Fix to use SD15Txt2Img.

cmd/infrasctucture.py

@@ -0,0 +1,98 @@
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING
+
+import modal
+
+if TYPE_CHECKING:
+    from domain import Prompts, Seed
+
+
+class Txt2ImgInterface(ABC):
+    @abstractmethod
+    def run_inference(self, seed: Seed) -> list[bytes]:
+        pass
+
+
+class SDXLTxt2Img(Txt2ImgInterface):
+    def __init__(self, prompts: Prompts, output_format: str, *, use_upscaler: bool) -> None:
+        self.__prompts = prompts
+        self.__output_format = output_format
+        self.__use_upscaler = use_upscaler
+        self.__run_inference = modal.Function.from_name(
+            "stable-diffusion-cli",
+            "SDXLTxt2Img.run_inference",
+        )
+
+    def run_inference(self, seed: Seed) -> list[bytes]:
+        return self.__run_inference.remote(
+            prompt=self.__prompts.prompt,
+            n_prompt=self.__prompts.n_prompt,
+            height=self.__prompts.height,
+            width=self.__prompts.width,
+            steps=self.__prompts.steps,
+            seed=seed.value,
+            use_upscaler=self.__use_upscaler,
+            output_format=self.__output_format,
+        )
+
+
+class SD15Txt2Img(Txt2ImgInterface):
+    def __init__(
+        self,
+        prompts: Prompts,
+        output_format: str,
+        *,
+        use_upscaler: bool,
+        fix_by_controlnet_tile: bool,
+    ) -> None:
+        self.__prompts = prompts
+        self.__output_format = output_format
+        self.__use_upscaler = use_upscaler
+        self.__fix_by_controlnet_tile = fix_by_controlnet_tile
+        self.__run_inference = modal.Function.from_name(
+            "stable-diffusion-cli",
+            "SD15.run_txt2img_inference",
+        )
+
+    def run_inference(self, seed: Seed) -> list[bytes]:
+        return self.__run_inference.remote(
+            prompt=self.__prompts.prompt,
+            n_prompt=self.__prompts.n_prompt,
+            height=self.__prompts.height,
+            width=self.__prompts.width,
+            batch_size=1,
+            steps=self.__prompts.steps,
+            seed=seed.value,
+            use_upscaler=self.__use_upscaler,
+            fix_by_controlnet_tile=self.__fix_by_controlnet_tile,
+            output_format=self.__output_format,
+        )
+
+
+def new_txt2img(
+    version: str,
+    prompts: Prompts,
+    output_format: str,
+    *,
+    use_upscaler: bool,
+    fix_by_controlnet_tile: bool,
+) -> Txt2ImgInterface:
+    match version:
+        case "sd15":
+            return SD15Txt2Img(
+                prompts=prompts,
+                output_format=output_format,
+                use_upscaler=use_upscaler,
+                fix_by_controlnet_tile=fix_by_controlnet_tile,
+            )
+        case "sdxl":
+            return SDXLTxt2Img(
+                prompts=prompts,
+                use_upscaler=use_upscaler,
+                output_format=output_format,
+            )
+        case _:
+            msg = f"Invalid version: {version}. Must be 'sd15' or 'sdxl'."
+            raise ValueError(msg)

cmd/sdxl_txt2img.py

@@ -5,33 +5,7 @@ import time
 
 import modal
 from domain import OutputDirectory, Prompts, Seed, StableDiffusionOutputManger
-from infrasctucture import RunInferenceInterface, RunInferenceSDXLTxt2Img
-
-
-def new_run_inference(
-    version: str,
-    prompts: Prompts,
-    output_format: str,
-    *,
-    use_upscaler: bool,
-) -> RunInferenceInterface:
-    match version:
-        case "sd15":
-            # TODO: sd15用のクラスを実装したら置き換える
-            return RunInferenceSDXLTxt2Img(
-                prompts=prompts,
-                use_upscaler=use_upscaler,
-                output_format=output_format,
-            )
-        case "sdxl":
-            return RunInferenceSDXLTxt2Img(
-                prompts=prompts,
-                use_upscaler=use_upscaler,
-                output_format=output_format,
-            )
-        case _:
-            msg = f"Invalid version: {version}. Must be 'sd15' or 'sdxl'."
-            raise ValueError(msg)
+from infrasctucture import new_txt2img
 
 
 @modal.App("run-stable-diffusion-cli").local_entrypoint()
@@ -45,6 +19,7 @@ def main(
     steps: int = 20,
     seed: int = -1,
     use_upscaler: str = "False",
+    fix_by_controlnet_tile: str = "True",
     output_format: str = "png",
 ) -> None:
     """This function is the entrypoint for the Runway CLI.
@@ -65,17 +40,18 @@ def main(
     prompts = Prompts(prompt, n_prompt, height, width, samples, steps)
     sd_output_manager = StableDiffusionOutputManger(prompts, directory_path)
 
-    run_inference = new_run_inference(
+    txt2img = new_txt2img(
         version,
         prompts,
         output_format,
         use_upscaler=use_upscaler == "True",
+        fix_by_controlnet_tile=fix_by_controlnet_tile == "True",
     )
 
     for sample_index in range(samples):
         start_time = time.time()
         new_seed = Seed(seed)
-        images = run_inference.exec(new_seed)
+        images = txt2img.run_inference(new_seed)
         for generated_image_index, image_bytes in enumerate(images):
             saved_path = sd_output_manager.save_image(
                 image_bytes,