From 29d06a049b568f8e000225b73edaf918a9996079 Mon Sep 17 00:00:00 2001 From: tazlin Date: Sat, 20 Jul 2024 17:31:58 -0400 Subject: [PATCH 01/12] fix: don't collect custom node stdout ComfyUI uses logger now and all of the emitted messages are captured/handled elsewhere --- hordelib/comfy_horde.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/hordelib/comfy_horde.py b/hordelib/comfy_horde.py index 996132b..72109f4 100644 --- a/hordelib/comfy_horde.py +++ b/hordelib/comfy_horde.py @@ -366,11 +366,8 @@ def __init__( # Load our pipelines self._load_pipelines() - stdio = OutputCollector() - with contextlib.redirect_stdout(stdio): - # Load our custom nodes - self._load_custom_nodes() - stdio.replay() + # Load our custom nodes + self._load_custom_nodes() self._comfyui_callback = comfyui_callback From 03980533919f1170cfd5bc1f3deceb604f57633f Mon Sep 17 00:00:00 2001 From: tazlin Date: Sat, 20 Jul 2024 18:29:26 -0400 Subject: [PATCH 02/12] fix: use latest compat. horde deps --- requirements.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/requirements.txt b/requirements.txt index 90cec3c..ae77512 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,7 +1,7 @@ # Add this in for tox, comment out for build --extra-index-url https://download.pytorch.org/whl/cu121 -horde_sdk>=0.13.0 -horde_model_reference>=0.7.0 +horde_sdk>=0.13.1 +horde_model_reference>=0.8.0 pydantic numpy==1.26.4 torch>=2.3.1 From 8a088b9804421addbf1341c2d6b26845d12c7ec5 Mon Sep 17 00:00:00 2001 From: tazlin Date: Sat, 20 Jul 2024 18:34:44 -0400 Subject: [PATCH 03/12] fix: better SDXL hires + calc steps more effectively --- hordelib/horde.py | 60 ++++-- hordelib/initialisation.py | 3 +- hordelib/model_manager/base.py | 17 +- hordelib/shared_model_manager.py | 8 +- hordelib/utils/image_utils.py | 111 +++++++++++ images_expected/lora_blue_hires_fix.png | Bin 1199964 -> 1197085 bytes images_expected/lora_character_hires_fix.png | Bin 2854892 -> 2908218 bytes .../lora_character_hires_fix_sdxl.png | Bin 0 -> 2358885 bytes .../sdxl_text_to_image_hires_fix.png | Bin 2588076 -> 2630266 bytes tests/conftest.py | 186 +++++++++++++++++- tests/test_utils.py | 59 ++++++ tests/testing_shared_classes.py | 19 ++ 12 files changed, 423 insertions(+), 40 deletions(-) create mode 100644 images_expected/lora_character_hires_fix_sdxl.png create mode 100644 tests/testing_shared_classes.py diff --git a/hordelib/horde.py b/hordelib/horde.py index 404dea7..8ff40c6 100644 --- a/hordelib/horde.py +++ b/hordelib/horde.py @@ -13,6 +13,7 @@ from enum import Enum, auto from types import FunctionType +from horde_model_reference.meta_consts import get_baseline_native_resolution from horde_sdk.ai_horde_api.apimodels import ImageGenerateJobPopResponse from horde_sdk.ai_horde_api.apimodels.base import ( GenMetadataEntry, @@ -78,15 +79,32 @@ def __init__( self.faults = faults -def _calc_upscale_sampler_steps(payload): - """Calculates the amount of hires_fix upscaler steps based on the denoising used and the steps used for the - primary image""" - upscale_steps = round(payload["ddim_steps"] * (0.9 - payload["hires_fix_denoising_strength"])) - if upscale_steps < 3: - upscale_steps = 3 +def _calc_upscale_sampler_steps( + payload: dict, +) -> int: + """Use `ImageUtils.calc_upscale_sampler_steps(...)` to calculate the number of steps for the upscale sampler. - logger.debug(f"Upscale steps calculated as {upscale_steps}") - return upscale_steps + Args: + payload (dict): The payload to use for the calculation. + + Returns: + int: The number of steps to use. + """ + model_name = payload.get("model_name") + baseline = None + native_resolution = None + if model_name is not None: + baseline = SharedModelManager.model_reference_manager.stable_diffusion.get_model_baseline(model_name) + if baseline is not None: + native_resolution = get_baseline_native_resolution(baseline) + + return ImageUtils.calc_upscale_sampler_steps( + model_native_resolution=native_resolution, + width=payload.get("width"), + height=payload.get("height"), + hires_fix_denoising_strength=payload.get("hires_fix_denoising_strength"), + ddim_steps=payload.get("ddim_steps"), + ) class HordeLib: @@ -874,16 +892,22 @@ def _final_pipeline_adjustments(self, payload, pipeline_data) -> tuple[dict, lis baseline = None if model_details: baseline = model_details.get("baseline") - if baseline and (baseline == "stable_cascade" or baseline == "stable_diffusion_xl"): - new_width, new_height = ImageUtils.get_first_pass_image_resolution_max( - original_width, - original_height, - ) - else: - new_width, new_height = ImageUtils.get_first_pass_image_resolution_min( - original_width, - original_height, - ) + if baseline: + if baseline == "stable_cascade": + new_width, new_height = ImageUtils.get_first_pass_image_resolution_max( + original_width, + original_height, + ) + elif baseline == "stable_diffusion_xl": + new_width, new_height = ImageUtils.get_first_pass_image_resolution_sdxl( + original_width, + original_height, + ) + else: # fall through case; only `stable diffusion 1`` at time of writing + new_width, new_height = ImageUtils.get_first_pass_image_resolution_min( + original_width, + original_height, + ) # This is the *target* resolution pipeline_params["latent_upscale.width"] = original_width diff --git a/hordelib/initialisation.py b/hordelib/initialisation.py index 0577637..014d8e4 100644 --- a/hordelib/initialisation.py +++ b/hordelib/initialisation.py @@ -27,6 +27,7 @@ def initialise( force_normal_vram_mode: bool = True, extra_comfyui_args: list[str] | None = None, disable_smart_memory: bool = False, + do_not_load_model_mangers: bool = False, ): """Initialise hordelib. This is required before using any other hordelib functions. @@ -96,7 +97,7 @@ def initialise( # Initialise model manager from hordelib.shared_model_manager import SharedModelManager - SharedModelManager() + SharedModelManager(do_not_load_model_mangers=do_not_load_model_mangers) sys.argv = sys_arg_bkp diff --git a/hordelib/model_manager/base.py b/hordelib/model_manager/base.py index eca5042..56abfe7 100644 --- a/hordelib/model_manager/base.py +++ b/hordelib/model_manager/base.py @@ -138,22 +138,7 @@ def load_model_database(self) -> None: ) def download_model_reference(self) -> dict: - try: - logger.debug(f"Downloading Model Reference for {self.models_db_name}") - response = requests.get(self.remote_db) - logger.debug("Downloaded Model Reference successfully") - models = response.json() - logger.info("Updated Model Reference from remote.") - return models - except Exception as e: # XXX Double check and/or rework this - logger.error( - f"Download failed: {e}", - ) - logger.warning("Model Reference not downloaded, using local copy") - if self.models_db_path.exists(): - return json.loads(self.models_db_path.read_text()) - logger.error("No local copy of Model Reference found!") - return {} + raise NotImplementedError("Downloading model databases is no longer supported within hordelib.") def get_free_ram_mb(self) -> int: """Returns the amount of free RAM in MB rounded down to the nearest integer. diff --git a/hordelib/shared_model_manager.py b/hordelib/shared_model_manager.py index e546423..6ac25d3 100644 --- a/hordelib/shared_model_manager.py +++ b/hordelib/shared_model_manager.py @@ -6,7 +6,7 @@ import torch from horde_model_reference import get_model_reference_file_path -from horde_model_reference.legacy import LegacyReferenceDownloadManager +from horde_model_reference.model_reference_manager import ModelReferenceManager from loguru import logger from typing_extensions import Self @@ -59,6 +59,7 @@ def do_migrations(): class SharedModelManager: _instance: Self = None # type: ignore manager: ModelManager + model_reference_manager: ModelReferenceManager cuda_available: bool def __new__(cls, do_not_load_model_mangers: bool = False): @@ -101,16 +102,17 @@ def load_model_managers( args_passed = locals().copy() # XXX This is temporary args_passed.pop("cls") # XXX This is temporary - lrdm = LegacyReferenceDownloadManager() if download_legacy_references: try: - lrdm.download_all_legacy_model_references(overwrite_existing=overwrite_existing_references) + cls.model_reference_manager = ModelReferenceManager(download_and_convert_legacy_dbs=True) except Exception as e: logger.error(f"Failed to download legacy model references: {e}") logger.error( "If this continues to happen, " "github may be down or your internet connection may be having issues.", ) + else: + cls.model_reference_manager = ModelReferenceManager() references = {} for reference in managers_to_load: diff --git a/hordelib/utils/image_utils.py b/hordelib/utils/image_utils.py index 19c0dd2..6d75937 100644 --- a/hordelib/utils/image_utils.py +++ b/hordelib/utils/image_utils.py @@ -10,6 +10,20 @@ DEFAULT_IMAGE_MIN_RESOLUTION = 512 DEFAULT_HIGHER_RES_MAX_RESOLUTION = 1024 +IDEAL_SDXL_RESOLUTIONS = [ + (1024, 1024), + (1152, 896), + (896, 1152), + (1216, 832), + (832, 1216), + (1344, 768), + (768, 1344), + (1536, 640), + (640, 1536), +] + +IDEAL_SDXL_RESOLUTIONS_ASPECT_RATIOS = [width / height for width, height in IDEAL_SDXL_RESOLUTIONS] + class ImageUtils: @classmethod @@ -110,6 +124,103 @@ def get_first_pass_image_resolution_max( ) return width, height + @classmethod + def get_first_pass_image_resolution_sdxl( + cls, + width: int, + height: int, + ): + """Resize the image dimensions fit in one of the pre-defined SDXL resolution buckets which most closely + matches the aspect ratio of the image. + """ + + aspect_ratio = width / height + closest_aspect_ratio = min( + IDEAL_SDXL_RESOLUTIONS_ASPECT_RATIOS, + key=lambda x: abs(aspect_ratio - x), + ) + + index = IDEAL_SDXL_RESOLUTIONS_ASPECT_RATIOS.index(closest_aspect_ratio) + return IDEAL_SDXL_RESOLUTIONS[index] + + @staticmethod + def calc_upscale_sampler_steps( + model_native_resolution: int | None, + width: int, + height: int, + hires_fix_denoising_strength: float, + ddim_steps: int, + ) -> int: + """Calculate the number of upscale steps to use for the upscale sampler based on the input parameters. + + Note: The resulting values are non-linear to the input values. The heuristic is based on the native resolution + of the model, the requested resolution, the denoising strength and the number of steps used for the ddim + sampler. + + Args: + model_name (str | None): The model name to use for the calculation. + width (int): The width of the image to generate. + height (int): The height of the image to generate. + hires_fix_denoising_strength (float): The denoising strength to use for the upscale sampler. + ddim_steps (int): The number of steps used for the sampler. + + Returns: + int: The number of upscale steps to use for the upscale sampler. + """ + MIN_DENOISING_STRENGTH = 0.01 + MAX_DENOISING_STRENGTH = 1.0 + DECAY_RATE = 2 + """The rate at which the upscale steps decay based on the denoising strength""" + MIN_STEPS = 3 + """The minimum number of steps to use for the upscaling sampler""" + UPSCALE_ADJUSTMENT_FACTOR = 0.5 + """The factor by which the upscale steps are adjusted based on the native resolution distance factor""" + UPSCALE_DIVISOR = 2.25 + """The divisor used to adjust the upscale steps based on the native resolution distance factor""" + + STANDARD_RESOLUTION = 512 + + native_resolution_distance_factor: float = 0 + + if model_native_resolution is not None: + native_resolution_pixels = model_native_resolution * model_native_resolution + + requested_pixels = width * height + native_resolution_distance_factor = requested_pixels / native_resolution_pixels + + resolution_penalty = 3 * (STANDARD_RESOLUTION / model_native_resolution) + native_resolution_distance_factor /= resolution_penalty + + hires_fix_denoising_strength = max( + MIN_DENOISING_STRENGTH, + min(MAX_DENOISING_STRENGTH, hires_fix_denoising_strength), + ) + + scale = ddim_steps - MIN_STEPS + upscale_steps = round(MIN_STEPS + scale * (hires_fix_denoising_strength**DECAY_RATE)) + + # if native_resolution_distance_factor > NATIVE_RESOLUTION_THRESHOLD: + upscale_steps = round( + upscale_steps * ((1 / (UPSCALE_ADJUSTMENT_FACTOR**native_resolution_distance_factor)) / UPSCALE_DIVISOR), + ) + + logger.debug(f"Upscale steps calculated as {upscale_steps}") + + if ddim_steps <= 18: + logger.debug(f"Upscale steps increased by {MIN_STEPS} due to low requested ddim steps") + upscale_steps += MIN_STEPS + + if upscale_steps > ddim_steps: + logger.debug(f"Upscale steps adjusted to {ddim_steps} from {upscale_steps}") + upscale_steps = ddim_steps + + step_floor = min(6, ddim_steps) + if step_floor > upscale_steps: + logger.debug(f"Upscale steps adjusted to {step_floor} from {upscale_steps}") + upscale_steps = step_floor + + return upscale_steps + @classmethod def add_image_alpha_channel(cls, source_image, alpha_image): # Convert images to RGBA mode diff --git a/images_expected/lora_blue_hires_fix.png b/images_expected/lora_blue_hires_fix.png index 23550bce7e72c169a7691c01149a31516165943a..8c15b701dcd901cc3734156b7c19bcc05a05e76b 100644 GIT binary patch literal 1197085 zcmV(tKijYzc)=YYcnSZ1|1bZ0 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