Per tensor symmetric quantiation

Hello !
I can’t understand where I have the error, in the configuration I write that I want fake per_tensor_symmetric quantization, but when I display the picture of the graph, he writes that I have a FakeQuantizePerTensorAffineBackward node.

What am I doing wrong?
Thank you in advance!

import torch
from torch import nn
from torchviz import make_dot

model = nn.Sequential()
model.add_module('W0', nn.Linear(8, 16))
model.add_module('tanh', nn.Tanh())
model.add_module('W1', nn.Linear(16, 1))
model.qconfig = torch.quantization.QConfig(activation=torch.quantization.FakeQuantize.with_args(observer=torch.quantization.MinMaxObserver, 
                   weight=torch.quantization.FakeQuantize.with_args(observer=torch.quantization.MinMaxObserver, quant_min=-128, quant_max=127,
                                                   dtype=torch.qint8, qscheme=torch.per_tensor_symmetric, reduce_range=False))
torch.quantization.prepare_qat(model, inplace=True)
x = torch.randn(1,8)
make_dot(model(x), params=dict(model.named_parameters()))

FakeQuantizePerTensorAffineBackward handles both symmetric and asymmetric. In case of symmetric the zero_point would be set to 0. So your example looks fine to me.