Assume cuda-related packages have been installed.
$ git clone https://github.com/dtlics/torchquantum
$ cd torchquantum
$ pip install --editable .
Please run
$ cd examples/quest
$ python train.py huge/default
as a simple example. and example output is as follows:
evalmode: False
dataset:
name: huge.data
split_ratio: [0.8, 0.1, 0.1]
model:
name: simple
use_only_global: False
use_global_features: True
use_gate_type: True
use_qubit_index: True
use_T1T2: True
use_gate_error: True
use_gate_index: True
num_layers: 2
num_epochs: 100
batch_size: 1000
criterion:
name: mse
optimizer:
name: adam
lr: 0.0005
weight_decay: 0.0001
scheduler:
name: constant
pdb: False
device: gpu
exp_name: huge/default
[2023-12-12 20:42:38.284] Model Size: 26417
Size of the data: 7000
[100 / 100],sqrtloss=0.02772982485849934 val_error:0.02812538752213184
700
test_error:0.02791733444759953
best_val_error:0.02812538752213184
The data_set is stored in Dataset Folder
The environment is as follows:
torch == 1.13.0
Torch-geometric == 2.2.0
Qiskit == 0.39.4
Python == 3.10.8