RuntimeError: shape '[64, 1, 1, 1]' is invalid for input of size 1

[Haleski47]

Hello, when i run the demo code, i meet a error RuntimeError: shape '[64, 1, 1, 1]' is invalid for input of size 1 and i feel confused.....

code is :

import torchvision.models as models
from mqbench.prepare_by_platform import prepare_by_platform, BackendType
from mqbench.utils.state import enable_calibration, enable_quantization
from mqbench.convert_deploy import convert_deploy

model = models.dict'resnet18'
model.eval()
backend = BackendType.Tensorrt
model = prepare_by_platform(model, backend)
enable_quantization(model)
input_shape = {'data': [1, 3, 224, 224]}
convert_deploy(model, backend, input_shape)

[Haleski47]

after modify reshape -> expand in _fake_quantize_learnable_per_channel_affine_training function, in lsq.py, bugs fixed
zero_point = grad_scale(zero_point, grad_factor).expand(new_shape) # reshape -> expand
scale = grad_scale(scale, grad_factor).expand(new_shape) # reshape -> expand

[Tracin]

The specific reason is that you skip the calibration stage, which scale shape modified in.
Anyway, replace reshape to expand looks great.

[github-actions]

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