From 45c6ae446f19c7c2216671778f58391472c6dd2e Mon Sep 17 00:00:00 2001 From: Yinon Polak Date: Thu, 23 Mar 2023 15:04:29 +0200 Subject: [PATCH] small docs change --- docs/freqai-configuration.md | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md index ba2976bec..63d7c571c 100644 --- a/docs/freqai-configuration.md +++ b/docs/freqai-configuration.md @@ -283,13 +283,12 @@ In addition, the trainer is responsible for the following: Like all freqai models, PyTorch models inherit `IFreqaiModel`. `IFreqaiModel` declares three abstract methods: `train`, `fit`, and `predict`. we implement these methods in three levels of hierarchy. From top to bottom: -![image](assets/freqai_pytorch-diagram.png) - 1. `BasePyTorchModel` - Implements the `train` method. all `BasePyTorch*` inherit it. responsible for general data preparation (e.g., data normalization) and calling the `fit` method. Sets `device _type` attribute used by children classes. Sets `model_type` attribute used by the parent class. 2. `BasePyTorch*` - Implements the `predict` method. Here, the `*` represents a group of algorithms, such as classifiers or regressors. responsible for data preprocessing, predicting, and postprocessing if needed. - 3. `PyTorch*Classifier` / `PyTorch*Regressor` - implements the `fit` method. responsible for the main train flaw, where we initialize the trainer and model objects. +![image](assets/freqai_pytorch-diagram.png) + #### Full example Building a PyTorch regressor using MLP (multilayer perceptron) model, MSELoss criterion, and AdamW optimizer.