[mention]torzdf[/mention] I tried out your branch and fixed some issues:
https://github.com/deepfakes/faceswap/pull/1238
Note that setup.py doesn't ask for Apple Silicon, so the backend gets set to CPU. This:
worked though.
Setup runs successfully using my PR, but when trying to run FS, I get this:
Code: Select all
Setting Faceswap backend to APPLE_SILICON
Traceback (most recent call last):
File "/Users/server/Documents/faceswap_test/faceswap.py", line 6, in <module>
from lib.cli import args as cli_args
File "/Users/server/Documents/faceswap_test/lib/cli/args.py", line 13, in <module>
from lib.gpu_stats import GPUStats
File "/Users/server/Documents/faceswap_test/lib/gpu_stats/__init__.py", line 20, in <module>
from .apple_silicon import AppleSiliconStats as GPUStats # noqa
File "/Users/server/Documents/faceswap_test/lib/gpu_stats/apple_silicon.py", line 7, in <module>
import tensorflow as tf
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/tensorflow/__init__.py", line 37, in <module>
from tensorflow.python.tools import module_util as _module_util
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/tensorflow/python/__init__.py", line 37, in <module>
from tensorflow.python.eager import context
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/tensorflow/python/eager/context.py", line 29, in <module>
from tensorflow.core.framework import function_pb2
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/tensorflow/core/framework/function_pb2.py", line 16, in <module>
from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/tensorflow/core/framework/attr_value_pb2.py", line 16, in <module>
from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/tensorflow/core/framework/tensor_pb2.py", line 16, in <module>
from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/tensorflow/core/framework/resource_handle_pb2.py", line 16, in <module>
from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/tensorflow/core/framework/tensor_shape_pb2.py", line 36, in <module>
_descriptor.FieldDescriptor(
File "/Users/server/miniforge3/envs/test3/lib/python3.9/site-packages/google/protobuf/descriptor.py", line 560, in __new__
_message.Message._CheckCalledFromGeneratedFile()
TypeError: Descriptors cannot not be created directly.
If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0.
If you cannot immediately regenerate your protos, some other possible workarounds are:
1. Downgrade the protobuf package to 3.20.x or lower.
2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).
More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates
Might be due to a new Python version?