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[kees_b]

Issue with Deep Learning

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I’m having a problem with a deep-learning project I’m working on. I’m trying to implement a convolutional neural network but I’m running into an issue with the code.

I’m getting an error saying “TypeError: unsupported operand type(s) for +: ‘NoneType’ and ‘int'”. Below is the code I’m having trouble with:
def convolutional_neural_network(x):
weights = {‘w_conv1’:tf.Variable(tf.random_normal([5,5,1,32])),
‘w_conv2’:tf.Variable(tf.random_normal([5,5,32,64])),
‘w_fc’:tf.Variable(tf.random_normal([7*7*64,1024])),
‘out’:tf.Variable(tf.random_normal([1024, n_classes]))}

biases = {‘b_conv1’:tf.Variable(tf.random_normal([32])),
‘b_conv2’:tf.Variable(tf.random_normal([64])),
‘b_fc’:tf.Variable(tf.random_normal([1024])),
‘out’:tf.Variable(tf.random_normal([n_classes]))}

x = tf.reshape(x, shape=[-1, 28, 28, 1])

conv1 = tf.nn.relu(conv2d(x, weights[‘w_conv1’]) + biases[‘b_conv1’])
conv1 = maxpool2d(conv1)

conv2 = tf.nn.relu(conv2d(conv1, weights[‘w_conv2’]) + biases[‘b_conv2’])
conv2 = maxpool2d(conv2)

fc = tf.reshape(conv2,[-1, 7*7*64])
fc = tf.nn.relu(tf.matmul(fc, weights[‘w_fc’])+biases[‘b_fc’])

output = tf.matmul(fc, weights[‘out’])+biases[‘out’]

return output

I’m not sure what is causing the issue, any help would be greatly appreciated

Note: off-topic link removed by moderator.

• This topic was modified 1 year, 8 months ago by kees_b.
• This topic was modified 1 year, 8 months ago by kees_b.

Topic

Re: issue

In reply to Issue with Deep Learning

https://www.techrepublic.com/forums/discussions/typeerror-nonetype-object-is-not-subscriptable/ explains a comparable case.

If one of the things you want to add is a number, the other can’t be of type None.

Reply To: Issue with Deep Learning

In reply to Issue with Deep Learning

Thanks for the reply.

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