train_template.py
def show_sample(max_len):
    """
    Shows some samples and their sizes as tensor to see how preprocessing works
    :param max_len: number of samples to show
    :return: None -> print some data on console
    """
    for i in range(len(train_dataset)):
        sample = train_dataset[i]

        X = sample['X']
        y_d = sample['y_descreen']
        y_e = sample['y_edge']
        print(i)

        print(type(X), X.size())
        print(type(y_d), y_d.size())
        print(type(y_e), y_e.size())

        if i == max_len:
            break

    Shows some samples and their sizes as tensor to see how preprocessing works
    :param max_len: number of samples to show
    :return: None -> print some data on console
    
Shows some samples and their sizes as tensor to see how preprocessing works
Shows some samples and their sizes as tensor to see how preprocessing works
def show_sample(max_len):
    for i in range(len(train_dataset)):
        sample = train_dataset[i]
        X = sample['X']
        y_d = sample['y_descreen']
        y_e = sample['y_edge']
        print(i)
        print(type(X), X.size())
        print(type(y_d), y_d.size())
        print(type(y_e), y_e.size())
        if i == max_len:
            break
def show_sample ( max_len ) : for i in range ( len ( train_dataset ) ) : sample = train_dataset [ i ] X = sample [ 'X' ] y_d = sample [ 'y_descreen' ] y_e = sample [ 'y_edge' ] print ( i ) print ( type ( X ) , X . size ( ) ) print ( type ( y_d ) , y_d . size ( ) ) print ( type ( y_e ) , y_e . size ( ) ) if i == max_len : break
Shows some samples and their sizes as tensor to see how preprocessing works
Shows some samples and their sizes as tensor to see how preprocessing works
"""
    Shows some samples and their sizes as tensor to see how preprocessing works
    :param max_len: number of samples to show
    :return: None -> print some data on console
    """
> print some data on console
> print some data on console
max_len
number of samples to show
number of samples to show