Glossary · Phase 4 · Deep learning
Eager execution
Running each operation as soon as its line runs, as PyTorch does by default; easy to debug, slower than a compiled graph.
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Forward computes the values. Backward multiplies the local slopes, one step at a time.
Learn it properly
Computation graphs · Every calculation as a graph of small operations. About 30 minutes.
Other terms from the same lesson
- computation graph: A map of every calculation a model did, which lets the computer trace each result back to its inputs.
- local derivative: How one small step in a computation graph changes its output when its input moves a little. Backpropagation multiplies these along the path.
- topological order: An order for the steps of a graph where every step comes after the steps it depends on.
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