Update README.md

README.md

@@ -58,19 +58,27 @@ Use `datasets.shuffle()` to properly shuffle the dataset. Use `datasets.map()` t
 ```py
 # Shuffle and apply your own preprocessing.
 dataset = dataset.shuffle(seed=42)
-dataset = dataset.map(preprocess, fn_kwargs={'tokenizer': tokenizer})
+dataset = dataset.map(preprocess, fn_kwargs={'tokenizer': tokenizer,
+                                             'score_fn': score_fn})
 ```
 
-For a quick working example, you can try to use the following:
+In this example, we're passing two additional arguments to the preprocess function in dataset.map(). You can use the following mock examples for inspiration:
 ```py
+# A mock tokenizer and functions for demonstration.
 class Tokenizer:
+    def __init__(self):
+        pass
     def __call__(self, example):
         return example
 
-def preprocess(example, useful_fn):
+# Transform Stockfish score and terminal outcomes.
+def score_fn(score):
+    return score
+
+def preprocess(example, tokenizer, score_fn):
     # Get number of moves made in the game.
     max_ply = len(example['moves']) 
-    pick_random_move = random.randint(0, max_ply)
+    pick_random_move = random.randint(0, max_ply-1)
 
     # Get the FEN, move and score for our random choice.
     fen = example['fens'][pick_random_move]
@@ -78,16 +86,19 @@ def preprocess(example, useful_fn):
     score = example['scores'][pick_random_move]
 
     # Transform data into the format of your choice.
-    example['fens'] = useful_fn(fen)
-    example['moves'] = useful_fn(move)
-    example['scores'] = useful_fn(score)
+    example['fens'] = tokenizer(fen)
+    example['moves'] = tokenizer(move)
+    example['scores'] = score_fn(score)
     return example
+
+tokenizer = Tokenizer()
 ```
 <br>
 <br>
 <br>
 
 # Complete Example
+You can try pasting this into Colab and it should work fine. Have fun!
 
 ```py
 import random
@@ -107,19 +118,19 @@ def score_fn(score):
 
 def preprocess(example, tokenizer, score_fn):
     # Get number of moves made in the game.
-      max_ply = len(example['moves']) 
-      pick_random_move = random.randint(0, max_ply-1)
-
-      # Get the FEN, move and score for our random choice.
-      fen = example['fens'][pick_random_move]
-      move = example['moves'][pick_random_move]
-      score = example['scores'][pick_random_move]
-
-      # Transform data into the format of your choice.
-      example['fens'] = tokenizer(fen)
-      example['moves'] = tokenizer(move)
-      example['scores'] = score_fn(score)
-      return example
+    max_ply = len(example['moves']) 
+    pick_random_move = random.randint(0, max_ply-1)
+
+    # Get the FEN, move and score for our random choice.
+    fen = example['fens'][pick_random_move]
+    move = example['moves'][pick_random_move]
+    score = example['scores'][pick_random_move]
+
+    # Transform data into the format of your choice.
+    example['fens'] = tokenizer(fen)
+    example['moves'] = tokenizer(move)
+    example['scores'] = score_fn(score)
+    return example
 
 
 tokenizer = Tokenizer()