diff --git a/README.md b/README.md index 63218b4..8ca3b02 100644 --- a/README.md +++ b/README.md @@ -29,9 +29,6 @@ poetry shell # test you can run this command skynet --help -# launch ipfs node -skynet run ipfs - # to launch worker skynet run dgpu @@ -77,9 +74,6 @@ docker pull guilledk/skynet:runtime-cuda # or build it (takes a bit of time) ./build_docker.sh -# launch simple ipfs node -./launch_ipfs.sh - # run worker with all gpus docker run \ -it \ diff --git a/docker/Dockerfile.runtime+cuda-py312 b/docker/Dockerfile.runtime+cuda-py312 new file mode 100644 index 0000000..43ad864 --- /dev/null +++ b/docker/Dockerfile.runtime+cuda-py312 @@ -0,0 +1,45 @@ +from nvidia/cuda:12.4.1-devel-ubuntu22.04 +from python:3.12 + +env DEBIAN_FRONTEND=noninteractive + +run apt-get update && apt-get install -y \ + git \ + llvm \ + ffmpeg \ + libsm6 \ + libxext6 \ + ninja-build + +# env CC /usr/bin/clang +# env CXX /usr/bin/clang++ +# +# # install llvm10 as required by llvm-lite +# run git clone https://github.com/llvm/llvm-project.git -b llvmorg-10.0.1 +# workdir /llvm-project +# # this adds a commit from 12.0.0 that fixes build on newer compilers +# run git cherry-pick -n b498303066a63a203d24f739b2d2e0e56dca70d1 +# run cmake -S llvm -B build -G Ninja -DCMAKE_BUILD_TYPE=Release +# run ninja -C build install # -j8 + +run curl -sSL https://install.python-poetry.org | python3 - + +env PATH "/root/.local/bin:$PATH" + +copy . /skynet + +workdir /skynet + +env POETRY_VIRTUALENVS_PATH /skynet/.venv + +run poetry install --with=cuda -v + +workdir /root/target + +env PYTORCH_CUDA_ALLOC_CONF max_split_size_mb:128 +env NVIDIA_VISIBLE_DEVICES=all + +copy docker/entrypoint.sh /entrypoint.sh +entrypoint ["/entrypoint.sh"] + +cmd ["skynet", "--help"] diff --git a/docker/build_docker.sh b/docker/build_docker.sh index 2e152fc..0eaf2a7 100755 --- a/docker/build_docker.sh +++ b/docker/build_docker.sh @@ -1,20 +1,7 @@ - docker build \ - -t guilledk/skynet:runtime \ - -f docker/Dockerfile.runtime . + -t guilledk/skynet:runtime-cuda-py312 \ + -f docker/Dockerfile.runtime+cuda-py312 . -docker build \ - -t guilledk/skynet:runtime-frontend \ - -f docker/Dockerfile.runtime+frontend . - -docker build \ - -t guilledk/skynet:runtime-cuda-py311 \ - -f docker/Dockerfile.runtime+cuda-py311 . - -docker build \ - -t guilledk/skynet:runtime-cuda \ - -f docker/Dockerfile.runtime+cuda-py311 . - -docker build \ - -t guilledk/skynet:runtime-cuda-py310 \ - -f docker/Dockerfile.runtime+cuda-py310 . +# docker build \ +# -t guilledk/skynet:runtime-cuda \ +# -f docker/Dockerfile.runtime+cuda-py311 . diff --git a/poetry.lock b/poetry.lock index 82832c8..a274848 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,44 +1,46 @@ -# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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optional = true @@ -32,31 +37,33 @@ optional = true [tool.poetry.group.dev.dependencies] pdbpp = {version = '^0.10.3'} pytest = {version = '^7.4.2'} +pytest-trio = "^0.8.0" [tool.poetry.group.cuda] optional = true [tool.poetry.group.cuda.dependencies] -torch = {version = '2.0.1+cu118', source = 'torch'} -scipy = {version = '^1.11.2'} -numba = {version = '0.57.0'} +torch = {version = '2.5.1+cu121', source = 'torch'} +scipy = {version = '1.15.1'} +numba = {version = '0.60.0'} quart = {version = '^0.19.3'} -triton = {version = '2.0.0', source = 'torch'} -basicsr = {version = '^1.4.2'} -xformers = {version = '^0.0.22'} +triton = {version = '3.1.0', source = 'torch'} +xformers = {version = '^0.0.29'} hypercorn = {version = '^0.14.4'} -diffusers = {version = '^0.21.2'} -realesrgan = {version = '^0.3.0'} +diffusers = {version = '0.32.1'} quart-trio = {version = '^0.11.0'} -torchvision = {version = '0.15.2+cu118', source = 'torch'} -accelerate = {version = '^0.23.0'} -transformers = {version = 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Asset from .config import * from .constants import * @@ -20,7 +20,7 @@ def skynet(*args, **kwargs): @click.command() -@click.option('--model', '-m', default='midj') +@click.option('--model', '-m', default=list(MODELS.keys())[-1]) @click.option( '--prompt', '-p', default='a red old tractor in a sunny wheat field') @click.option('--output', '-o', default='output.png') @@ -39,7 +39,7 @@ def txt2img(*args, **kwargs): utils.txt2img(hf_token, **kwargs) @click.command() -@click.option('--model', '-m', default=list(MODELS.keys())[0]) +@click.option('--model', '-m', default=list(MODELS.keys())[-2]) @click.option( '--prompt', '-p', default='a red old tractor in a sunny wheat field') @click.option('--input', '-i', default='input.png') @@ -66,6 +66,37 @@ def img2img(model, prompt, input, output, strength, guidance, steps, seed): seed=seed ) + +@click.command() +@click.option('--model', '-m', default=list(MODELS.keys())[-3]) +@click.option( + '--prompt', '-p', default='a red old tractor in a sunny wheat field') +@click.option('--input', '-i', default='input.png') +@click.option('--mask', '-M', default='mask.png') +@click.option('--output', '-o', default='output.png') +@click.option('--strength', '-Z', default=1.0) +@click.option('--guidance', '-g', default=10.0) +@click.option('--steps', '-s', default=26) +@click.option('--seed', '-S', default=None) +def inpaint(model, prompt, input, mask, output, strength, guidance, steps, seed): + from . import utils + config = load_skynet_toml() + hf_token = load_key(config, 'skynet.dgpu.hf_token') + hf_home = load_key(config, 'skynet.dgpu.hf_home') + set_hf_vars(hf_token, hf_home) + utils.inpaint( + hf_token, + model=model, + prompt=prompt, + img_path=input, + mask_path=mask, + output=output, + strength=strength, + guidance=guidance, + steps=steps, + seed=seed + ) + @click.command() @click.option('--input', '-i', default='input.png') @click.option('--output', '-o', default='output.png') @@ -147,7 +178,7 @@ def enqueue( 'user': Name(account), 'request_body': req, 'binary_data': binary, - 'reward': asset_from_str(reward), + 'reward': Asset.from_str(reward), 'min_verification': 1 }, account, key, permission, diff --git a/skynet/constants.py b/skynet/constants.py index 07412a4..6bc1867 100755 --- a/skynet/constants.py +++ b/skynet/constants.py @@ -4,31 +4,120 @@ VERSION = '0.1a12' DOCKER_RUNTIME_CUDA = 'skynet:runtime-cuda' -MODELS = { - 'prompthero/openjourney': {'short': 'midj', 'mem': 6}, - 'runwayml/stable-diffusion-v1-5': {'short': 'stable', 'mem': 6}, - 'stabilityai/stable-diffusion-2-1-base': {'short': 'stable2', 'mem': 6}, - 'snowkidy/stable-diffusion-xl-base-0.9': {'short': 'stablexl0.9', 'mem': 8.3}, - 'Linaqruf/anything-v3.0': {'short': 'hdanime', 'mem': 6}, - 'hakurei/waifu-diffusion': {'short': 'waifu', 'mem': 6}, - 'nitrosocke/Ghibli-Diffusion': {'short': 'ghibli', 'mem': 6}, - 'dallinmackay/Van-Gogh-diffusion': {'short': 'van-gogh', 'mem': 6}, - 'lambdalabs/sd-pokemon-diffusers': {'short': 'pokemon', 'mem': 6}, - 'Envvi/Inkpunk-Diffusion': {'short': 'ink', 'mem': 6}, - 'nousr/robo-diffusion': {'short': 'robot', 'mem': 6}, +import msgspec +from typing import Literal - # default is always last - 'stabilityai/stable-diffusion-xl-base-1.0': {'short': 'stablexl', 'mem': 8.3}, +class Size(msgspec.Struct): + w: int + h: int + +class ModelDesc(msgspec.Struct): + short: str + mem: float + size: Size + tags: list[Literal['txt2img', 'img2img', 'inpaint']] + +MODELS: dict[str, ModelDesc] = { + 'runwayml/stable-diffusion-v1-5': ModelDesc( + short='stable', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'stabilityai/stable-diffusion-2-1-base': ModelDesc( + short='stable2', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'snowkidy/stable-diffusion-xl-base-0.9': ModelDesc( + short='stablexl0.9', + mem=8.3, + size=Size(w=1024, h=1024), + tags=['txt2img'] + ), + 'Linaqruf/anything-v3.0': ModelDesc( + short='hdanime', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'hakurei/waifu-diffusion': ModelDesc( + short='waifu', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'nitrosocke/Ghibli-Diffusion': ModelDesc( + short='ghibli', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'dallinmackay/Van-Gogh-diffusion': ModelDesc( + short='van-gogh', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'lambdalabs/sd-pokemon-diffusers': ModelDesc( + short='pokemon', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'Envvi/Inkpunk-Diffusion': ModelDesc( + short='ink', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'nousr/robo-diffusion': ModelDesc( + short='robot', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img'] + ), + 'black-forest-labs/FLUX.1-schnell': ModelDesc( + short='flux', + mem=24, + size=Size(w=1024, h=1024), + tags=['txt2img'] + ), + 'black-forest-labs/FLUX.1-Fill-dev': ModelDesc( + short='flux-inpaint', + mem=24, + size=Size(w=1024, h=1024), + tags=['inpaint'] + ), + 'diffusers/stable-diffusion-xl-1.0-inpainting-0.1': ModelDesc( + short='stablexl-inpaint', + mem=8.3, + size=Size(w=1024, h=1024), + tags=['inpaint'] + ), + 'prompthero/openjourney': ModelDesc( + short='midj', + mem=6, + size=Size(w=512, h=512), + tags=['txt2img', 'img2img'] + ), + 'stabilityai/stable-diffusion-xl-base-1.0': ModelDesc( + short='stablexl', + mem=8.3, + size=Size(w=1024, h=1024), + tags=['txt2img'] + ), } SHORT_NAMES = [ - model_info['short'] + model_info.short for model_info in MODELS.values() ] def get_model_by_shortname(short: str): for model, info in MODELS.items(): - if short == info['short']: + if short == info.short: return model N = '\n' @@ -166,9 +255,7 @@ DEFAULT_UPSCALER = None DEFAULT_CONFIG_PATH = 'skynet.toml' -DEFAULT_INITAL_MODELS = [ - 'stabilityai/stable-diffusion-xl-base-1.0' -] +DEFAULT_INITAL_MODEL = list(MODELS.keys())[-1] DATE_FORMAT = '%B the %dth %Y, %H:%M:%S' @@ -193,3 +280,221 @@ TG_MAX_WIDTH = 1280 TG_MAX_HEIGHT = 1280 DEFAULT_SINGLE_CARD_MAP = 'cuda:0' + +GPU_CONTRACT_ABI = { + "version": "eosio::abi/1.2", + "types": [], + "structs": [ + { + "name": "account", + "base": "", + "fields": [ + {"name": "user", "type": "name"}, + {"name": "balance", "type": "asset"}, + {"name": "nonce", "type": "uint64"} + ] + }, + { + "name": "card", + "base": "", + "fields": [ + {"name": "id", "type": "uint64"}, + {"name": "owner", "type": "name"}, + {"name": "card_name", "type": "string"}, + {"name": "version", "type": "string"}, + {"name": "total_memory", "type": "uint64"}, + {"name": "mp_count", "type": "uint32"}, + {"name": "extra", "type": "string"} + ] + }, + { + "name": "clean", + "base": "", + "fields": [] + }, + { + "name": "config", + "base": "", + "fields": [ + {"name": "token_contract", "type": "name"}, + {"name": "token_symbol", "type": "symbol"} + ] + }, + { + "name": "dequeue", + "base": "", + "fields": [ + {"name": "user", "type": "name"}, + {"name": "request_id", "type": "uint64"} + ] + }, + { + "name": "enqueue", + "base": "", + "fields": [ + {"name": "user", "type": "name"}, + {"name": "request_body", "type": "string"}, + {"name": "binary_data", "type": "string"}, + {"name": "reward", "type": "asset"}, + {"name": "min_verification", "type": "uint32"} + ] + }, + { + "name": "gcfgstruct", + "base": "", + "fields": [ + {"name": "token_contract", "type": "name"}, + {"name": "token_symbol", "type": "symbol"} + ] + }, + { + "name": "submit", + "base": "", + "fields": [ + {"name": "worker", "type": "name"}, + {"name": "request_id", "type": "uint64"}, + {"name": "request_hash", "type": "checksum256"}, + {"name": "result_hash", "type": "checksum256"}, + {"name": "ipfs_hash", "type": "string"} + ] + }, + { + "name": "withdraw", + "base": "", + "fields": [ + {"name": "user", "type": "name"}, + {"name": "quantity", "type": "asset"} + ] + }, + { + "name": "work_request_struct", + "base": "", + "fields": [ + {"name": "id", "type": "uint64"}, + {"name": "user", "type": "name"}, + {"name": "reward", "type": "asset"}, + {"name": "min_verification", "type": "uint32"}, + {"name": "nonce", "type": "uint64"}, + {"name": "body", "type": "string"}, + {"name": "binary_data", "type": "string"}, + {"name": "timestamp", "type": "time_point_sec"} + ] + }, + { + "name": "work_result_struct", + "base": "", + "fields": [ + {"name": "id", "type": "uint64"}, + {"name": "request_id", "type": "uint64"}, + {"name": "user", "type": "name"}, + {"name": "worker", "type": "name"}, + {"name": "result_hash", "type": "checksum256"}, + {"name": "ipfs_hash", "type": "string"}, + {"name": "submited", "type": "time_point_sec"} + ] + }, + { + "name": "workbegin", + "base": "", + "fields": [ + {"name": "worker", "type": "name"}, + {"name": "request_id", "type": "uint64"}, + {"name": "max_workers", "type": "uint32"} + ] + }, + { + "name": "workcancel", + "base": "", + "fields": [ + {"name": "worker", "type": "name"}, + {"name": "request_id", "type": "uint64"}, + {"name": "reason", "type": "string"} + ] + }, + { + "name": "worker", + "base": "", + "fields": [ + {"name": "account", "type": "name"}, + {"name": "joined", "type": "time_point_sec"}, + {"name": "left", "type": "time_point_sec"}, + {"name": "url", "type": "string"} + ] + }, + { + "name": "worker_status_struct", + "base": "", + "fields": [ + {"name": "worker", "type": "name"}, + {"name": "status", "type": "string"}, + {"name": "started", "type": "time_point_sec"} + ] + } + ], + "actions": [ + {"name": "clean", "type": "clean", "ricardian_contract": ""}, + {"name": "config", "type": "config", "ricardian_contract": ""}, + {"name": "dequeue", "type": "dequeue", "ricardian_contract": ""}, + {"name": "enqueue", "type": "enqueue", "ricardian_contract": ""}, + {"name": "submit", "type": "submit", "ricardian_contract": ""}, + {"name": "withdraw", "type": "withdraw", "ricardian_contract": ""}, + {"name": "workbegin", "type": "workbegin", "ricardian_contract": ""}, + {"name": "workcancel", "type": "workcancel", "ricardian_contract": ""} + ], + "tables": [ + { + "name": "cards", + "index_type": "i64", + "key_names": [], + "key_types": [], + "type": "card" + }, + { + "name": "gcfgstruct", + "index_type": "i64", + "key_names": [], + "key_types": [], + "type": "gcfgstruct" + }, + { + "name": "queue", + "index_type": "i64", + "key_names": [], + "key_types": [], + "type": "work_request_struct" + }, + { + "name": "results", + "index_type": "i64", + "key_names": [], + "key_types": [], + "type": "work_result_struct" + }, + { + "name": "status", + "index_type": "i64", + "key_names": [], + "key_types": [], + "type": "worker_status_struct" + }, + { + "name": "users", + "index_type": "i64", + "key_names": [], + "key_types": [], + "type": "account" + }, + { + "name": "workers", + "index_type": "i64", + "key_names": [], + "key_types": [], + "type": "worker" + } + ], + "ricardian_clauses": [], + "error_messages": [], + "abi_extensions": [], + "variants": [], + "action_results": [] +} diff --git a/skynet/dgpu/compute.py b/skynet/dgpu/compute.py index de8a7b6..4523d48 100644 --- a/skynet/dgpu/compute.py +++ b/skynet/dgpu/compute.py @@ -13,36 +13,48 @@ from diffusers import DiffusionPipeline import trio import torch -from skynet.constants import DEFAULT_INITAL_MODELS, MODELS +from skynet.constants import DEFAULT_INITAL_MODEL, MODELS from skynet.dgpu.errors import DGPUComputeError, DGPUInferenceCancelled from skynet.utils import crop_image, convert_from_cv2_to_image, convert_from_image_to_cv2, convert_from_img_to_bytes, init_upscaler, pipeline_for - def prepare_params_for_diffuse( params: dict, - input_type: str, - binary = None + mode: str, + inputs: list[bytes] ): _params = {} - if binary != None: - match input_type: - case 'png': - image = crop_image( - binary, params['width'], params['height']) + match mode: + case 'inpaint': + image = crop_image( + inputs[0], params['width'], params['height']) - _params['image'] = image + mask = crop_image( + inputs[1], params['width'], params['height']) + + _params['image'] = image + _params['mask_image'] = mask + + if 'flux' in params['model'].lower(): + _params['max_sequence_length'] = 512 + else: _params['strength'] = float(params['strength']) - case 'none': - ... + case 'img2img': + image = crop_image( + inputs[0], params['width'], params['height']) - case _: - raise DGPUComputeError(f'Unknown input_type {input_type}') + _params['image'] = image + _params['strength'] = float(params['strength']) - else: - _params['width'] = int(params['width']) - _params['height'] = int(params['height']) + case 'txt2img' | 'diffuse': + ... + + case _: + raise DGPUComputeError(f'Unknown mode {mode}') + + # _params['width'] = int(params['width']) + # _params['height'] = int(params['height']) return ( params['prompt'], @@ -57,95 +69,55 @@ def prepare_params_for_diffuse( class SkynetMM: def __init__(self, config: dict): - self.upscaler = init_upscaler() - self.initial_models = ( - config['initial_models'] - if 'initial_models' in config else DEFAULT_INITAL_MODELS - ) - self.cache_dir = None if 'hf_home' in config: self.cache_dir = config['hf_home'] - self._models = {} - for model in self.initial_models: - self.load_model(model, False, force=True) + self._model_name = '' + self._model_mode = '' + + # self.load_model(DEFAULT_INITAL_MODEL, 'txt2img') def log_debug_info(self): logging.info('memory summary:') logging.info('\n' + torch.cuda.memory_summary()) - def is_model_loaded(self, model_name: str, image: bool): - for model_key, model_data in self._models.items(): - if (model_key == model_name and - model_data['image'] == image): - return True + def is_model_loaded(self, name: str, mode: str): + if (name == self._model_name and + mode == self._model_mode): + return True return False + def unload_model(self): + if getattr(self, '_model', None): + del self._model + + gc.collect() + torch.cuda.empty_cache() + + self._model_name = '' + self._model_mode = '' + def load_model( self, - model_name: str, - image: bool, - force=False + name: str, + mode: str ): - logging.info(f'loading model {model_name}...') - if force or len(self._models.keys()) == 0: - pipe = pipeline_for( - model_name, image=image, cache_dir=self.cache_dir) + logging.info(f'loading model {name}...') + self.unload_model() + self._model = pipeline_for( + name, mode, cache_dir=self.cache_dir) + self._model_mode = mode + self._model_name = name - self._models[model_name] = { - 'pipe': pipe, - 'generated': 0, - 'image': image - } - - else: - least_used = list(self._models.keys())[0] - - for model in self._models: - if self._models[ - least_used]['generated'] > self._models[model]['generated']: - least_used = model - - del self._models[least_used] - - logging.info(f'swapping model {least_used} for {model_name}...') - - gc.collect() - torch.cuda.empty_cache() - - pipe = pipeline_for( - model_name, image=image, cache_dir=self.cache_dir) - - self._models[model_name] = { - 'pipe': pipe, - 'generated': 0, - 'image': image - } - - logging.info(f'loaded model {model_name}') - return pipe - - def get_model(self, model_name: str, image: bool) -> DiffusionPipeline: - if model_name not in MODELS: - raise DGPUComputeError(f'Unknown model {model_name}') - - if not self.is_model_loaded(model_name, image): - pipe = self.load_model(model_name, image=image) - - else: - pipe = self._models[model_name]['pipe'] - - return pipe def compute_one( self, request_id: int, method: str, params: dict, - input_type: str = 'png', - binary: bytes | None = None + inputs: list[bytes] = [] ): def maybe_cancel_work(step, *args, **kwargs): if self._should_cancel: @@ -154,6 +126,8 @@ class SkynetMM: logging.warn(f'cancelling work at step {step}') raise DGPUInferenceCancelled() + return {} + maybe_cancel_work(0) output_type = 'png' @@ -163,20 +137,29 @@ class SkynetMM: output = None output_hash = None try: - match method: - case 'diffuse': - arguments = prepare_params_for_diffuse( - params, input_type, binary=binary) - prompt, guidance, step, seed, upscaler, extra_params = arguments - model = self.get_model(params['model'], 'image' in extra_params) + name = params['model'] - output = model( + match method: + case 'diffuse' | 'txt2img' | 'img2img' | 'inpaint': + if not self.is_model_loaded(name, method): + self.load_model(name, method) + + arguments = prepare_params_for_diffuse( + params, method, inputs) + prompt, guidance, step, seed, upscaler, extra_params = arguments + + if 'flux' in name.lower(): + extra_params['callback_on_step_end'] = maybe_cancel_work + + else: + extra_params['callback'] = maybe_cancel_work + extra_params['callback_steps'] = 1 + + output = self._model( prompt, guidance_scale=guidance, num_inference_steps=step, generator=seed, - callback=maybe_cancel_work, - callback_steps=1, **extra_params ).images[0] @@ -185,7 +168,7 @@ class SkynetMM: case 'png': if upscaler == 'x4': input_img = output.convert('RGB') - up_img, _ = self.upscaler.enhance( + up_img, _ = init_upscaler().enhance( convert_from_image_to_cv2(input_img), outscale=4) output = convert_from_cv2_to_image(up_img) @@ -197,6 +180,22 @@ class SkynetMM: output_hash = sha256(output_binary).hexdigest() + case 'upscale': + if self._model_mode != 'upscale': + self.unload_model() + self._model = init_upscaler() + self._model_mode = 'upscale' + self._model_name = 'realesrgan' + + input_img = inputs[0].convert('RGB') + up_img, _ = self._model.enhance( + convert_from_image_to_cv2(input_img), outscale=4) + + output = convert_from_cv2_to_image(up_img) + + output_binary = convert_from_img_to_bytes(output) + output_hash = sha256(output_binary).hexdigest() + case _: raise DGPUComputeError('Unsupported compute method') diff --git a/skynet/dgpu/daemon.py b/skynet/dgpu/daemon.py index 7cd68d2..220fe3c 100644 --- a/skynet/dgpu/daemon.py +++ b/skynet/dgpu/daemon.py @@ -117,6 +117,103 @@ class SkynetDGPUDaemon: return app + async def maybe_serve_one(self, req): + rid = req['id'] + + # parse request + body = json.loads(req['body']) + model = body['params']['model'] + + # if model not known + if model != 'RealESRGAN_x4plus' and model not in MODELS: + logging.warning(f'Unknown model {model}') + return False + + # if whitelist enabled and model not in it continue + if (len(self.model_whitelist) > 0 and + not model in self.model_whitelist): + return False + + # if blacklist contains model skip + if model in self.model_blacklist: + return False + + my_results = [res['id'] for res in self._snap['my_results']] + if rid not in my_results and rid in self._snap['requests']: + statuses = self._snap['requests'][rid] + + if len(statuses) == 0: + inputs = [] + for _input in req['binary_data'].split(','): + if _input: + for _ in range(3): + try: + img = await self.conn.get_input_data(_input) + inputs.append(img) + break + + except: + ... + + hash_str = ( + str(req['nonce']) + + + req['body'] + + + req['binary_data'] + ) + logging.info(f'hashing: {hash_str}') + request_hash = sha256(hash_str.encode('utf-8')).hexdigest() + + # TODO: validate request + + # perform work + logging.info(f'working on {body}') + + resp = await self.conn.begin_work(rid) + if not resp or 'code' in resp: + logging.info(f'probably being worked on already... skip.') + + else: + try: + output_type = 'png' + if 'output_type' in body['params']: + output_type = body['params']['output_type'] + + output = None + output_hash = None + match self.backend: + case 'sync-on-thread': + self.mm._should_cancel = self.should_cancel_work + output_hash, output = await trio.to_thread.run_sync( + partial( + self.mm.compute_one, + rid, + body['method'], body['params'], + inputs=inputs + ) + ) + + case _: + raise DGPUComputeError(f'Unsupported backend {self.backend}') + self._last_generation_ts = datetime.now().isoformat() + self._last_benchmark = self._benchmark + self._benchmark = [] + + ipfs_hash = await self.conn.publish_on_ipfs(output, typ=output_type) + + await self.conn.submit_work(rid, request_hash, output_hash, ipfs_hash) + + except BaseException as e: + traceback.print_exc() + await self.conn.cancel_work(rid, str(e)) + + finally: + return True + + else: + logging.info(f'request {rid} already beign worked on, skip...') + async def serve_forever(self): try: while True: @@ -133,92 +230,8 @@ class SkynetDGPUDaemon: ) for req in queue: - rid = req['id'] - - # parse request - body = json.loads(req['body']) - model = body['params']['model'] - - # if model not known - if model not in MODELS: - logging.warning(f'Unknown model {model}') - continue - - # if whitelist enabled and model not in it continue - if (len(self.model_whitelist) > 0 and - not model in self.model_whitelist): - continue - - # if blacklist contains model skip - if model in self.model_blacklist: - continue - - my_results = [res['id'] for res in self._snap['my_results']] - if rid not in my_results and rid in self._snap['requests']: - statuses = self._snap['requests'][rid] - - if len(statuses) == 0: - binary, input_type = await self.conn.get_input_data(req['binary_data']) - - hash_str = ( - str(req['nonce']) - + - req['body'] - + - req['binary_data'] - ) - logging.info(f'hashing: {hash_str}') - request_hash = sha256(hash_str.encode('utf-8')).hexdigest() - - # TODO: validate request - - # perform work - logging.info(f'working on {body}') - - resp = await self.conn.begin_work(rid) - if 'code' in resp: - logging.info(f'probably being worked on already... skip.') - - else: - try: - output_type = 'png' - if 'output_type' in body['params']: - output_type = body['params']['output_type'] - - output = None - output_hash = None - match self.backend: - case 'sync-on-thread': - self.mm._should_cancel = self.should_cancel_work - output_hash, output = await trio.to_thread.run_sync( - partial( - self.mm.compute_one, - rid, - body['method'], body['params'], - input_type=input_type, - binary=binary - ) - ) - - case _: - raise DGPUComputeError(f'Unsupported backend {self.backend}') - self._last_generation_ts = datetime.now().isoformat() - self._last_benchmark = self._benchmark - self._benchmark = [] - - ipfs_hash = await self.conn.publish_on_ipfs(output, typ=output_type) - - await self.conn.submit_work(rid, request_hash, output_hash, ipfs_hash) - - except BaseException as e: - traceback.print_exc() - await self.conn.cancel_work(rid, str(e)) - - finally: - break - - else: - logging.info(f'request {rid} already beign worked on, skip...') + if (await self.maybe_serve_one(req)): + break await trio.sleep(1) diff --git a/skynet/dgpu/network.py b/skynet/dgpu/network.py index dfe4d67..85c4d92 100644 --- a/skynet/dgpu/network.py +++ b/skynet/dgpu/network.py @@ -8,15 +8,16 @@ import logging from pathlib import Path from functools import partial -import asks import trio +import leap import anyio +import httpx from PIL import Image, UnidentifiedImageError from leap.cleos import CLEOS -from leap.sugar import Checksum256, Name, asset_from_str -from skynet.constants import DEFAULT_IPFS_DOMAIN +from leap.protocol import Asset +from skynet.constants import DEFAULT_IPFS_DOMAIN, GPU_CONTRACT_ABI from skynet.ipfs import AsyncIPFSHTTP, get_ipfs_file from skynet.dgpu.errors import DGPUComputeError @@ -32,25 +33,25 @@ async def failable(fn: partial, ret_fail=None): except ( OSError, json.JSONDecodeError, - asks.errors.RequestTimeout, - asks.errors.BadHttpResponse, - anyio.BrokenResourceError - ): + anyio.BrokenResourceError, + httpx.ReadError, + leap.errors.TransactionPushError + ) as e: return ret_fail class SkynetGPUConnector: def __init__(self, config: dict): - self.account = Name(config['account']) + self.account = config['account'] self.permission = config['permission'] self.key = config['key'] self.node_url = config['node_url'] self.hyperion_url = config['hyperion_url'] - self.cleos = CLEOS( - None, None, self.node_url, remote=self.node_url) + self.cleos = CLEOS(endpoint=self.node_url) + self.cleos.load_abi('gpu.scd', GPU_CONTRACT_ABI) self.ipfs_gateway_url = None if 'ipfs_gateway_url' in config: @@ -151,11 +152,11 @@ class SkynetGPUConnector: self.cleos.a_push_action, 'gpu.scd', 'workbegin', - { + list({ 'worker': self.account, 'request_id': request_id, 'max_workers': 2 - }, + }.values()), self.account, self.key, permission=self.permission ) @@ -168,11 +169,11 @@ class SkynetGPUConnector: self.cleos.a_push_action, 'gpu.scd', 'workcancel', - { + list({ 'worker': self.account, 'request_id': request_id, 'reason': reason - }, + }.values()), self.account, self.key, permission=self.permission ) @@ -191,10 +192,10 @@ class SkynetGPUConnector: self.cleos.a_push_action, 'gpu.scd', 'withdraw', - { + list({ 'user': self.account, - 'quantity': asset_from_str(balance) - }, + 'quantity': Asset.from_str(balance) + }.values()), self.account, self.key, permission=self.permission ) @@ -226,13 +227,13 @@ class SkynetGPUConnector: self.cleos.a_push_action, 'gpu.scd', 'submit', - { + list({ 'worker': self.account, 'request_id': request_id, - 'request_hash': Checksum256(request_hash), - 'result_hash': Checksum256(result_hash), + 'request_hash': request_hash, + 'result_hash': result_hash, 'ipfs_hash': ipfs_hash - }, + }.values()), self.account, self.key, permission=self.permission ) @@ -267,46 +268,15 @@ class SkynetGPUConnector: return file_cid - async def get_input_data(self, ipfs_hash: str) -> tuple[bytes, str]: - input_type = 'none' + async def get_input_data(self, ipfs_hash: str) -> Image: + link = f'https://{self.ipfs_domain}/ipfs/{ipfs_hash}' - if ipfs_hash == '': - return b'', input_type + res = await get_ipfs_file(link, timeout=1) + logging.info(f'got response from {link}') + if not res or res.status_code != 200: + logging.warning(f'couldn\'t get ipfs binary data at {link}!') - results = {} - ipfs_link = f'https://{self.ipfs_domain}/ipfs/{ipfs_hash}' - ipfs_link_legacy = ipfs_link + '/image.png' + # attempt to decode as image + input_data = Image.open(io.BytesIO(res.raw)) - async with trio.open_nursery() as n: - async def get_and_set_results(link: str): - res = await get_ipfs_file(link, timeout=1) - logging.info(f'got response from {link}') - if not res or res.status_code != 200: - logging.warning(f'couldn\'t get ipfs binary data at {link}!') - - else: - try: - # attempt to decode as image - results[link] = Image.open(io.BytesIO(res.raw)) - input_type = 'png' - n.cancel_scope.cancel() - - except UnidentifiedImageError: - logging.warning(f'couldn\'t get ipfs binary data at {link}!') - - n.start_soon( - get_and_set_results, ipfs_link) - n.start_soon( - get_and_set_results, ipfs_link_legacy) - - input_data = None - if ipfs_link_legacy in results: - input_data = results[ipfs_link_legacy] - - if ipfs_link in results: - input_data = results[ipfs_link] - - if input_data == None: - raise DGPUComputeError('Couldn\'t gather input data from ipfs') - - return input_data, input_type + return input_data diff --git a/skynet/dgpu/pipes/flux.py b/skynet/dgpu/pipes/flux.py new file mode 100644 index 0000000..57642c0 --- /dev/null +++ b/skynet/dgpu/pipes/flux.py @@ -0,0 +1,50 @@ +#!/usr/bin/python + +import torch + +from diffusers import ( + DiffusionPipeline, + FluxPipeline, + FluxTransformer2DModel +) +from transformers import T5EncoderModel, BitsAndBytesConfig + +from huggingface_hub import hf_hub_download + +__model = { + 'name': 'black-forest-labs/FLUX.1-schnell' +} + +def pipeline_for( + model: str, + mode: str, + mem_fraction: float = 1.0, + cache_dir: str | None = None +) -> DiffusionPipeline: + qonfig = BitsAndBytesConfig( + load_in_4bit=True, + bnb_4bit_quant_type="nf4", + ) + params = { + 'torch_dtype': torch.bfloat16, + 'cache_dir': cache_dir, + 'device_map': 'balanced', + 'max_memory': {'cpu': '10GiB', 0: '11GiB'} + # 'max_memory': {0: '11GiB'} + } + + text_encoder = T5EncoderModel.from_pretrained( + 'black-forest-labs/FLUX.1-schnell', + subfolder="text_encoder_2", + torch_dtype=torch.bfloat16, + quantization_config=qonfig + ) + params['text_encoder_2'] = text_encoder + + pipe = FluxPipeline.from_pretrained( + model, **params) + + pipe.vae.enable_tiling() + pipe.vae.enable_slicing() + + return pipe diff --git a/skynet/dgpu/pipes/flux_inpaint.py b/skynet/dgpu/pipes/flux_inpaint.py new file mode 100644 index 0000000..2f88d58 --- /dev/null +++ b/skynet/dgpu/pipes/flux_inpaint.py @@ -0,0 +1,56 @@ +#!/usr/bin/python + +import torch + +from diffusers import ( + DiffusionPipeline, + FluxFillPipeline, + FluxTransformer2DModel +) +from transformers import T5EncoderModel, BitsAndBytesConfig + +__model = { + 'name': 'black-forest-labs/FLUX.1-Fill-dev' +} + +def pipeline_for( + model: str, + mode: str, + mem_fraction: float = 1.0, + cache_dir: str | None = None +) -> DiffusionPipeline: + qonfig = BitsAndBytesConfig( + load_in_4bit=True, + bnb_4bit_quant_type="nf4", + ) + params = { + 'torch_dtype': torch.bfloat16, + 'cache_dir': cache_dir, + 'device_map': 'balanced', + 'max_memory': {'cpu': '10GiB', 0: '11GiB'} + # 'max_memory': {0: '11GiB'} + } + + text_encoder = T5EncoderModel.from_pretrained( + 'sayakpaul/FLUX.1-Fill-dev-nf4', + subfolder="text_encoder_2", + torch_dtype=torch.bfloat16, + quantization_config=qonfig + ) + params['text_encoder_2'] = text_encoder + + transformer = FluxTransformer2DModel.from_pretrained( + 'sayakpaul/FLUX.1-Fill-dev-nf4', + subfolder="transformer", + torch_dtype=torch.bfloat16, + quantization_config=qonfig + ) + params['transformer'] = transformer + + pipe = FluxFillPipeline.from_pretrained( + model, **params) + + pipe.vae.enable_tiling() + pipe.vae.enable_slicing() + + return pipe diff --git a/skynet/frontend/__init__.py b/skynet/frontend/__init__.py index 30d6fa1..bb5e9bc 100644 --- a/skynet/frontend/__init__.py +++ b/skynet/frontend/__init__.py @@ -39,7 +39,7 @@ def validate_user_config_request(req: str): case 'model' | 'algo': attr = 'model' val = params[2] - shorts = [model_info['short'] for model_info in MODELS.values()] + shorts = [model_info.short for model_info in MODELS.values()] if val not in shorts: raise ConfigUnknownAlgorithm(f'no model named {val}') @@ -112,20 +112,10 @@ def validate_user_config_request(req: str): def perform_auto_conf(config: dict) -> dict: - model = config['model'] - prefered_size_w = 512 - prefered_size_h = 512 - - if 'xl' in model: - prefered_size_w = 1024 - prefered_size_h = 1024 - - else: - prefered_size_w = 512 - prefered_size_h = 512 + model = MODELS[config['model']] config['step'] = random.randint(20, 35) - config['width'] = prefered_size_w - config['height'] = prefered_size_h + config['width'] = model.size.w + config['height'] = model.size.h return config diff --git a/skynet/frontend/telegram/__init__.py b/skynet/frontend/telegram/__init__.py index d4fd549..2dd54a3 100644 --- a/skynet/frontend/telegram/__init__.py +++ b/skynet/frontend/telegram/__init__.py @@ -14,7 +14,7 @@ from contextlib import AsyncExitStack from contextlib import asynccontextmanager as acm from leap.cleos import CLEOS -from leap.sugar import Name, asset_from_str, collect_stdout +from leap.protocol import Name, Asset from leap.hyperion import HyperionAPI from telebot.types import InputMediaPhoto @@ -43,7 +43,6 @@ class SkynetTelegramFrontend: db_user: str, db_pass: str, ipfs_node: str, - remote_ipfs_node: str | None, key: str, explorer_domain: str, ipfs_domain: str @@ -56,22 +55,19 @@ class SkynetTelegramFrontend: self.db_host = db_host self.db_user = db_user self.db_pass = db_pass - self.remote_ipfs_node = remote_ipfs_node self.key = key self.explorer_domain = explorer_domain self.ipfs_domain = ipfs_domain self.bot = AsyncTeleBot(token, exception_handler=SKYExceptionHandler) - self.cleos = CLEOS(None, None, url=node_url, remote=node_url) + self.cleos = CLEOS(endpoint=node_url) + self.cleos.load_abi('gpu.scd', GPU_CONTRACT_ABI) self.hyperion = HyperionAPI(hyperion_url) self.ipfs_node = AsyncIPFSHTTP(ipfs_node) self._async_exit_stack = AsyncExitStack() async def start(self): - if self.remote_ipfs_node: - await self.ipfs_node.connect(self.remote_ipfs_node) - self.db_call = await self._async_exit_stack.enter_async_context( open_database_connection( self.db_user, self.db_pass, self.db_host)) @@ -116,7 +112,7 @@ class SkynetTelegramFrontend: method: str, params: dict, file_id: str | None = None, - binary_data: str = '' + inputs: list[str] = [] ) -> bool: if params['seed'] == None: params['seed'] = random.randint(0, 0xFFFFFFFF) @@ -145,13 +141,13 @@ class SkynetTelegramFrontend: res = await self.cleos.a_push_action( 'gpu.scd', 'enqueue', - { + list({ 'user': Name(self.account), 'request_body': body, - 'binary_data': binary_data, - 'reward': asset_from_str(reward), + 'binary_data': ','.join(inputs), + 'reward': Asset.from_str(reward), 'min_verification': 1 - }, + }.values()), self.account, self.key, permission=self.permission ) @@ -176,12 +172,12 @@ class SkynetTelegramFrontend: parse_mode='HTML' ) - out = collect_stdout(res) + out = res['processed']['action_traces'][0]['console'] request_id, nonce = out.split(':') request_hash = sha256( - (nonce + body + binary_data).encode('utf-8')).hexdigest().upper() + (nonce + body + ','.join(inputs)).encode('utf-8')).hexdigest().upper() request_id = int(request_id) @@ -189,7 +185,7 @@ class SkynetTelegramFrontend: tx_hash = None ipfs_hash = None - for i in range(60): + for i in range(60 * 3): try: submits = await self.hyperion.aget_actions( account=self.account, @@ -241,46 +237,28 @@ class SkynetTelegramFrontend: user, params, tx_hash, worker, reward, self.explorer_domain) # attempt to get the image and send it - results = {} ipfs_link = f'https://{self.ipfs_domain}/ipfs/{ipfs_hash}' - ipfs_link_legacy = ipfs_link + '/image.png' - async def get_and_set_results(link: str): - res = await get_ipfs_file(link) - logging.info(f'got response from {link}') - if not res or res.status_code != 200: - logging.warning(f'couldn\'t get ipfs binary data at {link}!') + res = await get_ipfs_file(ipfs_link) + logging.info(f'got response from {ipfs_link}') + if not res or res.status_code != 200: + logging.warning(f'couldn\'t get ipfs binary data at {ipfs_link}!') - else: - try: - with Image.open(io.BytesIO(res.raw)) as image: - w, h = image.size + else: + try: + with Image.open(io.BytesIO(res.raw)) as image: + w, h = image.size - if w > TG_MAX_WIDTH or h > TG_MAX_HEIGHT: - logging.warning(f'result is of size {image.size}') - image.thumbnail((TG_MAX_WIDTH, TG_MAX_HEIGHT)) + if w > TG_MAX_WIDTH or h > TG_MAX_HEIGHT: + logging.warning(f'result is of size {image.size}') + image.thumbnail((TG_MAX_WIDTH, TG_MAX_HEIGHT)) - tmp_buf = io.BytesIO() - image.save(tmp_buf, format='PNG') - png_img = tmp_buf.getvalue() + tmp_buf = io.BytesIO() + image.save(tmp_buf, format='PNG') + png_img = tmp_buf.getvalue() - results[link] = png_img - - except UnidentifiedImageError: - logging.warning(f'couldn\'t get ipfs binary data at {link}!') - - tasks = [ - get_and_set_results(ipfs_link), - get_and_set_results(ipfs_link_legacy) - ] - await asyncio.gather(*tasks) - - png_img = None - if ipfs_link_legacy in results: - png_img = results[ipfs_link_legacy] - - if ipfs_link in results: - png_img = results[ipfs_link] + except UnidentifiedImageError: + logging.warning(f'couldn\'t get ipfs binary data at {ipfs_link}!') if not png_img: await self.update_status_message( diff --git a/skynet/frontend/telegram/handlers.py b/skynet/frontend/telegram/handlers.py index 63abe60..6a1eb20 100644 --- a/skynet/frontend/telegram/handlers.py +++ b/skynet/frontend/telegram/handlers.py @@ -254,7 +254,7 @@ def create_handler_context(frontend: 'SkynetTelegramFrontend'): success = await work_request( user, status_msg, 'img2img', params, file_id=file_id, - binary_data=ipfs_hash + inputs=ipfs_hash ) if success: @@ -320,7 +320,7 @@ def create_handler_context(frontend: 'SkynetTelegramFrontend'): success = await work_request( user, status_msg, 'redo', params, file_id=file_id, - binary_data=binary + inputs=binary ) if success: diff --git a/skynet/frontend/telegram/utils.py b/skynet/frontend/telegram/utils.py index f438623..9d6f927 100644 --- a/skynet/frontend/telegram/utils.py +++ b/skynet/frontend/telegram/utils.py @@ -72,7 +72,7 @@ def generate_reply_caption( ): explorer_link = hlink( 'SKYNET Transaction Explorer', - f'https://explorer.{explorer_domain}/v2/explore/transaction/{tx_hash}' + f'https://{explorer_domain}/v2/explore/transaction/{tx_hash}' ) meta_info = prepare_metainfo_caption(tguser, worker, reward, params) diff --git a/skynet/ipfs/__init__.py b/skynet/ipfs/__init__.py index 2f18253..5a6384f 100644 --- a/skynet/ipfs/__init__.py +++ b/skynet/ipfs/__init__.py @@ -3,10 +3,10 @@ import logging from pathlib import Path -import asks +import httpx -class IPFSClientException(BaseException): +class IPFSClientException(Exception): ... @@ -16,19 +16,20 @@ class AsyncIPFSHTTP: self.endpoint = endpoint async def _post(self, sub_url: str, *args, **kwargs): - resp = await asks.post( - self.endpoint + sub_url, - *args, **kwargs - ) + async with httpx.AsyncClient() as client: + resp = await client.post( + self.endpoint + sub_url, + *args, **kwargs + ) if resp.status_code != 200: raise IPFSClientException(resp.text) return resp.json() - +#!/usr/bin/python async def add(self, file_path: Path, **kwargs): files = { - 'file': file_path + 'file': (file_path.name, file_path.open('rb')) } return await self._post( '/api/v0/add', @@ -55,18 +56,19 @@ class AsyncIPFSHTTP: ))['Peers'] -async def get_ipfs_file(ipfs_link: str, timeout: int = 60): +async def get_ipfs_file(ipfs_link: str, timeout: int = 60 * 5): logging.info(f'attempting to get image at {ipfs_link}') resp = None - for i in range(timeout): + for _ in range(timeout): try: - resp = await asks.get(ipfs_link, timeout=3) + async with httpx.AsyncClient() as client: + resp = await client.get(ipfs_link, timeout=3) - except asks.errors.RequestTimeout: - logging.warning('timeout...') + except httpx.RequestError as e: + logging.warning(f'Request error: {e}') - except asks.errors.BadHttpResponse as e: - logging.error(f'ifps gateway exception: \n{e}') + if resp is not None: + break if resp: logging.info(f'status_code: {resp.status_code}') diff --git a/skynet/ipfs/pinner.py b/skynet/ipfs/pinner.py index 1db06fe..0cc2836 100644 --- a/skynet/ipfs/pinner.py +++ b/skynet/ipfs/pinner.py @@ -55,9 +55,9 @@ class SkynetPinner: cids = [] for action in enqueues['actions']: - cid = action['act']['data']['binary_data'] - if cid and not self.is_pinned(cid): - cids.append(cid) + for cid in action['act']['data']['binary_data'].split(','): + if cid and not self.is_pinned(cid): + cids.append(cid) return cids diff --git a/skynet/utils.py b/skynet/utils.py index 5e88ed8..0662aca 100755 --- a/skynet/utils.py +++ b/skynet/utils.py @@ -6,26 +6,42 @@ import sys import time import random import logging +import importlib from typing import Optional from pathlib import Path -import asks +import trio import torch import numpy as np from PIL import Image -from basicsr.archs.rrdbnet_arch import RRDBNet from diffusers import ( DiffusionPipeline, - EulerAncestralDiscreteScheduler + AutoPipelineForText2Image, + AutoPipelineForImage2Image, + AutoPipelineForInpainting, + EulerAncestralDiscreteScheduler, ) -from realesrgan import RealESRGANer from huggingface_hub import login -import trio from .constants import MODELS +# Hack to fix a changed import in torchvision 0.17+, which otherwise breaks +# basicsr; see https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/13985 +try: + import torchvision.transforms.functional_tensor # noqa: F401 +except ImportError: + try: + import torchvision.transforms.functional as functional + sys.modules["torchvision.transforms.functional_tensor"] = functional + except ImportError: + pass # shrug... + +from basicsr.archs.rrdbnet_arch import RRDBNet +from realesrgan import RealESRGANer + + def time_ms(): return int(time.time() * 1000) @@ -58,14 +74,18 @@ def crop_image(image: Image, max_w: int, max_h: int) -> Image: return image.convert('RGB') +def convert_from_bytes_and_crop(raw: bytes, max_w: int, max_h: int) -> Image: + return crop_image(convert_from_bytes_to_img(raw), max_w, max_h) + def pipeline_for( model: str, + mode: str, mem_fraction: float = 1.0, - image: bool = False, cache_dir: str | None = None ) -> DiffusionPipeline: + logging.info(f'pipeline_for {model} {mode}') assert torch.cuda.is_available() torch.cuda.empty_cache() torch.backends.cuda.matmul.allow_tf32 = True @@ -79,21 +99,35 @@ def pipeline_for( torch.use_deterministic_algorithms(True) model_info = MODELS[model] + shortname = model_info.short + + # disable for compat with "diffuse" method + # assert mode in model_info.tags + + # default to checking if custom pipeline exist and return that if not, attempt generic + try: + normalized_shortname = shortname.replace('-', '_') + custom_pipeline = importlib.import_module(f'skynet.dgpu.pipes.{normalized_shortname}') + assert custom_pipeline.__model['name'] == model + return custom_pipeline.pipeline_for(model, mode, mem_fraction=mem_fraction, cache_dir=cache_dir) + + except ImportError: + ... + + + req_mem = model_info.mem - req_mem = model_info['mem'] mem_gb = torch.cuda.mem_get_info()[1] / (10**9) mem_gb *= mem_fraction over_mem = mem_gb < req_mem if over_mem: logging.warn(f'model requires {req_mem} but card has {mem_gb}, model will run slower..') - shortname = model_info['short'] - params = { 'safety_checker': None, 'torch_dtype': torch.float16, 'cache_dir': cache_dir, - 'variant': 'fp16' + 'variant': 'fp16', } match shortname: @@ -102,26 +136,37 @@ def pipeline_for( torch.cuda.set_per_process_memory_fraction(mem_fraction) - pipe = DiffusionPipeline.from_pretrained( + pipe_class = DiffusionPipeline + match mode: + case 'inpaint': + pipe_class = AutoPipelineForInpainting + + case 'img2img': + pipe_class = AutoPipelineForImage2Image + + case 'txt2img': + pipe_class = AutoPipelineForText2Image + + pipe = pipe_class.from_pretrained( model, **params) pipe.scheduler = EulerAncestralDiscreteScheduler.from_config( pipe.scheduler.config) - pipe.enable_xformers_memory_efficient_attention() + # pipe.enable_xformers_memory_efficient_attention() if over_mem: - if not image: - pipe.enable_vae_slicing() - pipe.enable_vae_tiling() - + if mode == 'txt2img': + pipe.vae.enable_tiling() + pipe.vae.enable_slicing() + pipe.enable_model_cpu_offload() else: - if sys.version_info[1] < 11: - # torch.compile only supported on python < 3.11 - pipe.unet = torch.compile( - pipe.unet, mode='reduce-overhead', fullgraph=True) + # if sys.version_info[1] < 11: + # # torch.compile only supported on python < 3.11 + # pipe.unet = torch.compile( + # pipe.unet, mode='reduce-overhead', fullgraph=True) pipe = pipe.to('cuda') @@ -130,7 +175,7 @@ def pipeline_for( def txt2img( hf_token: str, - model: str = 'prompthero/openjourney', + model: str = list(MODELS.keys())[-1], prompt: str = 'a red old tractor in a sunny wheat field', output: str = 'output.png', width: int = 512, height: int = 512, @@ -139,7 +184,7 @@ def txt2img( seed: Optional[int] = None ): login(token=hf_token) - pipe = pipeline_for(model) + pipe = pipeline_for(model, 'txt2img') seed = seed if seed else random.randint(0, 2 ** 64) prompt = prompt @@ -156,7 +201,7 @@ def txt2img( def img2img( hf_token: str, - model: str = 'prompthero/openjourney', + model: str = list(MODELS.keys())[-2], prompt: str = 'a red old tractor in a sunny wheat field', img_path: str = 'input.png', output: str = 'output.png', @@ -166,10 +211,12 @@ def img2img( seed: Optional[int] = None ): login(token=hf_token) - pipe = pipeline_for(model, image=True) + pipe = pipeline_for(model, 'img2img') + + model_info = MODELS[model] with open(img_path, 'rb') as img_file: - input_img = convert_from_bytes_and_crop(img_file.read(), 512, 512) + input_img = convert_from_bytes_and_crop(img_file.read(), model_info.size.w, model_info.size.h) seed = seed if seed else random.randint(0, 2 ** 64) prompt = prompt @@ -184,7 +231,48 @@ def img2img( image.save(output) -def init_upscaler(model_path: str = 'weights/RealESRGAN_x4plus.pth'): +def inpaint( + hf_token: str, + model: str = list(MODELS.keys())[-3], + prompt: str = 'a red old tractor in a sunny wheat field', + img_path: str = 'input.png', + mask_path: str = 'mask.png', + output: str = 'output.png', + strength: float = 1.0, + guidance: float = 10, + steps: int = 28, + seed: Optional[int] = None +): + login(token=hf_token) + pipe = pipeline_for(model, 'inpaint') + + model_info = MODELS[model] + + with open(img_path, 'rb') as img_file: + input_img = convert_from_bytes_and_crop(img_file.read(), model_info.size.w, model_info.size.h) + + with open(mask_path, 'rb') as mask_file: + mask_img = convert_from_bytes_and_crop(mask_file.read(), model_info.size.w, model_info.size.h) + + var_params = {} + if 'flux' not in model.lower(): + var_params['strength'] = strength + + seed = seed if seed else random.randint(0, 2 ** 64) + prompt = prompt + image = pipe( + prompt, + image=input_img, + mask_image=mask_img, + guidance_scale=guidance, num_inference_steps=steps, + generator=torch.Generator("cuda").manual_seed(seed), + **var_params + ).images[0] + + image.save(output) + + +def init_upscaler(model_path: str = 'hf_home/RealESRGAN_x4plus.pth'): return RealESRGANer( scale=4, model_path=model_path, @@ -203,7 +291,7 @@ def init_upscaler(model_path: str = 'weights/RealESRGAN_x4plus.pth'): def upscale( img_path: str = 'input.png', output: str = 'output.png', - model_path: str = 'weights/RealESRGAN_x4plus.pth' + model_path: str = 'hf_home/RealESRGAN_x4plus.pth' ): input_img = Image.open(img_path).convert('RGB') @@ -214,25 +302,3 @@ def upscale( image = convert_from_cv2_to_image(up_img) image.save(output) - - -async def download_upscaler(): - print('downloading upscaler...') - weights_path = Path('weights') - weights_path.mkdir(exist_ok=True) - upscaler_url = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth' - save_path = weights_path / 'RealESRGAN_x4plus.pth' - response = await asks.get(upscaler_url) - with open(save_path, 'wb') as f: - f.write(response.content) - print('done') - -def download_all_models(hf_token: str, hf_home: str): - assert torch.cuda.is_available() - - trio.run(download_upscaler) - - login(token=hf_token) - for model in MODELS: - print(f'DOWNLOADING {model.upper()}') - pipeline_for(model, cache_dir=hf_home) diff --git a/tests/conftest.py b/tests/conftest.py index 03ed434..0ea4821 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -2,7 +2,7 @@ import pytest -from skynet.db import open_new_database +from skynet.config import * from skynet.ipfs import AsyncIPFSHTTP from skynet.ipfs.docker import open_ipfs_node from skynet.nodeos import open_nodeos @@ -15,6 +15,7 @@ def ipfs_client(): @pytest.fixture(scope='session') def postgres_db(): + from skynet.db import open_new_database with open_new_database() as db_params: yield db_params @@ -22,3 +23,20 @@ def postgres_db(): def cleos(): with open_nodeos() as cli: yield cli + +@pytest.fixture(scope='session') +def dgpu(): + from skynet.dgpu.network import SkynetGPUConnector + from skynet.dgpu.compute import SkynetMM + from skynet.dgpu.daemon import SkynetDGPUDaemon + + config = load_skynet_toml(file_path='skynet.toml') + hf_token = load_key(config, 'skynet.dgpu.hf_token') + hf_home = load_key(config, 'skynet.dgpu.hf_home') + set_hf_vars(hf_token, hf_home) + config = config['skynet']['dgpu'] + conn = SkynetGPUConnector(config) + mm = SkynetMM(config) + daemon = SkynetDGPUDaemon(mm, conn, config) + + yield conn, mm, daemon diff --git a/tests/test_reqs.py b/tests/test_reqs.py new file mode 100644 index 0000000..d55c940 --- /dev/null +++ b/tests/test_reqs.py @@ -0,0 +1,112 @@ +import json + +from skynet.dgpu.compute import SkynetMM +from skynet.constants import * +from skynet.config import * + + +async def test_diffuse(dgpu): + conn, mm, daemon = dgpu + await conn.cancel_work(0, 'testing') + + daemon._snap['requests'][0] = {} + req = { + 'id': 0, + 'nonce': 0, + 'body': json.dumps({ + "method": "diffuse", + "params": { + "prompt": "Kronos God Realistic 4k", + "model": list(MODELS.keys())[-1], + "step": 21, + "width": 1024, + "height": 1024, + "seed": 168402949, + "guidance": "7.5" + } + }), + 'binary_data': '', + } + + await daemon.maybe_serve_one(req) + + +async def test_txt2img(dgpu): + conn, mm, daemon = dgpu + await conn.cancel_work(0, 'testing') + + daemon._snap['requests'][0] = {} + req = { + 'id': 0, + 'nonce': 0, + 'body': json.dumps({ + "method": "txt2img", + "params": { + "prompt": "Kronos God Realistic 4k", + "model": list(MODELS.keys())[-1], + "step": 21, + "width": 1024, + "height": 1024, + "seed": 168402949, + "guidance": "7.5" + } + }), + 'binary_data': '', + } + + await daemon.maybe_serve_one(req) + + +async def test_img2img(dgpu): + conn, mm, daemon = dgpu + await conn.cancel_work(0, 'testing') + + daemon._snap['requests'][0] = {} + req = { + 'id': 0, + 'nonce': 0, + 'body': json.dumps({ + "method": "img2img", + "params": { + "prompt": "a hindu cat god feline god on a house roof", + "model": list(MODELS.keys())[-2], + "step": 21, + "width": 1024, + "height": 1024, + "seed": 168402949, + "guidance": "7.5", + "strength": "0.5" + } + }), + 'binary_data': 'QmZcGdXXVQfpco1G3tr2CGFBtv8xVsCwcwuq9gnJBWDymi', + } + + await daemon.maybe_serve_one(req) + +async def test_inpaint(dgpu): + conn, mm, daemon = dgpu + await conn.cancel_work(0, 'testing') + + daemon._snap['requests'][0] = {} + req = { + 'id': 0, + 'nonce': 0, + 'body': json.dumps({ + "method": "inpaint", + "params": { + "prompt": "a black panther on a sunny roof", + "model": list(MODELS.keys())[-3], + "step": 21, + "width": 1024, + "height": 1024, + "seed": 168402949, + "guidance": "7.5", + "strength": "0.5" + } + }), + 'binary_data': + 'QmZcGdXXVQfpco1G3tr2CGFBtv8xVsCwcwuq9gnJBWDymi,' + + 'Qmccx1aXNmq5mZDS3YviUhgGHXWhQeHvca3AgA7MDjj2hR' + } + + await daemon.maybe_serve_one(req)