run error

[mathpopo]

stty: 标准输入: 对设备不适当的 ioctl 操作
Traceback (most recent call last):
File "/home/chenxin/disk1/github/MQBench_Quantize/main.py", line 21, in
from utils import progress_bar, choose_model, choose_backend
File "/home/chenxin/disk1/github/MQBench_Quantize/utils.py", line 49, in
_, term_width = os.popen('stty size', 'r').read().split()
ValueError: not enough values to unpack (expected 2, got 0)

[mathpopo]

use WuJie1010/Facial-Expression-Recognition.Pytorch#1 can run

but

Traceback (most recent call last):
File "/home/chenxin/disk1/github/MQBench_Quantize/main.py", line 170, in
net = choose_model(args)
File "/home/chenxin/disk1/github/MQBench_Quantize/utils.py", line 152, in choose_model
return ShuffleNetG2()
File "/home/chenxin/disk1/github/MQBench_Quantize/models/shufflenet.py", line 92, in ShuffleNetG2
return ShuffleNet(cfg)
File "/home/chenxin/disk1/github/MQBench_Quantize/models/shufflenet.py", line 61, in init
self.layer1 = self._make_layer(out_planes[0], num_blocks[0], groups)
File "/home/chenxin/disk1/github/MQBench_Quantize/models/shufflenet.py", line 71, in _make_layer
layers.append(Bottleneck(self.in_planes, out_planes-cat_planes, stride=stride, groups=groups))
File "/home/chenxin/disk1/github/MQBench_Quantize/models/shufflenet.py", line 29, in init
self.conv1 = nn.Conv2d(in_planes, mid_planes, kernel_size=1, groups=g, bias=False)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 388, in init
False, _pair(0), groups, bias, padding_mode)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 107, in init
out_channels, in_channels // groups, *kernel_size))
TypeError: new() received an invalid combination of arguments - got (float, int, int, int), but expected one of:

• (*, torch.device device)
• (torch.Storage storage)
• (Tensor other)
• (tuple of ints size, *, torch.device device)
• (object data, *, torch.device device)

Process finished with exit code 1

[mathpopo]

does mqbench0.02 version cannot support these?

main.py ShuffleNetV2 --quantize
==> Preparing data..
Files already downloaded and verified
Files already downloaded and verified
==> Building model..
[MQBENCH] INFO: Quantize model using BackendType.Tensorrt scheme.
[MQBENCH] INFO: Weight Qconfig:
FakeQuantize: LearnableFakeQuantize Params: {}
Oberver: MinMaxObserver Params: Symmetric: True / Bitwidth: 8 / Per channel: True / Pot scale: False
[MQBENCH] INFO: Activation Qconfig:
FakeQuantize: LearnableFakeQuantize Params: {}
Oberver: EMAMinMaxObserver Params: Symmetric: True / Bitwidth: 8 / Per channel: False / Pot scale: False
Traceback (most recent call last):
File "/home/chenxin/disk1/github/MQBench_Quantize/main.py", line 201, in
net = prepare_qat_fx_by_platform(net, backend)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/MQBench-0.0.2-py3.7.egg/mqbench/prepare_by_platform.py", line 257, in prepare_qat_fx_by_platform
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 605, in symbolic_trace
graph = tracer.trace(root, concrete_args)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 354, in trace
self.create_node('output', 'output', (self.create_arg(fn(*args)),), {},
File "/home/chenxin/disk1/github/MQBench_Quantize/models/shufflenetv2.py", line 124, in forward
out = self.layer1(out)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 343, in module_call_wrapper
return self.call_module(mod, forward, args, kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 222, in call_module
return forward(*args, **kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 339, in forward
return _orig_module_call(mod, *args, **kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/nn/modules/container.py", line 119, in forward
input = module(input)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 343, in module_call_wrapper
return self.call_module(mod, forward, args, kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 222, in call_module
return forward(*args, **kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 339, in forward
return _orig_module_call(mod, *args, **kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/chenxin/disk1/github/MQBench_Quantize/models/shufflenetv2.py", line 49, in forward
x1, x2 = self.split(x)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 343, in module_call_wrapper
return self.call_module(mod, forward, args, kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 222, in call_module
return forward(*args, **kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/fx/symbolic_trace.py", line 339, in forward
return _orig_module_call(mod, *args, **kwargs)
File "/home/chenxin/disk1/anaconda3/envs/MQBench_Quantize/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/chenxin/disk1/github/MQBench_Quantize/models/shufflenetv2.py", line 28, in forward
c = int(x.size(1) * self.ratio)
TypeError: int() argument must be a string, a bytes-like object or a number, not 'Proxy'

Process finished with exit code 1