From 1bd386f98bb076fe62696808e02a9bd9b9b64b42 Mon Sep 17 00:00:00 2001
From: Volpeon <git@volpeon.ink>
Date: Fri, 23 Dec 2022 21:47:12 +0100
Subject: Improved class prompt handling

---
 data/csv.py | 29 ++++++++++++-----------------
 1 file changed, 12 insertions(+), 17 deletions(-)

(limited to 'data/csv.py')

diff --git a/data/csv.py b/data/csv.py
index d400757..e25dd3f 100644
--- a/data/csv.py
+++ b/data/csv.py
@@ -38,6 +38,7 @@ class CSVDataItem(NamedTuple):
     instance_image_path: Path
     class_image_path: Path
     prompt: list[str]
+    cprompt: str
     nprompt: str
 
 
@@ -47,8 +48,6 @@ class CSVDataModule():
             batch_size: int,
             data_file: str,
             prompt_processor: PromptProcessor,
-            instance_identifier: str,
-            class_identifier: Optional[str] = None,
             class_subdir: str = "cls",
             num_class_images: int = 100,
             size: int = 512,
@@ -77,8 +76,6 @@ class CSVDataModule():
         self.num_class_images = num_class_images
 
         self.prompt_processor = prompt_processor
-        self.instance_identifier = instance_identifier
-        self.class_identifier = class_identifier
         self.size = size
         self.repeats = repeats
         self.dropout = dropout
@@ -96,14 +93,18 @@ class CSVDataModule():
     def prepare_items(self, template, expansions, data) -> list[CSVDataItem]:
         image = template["image"] if "image" in template else "{}"
         prompt = template["prompt"] if "prompt" in template else "{content}"
+        cprompt = template["cprompt"] if "cprompt" in template else "{content}"
         nprompt = template["nprompt"] if "nprompt" in template else "{content}"
 
         return [
             CSVDataItem(
                 self.data_root.joinpath(image.format(item["image"])),
                 None,
-                prompt_to_keywords(prompt.format(
-                    **prepare_prompt(item["prompt"] if "prompt" in item else "")), expansions),
+                prompt_to_keywords(
+                    prompt.format(**prepare_prompt(item["prompt"] if "prompt" in item else "")),
+                    expansions
+                ),
+                cprompt.format(**prepare_prompt(item["cprompt"] if "cprompt" in item else "")),
                 nprompt.format(**prepare_prompt(item["nprompt"] if "nprompt" in item else "")),
             )
             for item in data
@@ -123,6 +124,7 @@ class CSVDataModule():
                 item.instance_image_path,
                 self.class_root.joinpath(f"{item.instance_image_path.stem}_{i}{item.instance_image_path.suffix}"),
                 item.prompt,
+                item.cprompt,
                 item.nprompt,
             )
             for item in items
@@ -160,12 +162,10 @@ class CSVDataModule():
 
     def setup(self, stage=None):
         train_dataset = CSVDataset(self.data_train, self.prompt_processor, batch_size=self.batch_size,
-                                   instance_identifier=self.instance_identifier, class_identifier=self.class_identifier,
                                    num_class_images=self.num_class_images,
                                    size=self.size, interpolation=self.interpolation,
                                    center_crop=self.center_crop, repeats=self.repeats, dropout=self.dropout)
         val_dataset = CSVDataset(self.data_val, self.prompt_processor, batch_size=self.batch_size,
-                                 instance_identifier=self.instance_identifier,
                                  size=self.size, interpolation=self.interpolation,
                                  center_crop=self.center_crop)
         self.train_dataloader_ = DataLoader(train_dataset, batch_size=self.batch_size,
@@ -187,9 +187,7 @@ class CSVDataset(Dataset):
         self,
         data: List[CSVDataItem],
         prompt_processor: PromptProcessor,
-        instance_identifier: str,
         batch_size: int = 1,
-        class_identifier: Optional[str] = None,
         num_class_images: int = 0,
         size: int = 512,
         repeats: int = 1,
@@ -201,8 +199,6 @@ class CSVDataset(Dataset):
         self.data = data
         self.prompt_processor = prompt_processor
         self.batch_size = batch_size
-        self.instance_identifier = instance_identifier
-        self.class_identifier = class_identifier
         self.num_class_images = num_class_images
         self.dropout = dropout
         self.image_cache = {}
@@ -239,14 +235,12 @@ class CSVDataset(Dataset):
 
         return image
 
-    def get_input_ids(self, prompt, identifier):
-        return self.prompt_processor.get_input_ids(prompt.format(identifier))
-
     def get_example(self, i):
         item = self.data[i % self.num_instance_images]
 
         example = {}
         example["prompts"] = item.prompt
+        example["cprompts"] = item.cprompt
         example["nprompts"] = item.nprompt
         example["instance_images"] = self.get_image(item.instance_image_path)
         if self.num_class_images != 0:
@@ -260,13 +254,14 @@ class CSVDataset(Dataset):
         example = {}
 
         example["prompts"] = keywords_to_prompt(unprocessed_example["prompts"], self.dropout)
+        example["cprompts"] = unprocessed_example["cprompts"]
         example["nprompts"] = unprocessed_example["nprompts"]
 
         example["instance_images"] = self.image_transforms(unprocessed_example["instance_images"])
-        example["instance_prompt_ids"] = self.get_input_ids(example["prompts"], self.instance_identifier)
+        example["instance_prompt_ids"] = self.prompt_processor.get_input_ids(example["prompts"])
 
         if self.num_class_images != 0:
             example["class_images"] = self.image_transforms(unprocessed_example["class_images"])
-            example["class_prompt_ids"] = self.get_input_ids(example["prompts"], self.class_identifier)
+            example["class_prompt_ids"] = self.prompt_processor.get_input_ids(example["cprompts"])
 
         return example
-- 
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