click options

src/dotd/generate.py

@@ -3,6 +3,7 @@
 import re
 import os
 import torch
+import click
 from dotd.model import GRU
 from dotd.data import get_shakespeare, preprocess
 
@@ -57,13 +58,17 @@ def write_drama(seq, temp=0.7, max_seq_len=1000):
     return seq
 
 
-def main():
+@click.command()
+@click.option(
+    "--output", type=str, default="./dramaoftheday.md", help="Output file path"
+)
+def main(output):
     print(__file__)
     """main function"""
     init_seq = "TOM:"
     output_text = get_header() + make_pretty(write_drama(init_seq))
     with open(
-        os.path.join(os.path.dirname(__file__), "dramaoftheday.md"),
+        output,
         "w",
         encoding="utf-8",
     ) as file:

src/dotd/model.py

@@ -1,6 +1,7 @@
 # coding: utf-8
 """ module for training and creating the model """
 import torch
+import click
 from torch.utils.data import DataLoader
 from tqdm import tqdm  # type: ignore
 import numpy as np
@@ -55,7 +56,7 @@ def train_epoch(model, loader, optim, loss, device):
     return epoch_loss
 
 
-def train(epochs: int):
+def train(epochs: int, save_path: str):
     _, _, alphabet_size, _ = preprocess(
         get_shakespeare()
     )  # get amount of characters for one-hot to embedding
@@ -73,8 +74,20 @@ def train(epochs: int):
     for e in tqdm(range(epochs)):
         l = train_epoch(gru, loader, optim, loss, device)
         print(f"Epoch: {e}, Loss: {l}")
-    torch.save(gru.state_dict(), "saved_models/gru_{}epochs.pth".format(epochs + 1))
+    torch.save(gru.state_dict(), save_path + f"gru_{epochs+1}epochs.pth")
+
+
+@click.command()
+@click.option(
+    "--save_path",
+    type=str,
+    default="./saved_models",
+    help="Folder to store the weights in.",
+)
+@click.option("--epochs", type=int, default=20, help="Number of epochs to train")
+def main(epochs, save_path):
+    train(epochs, save_path)
 
 
 if __name__ == "__main__":
-    train(20)
+    main()