def test_logger_file():
logger = logging.get_logger(__name__)
assert logger.to_file("testing") is None
"""Dataset.
"""
from typing import Optional, Tuple
import numpy as np
import tensorflow as tf
import dualing.utils.exception as e
from dualing.utils import logging
logger = logging.get_logger(__name__)
class Dataset:
"""A Dataset class is responsible for receiving raw data, pre-processing it and
persisting batches that will be feed as inputs to the networks.
"""
def __init__(
self,
batch_size: Optional[int] = 1,
input_shape: Optional[Tuple[int, ...]] = None,
normalize: Optional[Tuple[int, int]] = (0, 1),
shuffle: Optional[bool] = True,
seed: Optional[int] = 0,
):
"""Initialization method.
Args:
batch_size: Batch size.
def test_get_logger():
logger = logging.get_logger(__name__)
assert logger.name == "test_logging"
assert logger.hasHandlers() is True
