implemented data loading and normalization

TicTacToe_AI/Net/pytorch_ai.py

@@ -0,0 +1,42 @@
+import random
+import torch
+from tqdm import tqdm
+
+
+def to_set(raw_list):
+    out_set = []
+    for line in tqdm(raw_list):
+        line = line.replace('\n', '')
+        raw_board, raw_label = line.split('|')[0], line.split('|')[1]
+
+        # convert string label to tensor
+        label = torch.zeros([1, 9])
+        if not (int(raw_label) is -1):
+            label[0][int(raw_label)] = 1
+
+        # convert board to tensor
+        raw_board = raw_board.split(',')
+        board = torch.zeros([1, 9])
+        for n, block in enumerate(raw_board):
+            if int(block) is -1:
+                board[0][n] = 0
+            elif int(block) is 0:
+                board[0][n] = 0.5
+            elif int(block) is 1:
+                board[0][n] = 1
+
+        out_set.append((board, label))
+
+    return out_set
+
+
+with open('boards.bds', 'r') as infile:
+    print('Loading file...')
+    alllines = infile.readlines()
+    random.shuffle(alllines)
+
+    print('Generating testset...')
+    testset = to_set(alllines[0:50000])
+
+    print('Generating trainset...')
+    trainset = to_set(alllines[50001:])