chore: fix flake8 errors

This commit fixes flake8 errors that were introduced into the codebase
in the last months.

.flake8

@@ -1,3 +1,5 @@
 [flake8]
 max-line-length = 88
 extend-ignore = E203,E701
+per-file-ignores =
+    __init__.py: F401

runner/app/pipelines/optim/deepcache.py

@@ -1,7 +1,7 @@
 """This module provides a function to enable DeepCache optimization for the pipeline.
 
 For more information, see the DeepCache project on GitHub: https://github.com/horseee/DeepCache
-"""
+"""  # noqa: E501
 
 import logging
 

runner/app/pipelines/optim/sfast.py

@@ -1,7 +1,7 @@
 """This module provides a function to enable StableFast optimization for the pipeline.
 
 For more information, see the DeepCache project on GitHub: https://github.com/chengzeyi/stable-fast
-"""
+"""  # noqa: E501
 
 import logging
 
@@ -25,13 +25,13 @@ def compile_model(pipe):
     # NOTE: Disable Triton if kernel generation, compilation, and fine-tuning are slow,
     # especially due to insufficient GPU VRAM or outdated architecture.
     try:
-        import xformers
+        import xformers  # noqa: F401
 
         config.enable_xformers = True
     except ImportError:
         logger.info("xformers not installed, skip")
     try:
-        import triton
+        import triton   # noqa: F401
 
         config.enable_triton = True
     except ImportError:

runner/app/pipelines/utils/__init__.py

@@ -1,4 +1,6 @@
-"""This module contains several utility functions that are used across the pipelines module."""
+"""This module contains several utility functions that are used across the pipelines
+module.
+"""
 
 from app.pipelines.utils.utils import (
     SafetyChecker,

runner/app/pipelines/utils/audio.py

@@ -1,4 +1,6 @@
-"""This module provides functionality for converting audio files between different formats."""
+"""This module provides functionality for converting audio files between different
+formats.
+"""
 
 from io import BytesIO
 

runner/app/pipelines/utils/utils.py

@@ -93,7 +93,8 @@ def split_prompt(
         separator (str): The character used to split the input prompt. Defaults to '|'.
         key_prefix (str): Prefix for keys in the returned dictionary for all prompts,
             including the main prompt. Defaults to 'prompt'.
-        max_splits (int): Maximum number of splits to perform. Defaults to -1 (no limit).
+        max_splits (int): Maximum number of splits to perform. Defaults to -1 (no
+            limit).
 
     Returns:
         Dict[str, str]: A dictionary of all prompts, including the main prompt.

runner/app/routes/image_to_image.py

@@ -50,38 +50,55 @@ async def image_to_image(
     strength: Annotated[
         float,
         Form(
-            description="Degree of transformation applied to the reference image (0 to 1)."
+            description=(
+                "Degree of transformation applied to the reference image (0 to 1)."
+            )
         ),
     ] = 0.8,
     guidance_scale: Annotated[
         float,
         Form(
-            description="Encourages model to generate images closely linked to the text prompt (higher values may reduce image quality)."
+            description=(
+                "Encourages model to generate images closely linked to the text prompt "
+                "(higher values may reduce image quality)."
+            )
         ),
     ] = 7.5,
     image_guidance_scale: Annotated[
         float,
         Form(
-            description="Degree to which the generated image is pushed towards the initial image."
+            description=(
+                "Degree to which the generated image is pushed towards the initial "
+                "image."
+            )
         ),
     ] = 1.5,
     negative_prompt: Annotated[
         str,
         Form(
-            description="Text prompt(s) to guide what to exclude from image generation. Ignored if guidance_scale < 1."
+            description=(
+                "Text prompt(s) to guide what to exclude from image generation. "
+                "Ignored if guidance_scale < 1."
+            )
         ),
     ] = "",
     safety_check: Annotated[
         bool,
         Form(
-            description="Perform a safety check to estimate if generated images could be offensive or harmful."
+            description=(
+                "Perform a safety check to estimate if generated images could be "
+                "offensive or harmful."
+            )
         ),
     ] = True,
     seed: Annotated[int, Form(description="Seed for random number generation.")] = None,
     num_inference_steps: Annotated[
         int,
         Form(
-            description="Number of denoising steps. More steps usually lead to higher quality images but slower inference. Modulated by strength."
+            description=(
+                "Number of denoising steps. More steps usually lead to higher quality "
+                "images but slower inference. Modulated by strength."
+            )
         ),
     ] = 100,  # NOTE: Hardcoded due to varying pipeline values.
     num_images_per_prompt: Annotated[

runner/app/routes/image_to_video.py

@@ -53,26 +53,38 @@ async def image_to_video(
     motion_bucket_id: Annotated[
         int,
         Form(
-            description="Used for conditioning the amount of motion for the generation. The higher the number the more motion will be in the video."
+            description=(
+                "Used for conditioning the amount of motion for the generation. The "
+                "higher the number the more motion will be in the video."
+            )
         ),
     ] = 127,
     noise_aug_strength: Annotated[
         float,
         Form(
-            description="Amount of noise added to the conditioning image. Higher values reduce resemblance to the conditioning image and increase motion."
+            description=(
+                "Amount of noise added to the conditioning image. Higher values reduce "
+                "resemblance to the conditioning image and increase motion."
+            )
         ),
     ] = 0.02,
     safety_check: Annotated[
         bool,
         Form(
-            description="Perform a safety check to estimate if generated images could be offensive or harmful."
+            description=(
+                "Perform a safety check to estimate if generated images could be "
+                "offensive or harmful."
+            )
         ),
     ] = True,
     seed: Annotated[int, Form(description="Seed for random number generation.")] = None,
     num_inference_steps: Annotated[
         int,
         Form(
-            description="Number of denoising steps. More steps usually lead to higher quality images but slower inference. Modulated by strength."
+            description=(
+                "Number of denoising steps. More steps usually lead to higher quality "
+                "images but slower inference. Modulated by strength."
+            )
         ),
     ] = 25,  # NOTE: Hardcoded due to varying pipeline values.
     pipeline: Pipeline = Depends(get_pipeline),

runner/app/routes/text_to_image.py

@@ -28,7 +28,10 @@ class TextToImageParams(BaseModel):
     prompt: Annotated[
         str,
         Field(
-            description="Text prompt(s) to guide image generation. Separate multiple prompts with '|' if supported by the model."
+            description=(
+                "Text prompt(s) to guide image generation. Separate multiple prompts "
+                "with '|' if supported by the model."
+            )
         ),
     ]
     height: Annotated[
@@ -43,21 +46,30 @@ class TextToImageParams(BaseModel):
         float,
         Field(
             default=7.5,
-            description="Encourages model to generate images closely linked to the text prompt (higher values may reduce image quality).",
+            description=(
+                "Encourages model to generate images closely linked to the text prompt "
+                "(higher values may reduce image quality)."
+            ),
         ),
     ]
     negative_prompt: Annotated[
         str,
         Field(
             default="",
-            description="Text prompt(s) to guide what to exclude from image generation. Ignored if guidance_scale < 1.",
+            description=(
+                "Text prompt(s) to guide what to exclude from image generation. "
+                "Ignored if guidance_scale < 1."
+            ),
         ),
     ]
     safety_check: Annotated[
         bool,
         Field(
             default=True,
-            description="Perform a safety check to estimate if generated images could be offensive or harmful.",
+            description=(
+                "Perform a safety check to estimate if generated images could be "
+                "offensive or harmful."
+            ),
         ),
     ]
     seed: Annotated[
@@ -67,7 +79,10 @@ class TextToImageParams(BaseModel):
         int,
         Field(
             default=50,
-            description="Number of denoising steps. More steps usually lead to higher quality images but slower inference. Modulated by strength.",
+            description=(
+                "Number of denoising steps. More steps usually lead to higher quality "
+                "images but slower inference. Modulated by strength."
+            ),
         ),
     ]
     num_images_per_prompt: Annotated[

runner/app/routes/upscale.py

@@ -50,14 +50,20 @@ async def upscale(
     safety_check: Annotated[
         bool,
         Form(
-            description="Perform a safety check to estimate if generated images could be offensive or harmful."
+            description=(
+                "Perform a safety check to estimate if generated images could be "
+                "offensive or harmful."
+            )
         ),
     ] = True,
     seed: Annotated[int, Form(description="Seed for random number generation.")] = None,
     num_inference_steps: Annotated[
         int,
         Form(
-            description="Number of denoising steps. More steps usually lead to higher quality images but slower inference. Modulated by strength."
+            description=(
+                "Number of denoising steps. More steps usually lead to higher quality "
+                "images but slower inference. Modulated by strength."
+            )
         ),
     ] = 75,  # NOTE: Hardcoded due to varying pipeline values.
     pipeline: Pipeline = Depends(get_pipeline),

runner/bench.py

@@ -67,13 +67,16 @@ def bench_pipeline(
 
         print(f"inference {i} {batch_size=} time: {inference_time[i]:.3f}s")
         print(
-            f"inference {i} {batch_size=} time per output: {inference_time_per_output[i]:.3f}s"
+            f"inference {i} {batch_size=} time per output: "
+            f"{inference_time_per_output[i]:.3f}s"
         )
         print(
-            f"inference {i} {batch_size=} max GPU memory allocated: {max_mem_allocated[i]:.3f}GiB"
+            f"inference {i} {batch_size=} max GPU memory allocated: "
+            f"{max_mem_allocated[i]:.3f}GiB"
         )
         print(
-            f"inference {i} {batch_size=} max GPU memory reserved: {max_mem_reserved[i]:.3f}GiB"
+            f"inference {i} {batch_size=} max GPU memory reserved: "
+            f"{max_mem_reserved[i]:.3f}GiB"
         )
 
     return BenchMetrics(
@@ -116,7 +119,8 @@ def bench_pipeline(
     args = parser.parse_args()
 
     print(
-        f"{args.pipeline=} {args.model_id=} {args.runs=} {args.batch_size=} {args.num_inference_steps=}"
+        f"{args.pipeline=} {args.model_id=} {args.runs=} {args.batch_size=} "
+        f"{args.num_inference_steps=}"
     )
 
     start = time()
@@ -150,13 +154,16 @@ def bench_pipeline(
     if os.getenv("SFAST", "").strip().lower() == "true":
         print(f"avg warmup inference time: {warmup_metrics.inference_time:.3f}s")
         print(
-            f"avg warmup inference time per output: {warmup_metrics.inference_time_per_output:.3f}s"
+            f"avg warmup inference time per output: "
+            f"{warmup_metrics.inference_time_per_output:.3f}s"
         )
         print(
-            f"avg warmup inference max GPU memory allocated: {warmup_metrics.max_mem_allocated:.3f}GiB"
+            f"avg warmup inference max GPU memory allocated: "
+            f"{warmup_metrics.max_mem_allocated:.3f}GiB"
         )
         print(
-            f"avg warmup inference max GPU memory reserved: {warmup_metrics.max_mem_reserved:.3f}GiB"
+            f"avg warmup inference max GPU memory reserved: "
+            f"{warmup_metrics.max_mem_reserved:.3f}GiB"
         )
 
     print(f"avg inference time: {metrics.inference_time:.3f}s")

runner/gateway.openapi.json

@@ -639,17 +639,6 @@
                 "type": "object",
                 "title": "HTTPValidationError"
             },
-            "HealthCheck": {
-                "properties": {
-                    "status": {
-                        "type": "string",
-                        "title": "Status",
-                        "default": "OK"
-                    }
-                },
-                "type": "object",
-                "title": "HealthCheck"
-            },
             "ImageResponse": {
                 "properties": {
                     "images": {

runner/gen_openapi.py

@@ -1,7 +1,6 @@
 import argparse
 import copy
 import json
-import os
 
 import yaml
 from app.main import app, use_route_names_as_operation_ids
@@ -41,8 +40,9 @@ def translate_to_gateway(openapi):
     Returns:
         dict: The translated OpenAPI schema.
     """
-    # Remove 'health' endpoint
+    # Remove 'health' related endpoints and schemas.
     openapi["paths"].pop("/health")
+    openapi["components"]["schemas"].pop("HealthCheck")
 
     # Enforce 'model_id' in all endpoints
     for _, methods in openapi["paths"].items():