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Datasets:
mauricett
/
lichess_sf

Tags:
chess
stockfish
License:
Dataset card Files Community
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mauricett commited on
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Update README.md

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  1. README.md +16 -14
README.md CHANGED
@@ -71,18 +71,19 @@ def score_fn(score):
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  return score
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  def preprocess(example, tokenizer, score_fn):
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- # Get number of moves made in the game.
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- max_ply = len(example['moves'])
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- pick_random_move = random.randint(0, max_ply-2)
 
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- # Get the FEN for our random choice.
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- fen = example['fens'][pick_random_move]
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  # To get the move that leads to the *next* FEN, we have to add
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  # +1 to the index. Same with the score, which is the evaluation
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  # of that move. Please read the section about the data format clearly!
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- move = example['moves'][pick_random_move + 1]
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- score = example['scores'][pick_random_move + 1]
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  # Transform data into the format of your choice.
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  example['fens'] = tokenizer(fen)
@@ -130,18 +131,19 @@ def score_fn(score):
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  return score
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  def preprocess(example, tokenizer, score_fn):
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- # Get number of moves made in the game.
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- max_ply = len(example['moves'])
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- pick_random_move = random.randint(0, max_ply-2)
 
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- # Get the FEN for our random choice.
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- fen = example['fens'][pick_random_move]
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  # To get the move that leads to the *next* FEN, we have to add
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  # +1 to the index. Same with the score, which is the evaluation
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  # of that move. Please read the section about the data format clearly!
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- move = example['moves'][pick_random_move + 1]
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- score = example['scores'][pick_random_move + 1]
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  # Transform data into the format of your choice.
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  example['fens'] = tokenizer(fen)
 
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  return score
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  def preprocess(example, tokenizer, score_fn):
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+ # Get number of moves made in the game...
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+ max_ply = len(example['moves'])
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+ # ...and pick a position at random.
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+ random_position = random.randint(0, max_ply-2)
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+ # Get the FEN of our random choice.
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+ fen = example['fens'][random_position]
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  # To get the move that leads to the *next* FEN, we have to add
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  # +1 to the index. Same with the score, which is the evaluation
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  # of that move. Please read the section about the data format clearly!
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+ move = example['moves'][random_position + 1]
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+ score = example['scores'][random_position + 1]
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  # Transform data into the format of your choice.
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  example['fens'] = tokenizer(fen)
 
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  return score
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  def preprocess(example, tokenizer, score_fn):
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+ # Get number of moves made in the game...
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+ max_ply = len(example['moves'])
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+ # ...and pick a position at random.
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+ random_position = random.randint(0, max_ply-2)
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+ # Get the FEN of our random choice.
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+ fen = example['fens'][random_position]
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  # To get the move that leads to the *next* FEN, we have to add
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  # +1 to the index. Same with the score, which is the evaluation
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  # of that move. Please read the section about the data format clearly!
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+ move = example['moves'][random_position + 1]
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+ score = example['scores'][random_position + 1]
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  # Transform data into the format of your choice.
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  example['fens'] = tokenizer(fen)