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cs501r_f2018:lab2 [2018/09/10 18:37] wingated |
cs501r_f2018:lab2 [2021/06/30 23:42] (current) |
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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” | + | |
- | ** Check out [[https://pytorch.org/docs/stable/nn.html#torch.nn.Module]] | + | - a model class that inherits from “nn.Module” |
- | ** Your model can contain any submodules you wish -- nn.Linear is a good, easy, starting point | + | * Check out [[https://pytorch.org/docs/stable/nn.html#torch.nn.Module]] |
- | * a dataset class that inherits from “Dataset” and produces samples from | + | * Your model can contain any submodules you wish -- nn.Linear is a good, easy, starting point |
- | [[https://pytorch.org/docs/stable/torchvision/datasets.html#fashion-mnist]] | + | - a dataset class that inherits from “Dataset” and produces samples from [[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: |