Paw*_*ngh 1 python numpy numpy-slicing
我有一个 numpyA的 shape数组(550,10)。我的批量大小为 100,即我想要从中获取多少数据行A。在每次迭代中,我想从 A 中提取 100 行。但是当我到达最后 50 行时,我想要从 A 中提取最后 50 行和前 50 行。
我有一个这样的函数:
def train(index, batch_size):
if(batch_size + index < A.shape(0)):
data_end_index = index + batch_size
batch_data = A[index:batch_end_index,:]
else:
data_end_index = index + batch_size - A.shape(0) #550+100-600 = 50
batch_data = A[500 to 549 and 0 to 49] # How to slice here ?
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如何执行最后一步?
你可以试试:
import numpy as np
data=np.random.rand(550,10)
batch_size=100
for index in range(0,data.shape[0],batch_size):
batch=data[index:min(index+batch_size,data.shape[0]),:]
print(batch.shape)
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输出:
(100, 10)
(100, 10)
(100, 10)
(100, 10)
(100, 10)
(50, 10)
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