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skynet
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Merge 5b935e5b4d into 868e2489b3

pull/49/merge
Guillermo Rodriguez 2025-02-21 14:05:33 +00:00 committed by GitHub
parent 868e2489b3 5b935e5b4d
commit d693065084
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GPG Key ID: B5690EEEBB952194
24 changed files with 1039 additions and 490 deletions
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29
.github/workflows/ci.yml vendored 100644
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@ -0,0 +1,29 @@
name: CI
on: [push]
jobs:
auto-tests:
name: Pytest Tests
runs-on: ubuntu-24.04
timeout-minutes: 10
steps:
- uses: actions/checkout@v2
with:
submodules: recursive
- name: Install the latest version of uv
uses: astral-sh/setup-uv@v5
- uses: actions/cache@v3
name: Cache venv
with:
path: ./.venv
key: venv-${{ hashFiles('uv.lock') }}
- name: Install with dev
run: uv sync
- name: Run tests
run: |
uv run pytest

36
default.nix 100644
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@ -0,0 +1,36 @@
with (import <nixpkgs> {});
let
glibStorePath = lib.getLib glib;
zstdStorePath = lib.getLib zstd;
libGLStorePath = lib.getLib libGL;
in
stdenv.mkDerivation {
name = "skynet";
buildInputs = [
# System requirements.
glib
zstd
libGL
libgcc.lib
# Python requirements.
python313Full
python313Packages.uv
];
src = null;
shellHook = ''
set -e
LIB_GCC_PATH="${libgcc.lib}/lib"
GLIB_PATH="${glibStorePath}/lib"
ZSTD_PATH="${zstdStorePath}/lib"
LIBGL_PATH="${libGLStorePath}/lib"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$LIB_GCC_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$GLIB_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$ZSTD_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$LIBGL_PATH"
export LD_LIBRARY_PATH
'';
}

2
pyproject.toml
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@ -77,7 +77,7 @@ explicit = true
torch = { index = "torch" } torch = { index = "torch" }
triton = { index = "torch" } triton = { index = "torch" }
torchvision = { index = "torch" } torchvision = { index = "torch" }
py-leap = { git = "https://github.com/guilledk/py-leap.git", rev = "v0.1a34" } py-leap = { git = "https://github.com/guilledk/py-leap.git", rev = "v0.1a35" }
pytest-dockerctl = { git = "https://github.com/pikers/pytest-dockerctl.git", branch = "g_update" } pytest-dockerctl = { git = "https://github.com/pikers/pytest-dockerctl.git", branch = "g_update" }
[build-system] [build-system]

32
skynet/_testing.py 100644
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@ -0,0 +1,32 @@
from contextlib import asynccontextmanager as acm
from skynet.config import Config, DgpuConfig, set_config_override
from skynet.dgpu import open_worker
def override_dgpu_config(**kwargs) -> DgpuConfig:
config = Config(
dgpu=DgpuConfig(**kwargs)
)
set_config_override(config)
return config.dgpu
@acm
async def open_test_worker(
cleos, ipfs_node,
account: str = 'testworker',
permission: str = 'active',
hf_token: str = '',
**kwargs
):
config = override_dgpu_config(
account=account,
permission=permission,
key=cleos.private_keys[account],
node_url=cleos.endpoint,
ipfs_url=ipfs_node[1].endpoint,
hf_token=hf_token,
**kwargs
)
async with open_worker(config) as worker:
yield worker

14
skynet/cli.py
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@ -1,16 +1,8 @@
import json import json
import logging import logging
import random
from functools import partial
import click import click
from leap.protocol import (
Name,
Asset,
)
from .config import ( from .config import (
load_skynet_toml, load_skynet_toml,
set_hf_vars, set_hf_vars,
@ -49,7 +41,7 @@ def txt2img(*args, **kwargs):
config = load_skynet_toml() config = load_skynet_toml()
set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home) set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home)
utils.txt2img(hf_token, **kwargs) utils.txt2img(config.dgpu.hf_token, **kwargs)
@click.command() @click.command()
@ -74,7 +66,7 @@ def img2img(model, prompt, input, output, strength, guidance, steps, seed):
config = load_skynet_toml() config = load_skynet_toml()
set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home) set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home)
utils.img2img( utils.img2img(
hf_token, config.dgpu.hf_token,
model=model, model=model,
prompt=prompt, prompt=prompt,
img_path=input, img_path=input,
@ -102,7 +94,7 @@ def inpaint(model, prompt, input, mask, output, strength, guidance, steps, seed)
config = load_skynet_toml() config = load_skynet_toml()
set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home) set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home)
utils.inpaint( utils.inpaint(
hf_token, config.dgpu.hf_token,
model=model, model=model,
prompt=prompt, prompt=prompt,
img_path=input, img_path=input,

12
skynet/config.py
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@ -1,5 +1,4 @@
import os import os
import toml
import msgspec import msgspec
@ -59,7 +58,18 @@ class Config(msgspec.Struct):
user: UserConfig | None = None user: UserConfig | None = None
__config_override = None
def set_config_override(config: Config):
global __config_override
__config_override = config
def load_skynet_toml(file_path=DEFAULT_CONFIG_PATH) -> Config: def load_skynet_toml(file_path=DEFAULT_CONFIG_PATH) -> Config:
global __config_override
if __config_override:
return __config_override
with open(file_path, 'r') as file: with open(file_path, 'r') as file:
return msgspec.toml.decode(file.read(), type=Config) return msgspec.toml.decode(file.read(), type=Config)

15
skynet/constants.py
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@ -1,20 +1,9 @@
import msgspec from skynet.types import ModelDesc
from enum import Enum VERSION = '0.1a13'
from typing import Literal
VERSION = '0.1a12'
DOCKER_RUNTIME_CUDA = 'skynet:runtime-cuda' DOCKER_RUNTIME_CUDA = 'skynet:runtime-cuda'
class ModelDesc(msgspec.Struct):
short: str # short unique name
mem: float # recomended mem
attrs: dict # additional mode specific attrs
tags: list[Literal['txt2img', 'img2img', 'inpaint', 'upscale']]
MODELS: dict[str, ModelDesc] = { MODELS: dict[str, ModelDesc] = {
'RealESRGAN_x4plus': ModelDesc( 'RealESRGAN_x4plus': ModelDesc(
short='realesrgan', short='realesrgan',

26
skynet/dgpu/__init__.py
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@ -5,9 +5,9 @@ import trio
import urwid import urwid
from skynet.config import Config from skynet.config import Config
from skynet.dgpu.tui import init_tui from skynet.dgpu.tui import init_tui, WorkerMonitor
from skynet.dgpu.daemon import dgpu_serve_forever from skynet.dgpu.daemon import dgpu_serve_forever
from skynet.dgpu.network import NetConnector from skynet.dgpu.network import NetConnector, maybe_open_contract_state_mngr
@acm @acm
@ -15,26 +15,28 @@ async def open_worker(config: Config):
# suppress logs from httpx (logs url + status after every query) # suppress logs from httpx (logs url + status after every query)
logging.getLogger("httpx").setLevel(logging.WARNING) logging.getLogger("httpx").setLevel(logging.WARNING)
tui = None tui: WorkerMonitor | None = None
if config.tui: if config.tui:
tui = init_tui(config) tui = init_tui(config)
conn = NetConnector(config) conn = NetConnector(config)
try: try:
n: trio.Nursery async with maybe_open_contract_state_mngr(conn) as state_mngr:
async with trio.open_nursery() as n: n: trio.Nursery
if tui: async with trio.open_nursery() as n:
n.start_soon(tui.run) if tui:
n.start_soon(tui.run)
n.start_soon(conn.iter_poll_update, config.poll_time) n.start_soon(dgpu_serve_forever, config, conn, state_mngr)
yield conn yield conn, state_mngr
n.cancel_scope.cancel()
except *urwid.ExitMainLoop: except *urwid.ExitMainLoop:
... ...
async def _dgpu_main(config: Config): async def _dgpu_main(config: Config):
async with open_worker(config) as conn: async with open_worker(config):
await dgpu_serve_forever(config, conn) await trio.sleep_forever()

178
skynet/dgpu/compute.py
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@ -7,81 +7,90 @@ import gc
import logging import logging
from hashlib import sha256 from hashlib import sha256
from typing import Callable, Generator
from contextlib import contextmanager as cm from contextlib import contextmanager as cm
import trio import trio
import torch import torch
from skynet.config import load_skynet_toml from skynet.config import load_skynet_toml
from skynet.types import ModelMode, BodyV0Params
from skynet.dgpu.tui import maybe_update_tui from skynet.dgpu.tui import maybe_update_tui
from skynet.dgpu.errors import ( from skynet.dgpu.errors import (
DGPUComputeError, DGPUComputeError,
DGPUInferenceCancelled, DGPUInferenceCancelled,
) )
from skynet.dgpu.utils import crop_image, convert_from_cv2_to_image, convert_from_image_to_cv2, convert_from_img_to_bytes, init_upscaler, pipeline_for from skynet.dgpu.utils import (
Pipeline,
crop_image,
convert_from_cv2_to_image,
convert_from_image_to_cv2,
convert_from_img_to_bytes,
pipeline_for
)
def prepare_params_for_diffuse( def prepare_params_for_diffuse(
params: dict, params: BodyV0Params,
mode: str, mode: ModelMode,
inputs: list[bytes] inputs: list[bytes]
): ):
_params = {} _params = {}
match mode: match mode:
case 'inpaint': case ModelMode.INPAINT:
image = crop_image( image = crop_image(
inputs[0], params['width'], params['height']) inputs[0], params.width, params.height)
mask = crop_image( mask = crop_image(
inputs[1], params['width'], params['height']) inputs[1], params.width, params.height)
_params['image'] = image _params['image'] = image
_params['mask_image'] = mask _params['mask_image'] = mask
if 'flux' in params['model'].lower(): if 'flux' in params.model.lower():
_params['max_sequence_length'] = 512 _params['max_sequence_length'] = 512
else: else:
_params['strength'] = float(params['strength']) _params['strength'] = float(params.strength)
case 'img2img': case ModelMode.IMG2IMG:
image = crop_image( image = crop_image(
inputs[0], params['width'], params['height']) inputs[0], params.width, params.height)
_params['image'] = image _params['image'] = image
_params['strength'] = float(params['strength']) _params['strength'] = float(params.strength)
case 'txt2img' | 'diffuse': case ModelMode.TXT2IMG | ModelMode.DIFFUSE:
... ...
case _: case _:
raise DGPUComputeError(f'Unknown mode {mode}') raise DGPUComputeError(f'Unknown mode {mode}')
# _params['width'] = int(params['width'])
# _params['height'] = int(params['height'])
return ( return (
params['prompt'], params.prompt,
float(params['guidance']), float(params.guidance),
int(params['step']), params.step,
torch.manual_seed(int(params['seed'])), torch.manual_seed(int(params.seed)),
params['upscaler'] if 'upscaler' in params else None,
_params _params
) )
_model_name: str = '' _model_name: str = ''
_model_mode: str = '' _model_mode: str = ''
_model = None _model: Pipeline | None = None
@cm @cm
def maybe_load_model(name: str, mode: str): def maybe_load_model(name: str, mode: ModelMode) -> Generator[Pipeline, None, None]:
if mode == 'diffuse': if mode == ModelMode.DIFFUSE:
mode = 'txt2img' mode = ModelMode.TXT2IMG
global _model_name, _model_mode, _model global _model_name, _model_mode, _model
config = load_skynet_toml().dgpu config = load_skynet_toml().dgpu
if _model_name != name or _model_mode != mode: if (
_model_name != name
or
_model_mode != mode
):
# unload model # unload model
_model = None _model = None
gc.collect() gc.collect()
@ -90,34 +99,33 @@ def maybe_load_model(name: str, mode: str):
_model_name = _model_mode = '' _model_name = _model_mode = ''
# load model # load model
if mode == 'upscale': _model = pipeline_for(
_model = init_upscaler() name, mode, cache_dir=config.hf_home)
else:
_model = pipeline_for(
name, mode, cache_dir=config.hf_home)
_model_name = name _model_name = name
_model_mode = mode _model_mode = mode
logging.debug('memory summary:') if torch.cuda.is_available():
logging.debug('\n' + torch.cuda.memory_summary()) logging.debug(
'memory summary:\n'
f'{torch.cuda.memory_summary()}'
)
yield _model yield _model
def compute_one( def compute_one(
model, model: Pipeline,
request_id: int, request_id: int,
method: str, method: ModelMode,
params: dict, params: BodyV0Params,
inputs: list[bytes] = [], inputs: list[bytes] = [],
should_cancel = None should_cancel: Callable[[int, ...], dict] = None
): ):
total_steps = params['step'] if 'step' in params else 1 total_steps = params.step
def inference_step_wakeup(*args, **kwargs): def inference_step_wakeup(*args, **kwargs):
'''This is a callback function that gets invoked every inference step, '''This is a callback function that gets invoked every inference step,
we need to raise an exception here if we need to cancel work we must raise DGPUInferenceCancelled here if we need to cancel work
''' '''
step = args[0] step = args[0]
# compat with callback_on_step_end # compat with callback_on_step_end
@ -128,6 +136,9 @@ def compute_one(
should_raise = False should_raise = False
if should_cancel: if should_cancel:
'''Pump main thread event loop, evaluate if we should keep working
on this request, based on latest network info like competitors...
'''
should_raise = trio.from_thread.run(should_cancel, request_id) should_raise = trio.from_thread.run(should_cancel, request_id)
if should_raise: if should_raise:
@ -140,68 +151,59 @@ def compute_one(
inference_step_wakeup(0) inference_step_wakeup(0)
output_type = 'png' output_type = params.output_type
if 'output_type' in params:
output_type = params['output_type']
output = None output = None
output_hash = None output_hash = None
try: name = params.model
name = params['model']
match method: match method:
case 'diffuse' | 'txt2img' | 'img2img' | 'inpaint': case (
arguments = prepare_params_for_diffuse( ModelMode.DIFFUSE |
params, method, inputs) ModelMode.TXT2IMG |
prompt, guidance, step, seed, upscaler, extra_params = arguments ModelMode.IMG2IMG |
ModelMode.INPAINT
):
arguments = prepare_params_for_diffuse(
params, method, inputs)
prompt, guidance, step, seed, extra_params = arguments
if 'flux' in name.lower(): if 'flux' in name.lower():
extra_params['callback_on_step_end'] = inference_step_wakeup extra_params['callback_on_step_end'] = inference_step_wakeup
else: else:
extra_params['callback'] = inference_step_wakeup extra_params['callback'] = inference_step_wakeup
extra_params['callback_steps'] = 1 extra_params['callback_steps'] = 1
output = model( output = model(
prompt, prompt,
guidance_scale=guidance, guidance_scale=guidance,
num_inference_steps=step, num_inference_steps=step,
generator=seed, generator=seed,
**extra_params **extra_params
).images[0] ).images[0]
output_binary = b'' output_binary = b''
match output_type: match output_type:
case 'png': case 'png':
if upscaler == 'x4': output_binary = convert_from_img_to_bytes(output)
input_img = output.convert('RGB')
up_img, _ = init_upscaler().enhance(
convert_from_image_to_cv2(input_img), outscale=4)
output = convert_from_cv2_to_image(up_img) case _:
raise DGPUComputeError(f'Unsupported output type: {output_type}')
output_binary = convert_from_img_to_bytes(output) output_hash = sha256(output_binary).hexdigest()
case _: case 'upscale':
raise DGPUComputeError(f'Unsupported output type: {output_type}') input_img = inputs[0].convert('RGB')
up_img, _ = model.enhance(
convert_from_image_to_cv2(input_img), outscale=4)
output_hash = sha256(output_binary).hexdigest() output = convert_from_cv2_to_image(up_img)
case 'upscale': output_binary = convert_from_img_to_bytes(output)
input_img = inputs[0].convert('RGB') output_hash = sha256(output_binary).hexdigest()
up_img, _ = model.enhance(
convert_from_image_to_cv2(input_img), outscale=4)
output = convert_from_cv2_to_image(up_img) case _:
raise DGPUComputeError('Unsupported compute method')
output_binary = convert_from_img_to_bytes(output)
output_hash = sha256(output_binary).hexdigest()
case _:
raise DGPUComputeError('Unsupported compute method')
except BaseException as err:
raise DGPUComputeError(str(err)) from err
maybe_update_tui(lambda tui: tui.set_status('')) maybe_update_tui(lambda tui: tui.set_status(''))

121
skynet/dgpu/daemon.py
View File

@ -1,32 +1,22 @@
import json
import logging import logging
import random
import time
from datetime import datetime
from functools import partial from functools import partial
from hashlib import sha256 from hashlib import sha256
import trio import trio
import msgspec
from skynet.config import DgpuConfig as Config from skynet.config import DgpuConfig as Config
from skynet.constants import ( from skynet.types import (
MODELS, BodyV0
VERSION,
)
from skynet.dgpu.errors import (
DGPUComputeError,
) )
from skynet.constants import MODELS
from skynet.dgpu.errors import DGPUComputeError
from skynet.dgpu.tui import maybe_update_tui, maybe_update_tui_async from skynet.dgpu.tui import maybe_update_tui, maybe_update_tui_async
from skynet.dgpu.compute import maybe_load_model, compute_one from skynet.dgpu.compute import maybe_load_model, compute_one
from skynet.dgpu.network import NetConnector from skynet.dgpu.network import (
NetConnector,
ContractState,
def convert_reward_to_int(reward_str): )
int_part, decimal_part = (
reward_str.split('.')[0],
reward_str.split('.')[1].split(' ')[0]
)
return int(int_part + decimal_part)
async def maybe_update_tui_balance(conn: NetConnector): async def maybe_update_tui_balance(conn: NetConnector):
@ -41,14 +31,18 @@ async def maybe_update_tui_balance(conn: NetConnector):
async def maybe_serve_one( async def maybe_serve_one(
config: Config, config: Config,
conn: NetConnector, conn: NetConnector,
req: dict, state_mngr: ContractState,
): ):
rid = req['id'] logging.info(f'maybe serve request pi: {state_mngr.poll_index}')
logging.info(f'maybe serve request #{rid}') req = state_mngr.first
# no requests in queue
if not req:
return
# parse request # parse request
body = json.loads(req['body']) body = msgspec.json.decode(req.body, type=BodyV0)
model = body['params']['model'] model = body.params.model
# if model not known, ignore. # if model not known, ignore.
if model not in MODELS: if model not in MODELS:
@ -70,32 +64,27 @@ async def maybe_serve_one(
and and
model in config.model_blacklist model in config.model_blacklist
): ):
logging.warning('model not blacklisted!, skip...') logging.warning('model is blacklisted!, skip...')
return return
results = [res['request_id'] for res in conn._tables['results']]
# if worker already produced a result for this request # if worker already produced a result for this request
if rid in results: if state_mngr.is_request_filled(req.id):
logging.info(f'worker already submitted a result for request #{rid}, skip...') logging.info(f'worker already submitted a result for request #{req.id}, skip...')
return return
statuses = conn._tables['requests'][rid]
# skip if workers in non_compete already on it # skip if workers in non_compete already on it
competitors = set((status['worker'] for status in statuses)) if not state_mngr.should_compete_for_id(req.id):
if bool(config.non_compete & competitors):
logging.info('worker in configured non_compete list already working on request, skip...') logging.info('worker in configured non_compete list already working on request, skip...')
return return
# resolve the ipfs hashes into the actual data behind them # resolve the ipfs hashes into the actual data behind them
inputs = [] inputs = []
raw_inputs = req['binary_data'].split(',') raw_inputs = req.binary_data.split(',')
if raw_inputs: if raw_inputs:
logging.info(f'fetching IPFS inputs: {raw_inputs}') logging.info(f'fetching IPFS inputs: {raw_inputs}')
retry = 3 retry = 3
for _input in req['binary_data'].split(','): for _input in raw_inputs:
if _input: if _input:
for r in range(retry): for r in range(retry):
try: try:
@ -114,24 +103,22 @@ async def maybe_serve_one(
# compute unique request hash used on submit # compute unique request hash used on submit
hash_str = ( hash_str = (
str(req['nonce']) str(req.nonce)
+ +
req['body'] req.body
+ +
req['binary_data'] req.binary_data
) )
logging.debug(f'hashing: {hash_str}') logging.debug(f'hashing: {hash_str}')
request_hash = sha256(hash_str.encode('utf-8')).hexdigest() request_hash = sha256(hash_str.encode('utf-8')).hexdigest()
logging.info(f'calculated request hash: {request_hash}') logging.info(f'calculated request hash: {request_hash}')
params = body['params'] total_step = body.params.step
total_step = params['step'] if 'step' in params else 1 mode = body.method
model = body['params']['model']
mode = body['method']
# TODO: validate request # TODO: validate request
resp = await conn.begin_work(rid) resp = await conn.begin_work(req.id)
if not resp or 'code' in resp: if not resp or 'code' in resp:
logging.info('begin_work error, probably being worked on already... skip.') logging.info('begin_work error, probably being worked on already... skip.')
return return
@ -140,22 +127,24 @@ async def maybe_serve_one(
try: try:
maybe_update_tui(lambda tui: tui.set_progress(0, done=total_step)) maybe_update_tui(lambda tui: tui.set_progress(0, done=total_step))
output_type = 'png' output_type = body.params.output_type
if 'output_type' in body['params']:
output_type = body['params']['output_type']
output = None output = None
output_hash = None output_hash = None
match config.backend: match config.backend:
case 'sync-on-thread': case 'sync-on-thread':
'''Block this task until inference completes, pass
state_mngr.should_cancel_work predicate as the inference_step_wakeup cb
used by torch each step of the inference, it will use a
trio.from_thread to unblock the main thread and pump the event loop
'''
output_hash, output = await trio.to_thread.run_sync( output_hash, output = await trio.to_thread.run_sync(
partial( partial(
compute_one, compute_one,
model, model,
rid, req.id,
mode, params, mode, body.params,
inputs=inputs, inputs=inputs,
should_cancel=conn.should_cancel_work, should_cancel=state_mngr.should_cancel_work,
) )
) )
@ -168,43 +157,39 @@ async def maybe_serve_one(
ipfs_hash = await conn.publish_on_ipfs(output, typ=output_type) ipfs_hash = await conn.publish_on_ipfs(output, typ=output_type)
await conn.submit_work(rid, request_hash, output_hash, ipfs_hash) await conn.submit_work(req.id, request_hash, output_hash, ipfs_hash)
await maybe_update_tui_balance(conn) await maybe_update_tui_balance(conn)
await state_mngr.update_state()
except BaseException as err: except BaseException as err:
if 'network cancel' not in str(err): if 'network cancel' not in str(err):
logging.exception('Failed to serve model request !?\n') logging.exception('Failed to serve model request !?\n')
if rid in conn._tables['requests']: if state_mngr.is_request_in_progress(req.id):
await conn.cancel_work(rid, 'reason not provided') await conn.cancel_work(req.id, 'reason not provided')
async def dgpu_serve_forever(config: Config, conn: NetConnector): async def dgpu_serve_forever(
config: Config,
conn: NetConnector,
state_mngr: ContractState
):
await maybe_update_tui_balance(conn) await maybe_update_tui_balance(conn)
last_poll_idx = -1 last_poll_idx = -1
try: try:
while True: while True:
await conn.wait_data_update() await state_mngr.wait_data_update()
if conn.poll_index == last_poll_idx: if state_mngr.poll_index == last_poll_idx:
await trio.sleep(config.poll_time) await trio.sleep(config.poll_time)
continue continue
last_poll_idx = conn.poll_index last_poll_idx = state_mngr.poll_index
queue = conn._tables['queue'] await maybe_serve_one(config, conn, state_mngr)
random.shuffle(queue)
queue = sorted(
queue,
key=lambda req: convert_reward_to_int(req['reward']),
reverse=True
)
if len(queue) > 0:
await maybe_serve_one(config, conn, queue[0])
except KeyboardInterrupt: except KeyboardInterrupt:
... ...

269
skynet/dgpu/network.py
View File

@ -1,9 +1,10 @@
import io import io
import json import json
import time import time
import random
import logging import logging
from pathlib import Path from pathlib import Path
from typing import AsyncGenerator from contextlib import asynccontextmanager as acm
from functools import partial from functools import partial
import trio import trio
@ -11,15 +12,21 @@ import leap
import anyio import anyio
import httpx import httpx
import outcome import outcome
import msgspec
from PIL import Image from PIL import Image
from leap.cleos import CLEOS from leap.cleos import CLEOS
from leap.protocol import Asset from leap.protocol import Asset
from skynet.dgpu.tui import maybe_update_tui from skynet.dgpu.tui import maybe_update_tui
from skynet.config import DgpuConfig as Config from skynet.config import DgpuConfig as Config, load_skynet_toml
from skynet.constants import ( from skynet.types import (
DEFAULT_IPFS_DOMAIN, ConfigV0,
GPU_CONTRACT_ABI, AccountV0,
BodyV0,
RequestV0,
WorkerStatusV0,
ResultV0
) )
from skynet.constants import GPU_CONTRACT_ABI
from skynet.ipfs import ( from skynet.ipfs import (
AsyncIPFSHTTP, AsyncIPFSHTTP,
@ -67,21 +74,12 @@ class NetConnector:
self.ipfs_client = AsyncIPFSHTTP(config.ipfs_url) self.ipfs_client = AsyncIPFSHTTP(config.ipfs_url)
# poll_index is used to detect stale data
self.poll_index = 0
self._tables = {
'queue': [],
'requests': {},
'results': []
}
self._data_event = trio.Event()
maybe_update_tui(lambda tui: tui.set_header_text(new_worker_name=self.config.account)) maybe_update_tui(lambda tui: tui.set_header_text(new_worker_name=self.config.account))
# blockchain helpers # blockchain helpers
async def get_work_requests_last_hour(self): async def get_work_requests_last_hour(self) -> list[RequestV0]:
logging.info('get_work_requests_last_hour') logging.info('get_work_requests_last_hour')
rows = await failable( rows = await failable(
partial( partial(
@ -89,28 +87,30 @@ class NetConnector:
'gpu.scd', 'gpu.scd', 'queue', 'gpu.scd', 'gpu.scd', 'queue',
index_position=2, index_position=2,
key_type='i64', key_type='i64',
lower_bound=int(time.time()) - 3600 lower_bound=int(time.time()) - 3600,
resp_cls=RequestV0
), ret_fail=[]) ), ret_fail=[])
logging.info(f'found {len(rows)} requests on queue') logging.info(f'found {len(rows)} requests on queue')
return rows return rows
async def get_status_by_request_id(self, request_id: int): async def get_status_by_request_id(self, request_id: int) -> list[WorkerStatusV0]:
logging.info('get_status_by_request_id') logging.info('get_status_by_request_id')
rows = await failable( rows = await failable(
partial( partial(
self.cleos.aget_table, self.cleos.aget_table,
'gpu.scd', request_id, 'status'), ret_fail=[]) 'gpu.scd', request_id, 'status', resp_cls=WorkerStatusV0), ret_fail=[])
logging.info(f'found status for workers: {[r["worker"] for r in rows]}') logging.info(f'found status for workers: {[r.worker for r in rows]}')
return rows return rows
async def get_global_config(self): async def get_global_config(self) -> ConfigV0:
logging.info('get_global_config') logging.info('get_global_config')
rows = await failable( rows = await failable(
partial( partial(
self.cleos.aget_table, self.cleos.aget_table,
'gpu.scd', 'gpu.scd', 'config')) 'gpu.scd', 'gpu.scd', 'config',
resp_cls=ConfigV0))
if rows: if rows:
cfg = rows[0] cfg = rows[0]
@ -120,7 +120,7 @@ class NetConnector:
logging.error('global config not found, is the contract initialized?') logging.error('global config not found, is the contract initialized?')
return None return None
async def get_worker_balance(self): async def get_worker_balance(self) -> str:
logging.info('get_worker_balance') logging.info('get_worker_balance')
rows = await failable( rows = await failable(
partial( partial(
@ -129,77 +129,18 @@ class NetConnector:
index_position=1, index_position=1,
key_type='name', key_type='name',
lower_bound=self.config.account, lower_bound=self.config.account,
upper_bound=self.config.account upper_bound=self.config.account,
resp_cls=AccountV0
)) ))
if rows: if rows:
b = rows[0]['balance'] b = rows[0].balance
logging.info(f'balance: {b}') logging.info(f'balance: {b}')
return b return b
else: else:
logging.info('no balance info found') logging.info('no balance info found')
return None return None
async def get_full_queue_snapshot(self):
'''
Get a "snapshot" of current contract table state
'''
snap = {
'requests': {},
'results': []
}
snap['queue'] = await self.get_work_requests_last_hour()
async def _run_and_save(d, key: str, fn, *args, **kwargs):
d[key] = await fn(*args, **kwargs)
async with trio.open_nursery() as n:
n.start_soon(_run_and_save, snap, 'results', self.find_results)
for req in snap['queue']:
n.start_soon(
_run_and_save, snap['requests'], req['id'], self.get_status_by_request_id, req['id'])
maybe_update_tui(lambda tui: tui.network_update(snap))
return snap
async def wait_data_update(self):
await self._data_event.wait()
async def iter_poll_update(self, poll_time: float):
'''
Long running task, polls gpu contract tables latest table rows,
awakes any self._data_event waiters
'''
while True:
start_time = time.time()
self._tables = await self.get_full_queue_snapshot()
elapsed = time.time() - start_time
self._data_event.set()
await trio.sleep(max(poll_time - elapsed, 0.1))
self._data_event = trio.Event()
self.poll_index += 1
async def should_cancel_work(self, request_id: int) -> bool:
logging.info('should cancel work?')
if request_id not in self._tables['requests']:
logging.info(f'request #{request_id} no longer in queue, likely its been filled by another worker, cancelling work...')
return True
competitors = set([
status['worker']
for status in self._tables['requests'][request_id]
if status['worker'] != self.config.account
])
logging.info(f'competitors: {competitors}')
should_cancel = bool(self.config.non_compete & competitors)
logging.info(f'cancel: {should_cancel}')
return should_cancel
async def begin_work(self, request_id: int): async def begin_work(self, request_id: int):
''' '''
Publish to the bc that the worker is beginning a model-computation Publish to the bc that the worker is beginning a model-computation
@ -261,7 +202,7 @@ class NetConnector:
) )
) )
async def find_results(self): async def find_results(self) -> list[ResultV0]:
logging.info('find_results') logging.info('find_results')
rows = await failable( rows = await failable(
partial( partial(
@ -270,7 +211,8 @@ class NetConnector:
index_position=4, index_position=4,
key_type='name', key_type='name',
lower_bound=self.config.account, lower_bound=self.config.account,
upper_bound=self.config.account upper_bound=self.config.account,
resp_cls=ResultV0
) )
) )
return rows return rows
@ -344,3 +286,158 @@ class NetConnector:
logging.info('decoded as image successfully') logging.info('decoded as image successfully')
return input_data return input_data
def convert_reward_to_int(reward_str):
int_part, decimal_part = (
reward_str.split('.')[0],
reward_str.split('.')[1].split(' ')[0]
)
return int(int_part + decimal_part)
class ContractState:
def __init__(self, conn: NetConnector):
self._conn = conn
self._poll_index = 0
self._queue: list[RequestV0] = []
self._status_by_rid: dict[int, list[WorkerStatusV0]] = {}
self._results: list[ResultV0] = []
self._new_data = trio.Event()
@property
def poll_index(self) -> int:
return self._poll_index
async def _fetch_results(self):
self._results = await self._conn.find_results()
async def _fetch_statuses_for_id(self, rid: int):
self._status_by_rid[rid] = await self._conn.get_status_by_request_id(rid)
async def update_state(self):
'''
Get a "snapshot" of current contract table state
'''
# raw queue from chain
_queue = await self._conn.get_work_requests_last_hour()
# filter out invalids
self._queue = []
for req in _queue:
try:
msgspec.json.decode(req.body, type=BodyV0)
self._queue.append(req)
except msgspec.ValidationError:
logging.exception(f'dropping req {req.id} due to:')
...
random.shuffle(self._queue)
self._queue = sorted(
self._queue,
key=lambda req: convert_reward_to_int(req.reward),
reverse=True
)
async with trio.open_nursery() as n:
n.start_soon(self._fetch_results)
for req in self._queue:
n.start_soon(
self._fetch_statuses_for_id, req.id)
maybe_update_tui(lambda tui: tui.network_update(self))
async def wait_data_update(self):
await self._new_data.wait()
async def _state_update_task(self, poll_time: float):
'''
Long running task, polls gpu contract tables latest table rows,
awakes any self._data_event waiters
'''
while True:
start_time = time.time()
await self.update_state()
elapsed = time.time() - start_time
self._new_data.set()
await trio.sleep(max(poll_time - elapsed, 0.1))
self._new_data = trio.Event()
self._poll_index += 1
# views into data
@property
def queue_len(self) -> int:
return len(self._queue)
@property
def first(self) -> RequestV0 | None:
if len(self._queue) > 0:
return self._queue[0]
else:
return None
def competitors_for_id(self, request_id: int) -> set[str]:
return set((
status.worker
for status in self._status_by_rid[request_id]
if status.worker != self._conn.config.account
))
# predicates
def is_request_filled(self, request_id: int) -> bool:
return request_id in [
result.request_id for result in self._results
]
def is_request_in_progress(self, request_id: int) -> bool:
return request_id in self._status_by_rid
def should_compete_for_id(self, request_id: int) -> bool:
return not bool(
self._conn.config.non_compete &
self.competitors_for_id(request_id)
)
async def should_cancel_work(self, request_id: int) -> bool:
logging.info('should cancel work?')
if request_id not in self._status_by_rid:
logging.info(f'request #{request_id} no longer in queue, likely its been filled by another worker, cancelling work...')
return True
should_cancel = not self.should_compete_for_id(request_id)
logging.info(f'cancel: {should_cancel}')
return should_cancel
__state_mngr = None
@acm
async def maybe_open_contract_state_mngr(conn: NetConnector):
global __state_mngr
if __state_mngr:
yield __state_mngr
return
config = load_skynet_toml().dgpu
mngr = ContractState(conn)
async with trio.open_nursery() as n:
await mngr.update_state()
n.start_soon(mngr._state_update_task, config.poll_time)
__state_mngr = mngr
yield mngr
n.cancel_scope.cancel()

0
skynet/dgpu/pipes/__init__.py 100644
View File

2
skynet/dgpu/pipes/tester.py
View File

@ -6,7 +6,7 @@ import msgspec
__model = { __model = {
'name': 'skygpu/txt2img-mocker' 'name': 'skygpu/mocker'
} }
class MockPipelineResult(msgspec.Struct): class MockPipelineResult(msgspec.Struct):

34
skynet/dgpu/pipes/tester_upscale.py 100644
View File

@ -0,0 +1,34 @@
from PIL import Image
import msgspec
from skynet.dgpu.utils import convert_from_image_to_cv2
__model = {
'name': 'skygpu/mocker-upscale'
}
class MockPipelineResult(msgspec.Struct):
images: list[Image]
class MockUpscalePipeline:
def enhance(
self,
img,
outscale: int
):
img = Image.new('RGB', (outscale, outscale), color='green')
output = convert_from_image_to_cv2(img)
return (output, None)
def pipeline_for(
model: str,
mode: str,
mem_fraction: float = 1.0,
cache_dir: str | None = None
):
return MockUpscalePipeline()

22
skynet/dgpu/tui.py
View File

@ -2,7 +2,6 @@ import json
import logging import logging
import warnings import warnings
import trio
import urwid import urwid
from skynet.config import DgpuConfig as Config from skynet.config import DgpuConfig as Config
@ -79,6 +78,11 @@ class WorkerMonitor:
""" """
row_widgets = [] row_widgets = []
requests = sorted(
requests,
key=lambda r: r['id']
)
for req in requests: for req in requests:
# Build a columns widget for the request row # Build a columns widget for the request row
prompt = req['prompt'] if 'prompt' in req else 'UPSCALE' prompt = req['prompt'] if 'prompt' in req else 'UPSCALE'
@ -137,10 +141,6 @@ class WorkerMonitor:
self.progress_bar.current = current self.progress_bar.current = current
pct = 0
if self.progress_bar.done != 0:
pct = int((self.progress_bar.current / self.progress_bar.done) * 100)
def update_requests(self, new_requests): def update_requests(self, new_requests):
""" """
Replace the data in the existing ListBox with new request widgets. Replace the data in the existing ListBox with new request widgets.
@ -157,14 +157,16 @@ class WorkerMonitor:
if new_balance is not None: if new_balance is not None:
self.balance_widget.set_text(new_balance) self.balance_widget.set_text(new_balance)
def network_update(self, snapshot: dict): def network_update(self, state_mngr):
queue = [ queue = [
{ {
**r, 'id': r.id,
**(json.loads(r['body'])['params']), 'user': r.user,
'workers': [s['worker'] for s in snapshot['requests'][r['id']]] 'reward': r.reward,
**(json.loads(r.body)['params']),
'workers': [s.worker for s in state_mngr._status_by_rid[r.id]]
} }
for r in snapshot['queue'] for r in state_mngr._queue
] ]
self.update_requests(queue) self.update_requests(queue)

9
skynet/dgpu/utils.py
View File

@ -1,7 +1,6 @@
import io import io
import os import os
import sys import sys
import time
import random import random
import logging import logging
import importlib import importlib
@ -76,6 +75,9 @@ class DummyPB:
def update(self): def update(self):
... ...
type Pipeline = DiffusionPipeline | RealESRGANer
@torch.compiler.disable @torch.compiler.disable
@contextmanager @contextmanager
def dummy_progress_bar(*args, **kwargs): def dummy_progress_bar(*args, **kwargs):
@ -91,7 +93,7 @@ def pipeline_for(
mode: str, mode: str,
mem_fraction: float = 1.0, mem_fraction: float = 1.0,
cache_dir: str | None = None cache_dir: str | None = None
) -> DiffusionPipeline: ) -> Pipeline:
diffusers.utils.logging.disable_progress_bar() diffusers.utils.logging.disable_progress_bar()
logging.info(f'pipeline_for {model} {mode}') logging.info(f'pipeline_for {model} {mode}')
@ -125,6 +127,9 @@ def pipeline_for(
except ImportError: except ImportError:
logging.info(f'didn\'t find a custom pipeline file for {shortname}') logging.info(f'didn\'t find a custom pipeline file for {shortname}')
# for now, upscaler special case...
if mode == 'upscale':
return init_upscaler()
req_mem = model_info.mem req_mem = model_info.mem

230
skynet/types.py 100644
View File

@ -0,0 +1,230 @@
from enum import StrEnum
from msgspec import Struct
class ModelMode(StrEnum):
DIFFUSE = 'diffuse'
TXT2IMG = 'txt2img'
IMG2IMG = 'img2img'
UPSCALE = 'upscale'
INPAINT = 'inpaint'
class ModelDesc(Struct):
short: str # short unique name
mem: float # recomended mem in gb
attrs: dict # additional mode specific attrs
tags: list[ModelMode]
# smart contract types
# https://github.com/guilledk/telos.contracts/blob/gpu_contracts/contracts/telos.gpu/include/telos.gpu/telos.gpu.hpp
'''
ConfigV0
singleton containing global info about system, definition:
```c++
struct [[eosio::table]] global_configuration_struct {
name token_contract;
symbol token_symbol;
} global_config_row;
typedef eosio::singleton<"config"_n, global_configuration_struct> global_config;
```
'''
class ConfigV0:
token_contract: str
token_symbol: str
'''
RequestV0
a request placed on the queue, definition:
scope: get_self()
```c++
struct [[eosio::table]] work_request_struct {
uint64_t id;
name user;
asset reward;
uint32_t min_verification;
uint64_t nonce;
string body;
string binary_data;
time_point_sec timestamp;
uint64_t primary_key() const { return id; }
uint64_t by_time() const { return (uint64_t)timestamp.sec_since_epoch(); }
};
typedef eosio::multi_index<
"queue"_n,
work_request_struct,
indexed_by<
"bytime"_n, const_mem_fun<work_request_struct, uint64_t, &work_request_struct::by_time>
>
> work_queue;
```
'''
class BodyV0Params(Struct):
prompt: str
model: str
seed: int
step: int = 1
guidance: str | float | None = None
width: int | None = None
height: int | None = None
strength: str | float | None = None
output_type: str | None = 'png'
upscaler: str | None = None
class BodyV0(Struct):
method: ModelMode
params: BodyV0Params
class RequestV0(Struct):
id: int
user: str
reward: str
min_verification: int
nonce: int
body: str
binary_data: str
timestamp: str
'''
AccountV0
a user account, users must deposit tokens in order to enqueue requests, definition:
scope: get_self()
```c++
struct [[eosio::table]] account {
name user;
asset balance;
uint64_t nonce;
uint64_t primary_key()const { return user.value; }
};
typedef eosio::multi_index<"users"_n, account> users;
```
'''
class AccountV0(Struct):
user: str
balance: str
nonce: int
'''
WorkerV0
a registered worker info, definition:
scope: get_self()
```c++
struct [[eosio::table]] worker {
name account;
time_point_sec joined;
time_point_sec left;
string url;
uint64_t primary_key()const { return account.value; }
};
typedef eosio::multi_index<"workers"_n, worker> workers;
```
'''
class WorkerV0(Struct):
account: str
joined: str
left: str
url: str
'''
WorkerStatusV0
a worker's status related to a currently in progress fill, definition:
scope: request id
```c++
struct [[eosio::table]] worker_status_struct {
name worker;
string status;
time_point_sec started;
uint64_t primary_key() const { return worker.value; }
};
```
'''
class WorkerStatusV0(Struct):
worker: str
status: str
started: str
'''
ResultV0
a submited result related to a request, definition:
scope: get_self()
```c++
struct [[eosio::table]] work_result_struct {
uint64_t id;
uint64_t request_id;
name user;
name worker;
checksum256 result_hash;
string ipfs_hash;
time_point_sec submited;
uint64_t primary_key() const { return id; }
uint64_t by_request_id() const { return request_id; }
checksum256 by_result_hash() const { return result_hash; }
uint64_t by_worker() const { return worker.value; }
uint64_t by_time() const { return (uint64_t)submited.sec_since_epoch(); }
};
typedef eosio::multi_index<
"results"_n,
work_result_struct,
indexed_by<
"byreqid"_n, const_mem_fun<work_result_struct, uint64_t, &work_result_struct::by_request_id>
>,
indexed_by<
"byresult"_n, const_mem_fun<work_result_struct, checksum256, &work_result_struct::by_result_hash>
>,
indexed_by<
"byworker"_n, const_mem_fun<work_result_struct, uint64_t, &work_result_struct::by_worker>
>,
indexed_by<
"bytime"_n, const_mem_fun<work_result_struct, uint64_t, &work_result_struct::by_time>
>
> work_results;
```
'''
class ResultV0(Struct):
id: int
request_id: int
user: str
worker: str
result_hash: str
ipfs_hash: str
submited: str

65
tests/conftest.py
View File

@ -1,7 +1,7 @@
import pytest import pytest
from skynet.config import *
from skynet.ipfs import AsyncIPFSHTTP from skynet.ipfs import AsyncIPFSHTTP
from skynet._testing import override_dgpu_config
@pytest.fixture(scope='session') @pytest.fixture(scope='session')
@ -20,35 +20,76 @@ def postgres_db():
def skynet_cleos(cleos_bs): def skynet_cleos(cleos_bs):
cleos = cleos_bs cleos = cleos_bs
priv, pub = cleos.create_key_pair() # priv, pub = cleos.create_key_pair()
cleos.import_key('telos.gpu', priv) # cleos.import_key('gpu.scd', priv)
cleos.new_account('telos.gpu', ram=4200000, key=pub) cleos.new_account('gpu.scd', ram=4200000)
cleos.deploy_contract_from_path( cleos.deploy_contract_from_path(
'telos.gpu', 'gpu.scd',
'tests/contracts/telos.gpu', 'tests/contracts/gpu.scd',
create_account=False create_account=False
) )
cleos.push_action( cleos.push_action(
'telos.gpu', 'gpu.scd',
'config', 'config',
['eosio.token', '4,GPU'], ['eosio.token', '4,TLOS'],
'telos.gpu' 'gpu.scd'
) )
cleos.new_account('testworker')
yield cleos yield cleos
@pytest.fixture @pytest.fixture
def inject_mockers(): def inject_mockers():
from skynet.constants import MODELS, ModelDesc from skynet.constants import MODELS
from skynet.types import ModelDesc, ModelMode
MODELS['skygpu/txt2img-mocker'] = ModelDesc( MODELS['skygpu/mocker'] = ModelDesc(
short='tester', short='tester',
mem=0.01, mem=0.01,
attrs={}, attrs={},
tags=['txt2img'] tags=[
ModelMode.TXT2IMG,
ModelMode.IMG2IMG,
ModelMode.INPAINT
]
)
MODELS['skygpu/mocker-upscale'] = ModelDesc(
short='tester-upscale',
mem=0.01,
attrs={},
tags=[
ModelMode.UPSCALE
]
)
override_dgpu_config(
account='testworker1',
permission='active',
key='',
node_url='',
ipfs_url='http://127.0.0.1:5001',
hf_token=''
) )
yield yield
@pytest.fixture(scope='session')
def ipfs_node(dockerctl):
rpc_port = 15001
with dockerctl.run(
'ipfs/go-ipfs:latest',
name='skynet-ipfs',
ports={
'8080/tcp': 18080,
'4001/tcp': 14001,
'5001/tcp': ('127.0.0.1', rpc_port)
},
timeout=60
) as cntr:
yield cntr, AsyncIPFSHTTP(f'http://127.0.0.1:{rpc_port}')

0
tests/contracts/telos.gpu/telos.gpu.abi → tests/contracts/gpu.scd/gpu.scd.abi
View File

0
tests/contracts/telos.gpu/telos.gpu.wasm → tests/contracts/gpu.scd/gpu.scd.wasm
View File

53
tests/test_chain.py
View File

@ -1,3 +1,52 @@
def test_dev(skynet_cleos): import trio
from msgspec import json
from skynet.types import BodyV0, BodyV0Params
from skynet._testing import open_test_worker
async def test_full_flow(inject_mockers, skynet_cleos, ipfs_node):
cleos = skynet_cleos cleos = skynet_cleos
...
# create account and deposit tokens into gpu
account = cleos.new_account()
quantity = '1000.0000 TLOS'
cleos.transfer_token('eosio', account, quantity)
cleos.transfer_token(account, 'gpu.scd', quantity)
og_body = BodyV0(
method='txt2img',
params=BodyV0Params(
prompt='cyberpunk hacker travis bickle dystopic alley graffiti',
model='skygpu/mocker',
step=4,
seed=0,
guidance=10.0
)
)
body = json.encode(og_body).decode('utf-8')
binary_data = ''
reward = '1.0000 TLOS'
min_verification = 1
# send enqueue req
cleos.push_action(
'gpu.scd',
'enqueue',
[
account,
body,
binary_data,
reward,
min_verification
],
account,
key=cleos.private_keys[account]
)
# open worker and fill request
async with open_test_worker(cleos, ipfs_node) as (_conn, state_mngr):
while state_mngr.queue_len > 0:
await trio.sleep(1)

14
tests/test_ipfs_client.py
View File

@ -1,14 +1,16 @@
from pathlib import Path from pathlib import Path
async def test_connection(ipfs_client): # async def test_connection(ipfs_node):
await ipfs_client.connect( # _, ipfs_client = ipfs_node
'/ip4/169.197.140.154/tcp/4001/p2p/12D3KooWKWogLFNEcNNMKnzU7Snrnuj84RZdMBg3sLiQSQc51oEv') # await ipfs_client.connect(
peers = await ipfs_client.peers() # '/ip4/169.197.140.154/tcp/4001/p2p/12D3KooWKWogLFNEcNNMKnzU7Snrnuj84RZdMBg3sLiQSQc51oEv')
assert '12D3KooWKWogLFNEcNNMKnzU7Snrnuj84RZdMBg3sLiQSQc51oEv' in [p['Peer'] for p in peers] # peers = await ipfs_client.peers()
# assert '12D3KooWKWogLFNEcNNMKnzU7Snrnuj84RZdMBg3sLiQSQc51oEv' in [p['Peer'] for p in peers]
async def test_add_and_pin_file(ipfs_client): async def test_add_and_pin_file(ipfs_node):
_, ipfs_client = ipfs_node
test_file = Path('hello_world.txt') test_file = Path('hello_world.txt')
with open(test_file, 'w+') as file: with open(test_file, 'w+') as file:
file.write('Hello Skynet!') file.write('Hello Skynet!')

71
tests/test_reqs.py
View File

@ -1,39 +1,50 @@
import pytest import pytest
from PIL import Image
from skynet.types import ModelMode, BodyV0Params
from skynet.dgpu.compute import maybe_load_model, compute_one from skynet.dgpu.compute import maybe_load_model, compute_one
@pytest.mark.parametrize("mode", [ @pytest.mark.parametrize('mode,model', [
('diffuse'), ('txt2img') (ModelMode.DIFFUSE, 'skygpu/mocker'),
(ModelMode.TXT2IMG, 'skygpu/mocker'),
(ModelMode.IMG2IMG, 'skygpu/mocker'),
(ModelMode.INPAINT, 'skygpu/mocker'),
(ModelMode.UPSCALE, 'skygpu/mocker-upscale'),
]) ])
async def test_pipeline_mocker(inject_mockers, mode): async def test_pipeline_mocker(inject_mockers, mode, model):
model = 'skygpu/txt2img-mocker' # always insert at least two inputs to make all modes pass
params = { inputs = [
"prompt": "Kronos God Realistic 4k", Image.new('RGB', (1, 1), color='green')
"model": model, for i in range(2)
"step": 21, ]
"width": 1024, params = BodyV0Params(
"height": 1024, prompt="Kronos God Realistic 4k",
"seed": 168402949, model=model,
"guidance": "7.5" step=4,
} width=1024,
height=1024,
seed=168402949,
guidance="7.5",
strength="0.65"
)
with maybe_load_model(model, mode) as model: with maybe_load_model(model, mode) as model:
compute_one(model, 0, mode, params) compute_one(model, 0, mode, params, inputs)
# disable for now (cuda)
async def test_pipeline(): # async def test_pipeline():
model = 'stabilityai/stable-diffusion-xl-base-1.0' # model = 'stabilityai/stable-diffusion-xl-base-1.0'
mode = 'txt2img' # mode = 'txt2img'
params = { # params = BodyV0Params(
"prompt": "Kronos God Realistic 4k", # prompt="Kronos God Realistic 4k",
"model": model, # model=model,
"step": 21, # step=21,
"width": 1024, # width=1024,
"height": 1024, # height=1024,
"seed": 168402949, # seed=168402949,
"guidance": "7.5" # guidance="7.5"
} # )
#
with maybe_load_model(model, mode) as model: # with maybe_load_model(model, mode) as model:
compute_one(model, 0, mode, params) # compute_one(model, 0, mode, params)

295
uv.lock
View File

@ -1,5 +1,5 @@
# vim: ft=toml
version = 1 version = 1
revision = 1
requires-python = ">=3.10, <3.13" requires-python = ">=3.10, <3.13"
resolution-markers = [ resolution-markers = [
"python_full_version >= '3.12' and sys_platform == 'darwin'", "python_full_version >= '3.12' and sys_platform == 'darwin'",
@ -51,16 +51,16 @@ wheels = [
[[package]] [[package]]
name = "aiohappyeyeballs" name = "aiohappyeyeballs"
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[[package]] [[package]]
name = "aiohttp" name = "aiohttp"
version = "3.11.11" version = "3.11.12"
source = { registry = "https://pypi.org/simple" } source = { registry = "https://pypi.org/simple" }
dependencies = [ dependencies = [
{ name = "aiohappyeyeballs" }, { name = "aiohappyeyeballs" },
@ -72,53 +72,56 @@ dependencies = [
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{ name = "yarl" }, { name = "yarl" },
] ]
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