IndexError: list assignment index out of range for CNN program from scratch

Question

当我的数组维度与我的循环限制匹配时，我一直收到此错误，我应该更改什么。

本程序旨在从头开始使用神经网络对 32*32p 黑白图像进行分类。

import numpy as np
import matplotlib.pyplot as plt
import pickle
from math import exp
from random import seed
from random import random

def unpickle(file):
    with open(file, 'rb') as fo:
        data = pickle.load(fo, encoding='bytes')
    return data

def load_data(data_dir, negatives=False):

    meta_data_dict = unpickle("batches.meta")
    data_label_names = meta_data_dict[b'label_names']
    data_label_names = np.array(data_label_names)

    # training data
    train_data = None
    train_filenames = []
    train_labels = []
    
    train_data_dict = unpickle("data_batch_1")
    train_data = train_data_dict[b'data']
    train_filenames += train_data_dict[b'filenames']
    train_labels += train_data_dict[b'labels']

    train_data = train_data.reshape((len(train_data), 1, 32, 32))
    if negatives:
        train_data = train_data.transpose(0, 2, 3, 1).astype(np.float32)
    else:
        train_data = np.rollaxis(train_data, 1, 4)
    train_filenames = np.array(train_filenames)
    train_labels = np.array(train_labels)

    return train_data, train_filenames, train_labels, data_label_names

data_dir = 'data-batches-py'
x_train, x_train_filenames, y_train_labels, y_label_names =load_cifar_10_data(data_dir)
print (x_train.shape)
print (len(x_train))

# Initialize a network
def initialize_network(n_hidden):
    network = list()
    hidden_layer = [{'weights':[random() for i in range(len(x_train) + 1)]} for i in range(n_hidden)]
    network.append(hidden_layer)
    output_layer = [{'weights':[random() for i in range(n_hidden +1)]} for i in range(10)]
    network.append(output_layer)
    return network


def sum(inputs):
    sum_row=[]
    for i in range(len(x_train)):
        for a in range(32):
            for b in range(32):
                sum_row[i]=0
                sum_row[i]+= inputs[i][a][b][1]
    return sum_row
# Calculate neuron activation for an input
def activate(weights, inputs):
    flattened= sum(inputs)
    activation = weights[-1]
    for i in range(len(weights)-1):
        activation += weights[i] * flattened[i]
    return activation

# Transfer neuron activation
def transfer(activation):
    return 1.0 / (1.0 + exp(-activation))

# Forward propagate input to a network output
def forward_propagate(network, row):
    inputs = row
    for layer in network:
        new_inputs = []
        for neuron in layer:
            activation = activate(neuron['weights'], inputs)
            neuron['output'] = transfer(activation)
            new_inputs.append(neuron['output'])
        inputs = new_inputs
    return inputs

network = initialize_network(1)
row = x_train
output = forward_propagate(network, row)
print(output)

在运行这段代码之后我得到以下输出

(10000, 32, 32, 1)
10000
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
/var/folders/gm/z9_jyr1s5k1232zgf4xf7cxc0000gn/T/ipykernel_15670/2752672525.py in <module>
    153 network = initialize_network(1)
    154 row = x_train
--> 155 output = forward_propagate(network, row)
    156 print(output)

/var/folders/gm/z9_jyr1s5k1232zgf4xf7cxc0000gn/T/ipykernel_15670/2752672525.py in forward_propagate(network, row)
     78                 new_inputs = []
     79                 for neuron in layer:
---> 80                         activation = activate(neuron['weights'], inputs)
     81                         neuron['output'] = transfer(activation)
     82                         new_inputs.append(neuron['output'])

/var/folders/gm/z9_jyr1s5k1232zgf4xf7cxc0000gn/T/ipykernel_15670/2752672525.py in activate(weights, inputs)
     62 # Calculate neuron activation for an input
     63 def activate(weights, inputs):
---> 64     flattened= sum(inputs)
     65     activation = weights[-1]
     66     for i in range(len(weights)-1):

/var/folders/gm/z9_jyr1s5k1232zgf4xf7cxc0000gn/T/ipykernel_15670/2752672525.py in sum(inputs)
     57         for a in range(32):
     58             for b in range(32):
---> 59                 sum_row[i]=0
     60                 sum_row[i]+= inputs[i][a][b][1]
     61     return sum_row

IndexError: list assignment index out of range

可以看到输入的维度是100003232*1，那为什么会报错呢？

Answer 1

错误在

def sum(inputs):
    sum_row=[]
    for i in range(len(x_train)):
        for a in range(32):
            for b in range(32):
                sum_row[i]=0
                sum_row[i]+= inputs[i][a][b][1]
    return sum_row

错误的原因是您试图访问 sum_row 的元素，但 sum_row 中没有任何元素（因为您在 sum_row 之前将其设置为 [] for 循环）。在 for 循环中，您尝试访问它没有的成员。而不是做 sum_row[i] = 0 你应该做 sum_row.append(0) 向该列表添加一个元素。然后你可以通过 sum_row[-1] += inputs[i][a][b][1]

访问它

IndexError: list assignment index out of range for CNN program from scratch

IndexError: list assignment index out of range for CNN program from scratch

python

python-3.x

deep-learning

conv-neural-network