config.yaml

[ThiinhUET]

Hello, Can you please upload config.yaml file ?

I am trying to run the training code but the config file is missing. Thank you so much !

[benjimaclellan]

Hi @ThiinhUET, The configurations are generated from the queso/configs/Configuration dataclasses. You can initialize this dataclass with the desired hyperparameters and save to a YAML file for running the training scripts. Here's an example snippet:

import copy
import itertools
import os
import sys
import pathlib
import subprocess
from math import pi
import platform
import numpy as np
from dotenv import load_dotenv
import pathlib
import jax

from queso.io import IO
from queso.configs import Configuration

ansatze = "hardware_efficient_ansatz"
ns = 4
loss_funcs = "loss_cfi"

  print(n, ansatz)
  config = Configuration()
  config.preparation = ansatz
  config.n = n
  config.k = n

  prefix = f"{config.preparation}"
  folder = f"vqs-example-data/n{config.n}_{loss_fi}"

  config.train_circuit = False
  config.sample_circuit_training_data = False
  config.sample_circuit_testing_data = True
  config.train_nn = False
  config.benchmark_estimator = True

  config.n_grid = 250

  config.seed = 744

  config.interaction = 'local_rz'
  config.detection = 'local_r'
  config.loss_fi = loss_fi

  config.lr_circ = 0.5e-3
  config.n_shots = 1000
  config.n_shots_test = 10000
  config.n_phis = 250
  config.phi_center = pi/2/n
  config.phi_range = [-pi/2/n + config.phi_center, pi/2/n + config.phi_center]

  config.phis_test = np.linspace(-pi/3/n + config.phi_center, pi/3/n + config.phi_center, 5).tolist()
  config.n_sequences = np.logspace(0, 3, 10, dtype='int').tolist()
  config.n_epochs = 3000
  config.lr_nn = 1.0e-3
  config.l2_regularization = 0.01

  # config.n_grid = 500
  config.nn_dims = [64, 64, 64]
  config.batch_size = 1000

  io = IO(path=data_path, folder=folder)
  io.save_yaml(config, 'config.yaml')
  vqs(io, config)