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pytorch hooks

Roezz answered on April 17, 2022 Popularity 7/10 Helpfulness 1/10

answer pytorch hooks

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pytorch hooks

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 conda install -c anaconda xarray

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Source: anaconda.org

Tags: pytorch whatever

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Contributed on Apr 17 2022

Roezz

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pytorch hooks

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def printnorm(self, input, output):
    # input is a tuple of packed inputs
    # output is a Tensor. output.data is the Tensor we are interested
    print('Inside ' + self.__class__.__name__ + ' forward')
    print('')
    print('input: ', type(input))
    print('input[0]: ', type(input[0]))
    print('output: ', type(output))
    print('')
    print('input size:', input[0].size())
    print('output size:', output.data.size())
    print('output norm:', output.data.norm())


net.conv2.register_forward_hook(printnorm)

out = net(input)

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Source: pytorch.org

Tags: pytorch python pyt

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Contributed on Apr 17 2022

Roezz

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pytorch hooks

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def printgradnorm(self, grad_input, grad_output):
    print('Inside ' + self.__class__.__name__ + ' backward')
    print('Inside class:' + self.__class__.__name__)
    print('')
    print('grad_input: ', type(grad_input))
    print('grad_input[0]: ', type(grad_input[0]))
    print('grad_output: ', type(grad_output))
    print('grad_output[0]: ', type(grad_output[0]))
    print('')
    print('grad_input size:', grad_input[0].size())
    print('grad_output size:', grad_output[0].size())
    print('grad_input norm:', grad_input[0].norm())


net.conv2.register_backward_hook(printgradnorm)

out = net(input)
err = loss_fn(out, target)
err.backward()

Popularity 7/10 Helpfulness 1/10 Language python

Source: pytorch.org

Tags: pytorch python

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Contributed on Apr 17 2022

Roezz

0 Answers Avg Quality 2/10

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