Skip to main content
Join the official 2019 Python Developers SurveyStart the survey!

Simple easy to use module to get the intermediate results from chosen submodules

Project description

Simple easy to use module to get the intermediate results from chosen submodules. Supports submodule annidation. Inspired in this but does not assume that submodules are executed sequentially.

Installation

pip install torch_intermediate_layer_getter

Usage

Example

import torch
import torch.nn as nn

from torch_intermediate_layer_getter import IntermediateLayerGetter as MidGetter

class Model(nn.Module):
    def __init__(self):
        super().__init__()

        self.fc1 = nn.Linear(2, 2)
        self.fc2 = nn.Linear(2, 2)
        self.nested = nn.Sequential(
            nn.Sequential(nn.Linear(2, 2), nn.Linear(2, 3)),
            nn.Linear(3, 1),
        )
        self.interaction_idty = nn.Identity() # Simple trick for operations not performed as modules

    def forward(self, x):
        x1 = self.fc1(x)
        x2 = self.fc2(x)

        interaction = x1 * x2
        self.interaction_idty(interaction)

        x_out = self.nested(interaction)

        return x_out
        
model = Model()
return_layers = {
    'fc2': 'fc2',
    'nested.0.1': 'nested',
    'interaction_idty': 'interaction',
}
mid_getter = MidGetter(model, return_layers=return_layers, keep_output=True)
mid_outputs, model_output = mid_getter(torch.randn(1, 2))

print(model_output)
>> tensor([[0.3219]], grad_fn=<AddmmBackward>)
print(mid_outputs)
>> OrderedDict([('fc2', tensor([[-1.5125,  0.9334]], grad_fn=<AddmmBackward>)),
  ('interaction', tensor([[-0.0687, -0.1462]], grad_fn=<MulBackward0>)),
  ('nested', tensor([[-0.1697,  0.1432,  0.2959]], grad_fn=<AddmmBackward>))])

# model_output is None if keep_ouput is False
# if keep_output is True the model_output contains the final model's output

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for torch-intermediate-layer-getter, version 0.1.post1
Filename, size File type Python version Upload date Hashes
Filename, size torch_intermediate_layer_getter-0.1.post1.tar.gz (3.0 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page