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April 18, 2021 04:15 pm GMT

AdaptiveAvgPool2d in PyTorch

I had trouble understanding the AdaptiveAvgPool2d function in PyTorch. The following examples helped me to teach myself better. Hopefully, somebody may benefit from this.

Example 1

import torchimport torch.nn as nnimport numpy as npm = nn.AdaptiveAvgPool2d((1))x = np.array([    [ 2. , 3.],    [ 4. , 1.],])input = torch.tensor(x)print(input)output = m(input)print(output)print(torch.mean(input))

The output will be equal to torch.mean(input)

Example 2 with a 3 x 3 x 3 tensor

x = np.array([    [        [ 2. , 3. , 2.],        [ 2. , 3. , 2.],        [ 2. , 3. , 2.],    ],    [        [ 1. , 4. , 5.],        [ 1. , 4. , 5.],        [ 1. , 4. ,  5. ],    ],    [        [ 7. , 3. , 2.],        [ 7. , 3. , 2.],        [ 7. , 3. , 2.],    ]])

This is a 3 x 3 x 3 array

input = torch.tensor(x)m = nn.AdaptiveAvgPool2d((2))output = m(input)print(output)

Let's investigate why the 1st element is 2.5

We take a 2 x 2 tensor out of the 3 x 3 x 3 tensor and take the mean and see that it is 2.5

x2 = torch.tensor(np.array([2. , 3. , 2. , 3.]))torch.mean(x2)

Example 3

We see that the 6th element is 4.5. How is this calculated?

We take the mean of the following section

x3 = torch.tensor(np.array([ 4.0 , 5. , 4. , 5.]))torch.mean(x3)

Example 4 with a 4 x 3 x 3 tensor

x = np.array([    [        [ 2. , 3. , 2.],        [ 2. , 3. , 2.],        [ 2. , 3. , 2.],    ],    [        [ 1. , 4. , 5.],        [ 1. , 4. , 5.],        [ 1. , 4. ,  5. ],    ],    [        [ 7. , 3. , 2.],        [ 7. , 3. , 2.],        [ 7. , 3. , 2.],    ],    [        [ 8. , 3. , 2.],        [ 8. , 3. , 2.],        [ 8. , 3. , 2.],    ]])input = torch.tensor(x)print(input)print(input.shape)

This is a 4 x 3 x 3 tensor

m = nn.AdaptiveAvgPool2d([1,1])output= m(input)print(output)

Let us explore why the first element is 2.3333

x4 = torch.tensor(    np.array( [ 2. , 3. , 2.,  2. , 3. , 2.,  2. , 3. , 2.])                 )print(torch.mean(x4))

Original Link: https://dev.to/ambarishg/adaptiveavgpool2d-in-pytorch-1dke

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