Dynamic prompt generation script for parameter scans (#2831)

# Programatically generate a large number of images varying by prompt
and other image generation parameters

This is a little standalone script named `dynamic_prompting.py` that
enables the generation of dynamic prompts. Using YAML syntax, you
specify a template of prompt phrases and lists of generation parameters,
and the script will generate a cross product of prompts and generation
settings for you. You can save these prompts to disk for later use, or
pipe them to the invokeai CLI to generate the images on the fly.

Typical uses are testing step and CFG values systematically while
holding the seed and prompt constant, testing out various artist's
styles, and comparing the results of the same prompt across different
models.

A typical template will look like this:

```
model: stable-diffusion-1.5
steps: 30;50;10
seed: 50
dimensions: 512x512
cfg:
  - 7
  - 12
sampler:
  - k_euler_a
  - k_lms
prompt:
  style:
       - greg rutkowski
       - gustav klimt
  location:
       - the mountains
       - a desert
  object:
       - luxurious dwelling
       - crude tent
  template: a {object} in {location}, in the style of {style}
```

This will generate 96 different images, each of which varies by one of
the dimensions specified in the template. For example, the prompt axis
will generate a cross product list like:
```
a luxurious dwelling in the mountains, in the style of greg rutkowski
a luxurious dwelling in the mountains, in the style of gustav klimt
a luxious dwelling in a desert, in the style of greg rutkowski
... etc
```

A typical usage would be:
```
python scripts/dynamic_prompts.py --invoke --outdir=/tmp/scanning my_template.yaml
```
This will populate `/tmp/scanning` with each of the requested images,
and also generate a `log.md` file which you can open with an e-book
reader to show something like this:


![image](https://user-images.githubusercontent.com/111189/221970165-4bbd9070-3f32-4d89-8ff2-b03a82ada575.png)

Full instructions can be obtained using the `--instructions` switch, and
an example template can be printed out using `--example`:

```
python scripts/dynamic_prompts.py --instructions
python scripts/dynamic_prompts.py --example > my_first_template.yaml
```

Author: lstein

invokeai/frontend/stats.html

@@ -200,6 +200,8 @@ def __init__(
         # it wasn't actually doing anything. This logic could be reinstated.
         self.device = torch.device(choose_torch_device())
         print(f">> Using device_type {self.device.type}")
+        if self.device.type == 'cuda':
+            print(f">> CUDA device '{torch.cuda.get_device_name(torch.cuda.current_device())}' (GPU {os.environ.get('CUDA_VISIBLE_DEVICES') or 0})")
         if full_precision:
             if self.precision != "auto":
                 raise ValueError("Remove --full_precision / -F if using --precision")

ldm/generate.py

@@ -389,6 +389,7 @@ def image_writer(
                         prior_variations,
                         postprocessed,
                         first_seed,
+                        gen.model_name,
                     )
                     path = file_writer.save_image_and_prompt_to_png(
                         image=image,
@@ -402,6 +403,7 @@ def image_writer(
                                 else first_seed
                             ],
                             model_hash=gen.model_hash,
+                            model_id=gen.model_name,
                         ),
                         name=filename,
                         compress_level=opt.png_compression,
@@ -941,21 +943,24 @@ def add_postprocessing_to_metadata(opt, original_file, new_file, tool, command):
 
 
 def prepare_image_metadata(
-    opt,
-    prefix,
-    seed,
-    operation="generate",
-    prior_variations=[],
-    postprocessed=False,
-    first_seed=None,
+        opt,
+        prefix,
+        seed,
+        operation="generate",
+        prior_variations=[],
+        postprocessed=False,
+        first_seed=None,
+        model_id='unknown',
 ):
     if postprocessed and opt.save_original:
         filename = choose_postprocess_name(opt, prefix, seed)
     else:
         wildcards = dict(opt.__dict__)
         wildcards["prefix"] = prefix
         wildcards["seed"] = seed
+        wildcards["model_id"] = model_id
         try:
+            print(f'DEBUG: fnformat={opt.fnformat}')
             filename = opt.fnformat.format(**wildcards)
         except KeyError as e:
             print(
@@ -972,18 +977,17 @@ def prepare_image_metadata(
         first_seed = first_seed or seed
         this_variation = [[seed, opt.variation_amount]]
         opt.with_variations = prior_variations + this_variation
-        formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed)
+        formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed,model_id=model_id)
     elif len(prior_variations) > 0:
-        formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed)
+        formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed,model_id=model_id)
     elif operation == "postprocess":
         formatted_dream_prompt = "!fix " + opt.dream_prompt_str(
-            seed=seed, prompt=opt.input_file_path
+            seed=seed, prompt=opt.input_file_path, model_id=model_id,
         )
     else:
-        formatted_dream_prompt = opt.dream_prompt_str(seed=seed)
+        formatted_dream_prompt = opt.dream_prompt_str(seed=seed,model_id=model_id)
     return filename, formatted_dream_prompt
 
-
 def choose_postprocess_name(opt, prefix, seed) -> str:
     match = re.search("postprocess:(\w+)", opt.last_operation)
     if match:

ldm/invoke/CLI.py

@@ -333,7 +333,7 @@ def dream_prompt_str(self,**kwargs):
             switches.append(f'-V {formatted_variations}')
         if 'variations' in a and len(a['variations'])>0:
             switches.append(f'-V {a["variations"]}')
-        return ' '.join(switches)
+        return ' '.join(switches) + f' # model_id={kwargs.get("model_id","unknown model")}'
 
     def __getattribute__(self,name):
         '''
@@ -878,7 +878,7 @@ def _create_dream_cmd_parser(self):
         )
         render_group.add_argument(
             '--fnformat',
-            default='{prefix}.{seed}.png',
+            default=None,
             type=str,
             help='Overwrite the filename format. You can use any argument as wildcard enclosed in curly braces. Default is {prefix}.{seed}.png',
         )
@@ -1155,6 +1155,7 @@ def format_metadata(**kwargs):
 def metadata_dumps(opt,
                    seeds=[],
                    model_hash=None,
+                   model_id=None,
                    postprocessing=None):
     '''
     Given an Args object, returns a dict containing the keys and
@@ -1167,7 +1168,7 @@ def metadata_dumps(opt,
     # top-level metadata minus `image` or `images`
     metadata = {
         'model'       : 'stable diffusion',
-        'model_id'    : opt.model,
+        'model_id'    : model_id or opt.model,
         'model_hash'  : model_hash,
         'app_id'      : ldm.invoke.__app_id__,
         'app_version' : ldm.invoke.__version__,