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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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