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skynet
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First pass adding msgspec structs 

Added nix-shell dev file
Switch to dev branch of py-leap for get_table row auto struct unpack
Add testing module with helpers like override global load config function
Add types for Queue V0
Rename test contract to gpu.scd to match current
Add new enqueue test
Update lock
structify
Guillermo Rodriguez 2025-02-11 14:08:17 -03:00
parent 868e2489b3
commit 08b6b983a2
No known key found for this signature in database
GPG Key ID: 002CC5F1E6BDA53E
15 changed files with 423 additions and 267 deletions
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36
default.nix 100644
View File

@ -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
View File

@ -77,7 +77,7 @@ explicit = true
torch = { index = "torch" }
triton = { 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", branch = "struct_unwrap" }
pytest-dockerctl = { git = "https://github.com/pikers/pytest-dockerctl.git", branch = "g_update" }
[build-system]

9
skynet/_testing.py 100644
View File

@ -0,0 +1,9 @@
from skynet.config import Config, DgpuConfig, set_config_override
def override_dgpu_config(**kwargs) -> DgpuConfig:
config = Config(
dgpu=DgpuConfig(**kwargs)
)
set_config_override(config)
return config.dgpu

12
skynet/config.py
View File

@ -1,5 +1,4 @@
import os
import toml
import msgspec
@ -59,7 +58,18 @@ class Config(msgspec.Struct):
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:
global __config_override
if __config_override:
return __config_override
with open(file_path, 'r') as file:
return msgspec.toml.decode(file.read(), type=Config)

15
skynet/constants.py
View File

@ -1,20 +1,9 @@
import msgspec
from skynet.types import ModelDesc
from enum import Enum
from typing import Literal
VERSION = '0.1a12'
VERSION = '0.1a13'
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] = {
'RealESRGAN_x4plus': ModelDesc(
short='realesrgan',

53
skynet/dgpu/compute.py
View File

@ -13,6 +13,7 @@ import trio
import torch
from skynet.config import load_skynet_toml
from skynet.types import ModelMode, BodyV0, BodyV0Params
from skynet.dgpu.tui import maybe_update_tui
from skynet.dgpu.errors import (
DGPUComputeError,
@ -23,13 +24,13 @@ from skynet.dgpu.utils import crop_image, convert_from_cv2_to_image, convert_fro
def prepare_params_for_diffuse(
params: dict,
mode: str,
params: BodyV0Params,
mode: ModelMode,
inputs: list[bytes]
):
_params = {}
match mode:
case 'inpaint':
case ModelMode.INPAINT:
image = crop_image(
inputs[0], params['width'], params['height'])
@ -44,28 +45,25 @@ def prepare_params_for_diffuse(
else:
_params['strength'] = float(params['strength'])
case 'img2img':
case ModelMode.IMG2IMG:
image = crop_image(
inputs[0], params['width'], params['height'])
_params['image'] = image
_params['strength'] = float(params['strength'])
case 'txt2img' | 'diffuse':
case ModelMode.TXT2IMG | ModelMode.DIFFUSE:
...
case _:
raise DGPUComputeError(f'Unknown mode {mode}')
# _params['width'] = int(params['width'])
# _params['height'] = int(params['height'])
return (
params['prompt'],
float(params['guidance']),
int(params['step']),
torch.manual_seed(int(params['seed'])),
params['upscaler'] if 'upscaler' in params else None,
params.prompt,
params.guidance,
params.step,
torch.manual_seed(int(params.seed)),
params.upscaler,
_params
)
@ -74,9 +72,9 @@ _model_mode: str = ''
_model = None
@cm
def maybe_load_model(name: str, mode: str):
if mode == 'diffuse':
mode = 'txt2img'
def maybe_load_model(name: str, mode: ModelMode):
if mode == ModelMode.DIFFUSE:
mode = ModelMode.TXT2IMG
global _model_name, _model_mode, _model
config = load_skynet_toml().dgpu
@ -90,7 +88,7 @@ def maybe_load_model(name: str, mode: str):
_model_name = _model_mode = ''
# load model
if mode == 'upscale':
if mode == ModelMode.UPSCALE:
_model = init_upscaler()
else:
@ -100,6 +98,7 @@ def maybe_load_model(name: str, mode: str):
_model_name = name
_model_mode = mode
if torch.cuda.is_available():
logging.debug('memory summary:')
logging.debug('\n' + torch.cuda.memory_summary())
@ -109,12 +108,12 @@ def maybe_load_model(name: str, mode: str):
def compute_one(
model,
request_id: int,
method: str,
params: dict,
method: ModelMode,
params: BodyV0Params,
inputs: list[bytes] = [],
should_cancel = None
):
total_steps = params['step'] if 'step' in params else 1
total_steps = params.step
def inference_step_wakeup(*args, **kwargs):
'''This is a callback function that gets invoked every inference step,
we need to raise an exception here if we need to cancel work
@ -140,17 +139,19 @@ def compute_one(
inference_step_wakeup(0)
output_type = 'png'
if 'output_type' in params:
output_type = params['output_type']
output_type = params.output_type
output = None
output_hash = None
try:
name = params['model']
name = params.model
match method:
case 'diffuse' | 'txt2img' | 'img2img' | 'inpaint':
case (
ModelMode.DIFFUSE |
ModelMode.TXT2IMG |
ModelMode.IMG2IMG |
ModelMode.INPAINT
):
arguments = prepare_params_for_diffuse(
params, method, inputs)
prompt, guidance, step, seed, upscaler, extra_params = arguments

63
skynet/dgpu/daemon.py
View File

@ -1,21 +1,18 @@
import json
import logging
import random
import time
from datetime import datetime
from functools import partial
from hashlib import sha256
import trio
import msgspec
from skynet.config import DgpuConfig as Config
from skynet.constants import (
MODELS,
VERSION,
)
from skynet.dgpu.errors import (
DGPUComputeError,
from skynet.types import (
RequestV0,
BodyV0
)
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.compute import maybe_load_model, compute_one
from skynet.dgpu.network import NetConnector
@ -41,14 +38,13 @@ async def maybe_update_tui_balance(conn: NetConnector):
async def maybe_serve_one(
config: Config,
conn: NetConnector,
req: dict,
req: RequestV0,
):
rid = req['id']
logging.info(f'maybe serve request #{rid}')
logging.info(f'maybe serve request #{req.id}')
# parse request
body = json.loads(req['body'])
model = body['params']['model']
body = msgspec.json.decode(req.body, type=BodyV0)
model = body.params.model
# if model not known, ignore.
if model not in MODELS:
@ -76,11 +72,11 @@ async def maybe_serve_one(
results = [res['request_id'] for res in conn._tables['results']]
# if worker already produced a result for this request
if rid in results:
logging.info(f'worker already submitted a result for request #{rid}, skip...')
if req.id in results:
logging.info(f'worker already submitted a result for request #{req.id}, skip...')
return
statuses = conn._tables['requests'][rid]
statuses = conn._tables['requests'][req.id]
# skip if workers in non_compete already on it
competitors = set((status['worker'] for status in statuses))
@ -90,12 +86,12 @@ async def maybe_serve_one(
# resolve the ipfs hashes into the actual data behind them
inputs = []
raw_inputs = req['binary_data'].split(',')
raw_inputs = req.binary_data.split(',')
if raw_inputs:
logging.info(f'fetching IPFS inputs: {raw_inputs}')
retry = 3
for _input in req['binary_data'].split(','):
for _input in raw_inputs:
if _input:
for r in range(retry):
try:
@ -114,24 +110,22 @@ async def maybe_serve_one(
# compute unique request hash used on submit
hash_str = (
str(req['nonce'])
str(req.nonce)
+
req['body']
req.body
+
req['binary_data']
req.binary_data
)
logging.debug(f'hashing: {hash_str}')
request_hash = sha256(hash_str.encode('utf-8')).hexdigest()
logging.info(f'calculated request hash: {request_hash}')
params = body['params']
total_step = params['step'] if 'step' in params else 1
model = body['params']['model']
mode = body['method']
total_step = body.params.step
mode = body.method
# TODO: validate request
resp = await conn.begin_work(rid)
resp = await conn.begin_work(req.id)
if not resp or 'code' in resp:
logging.info('begin_work error, probably being worked on already... skip.')
return
@ -140,10 +134,7 @@ async def maybe_serve_one(
try:
maybe_update_tui(lambda tui: tui.set_progress(0, done=total_step))
output_type = 'png'
if 'output_type' in body['params']:
output_type = body['params']['output_type']
output_type = body.params.output_type
output = None
output_hash = None
match config.backend:
@ -152,8 +143,8 @@ async def maybe_serve_one(
partial(
compute_one,
model,
rid,
mode, params,
req.id,
mode, body.params,
inputs=inputs,
should_cancel=conn.should_cancel_work,
)
@ -168,7 +159,7 @@ async def maybe_serve_one(
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)
@ -177,8 +168,8 @@ async def maybe_serve_one(
if 'network cancel' not in str(err):
logging.exception('Failed to serve model request !?\n')
if rid in conn._tables['requests']:
await conn.cancel_work(rid, 'reason not provided')
if req.id in conn._tables['requests']:
await conn.cancel_work(req.id, 'reason not provided')
async def dgpu_serve_forever(config: Config, conn: NetConnector):

12
skynet/dgpu/network.py
View File

@ -3,7 +3,6 @@ import json
import time
import logging
from pathlib import Path
from typing import AsyncGenerator
from functools import partial
import trio
@ -16,10 +15,8 @@ from leap.cleos import CLEOS
from leap.protocol import Asset
from skynet.dgpu.tui import maybe_update_tui
from skynet.config import DgpuConfig as Config
from skynet.constants import (
DEFAULT_IPFS_DOMAIN,
GPU_CONTRACT_ABI,
)
from skynet.types import RequestV0
from skynet.constants import GPU_CONTRACT_ABI
from skynet.ipfs import (
AsyncIPFSHTTP,
@ -81,7 +78,7 @@ class NetConnector:
# 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')
rows = await failable(
partial(
@ -89,7 +86,8 @@ class NetConnector:
'gpu.scd', 'gpu.scd', 'queue',
index_position=2,
key_type='i64',
lower_bound=int(time.time()) - 3600
lower_bound=int(time.time()) - 3600,
resp_cls=RequestV0
), ret_fail=[])
logging.info(f'found {len(rows)} requests on queue')

47
skynet/types.py 100644
View File

@ -0,0 +1,47 @@
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
attrs: dict # additional mode specific attrs
tags: list[ModelMode]
class BodyV0Params(Struct):
prompt: str
model: str
seed: int
step: int = 1
guidance: float | None = None
width: int | None = None
height: int | None = None
strength: 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

18
tests/conftest.py
View File

@ -1,6 +1,5 @@
import pytest
from skynet.config import *
from skynet.ipfs import AsyncIPFSHTTP
@ -21,20 +20,20 @@ def skynet_cleos(cleos_bs):
cleos = cleos_bs
priv, pub = cleos.create_key_pair()
cleos.import_key('telos.gpu', priv)
cleos.new_account('telos.gpu', ram=4200000, key=pub)
cleos.import_key('gpu.scd', priv)
cleos.new_account('gpu.scd', ram=4200000, key=pub)
cleos.deploy_contract_from_path(
'telos.gpu',
'tests/contracts/telos.gpu',
'gpu.scd',
'tests/contracts/gpu.scd',
create_account=False
)
cleos.push_action(
'telos.gpu',
'gpu.scd',
'config',
['eosio.token', '4,GPU'],
'telos.gpu'
['eosio.token', '4,TLOS'],
'gpu.scd'
)
yield cleos
@ -42,7 +41,8 @@ def skynet_cleos(cleos_bs):
@pytest.fixture
def inject_mockers():
from skynet.constants import MODELS, ModelDesc
from skynet.constants import MODELS
from skynet.types import ModelDesc
MODELS['skygpu/txt2img-mocker'] = ModelDesc(
short='tester',

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

66
tests/test_chain.py
View File

@ -1,3 +1,65 @@
def test_dev(skynet_cleos):
from msgspec import json
from skynet.types import BodyV0, BodyV0Params
from skynet.dgpu.network import NetConnector
from skynet._testing import override_dgpu_config
async def test_enqueue(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/txt2img-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]
)
config = override_dgpu_config(
account='testworker1',
permission='active',
key='',
node_url=cleos.endpoint,
ipfs_url='http://127.0.0.1:5001',
hf_token=''
)
net = NetConnector(config)
queue = await net.get_work_requests_last_hour()
assert len(queue) == 1
req = queue[0]
body = json.decode(req.body, type=BodyV0)
assert og_body == body

49
tests/test_reqs.py
View File

@ -1,22 +1,33 @@
import pytest
from skynet.types import ModelMode, BodyV0Params
from skynet.dgpu.compute import maybe_load_model, compute_one
from skynet._testing import override_dgpu_config
@pytest.mark.parametrize("mode", [
('diffuse'), ('txt2img')
(ModelMode.DIFFUSE), (ModelMode.TXT2IMG)
])
async def test_pipeline_mocker(inject_mockers, mode):
override_dgpu_config(
account='testworker1',
permission='active',
key='',
node_url='',
ipfs_url='http://127.0.0.1:5001',
hf_token=''
)
model = 'skygpu/txt2img-mocker'
params = {
"prompt": "Kronos God Realistic 4k",
"model": model,
"step": 21,
"width": 1024,
"height": 1024,
"seed": 168402949,
"guidance": "7.5"
}
params = BodyV0Params(
prompt="Kronos God Realistic 4k",
model=model,
step=4,
width=1024,
height=1024,
seed=168402949,
guidance="7.5"
)
with maybe_load_model(model, mode) as model:
compute_one(model, 0, mode, params)
@ -25,15 +36,15 @@ async def test_pipeline_mocker(inject_mockers, mode):
async def test_pipeline():
model = 'stabilityai/stable-diffusion-xl-base-1.0'
mode = 'txt2img'
params = {
"prompt": "Kronos God Realistic 4k",
"model": model,
"step": 21,
"width": 1024,
"height": 1024,
"seed": 168402949,
"guidance": "7.5"
}
params = BodyV0Params(
prompt="Kronos God Realistic 4k",
model=model,
step=21,
width=1024,
height=1024,
seed=168402949,
guidance="7.5"
)
with maybe_load_model(model, mode) as model:
compute_one(model, 0, mode, params)

304
uv.lock
View File

@ -1,4 +1,3 @@
# vim: ft=toml
version = 1
requires-python = ">=3.10, <3.13"
resolution-markers = [
@ -51,16 +50,16 @@ wheels = [
[[package]]
name = "aiohappyeyeballs"
version = "2.4.4"
version = "2.4.6"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/7f/55/e4373e888fdacb15563ef6fa9fa8c8252476ea071e96fb46defac9f18bf2/aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745", size = 21977 }
sdist = { url = "https://files.pythonhosted.org/packages/08/07/508f9ebba367fc3370162e53a3cfd12f5652ad79f0e0bfdf9f9847c6f159/aiohappyeyeballs-2.4.6.tar.gz", hash = "sha256:9b05052f9042985d32ecbe4b59a77ae19c006a78f1344d7fdad69d28ded3d0b0", size = 21726 }
wheels = [
{ url = "https://files.pythonhosted.org/packages/b9/74/fbb6559de3607b3300b9be3cc64e97548d55678e44623db17820dbd20002/aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8", size = 14756 },
{ url = "https://files.pythonhosted.org/packages/44/4c/03fb05f56551828ec67ceb3665e5dc51638042d204983a03b0a1541475b6/aiohappyeyeballs-2.4.6-py3-none-any.whl", hash = "sha256:147ec992cf873d74f5062644332c539fcd42956dc69453fe5204195e560517e1", size = 14543 },
]
[[package]]
name = "aiohttp"
version = "3.11.11"
version = "3.11.12"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiohappyeyeballs" },
@ -72,53 +71,56 @@ dependencies = [
{ name = "propcache" },
{ name = "yarl" },
]
sdist = { url = "https://files.pythonhosted.org/packages/fe/ed/f26db39d29cd3cb2f5a3374304c713fe5ab5a0e4c8ee25a0c45cc6adf844/aiohttp-3.11.11.tar.gz", hash = "sha256:bb49c7f1e6ebf3821a42d81d494f538107610c3a705987f53068546b0e90303e", size = 7669618 }
sdist = { url = "https://files.pythonhosted.org/packages/37/4b/952d49c73084fb790cb5c6ead50848c8e96b4980ad806cf4d2ad341eaa03/aiohttp-3.11.12.tar.gz", hash = "sha256:7603ca26d75b1b86160ce1bbe2787a0b706e592af5b2504e12caa88a217767b0", size = 7673175 }
wheels = [
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