Python 使用省略号重塑numpy数组的问题

我正在尝试为一个项目复制以下批处理生成器。但是，我在重塑数据时遇到了问题。该函数的目标是获取[60003000]的数组，并将其重塑为[batch_size，1003000,1]的形状

我试图复制的功能代码

def gen(dict_files, aug=False):
while True:
    record_name = random.choice(list(dict_files.keys()))
    batch_data = dict_files[record_name]
    all_rows = batch_data['x']

    for i in range(batch_size):
        start_index = random.choice(range(all_rows.shape[0]-WINDOW_SIZE))

        X = all_rows[start_index:start_index+WINDOW_SIZE, ...]
        Y = batch_data['y'][start_index:start_index+WINDOW_SIZE]

        X = np.expand_dims(X, 0)
        Y = np.expand_dims(Y, -1)
        Y = np.expand_dims(Y, 0)
        yield X, Y

发电机输出X、Y：

X.shape=(batch_size, 100, 3000, 1)
Y.shape=(batch_size, 100, 1)

我的代码：

参数定义：

功能=阵列[60003000]&标签=阵列[6000，]

def generator(features, labels, batch_size):

##Define batch shapes
X_train_batch = np.zeros((batch_size,100, 3000, 1))
y_train_batch = np.zeros((batch_size,100, 1))

while True:
    sample_index = random.choice(range(features.shape[0]))
    sample_data = features[sample_index]

    ##Generating training batches
    for i in range(batch_size):
        start_index = random.choice(range(sample_data.shape[0]-100))   #pick random start point in signal (of length 3000timesteps)

        X = sample_data[start_index:start_index + 100, ...] #record 100 timesteps in signal from rand start point
        Y = labels[start_index:start_index + 100] #Record classification of X
        #print(X.shape)                    #gives arrays of (100,), should be (100,3000)

        ##reshaping to input shape taken by model
        X = np.expand_dims(X, 0)
        Y = np.expand_dims(Y, -1)
        Y = np.expand_dims(Y, 0)

        ##Collecting samples into correct batch size
        #X_train_batch[i] = X
        #y_train_batch[i] = Y
        print(y_train_batch.shape) #gives (32,100,1) which is correct!
generator(features, labels, 32)

有人能解释一下这里的省略号（“…”）的功能吗

X=all_行[开始索引：开始索引+窗口大小，…]

？根据我的理解，省略号放置了3000个时间步的样本_数据以给出输出（1003000），但我显然不理解某些东西，因为我无法在代码中获得相同的行为

接下来，我如何用代码复制gen输出的内容