1580158
/
automatic
mirror of https://github.com/vladmandic/automatic
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

OpenVINO fixes

pull/2088/head
Disty0 2023-08-21 21:34:53 +03:00
parent 698c8d56cd
commit ebf7b90e3e
5 changed files with 109 additions and 15 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
.gitignore vendored
View File

@ -15,6 +15,7 @@ pnpm-lock.yaml
package-lock.json
venv
.history
cache
# all models and temp files
*.log

5
README.md
View File

@ -68,7 +68,8 @@ Additional models will be added as they become available and there is public int
Support will be extended to *Windows* once AMD releases ROCm for Windows
- Any GPU compatibile with *DirectX* on *Windows* using **DirectML** libraries.
This includes support for AMD GPUs that are not supported by native ROCm libraries
- *Intel Arc* GPUs using *Intel OneAPI* **Ipex/XPU** libraries
- *Intel Arc* GPUs using *Intel OneAPI* **Ipex/XPU** libraries
- *Intel* iGPUs using *Intel OneAPI* **OpenVINO** libraries
- *Apple M1/M2* on *OSX* using built-in support in Torch with **MPS** optimizations
## Install & Run
@ -94,8 +95,8 @@ Once SD.Next is installed, simply run `webui.bat` (*Windows*) or `webui.sh` (*Li
Below is partial list of all available parameters, run `webui --help` for the full list:
Setup options:
--use-ipex Use Intel OneAPI XPU backend, default: False
--use-directml Use DirectML if no compatible GPU is detected, default: False
--use-ipex Force use Intel OneAPI XPU backend, default: False
--use-cuda Force use nVidia CUDA backend, default: False
--use-rocm Force use AMD ROCm backend, default: False
--skip-update Skip update of extensions and submodules, default: False

3
installer.py
View File

@ -458,6 +458,7 @@ def check_torch():
install('hidet', 'hidet')
if opts.get('cuda_compile_backend', '') == 'openvino_fx':
install('openvino==2023.1.0.dev20230811', 'openvino')
os.environ.setdefault('PYTORCH_TRACING_MODE', 'TORCHFX')
if args.profile:
print_profile(pr, 'Torch')
@ -829,8 +830,8 @@ def add_args(parser):
group.add_argument('--upgrade', default = False, action='store_true', help = "Upgrade main repository to latest version, default: %(default)s")
group.add_argument('--requirements', default = False, action='store_true', help = "Force re-check of requirements, default: %(default)s")
group.add_argument('--quick', default = False, action='store_true', help = "Run with startup sequence only, default: %(default)s")
group.add_argument("--use-ipex", default = False, action='store_true', help="Use Intel OneAPI XPU backend, default: %(default)s")
group.add_argument('--use-directml', default = False, action='store_true', help = "Use DirectML if no compatible GPU is detected, default: %(default)s")
group.add_argument("--use-ipex", default = False, action='store_true', help="Force use Intel OneAPI XPU backend, default: %(default)s")
group.add_argument("--use-cuda", default=False, action='store_true', help="Force use nVidia CUDA backend, default: %(default)s")
group.add_argument("--use-rocm", default=False, action='store_true', help="Force use AMD ROCm backend, default: %(default)s")
group.add_argument('--skip-requirements', default = False, action='store_true', help = "Skips checking and installing requirements, default: %(default)s")

2
modules/cmd_args.py
View File

@ -40,8 +40,8 @@ group.add_argument("--no-download", action='store_true', help="Disable download
group.add_argument("--profile", action='store_true', help="Run profiler, default: %(default)s")
group.add_argument("--disable-queue", action='store_true', help="Disable queues, default: %(default)s")
group.add_argument('--debug', default = False, action='store_true', help = "Run installer with debug logging, default: %(default)s")
group.add_argument("--use-ipex", default = False, action='store_true', help="Use Intel OneAPI XPU backend, default: %(default)s")
group.add_argument('--use-directml', default = False, action='store_true', help = "Use DirectML if no compatible GPU is detected, default: %(default)s")
group.add_argument("--use-ipex", default = False, action='store_true', help="Force use Intel OneAPI XPU backend, default: %(default)s")
group.add_argument("--use-cuda", default=False, action='store_true', help="Force use nVidia CUDA backend, default: %(default)s")
group.add_argument("--use-rocm", default=False, action='store_true', help="Force use AMD ROCm backend, default: %(default)s")
group.add_argument('--subpath', type=str, help='Customize the URL subpath for usage with reverse proxy')

113
modules/intel/openvino/__init__.py
View File

@ -2,23 +2,114 @@ import os
import torch
from openvino.frontend.pytorch.torchdynamo.execute import execute
from openvino.frontend.pytorch.torchdynamo.partition import Partitioner
from openvino.runtime import Core, Type, PartialShape
from torch._dynamo.backends.common import fake_tensor_unsupported
from torch._dynamo.backends.registry import register_backend
from torch.fx.experimental.proxy_tensor import make_fx
from torch._inductor.compile_fx import compile_fx
from hashlib import sha256
import modules.shared
class ModelState:
def __init__(self):
self.recompile = 1
self.device = "CPU"
self.height = 512
self.width = 512
self.batch_size = 1
self.mode = 0
self.partition_id = 0
self.model_hash = ""
model_state = ModelState()
@register_backend
@fake_tensor_unsupported
def openvino_fx(subgraph, example_inputs):
if os.getenv("OPENVINO_TORCH_BACKEND_DEVICE") is None:
os.environ.setdefault("OPENVINO_TORCH_BACKEND_DEVICE", "GPU")
try:
executor_parameters = None
core = Core()
if os.getenv("OPENVINO_TORCH_MODEL_CACHING") != "0":
os.environ.setdefault('OPENVINO_TORCH_MODEL_CACHING', "1")
model_hash_str = sha256(subgraph.code.encode('utf-8')).hexdigest()
model_hash_str_file = model_hash_str + str(model_state.partition_id)
model_state.partition_id = model_state.partition_id + 1
executor_parameters = {"model_hash_str": model_hash_str}
model = make_fx(subgraph)(*example_inputs)
with torch.no_grad():
model.eval()
partitioner = Partitioner()
compiled_model = partitioner.make_partitions(model)
example_inputs.reverse()
cache_root = "./cache/"
if os.getenv("OPENVINO_TORCH_CACHE_DIR") is not None:
cache_root = os.getenv("OPENVINO_TORCH_CACHE_DIR")
def _call(*args):
res = execute(compiled_model, *args, executor="openvino")
return res
return _call
device = "GPU"
if os.getenv("OPENVINO_TORCH_BACKEND_DEVICE") is not None:
device = os.getenv("OPENVINO_TORCH_BACKEND_DEVICE")
assert device in core.available_devices, "Specified device " + device + " is not in the list of OpenVINO Available Devices"
else:
os.environ.setdefault('OPENVINO_TORCH_BACKEND_DEVICE', device)
file_name = get_cached_file_name(*example_inputs, model_hash_str=model_hash_str_file, device=device, cache_root=cache_root)
if file_name is not None and os.path.isfile(file_name + ".xml") and os.path.isfile(file_name + ".bin"):
om = core.read_model(file_name + ".xml")
dtype_mapping = {
torch.float32: Type.f32,
torch.float64: Type.f64,
torch.float16: Type.f16,
torch.int64: Type.i64,
torch.int32: Type.i32,
torch.uint8: Type.u8,
torch.int8: Type.i8,
torch.bool: Type.boolean
}
for idx, input_data in enumerate(example_inputs):
om.inputs[idx].get_node().set_element_type(dtype_mapping[input_data.dtype])
om.inputs[idx].get_node().set_partial_shape(PartialShape(list(input_data.shape)))
om.validate_nodes_and_infer_types()
if model_hash_str is not None:
core.set_property({'CACHE_DIR': cache_root + '/blob'})
compiled_model = core.compile_model(om, device)
def _call(*args):
ov_inputs = [a.detach().cpu().numpy() for a in args]
ov_inputs.reverse()
res = compiled_model(ov_inputs)
result = [torch.from_numpy(res[out]) for out in compiled_model.outputs]
return result
return _call
else:
example_inputs.reverse()
model = make_fx(subgraph)(*example_inputs)
with torch.no_grad():
model.eval()
partitioner = Partitioner()
compiled_model = partitioner.make_partitions(model)
def _call(*args):
res = execute(compiled_model, *args, executor="openvino",
executor_parameters=executor_parameters)
return res
return _call
except Exception:
return compile_fx(subgraph, example_inputs)
def get_cached_file_name(*args, model_hash_str, device, cache_root):
file_name = None
if model_hash_str is not None:
model_cache_dir = cache_root + "/model/"
try:
os.makedirs(model_cache_dir, exist_ok=True)
file_name = model_cache_dir + model_hash_str + "_" + device
for input_data in args:
if file_name is not None:
file_name += "_" + str(input_data.type()) + str(input_data.size())[11:-1].replace(" ", "")
except OSError as error:
print("Cache directory ", cache_root, " cannot be created. Model caching is disabled. Error: ", error)
file_name = None
model_hash_str = None
return file_name