How to use eval_in method in fMBT

Best Python code snippet using fMBT_python

henri_2_23_21.py

Source:henri_2_23_21.py

...6    table = dict(pairs)7    return lambda a: a == table8def eval_in_for(se, e, v, n, answer):9    return Question("Rewrite the expression '{}' in '{}' for {} = {}".format(se, e, v, n), check_q(answer))10def eval_in(se, e, answer):11    return Question("Rewrite the expression '{}' in '{}'".format(se, e), check_q(answer))12questions = [13    eval_in_for("3 * r", "21 + (3 * r)", "r", 1, Plus(Int(21), Int(3))),14    eval_in("21 + 3", "21 + 3", Int(24)),15    eval_in_for("3 * r", "21 + (3 * r)", "r", 2, Plus(Int(21), Int(6))),16    eval_in("21 + 6", "21 + 6", Int(27)),17    eval_in_for("3 * r", "21 + (3 * r)", "r", 3, Plus(Int(21), Int(9))),18    eval_in("21 + 9", "21 + 9", Int(30)),19    eval_in_for("3 * r", "21 + (3 * r)", "r", 7, Plus(Int(21), Int(21))),20    eval_in("21 + 21", "21 + 21", Int(42)),21    eval_in_for("3 * r", "21 + (3 * r)", "r", 20, Plus(Int(21), Int(60))),22    eval_in("21 + 60", "21 + 60", Int(81)),23    eval_in_for("3 * r", "21 + (3 * r)", "r", 50, Plus(Int(21), Int(150))),24    eval_in("21 + 150", "21 + 150", Int(171)),25    Question(26        "Make a dictionary of '21 + (3 * r)' for r = 1, 2, 3, 7, 20, and 50",27        check_q_table(28            Plus(Int(21), Times(Int(3), Var("r"))),29            [[Int(1), Int(24)], [Int(2), Int(27)], [Int(3), Int(30)], [Int(7), Int(42)], [Int(20), Int(81)], [Int(50), Int(171)]])),30    eval_in_for("45 - w", "2 * (45 - w)", "w", 1, Times(Int(2), Int(44))),31    eval_in("2 * 44", "2 * 44", Int(88)),32    eval_in_for("45 - w", "2 * (45 - w)", "w", 2, Plus(Int(21), Int(43))),33    eval_in("2 * 43", "2 * 43", Int(27)),34    eval_in_for("45 - w", "2 * (45 - w)", "w", 3, Plus(Int(21), Int(42))),35    eval_in("2 * 42", "2 * 42", Int(30)),36    eval_in_for("45 - w", "2 * (45 - w)", "w", 15, Plus(Int(21), Int(30))),37    eval_in("2 * 30", "2 * 30", Int(42)),38    eval_in_for("45 - w", "2 * (45 - w)", "w", 20, Plus(Int(21), Int(25))),39    eval_in("2 * 25", "2 * 25", Int(81)),40    eval_in_for("45 - w", "2 * (45 - w)", "w", 35, Plus(Int(21), Int(10))),41    eval_in("2 * 10", "2 * 10", Int(171)),42    Question(43        "Make a dictionary of '2 * (45 - w)' for k = 1, 2, 3, 15, 20, and 35",44        check_q_table(45            Plus(Int(21), Times(Int(3), Var("r"))),46            [[Int(1), Int(88)], [Int(2), Int(86)], [Int(3), Int(84)], [Int(15), Int(60)], [Int(20), Int(50)], [Int(35), Int(20)]]))...

henri_2_25_21.py

Source:henri_2_25_21.py

...6    table = dict(pairs)7    return lambda a: a == table8def eval_in_for(se, e, v, n, answer):9    return Question("Rewrite the expression '{}' in '{}' for {} = {}".format(se, e, v, n), check_q(answer))10def eval_in(se, e, answer):11    return Question("Rewrite the expression '{}' in '{}'".format(se, e), check_q(answer))12questions = [13    eval_in_for("3 * r", "21 + (3 * r)", "r", 1, Plus(Int(21), Int(3))),14    eval_in("21 + 3", "21 + 3", Int(24)),15    eval_in_for("3 * r", "21 + (3 * r)", "r", 2, Plus(Int(21), Int(6))),16    eval_in("21 + 6", "21 + 6", Int(27)),17    eval_in_for("3 * r", "21 + (3 * r)", "r", 3, Plus(Int(21), Int(9))),18    eval_in("21 + 9", "21 + 9", Int(30)),19    eval_in_for("3 * r", "21 + (3 * r)", "r", 7, Plus(Int(21), Int(21))),20    eval_in("21 + 21", "21 + 21", Int(42)),21    eval_in_for("3 * r", "21 + (3 * r)", "r", 20, Plus(Int(21), Int(60))),22    eval_in("21 + 60", "21 + 60", Int(81)),23    eval_in_for("3 * r", "21 + (3 * r)", "r", 50, Plus(Int(21), Int(150))),24    eval_in("21 + 150", "21 + 150", Int(171)),25    Question(26        "Make a dictionary of '21 + (3 * r)' for r = 1, 2, 3, 7, 20, and 50",27        check_q_table(28            Plus(Int(21), Times(Int(3), Var("r"))),29            [[Int(1), Int(24)], [Int(2), Int(27)], [Int(3), Int(30)], [Int(7), Int(42)], [Int(20), Int(81)], [Int(50), Int(171)]])),30    eval_in_for("45 - w", "2 * (45 - w)", "w", 1, Times(Int(2), Int(44))),31    eval_in("2 * 44", "2 * 44", Int(88)),32    eval_in_for("45 - w", "2 * (45 - w)", "w", 2, Plus(Int(21), Int(43))),33    eval_in("2 * 43", "2 * 43", Int(27)),34    eval_in_for("45 - w", "2 * (45 - w)", "w", 3, Plus(Int(21), Int(42))),35    eval_in("2 * 42", "2 * 42", Int(30)),36    eval_in_for("45 - w", "2 * (45 - w)", "w", 15, Plus(Int(21), Int(30))),37    eval_in("2 * 30", "2 * 30", Int(42)),38    eval_in_for("45 - w", "2 * (45 - w)", "w", 20, Plus(Int(21), Int(25))),39    eval_in("2 * 25", "2 * 25", Int(81)),40    eval_in_for("45 - w", "2 * (45 - w)", "w", 35, Plus(Int(21), Int(10))),41    eval_in("2 * 10", "2 * 10", Int(171)),42    Question(43        "Make a dictionary of '2 * (45 - w)' for k = 1, 2, 3, 15, 20, and 35",44        check_q_table(45            Plus(Int(21), Times(Int(3), Var("r"))),46            [[Int(1), Int(88)], [Int(2), Int(86)], [Int(3), Int(84)], [Int(15), Int(60)], [Int(20), Int(50)], [Int(35), Int(20)]]))...

DataReader.py

Source:DataReader.py

1import numpy as np2import pandas3import torch4from torch.utils.data import Dataset5import FeatureExtraction6_DATA_PATH = "data/chessData.csv"7DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'8def _eval_to_int(eval_in):9    if eval_in.startswith("\ufeff"):10        eval_in = eval_in[1:]11    if eval_in.startswith("#"):12        eval_in = eval_in[1:]13    return float(eval_in)14def read_data(data_path, num_rows=10000):15    df = pandas.read_csv(data_path, nrows=num_rows)16    df['Evaluation'] = df['Evaluation'].map(_eval_to_int)17    df['Features'] = df['FEN'].map(FeatureExtraction.features_from_fen)18    return torch.vstack(tuple(df['Features'].values)).to(DEVICE), torch.tensor(df['Evaluation'].values).float().to(DEVICE)19# def construct_dataset(num_rows=10000, train_split=.8):20#     data = EvalDataset(*read_data(num_rows))21#     train_samples = int(num_rows * train_split)22#     train, test = torch.utils.data.random_split(data, [train_samples, len(data)-train_samples])23#     return train, test24def construct_dataset(data_path=_DATA_PATH, num_rows=10000, train_split=.8):25    xs, ys = read_data(data_path, num_rows)26    indices = np.arange(num_rows)27    np.random.shuffle(indices)28    train_samples = int(num_rows * train_split)29    return EvalDataset(xs[indices[:train_samples]], ys[indices[:train_samples]]), \30           EvalDataset(xs[indices[train_samples:]], ys[indices[train_samples:]])31class EvalDataset(Dataset):32    def __init__(self, xs, ys):33        self.xs = xs34        self.ys = ys35    def __getitem__(self, item):36        return self.xs[item], self.ys[item]37    def __len__(self):38        return self.xs.shape[0]39if __name__ == '__main__':40    test_dataset = construct_dataset(num_rows=200000)41    with open("data/training_data.pt", 'wb+') as outfile:42        torch.save(test_dataset[0], outfile)43    with open("data/testing_data.pt", 'wb+') as outfile:...

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