# The full config for training the VSQL model.
# The task of this config. Available values: 'train' | 'test'.
task = 'train'
# The name of the model, which is used to save the model.
model_name = 'vsql-model'
# The path to save the model. Both relative and absolute paths are allowed.
# It saves the model to the current path by default.
# saved_path = './'
# The number of qubits which the quantum circuit contains.
num_qubits = 10
# The number of qubits which the shadow circuit contains.
num_shadow = 2
# The depth of the quantum circuit, default to 1.
# depth = 1
# The size of the batch samplers.
batch_size = 16
# The number of epochs to train the model.
num_epochs = 10
# The learning rate used to update the parameters, default to 0.01.
# learning_rate = 0.01
# The path of the dataset. It defaults to MNIST, which is a built-in dataset.
dataset = 'MNIST'
# The classes of handwrite digits to be predicted.
# It will use all labels if the value is not provided.
classes = [0, 1]
# Whether use the validation.
# It is true means the dataset contains training, validation and test datasets.
# It is false means the dataset only contains training datasets and test datasets. 
using_validation = false
# The number of the data in the training dataset.
# The value defaults to 0 which means using all data.
# num_train = 0
# The number of the data in the validation dataset.
# The value defaults to 0 which means using all data.
# num_dev = 0
# The number of the data in the test dataset.
# The value defaults to 0 which means using all data.
# num_test = 0
# Number of epochs with no improvement after which training will be stopped.
# early_stopping = 1000
# The number of subprocess to load data, 0 for no subprocess used and loading data in main process, defaults to 0.
# num_workers = 0