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I know that if we input an image of shape [6,128] to a convolutional layer with 5 filters each of shape[3,128] with S=1 and P=0 , then there will be 5 activation maps as output from the layer ..each map has a shape of [4,1]

But what about the number of maps outputted when we use batching ?

I mean if we are using a batch with size of 2 images (each of shape[6,128]) as input to a convolutional layer with 5 filters each of shape[3,128] with S=1 and P=0 also , then there will be 10 activation maps as output from the layer instead of 5 (each image in the batch has 5 maps) ?? or we will have also 5 maps but each of shape[2,4,1] ???

I think there will be 10 maps since if we apply then max pooling , we want to choose the max from each image independently , right? so each image must have separate maps from the maps of the other image..

Sarsoura
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  • Which framework do you usually rely on? Some frameworks allow you to visualize the input and output array shapes of each layer, which would allow you to see for yourself. The short answer is that usually there is a batch size dimension for all of them, all the way until you get to the loss and gradients. However, this is too technology-agnostic to be answered in Stack Overflow. If you visit [Data Science SE](https://datascience.stackexchange.com), you'll find that this question is better asked there. – E_net4 Aug 11 '17 at 09:29
  • Voting to close, as it's been asked in a more suitable site now: https://datascience.stackexchange.com/q/22174/17538 – E_net4 Aug 13 '17 at 00:42

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