PyTorch – Neural Networks to Functional Blocks
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Training a deep learning algorithm involves the following steps −
- Building a data pipeline
- Building a network architecture
- Evaluating the architecture using a loss function
- Optimizing the network architecture weights using an optimization algorithm
Training a specific deep learning algorithm is the exact requirement of converting a neural network to functional blocks as shown below −
With respect to the above diagram, any deep learning algorithm involves getting the input data, building the respective architecture which includes a bunch of layers embedded in them.
If you observe the above diagram, the accuracy is evaluated using a loss function with respect to optimization of the weights of neural network.
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