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cs501r_f2018:lab2 [2018/09/10 18:38]
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cs501r_f2018:lab2 [2018/09/12 15:35]
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   * 50% Successfully followed lab video and typed in code   * 50% Successfully followed lab video and typed in code
   * 20% Modified code to include a test/train split   * 20% Modified code to include a test/train split
-  * 20% Modified code to include a visualization of train/​test ​accuracies+  * 20% Modified code to include a visualization of train/​test ​losses
   * 10% Tidy and legible figures, including labeled axes where appropriate   * 10% Tidy and legible figures, including labeled axes where appropriate
  
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 **Step 4.** Construct  ​ **Step 4.** Construct  ​
 +
 - a model class that inherits from “nn.Module” ​ - a model class that inherits from “nn.Module” ​
-    ​* Check out [[https://​pytorch.org/​docs/​stable/​nn.html#​torch.nn.Module]] +  ​* Check out [[https://​pytorch.org/​docs/​stable/​nn.html#​torch.nn.Module]] 
-    * Your model can contain any submodules you wish -- nn.Linear is a good, easy, starting point +  * Your model can contain any submodules you wish -- nn.Linear is a good, easy, starting point 
-- a dataset class that inherits from “Dataset” and produces samples from  +- a dataset class that inherits from “Dataset” and produces samples from [[https://​pytorch.org/​docs/​stable/​torchvision/​datasets.html#​fashion-mnist]] 
-[[https://​pytorch.org/​docs/​stable/​torchvision/​datasets.html#​fashion-mnist]] +  * You may be tempted to use this dataset directly (as it already inherits from Dataset) but we want you to learn how a dataset is constructed. Your class should be pretty simple and output items from FashionMNIST
-    * You may be tempted to use this dataset directly (as it already inherits from Dataset) but we want you to learn how a dataset is constructed. Your class should be pretty simple and output items from FashionMNIST+
  
 **Step 5.** Create instances of the following objects: **Step 5.** Create instances of the following objects:
cs501r_f2018/lab2.txt · Last modified: 2021/06/30 23:42 (external edit)