
-Please see https://github.com/ssube/onnx-web/blob/main/docs/user-guide.md#adding-your-own-models for more details.
+- vae_encoder

docs/user-guide.md

@@ -126,6 +126,7 @@ Please see [the server admin guide](server-admin.md) for details on how to confi
       - [The expanded size of the tensor must match the existing size](#the-expanded-size-of-the-tensor-must-match-the-existing-size)
       - [Shape mismatch attempting to re-use buffer](#shape-mismatch-attempting-to-re-use-buffer)
       - [Cannot read properties of undefined (reading 'default')](#cannot-read-properties-of-undefined-reading-default)
+      - [Missing key(s) in state\_dict](#missing-keys-in-state_dict)
   - [Output Image Sizes](#output-image-sizes)
 
 ## Outline
@@ -1719,6 +1720,26 @@ Could not fetch parameters from the onnx-web API server at http://10.2.2.34:5000
 Cannot read properties of undefined (reading 'default')
 ```
 
+#### Missing key(s) in state_dict
+
+This can happen when you try to convert a newer Stable Diffusion checkpoint with Torch model extraction enabled. The
+code used for model extraction does not support some keys in recent models and will throw an error.
+
+Make sure you have set the `ONNX_WEB_CONVERT_EXTRACT` environment variable to `FALSE`.
+
+Example error:
+
+```none
+Traceback (most recent call last):
+  File "/opt/onnx-web/api/onnx_web/convert/diffusion/checkpoint.py", line 1570, in extract_checkpoint
+    vae.load_state_dict(converted_vae_checkpoint)
+  File "/home/ssube/miniconda3/envs/onnx-web-rocm-pytorch2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 2041, in load_state_dict
+    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
+RuntimeError: Error(s) in loading state_dict for AutoencoderKL:
+        Missing key(s) in state_dict: "encoder.mid_block.attentions.0.to_q.weight", "encoder.mid_block.attentions.0.to_q.bias", "encoder.mid_block.attentions.0.to_k.weight", "encoder.mid_block.attentions.0.to_k.bias", "encoder.mid_block.attentions.0.to_v.weight", "encoder.mid_block.attentions.0.to_v.bias", "encoder.mid_block.attentions.0.to_out.0.weight", "encoder.mid_block.attentions.0.to_out.0.bias", "decoder.mid_block.attentions.0.to_q.weight", "decoder.mid_block.attentions.0.to_q.bias", "decoder.mid_block.attentions.0.to_k.weight", "decoder.mid_block.attentions.0.to_k.bias", "decoder.mid_block.attentions.0.to_v.weight", "decoder.mid_block.attentions.0.to_v.bias", "decoder.mid_block.attentions.0.to_out.0.weight", "decoder.mid_block.attentions.0.to_out.0.bias".
+        Unexpected key(s) in state_dict: "encoder.mid_block.attentions.0.key.bias", "encoder.mid_block.attentions.0.key.weight", "encoder.mid_block.attentions.0.proj_attn.bias", "encoder.mid_block.attentions.0.proj_attn.weight", "encoder.mid_block.attentions.0.query.bias", "encoder.mid_block.attentions.0.query.weight", "encoder.mid_block.attentions.0.value.bias", "encoder.mid_block.attentions.0.value.weight", "decoder.mid_block.attentions.0.key.bias", "decoder.mid_block.attentions.0.key.weight", "decoder.mid_block.attentions.0.proj_attn.bias", "decoder.mid_block.attentions.0.proj_attn.weight", "decoder.mid_block.attentions.0.query.bias", "decoder.mid_block.attentions.0.query.weight", "decoder.mid_block.attentions.0.value.bias", "decoder.mid_block.attentions.0.value.weight".
+```
+
 ## Output Image Sizes
 
 You can use this table to figure out the final size for each image, based on the combination of parameters that you are