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One day our MLP will become a CNN, for which we need a MaxPooling Layer.
https://www.deeplearningbook.org/contents/convnets.html
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**Describe the bug**
Here is the unit tests of failing maxpool op of each resolution:
**When Maxpooling=True, Encoder res: 4094x510**
- To reproduce the issue, run the command: `pytest tests/ttnn…
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The paper seems to have the Maxpooling layers after Fire 4 and Fire 8 modules, but in your implementation they are present after Fire 3 and Fire 8. Any particular reason why this change in architectur…
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Negative dimension size caused by subtracting 2 from 1 for 'max_pooling2d_11/MaxPool' (op: 'MaxPool') with input shapes: [?,1,512,64]
想问一下这个报错是怎么回事?谢谢
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Hello, I've found there are 2 maxPooling layers in R_Net.
net = slim.max_pool2d(net, kernel_size=[3, 3], stride=2, scope="pool1", padding='SAME')
net = slim.conv2d(net,num_outputs=48,kernel_si…
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Hello,
I checked both shapes of conv1 and pool1 and they don't seem to be coherent:
K.int_shape(conv1)
(None, 32, 48, 48)
K.int_shape(pool1)
(None, 16, 24, 48)
It looks like you're doing the m…
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In network.py you using maxpooling in branches, not avgpooling in the paper, why ?
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Hi @farquasar1 , thanks for the code sharing.
I tried to implement this network to do some 3d image segmentation, my input shape is (80,40,40,3),
which 80 is frame size, 40 and 40 are rows and col…
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hello, I'm confused about this change in class PillarFeatureNet
https://github.com/SmallMunich/nutonomy_pointpillars/blob/68d3181d35702608d410e948608e9815815677b9/second/pytorch/models/pointpillars…