将迭代馈送到会话ValueError: setting an array element with a sequence.时发生在_, err = sess.run([train, loss], feed_dict={image: epoch_x, label: epoch_y})
data是一个二维矩阵，第一列为图像，第二列为一个热标签。
代码片段：
for epoch in range(epochs):
epoch_loss = 0
# data = np.random.shuffle(data)
data = shuffle(data) #sklearn.utils.shuffle
ptr = 0
for iter in range(int(n_examples/batch_size)): #batch_size = 10
epoch_data = data[ptr : ptr + batch_size] # to get the batch
epoch_x = epoch_data[:, 0] # fist col - images
epoch_y = epoch_data[:, 1] # second col - labels
ptr += batch_size
_, err = sess.run([train, loss], feed_dict={image: epoch_x, label: epoch_y}) # error occurs here.
epoch_loss += err
print("Epoch: ", epoch, " - Completed out of: ", epochs, " - Loss: ", epoch_loss)
epoch_x是一批彩色图像：
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[0.7254902 , 0.72941176, 0.71372549],
[0.7254902 , 0.72941176, 0.71372549],
...,
[0.68235294, 0.6745098 , 0.67058824],
[0.68627451, 0.68235294, 0.66666667],
[0.69019608, 0.68627451, 0.67058824]],
[[0.7254902 , 0.72941176, 0.71372549],
[0.7254902 , 0.72941176, 0.71372549],
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[[0.7254902 , 0.72941176, 0.71372549],
[0.7254902 , 0.72941176, 0.71372549],
[0.7254902 , 0.72941176, 0.71372549],
...,
[0.6745098 , 0.66666667, 0.6627451 ],
[0.68235294, 0.6745098 , 0.67058824],
[0.68235294, 0.67843137, 0.6627451 ]],
...,
[[0.39607843, 0.30980392, 0.61568627],
[0.4 , 0.30588235, 0.61176471],
[0.39215686, 0.29411765, 0.60784314],
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[0.38039216, 0.27843137, 0.60392157],
[0.38431373, 0.28235294, 0.61176471],
...,
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[0.27058824, 0.19607843, 0.51372549],
[0.2745098 , 0.2 , 0.51764706]],
[[0.39215686, 0.28235294, 0.63137255],
[0.39607843, 0.28627451, 0.63529412],
[0.39215686, 0.28235294, 0.63529412],
...,
[0.29411765, 0.22745098, 0.54509804],
[0.3254902 , 0.25098039, 0.56078431],
[0.30588235, 0.23137255, 0.54117647]]])
array([[[0.85098039, 0.89803922, 0.91372549],
[0.85490196, 0.90196078, 0.91764706],
[0.85490196, 0.90196078, 0.91764706],
...,
[0.09411765, 0.10588235, 0.09803922],
[0.10196078, 0.11372549, 0.10588235],
[0.11372549, 0.1254902 , 0.11764706]],
[[0.85882353, 0.90588235, 0.92156863],
[0.85882353, 0.90588235, 0.92156863],
[0.8627451 , 0.90980392, 0.9254902 ],
...,
[0.10980392, 0.11764706, 0.11764706],
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[0.8627451 , 0.90980392, 0.9254902 ],
...,
[0.14901961, 0.14509804, 0.15294118],
[0.15294118, 0.14901961, 0.16470588],
[0.14117647, 0.1372549 , 0.15294118]],
...,
[[0.55294118, 0.52941176, 0.47843137],
[0.56470588, 0.54117647, 0.49019608],
[0.58823529, 0.55686275, 0.50588235],
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[0.12941176, 0.09803922, 0.10196078],
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[0.58823529, 0.56078431, 0.50196078],
[0.60784314, 0.58039216, 0.52156863],
...,
[0.13333333, 0.10196078, 0.10588235],
[0.13333333, 0.10196078, 0.10588235],
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[[0.60784314, 0.58039216, 0.52156863],
[0.60392157, 0.57647059, 0.50980392],
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...,
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[0.12941176, 0.09803922, 0.10196078],
[0.1254902 , 0.09411765, 0.09803922]]])
array([[[0.68627451, 0.69411765, 0.67058824],
[0.68627451, 0.69411765, 0.67058824],
[0.68627451, 0.69411765, 0.67058824],
...,
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...,
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[0.1254902 , 0.12156863, 0.27843137],
[0.14509804, 0.13333333, 0.30980392]]])
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[0.8627451 , 0.80392157, 0.41176471],
[0.8627451 , 0.80392157, 0.41176471],
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[0.77647059, 0.70980392, 0.32941176],
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...,
[0.30588235, 0.31372549, 0.35294118],
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[0.68235294, 0.61568627, 0.04705882],
...,
[0.33333333, 0.34901961, 0.39215686],
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...,
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[0.45490196, 0.49411765, 0.56078431],
[0.54509804, 0.58823529, 0.66666667]]])
array([[[0.71372549, 0.71764706, 0.70980392],
[0.71372549, 0.71764706, 0.70980392],
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array([[[0.7254902 , 0.72941176, 0.71372549],
[0.7254902 , 0.72941176, 0.71372549],
[0.7254902 , 0.72941176, 0.71372549],
...,
[0.69803922, 0.69019608, 0.68627451],
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[0.36470588, 0.25490196, 0.60784314],
[0.39215686, 0.28235294, 0.63529412]]])
array([[[0.75294118, 0.75294118, 0.75294118],
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array([[[0.7254902 , 0.72941176, 0.71372549],
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...,
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[0.32156863, 0.23921569, 0.57254902],
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array([[[0.80784314, 0.84313725, 0.85490196],
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array([[[0.7254902 , 0.72941176, 0.71372549],
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[0.40784314, 0.30980392, 0.64705882],
...,
[0.06666667, 0.03529412, 0.27058824],
[0.09411765, 0.0627451 , 0.30196078],
[0.21568627, 0.18039216, 0.42745098]],
[[0.42745098, 0.32156863, 0.65882353],
[0.39607843, 0.29019608, 0.62745098],
[0.42745098, 0.3254902 , 0.65490196],
...,
[0.10980392, 0.0745098 , 0.32156863],
[0.20392157, 0.16078431, 0.43529412],
[0.3254902 , 0.27843137, 0.56078431]],
[[0.39215686, 0.27843137, 0.61176471],
[0.40392157, 0.30196078, 0.63137255],
[0.39215686, 0.29019608, 0.61568627],
...,
[0.18823529, 0.14901961, 0.40784314],
[0.29803922, 0.25098039, 0.53333333],
[0.31764706, 0.2627451 , 0.56862745]]])]
和epoch_y是具有3类的标签批处理：
[list([0, 1, 0]) list([0, 0, 1]) list([0, 1, 0]) list([1, 0, 0])
list([0, 1, 0]) list([0, 1, 0]) list([0, 0, 1]) list([0, 1, 0])
list([0, 0, 1]) list([0, 1, 0])]
喂入这批图像和标签时，我得到ValueError: setting an array element with a sequence.
答案 0 :(得分：0)
好的，我解决了。发生这种情况的原因是因为我将数据预处理到另一个文件中，然后将其保存为pickle格式。我的标签应该是[]，而不是list（）。
我已经将数据从pickle格式加载到模型文件中，然后使用data = np.asarray(data)将其转换为numpy数组。我不知道是什么导致了问题，但是删除此问题可以解决问题。我的epoch_y现在出现在[]中，而不是list()。