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Merge branch 'master' into patch-2
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beginner_source/basics/quickstart_tutorial.py

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# Get cpu or gpu device for training.
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device = "cuda" if torch.cuda.is_available() else "cpu"
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print("Using {} device".format(device))
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print(f"Using {device} device")
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# Define model
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class NeuralNetwork(nn.Module):

beginner_source/examples_autograd/polynomial_custom_function.py

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# -*- coding: utf-8 -*-
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r"""
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"""
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PyTorch: Defining New autograd Functions
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----------------------------------------
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recipes_source/recipes/Captum_Recipe.py

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# attribution algorithms such as \ ``Guided GradCam``\ and
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# \ ``Integrated Gradients``\ in a unified way.
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#
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# In this recipe you will learn how to use Captum to: \* attribute the
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# predictions of an image classifier to their corresponding image
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# features. \* visualize the attribution results.
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# In this recipe you will learn how to use Captum to:
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#
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# - Attribute the predictions of an image classifier to their corresponding image features.
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# - Visualize the attribution results.
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#
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