Repository: stable-diffusion-webui
Issue: [Bug]: train textual inversion, read parameter for previews, gets wrong argument in line 593 in train_embedding.py
Labels: bug-report

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What happened?

Training an embedding, selecting "Read parameters (prompt, etc...) from txt2img tab when making previews", generated an exception in line 593 because the index expected int, got str:

> p.sampler_name = sd_samplers.samplers[preview_sampler_index].name

After hacking that line, I'm pretty sure some arguments are coming in to that function in the wrong order.

>     p.sampler_name = sd_samplers.samplers[int(preview_sampler_index)].name
                                              ^^^^^^^^^^^^^^^^^^^^^^^^^^
>  ValueError: invalid literal for int() with base 10: 'DPM++ 2M Karras'

### Steps to reproduce the problem

Train an embedding with "Read parameters (prompt, etc...) from txt2img tab when making previews" selected.

### What should have happened?

_Not_ generating an exception due to an index finding a str when it expected an int or range.

### Sysinfo

{
    "Platform": "Windows-10-10.0.22621-SP0",
    "Python": "3.11.5",
    "Version": "v1.6.0",
    "Commit": "5ef669de080814067961f28357256e8fe27544f4",
    "Script path": "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui",
    "Data path": "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui",
    "Extensions dir": "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\extensions",
    "Checksum": "a0918115d0ddb75f9885f64424058ba418c5029b599ee9ab0a36de2defb0ab6e",
    "Commandline": [
        "launch.py"
    ],
    "Torch env info": "'NoneType' object has no attribute 'splitlines'",
    "Exceptions": [
        {
            "exception": "[WinError 5] Access is denied: 'textual_inversion\\\\2023-09-12\\\\Peranza\\\\images\\\\Peranza-750.tmp' -> 'textual_inversion\\\\2023-09-12\\\\Peranza\\\\images\\\\Peranza-750.png'",
            "traceback": [
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\textual_inversion\\textual_inversion.py, line 648, train_embedding",
                    "last_saved_image, last_text_info = images.save_image(image, images_dir, \"\", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)"
                ],
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\images.py, line 672, save_image",
                    "_atomically_save_image(image, fullfn_without_extension, extension)"
                ],
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\images.py, line 664, _atomically_save_image",
                    "os.replace(temp_file_path, filename_without_extension + extension)"
                ]
            ]
        },
        {
            "exception": "[WinError 5] Access is denied: 'textual_inversion\\\\2023-09-12\\\\Peranza\\\\images\\\\Peranza-200.tmp' -> 'textual_inversion\\\\2023-09-12\\\\Peranza\\\\images\\\\Peranza-200.png'",
            "traceback": [
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\textual_inversion\\textual_inversion.py, line 648, train_embedding",
                    "last_saved_image, last_text_info = images.save_image(image, images_dir, \"\", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)"
                ],
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\images.py, line 672, save_image",
                    "_atomically_save_image(image, fullfn_without_extension, extension)"
                ],
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\images.py, line 664, _atomically_save_image",
                    "os.replace(temp_file_path, filename_without_extension + extension)"
                ]
            ]
        },
        {
            "exception": "invalid literal for int() with base 10: 'DPM++ 2M Karras'",
            "traceback": [
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\textual_inversion\\textual_inversion.py, line 593, train_embedding",
                    "p.sampler_name = sd_samplers.samplers[int(preview_sampler_index)].name"
                ]
            ]
        },
        {
            "exception": "Dataset directory is empty",
            "traceback": [
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\call_queue.py, line 36, f",
                    "res = func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\textual_inversion\\ui.py, line 33, train_embedding",
                    "embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args)"
                ],
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\textual_inversion\\textual_inversion.py, line 395, train_embedding",
                    "validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_embedding_every, create_image_every, log_directory, name=\"embedding\")"
                ],
                [
                    "C:\\Users\\yudko\\Dropbox\\PC (2)\\Desktop\\stable-diffusion-webui\\modules\\textual_inversion\\textual_inversion.py, line 372, validate_train_inputs",
                    "assert data_root, \"Dataset directory is empty\""
                ]
            ]
        }
    ],
    "CPU": {
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        "count physical": 14
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        "used": "21GB",
        "free": "43GB"
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        "samples_filename_pattern": "",
        "save_images_add_number": true,
        "grid_save": true,
        "grid_format": "png",
        "grid_extended_filename": false,
        "grid_only_if_multiple": true,
        "grid_prevent_empty_spots": false,
        "grid_zip_filename_pattern": "",
        "n_rows": -1,
        "font": "",
        "grid_text_active_color": "#000000",
        "grid_text_inactive_color": "#999999",
        "grid_background_color": "#ffffff",
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        "save_images_before_face_restoration": false,
        "save_images_before_highres_fix": false,
        "save_images_before_color_correction": false,
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        "save_mask_composite": false,
        "jpeg_quality": 80,
        "webp_lossless": false,
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        "save_selected_only": true,
        "save_init_img": false,
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        "clean_temp_dir_at_start": false,
        "save_incomplete_images": false,
        "outdir_samples": "",
        "outdir_txt2img_samples": "outputs/txt2img-images",
        "outdir_img2img_samples": "outputs/img2img-images",
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        "outdir_grids": "",
        "outdir_txt2img_grids": "outputs/txt2img-grids",
        "outdir_img2img_grids": "outputs/img2img-grids",
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        "outdir_init_images": "outputs/init-images",
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            "R-ESRGAN 4x+ Anime6B"
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        "enable_batch_seeds": true,
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        "randn_source": "GPU",
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        "sd_vae_explanation": "<abbr title='Variational autoencoder'>VAE</abbr> is a neural network that transforms a standard <abbr title='red/green/blue'>RGB</abbr>\nimage into latent space representation and back. Latent space representation is what stable diffusion is working on during sampling\n(i.e. when the progress bar is between empty and full). For txt2img, VAE is used to create a resulting image after the sampling is finished.\nFor img2img, VAE is used to process user's input image before the sampling, and to create an image after sampling.",
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        "textual_inversion_print_at_load": false,
        "textual_inversion_add_hashes_to_infotext": true,
        "sd_hypernetwork": "None",
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        "gradio_theme": "Default",
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        "return_grid": true,
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        "send_seed": true,
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        "hidden_tabs": [],
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        "referencing==0.30.2",
        "regex==2023.8.8",
        "requests-oauthlib==1.3.1",
        "requests==2.31.0",
        "resize-right==0.0.2",
        "rpds-py==0.10.2",
        "rsa==4.9",
        "safetensors==0.3.1",
        "scikit-image==0.21.0",
        "scipy==1.11.2",
        "semantic-version==2.10.0",
        "sentencepiece==0.1.99",
        "setuptools==65.5.0",
        "six==1.16.0",
        "smmap==5.0.0",
        "sniffio==1.3.0",
        "soupsieve==2.5",
        "starlette==0.26.1",
        "sympy==1.12",
        "tb-nightly==2.15.0a20230911",
        "tensorboard-data-server==0.7.1",
        "tifffile==2023.8.30",
        "timm==0.9.2",
        "tokenizers==0.13.3",
        "tomesd==0.1.3",
        "tomli==2.0.1",
        "toolz==0.12.0",
        "torch==2.0.1+cu118",
        "torchdiffeq==0.2.3",
        "torchmetrics==1.1.2",
        "torchsde==0.2.5",
        "torchvision==0.15.2+cu118",
        "tqdm==4.66.1",
        "trampoline==0.1.2",
        "transformers==4.30.2",
        "typing-extensions==4.7.1",
        "tzdata==2023.3",
        "urllib3==1.26.16",
        "uvicorn==0.23.2",
        "wcwidth==0.2.6",
        "websockets==11.0.3",
        "werkzeug==2.3.7",
        "wheel==0.41.2",
        "yapf==0.40.1",
        "yarl==1.9.2",
        "zipp==3.16.2"
    ]
}

### What browsers do you use to access the UI ?

Google Chrome

### Console logs

```Shell
venv "C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\venv\Scripts\Python.exe"
==============================================================================================================
INCOMPATIBLE PYTHON VERSION

This program is tested with 3.10.6 Python, but you have 3.11.5.
If you encounter an error with "RuntimeError: Couldn't install torch." message,
or any other error regarding unsuccessful package (library) installation,
please downgrade (or upgrade) to the latest version of 3.10 Python
and delete current Python and "venv" folder in WebUI's directory.

You can download 3.10 Python from here: https://www.python.org/downloads/release/python-3106/

Alternatively, use a binary release of WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases

Use --skip-python-version-check to suppress this warning.
==============================================================================================================
Python 3.11.5 (tags/v3.11.5:cce6ba9, Aug 24 2023, 14:38:34) [MSC v.1936 64 bit (AMD64)]
Version: v1.6.0
Commit hash: 5ef669de080814067961f28357256e8fe27544f4
Launching Web UI with arguments:
no module 'xformers'. Processing without...
no module 'xformers'. Processing without...
No module 'xformers'. Proceeding without it.
Loading weights [6ce0161689] from C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Creating model from config: C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\configs\v1-inference.yaml
Startup time: 9.4s (prepare environment: 1.9s, import torch: 2.8s, import gradio: 1.4s, setup paths: 0.7s, initialize shared: 0.4s, other imports: 0.6s, setup codeformer: 0.2s, load scripts: 0.8s, create ui: 0.3s, gradio launch: 0.3s).
Applying attention optimization: Doggettx... done.
Calculating sha256 for C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\embeddings\Peranza.pt: 797c28f4c2bfa1657425c876a2f3221898f6cd56e46736c0e5d0af52ef6eb5d6
Model loaded in 5.7s (load weights from disk: 0.5s, create model: 0.3s, apply weights to model: 2.4s, apply half(): 1.2s, calculate empty prompt: 1.2s).
Applying attention optimization: Doggettx... done.
*** Error completing request
*** Arguments: ('task(vj1hxqyrkp04hm1)', 'Peranza', '0.005', 1, 1, '', 'textual_inversion', 400, 400, False, 10000, 'value', '0.1', True, 0, 'once', False, 50, 50, 'style_filewords.txt', True, True, '', '', 20, 'DPM++ 2M Karras', 7, -1, 512, 512) {}
    Traceback (most recent call last):
      File "C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
                   ^^^^^^^^^^^^^^^^^^^^^
      File "C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
              ^^^^^^^^^^^^^^^^^^^^^
      File "C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\modules\textual_inversion\ui.py", line 33, in train_embedding
        embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args)
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
      File "C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\modules\textual_inversion\textual_inversion.py", line 395, in train_embedding
        validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_embedding_every, create_image_every, log_directory, name="embedding")
      File "C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\modules\textual_inversion\textual_inversion.py", line 372, in validate_train_inputs
        assert data_root, "Dataset directory is empty"
    AssertionError: Dataset directory is empty

---
Training at rate of 0.005 until step 10000
Preparing dataset...
100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00,  5.24it/s]
Training textual inversion [Epoch 16: 2/3] loss: 0.0035710:   0%|                   | 49/10000 [00:15<45:37,  3.64it/s]*** Error training embedding
    Traceback (most recent call last):
      File "C:\Users\yudko\Dropbox\PC (2)\Desktop\stable-diffusion-webui\modules\textual_inversion\textual_inversion.py", line 593, in train_embedding
        p.sampler_name = sd_samplers.samplers[int(preview_sampler_index)].name
                                              ^^^^^^^^^^^^^^^^^^^^^^^^^^
    ValueError: invalid literal for int() with base 10: 'DPM++ 2M Karras'
```


### Additional information

_No response_