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testing/examples.ipynb

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"source": [
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"# TensorSensor\n",
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"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/parrt/tensor-sensor/blob/sbrugman-patch-2/testing/examples.ipynb)\n",
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"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/parrt/tensor-sensor/blob/master/testing/examples.ipynb)\n",
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"TensorSensor clarifies exceptions by augmenting messages and visualizing Python code to indicate the shape of tensor variables (see figure to the right for a teaser). It works with Tensorflow, PyTorch, JAX, and Numpy, as well as higher-level libraries like Keras and fastai. Besides trapping exceptions, TensorSensor can provide visualizations of code that executes without exception. You can also see the complete expression tree computation and the shapes of self-expression partial results.\n",
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