问题描述
我解码了JPEG图像，并以二维numpy.ndarray的形式将其以n_samples x n_features的形状显示.我将其喂入tensorflow如下:
I decoded a JPEG image and have it in the shape n_samples x n_features as a two-dimensional numpy.ndarray. I feed this to tensorflow as following:
sess.run(train_step, feed_dict={X : train_set.Features, y_ : train_set.labels})
这将返回TypeError:TypeError: unhashable type: 'numpy.ndarray'.
This returns a TypeError: TypeError: unhashable type: 'numpy.ndarray'.
我认为这是一个简单的问题，但是我找不到很好的建议.我最近发现的是有关堆栈溢出的帖子，但据我了解，这就是我的工作.
I think it is a simple issue, but I cannot find good advise on that. Closest I found was this post on stack overflow but as far as I understand, that's what I do.
推荐答案
我猜您的X和train_set.Features可能具有不同的形状.例如，
I guess your X and train_set.Features maybe have different shape.for examples,
# cifar10 datasets
x = tf.placeholder(tf.float32,shape = (None,32,32,3))
y = tf.placeholder(tf.float32,shape = (None,10))
print x_batch.shape # (batch_size,32,32,3)
print y_batch.shape # (batch_size,10)
# and feed_dict should be
feed_dict = {x:x_batch,y:y_batch}
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