Merge remote-tracking branch 'origin/eager_eval' into eager_eval
This commit is contained in:
commit
2c02689577
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@ -73,29 +73,49 @@ int no_block_at_to_idx(int to_state, int player) {
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else return 1;
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}
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int can_bear_off(int board[], int player, int from_idx) {
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int can_bear_off(int board[], int player, int from_idx, int to_idx) {
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int* checker_idxs = idxs_with_checkers_of_player(board, player);
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if (player == 1) {
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for (int i = 1; i <= checker_idxs[0]; i++) {
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if ( !((checker_idxs[i] >= from_idx) &&
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(checker_idxs[i] >= 19)) ) {
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free(checker_idxs);
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return 0;
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int moving_backmost_checker = 1;
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int bearing_directly_off = 0;
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int all_checkers_in_last_quadrant = 1;
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/* Check if bearing directly off */
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if (player == 1 && to_idx == 25) bearing_directly_off = 1;
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else if (player == -1 && to_idx == 0) bearing_directly_off = 1;
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for (int i = 1; i <= checker_idxs[0]; i++) {
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if (player == 1 ) {
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/* Check if all checkers are in last quardrant */
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if (checker_idxs[i] < 19) {
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all_checkers_in_last_quadrant = 0;
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break;
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}
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}
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} else {
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for (int i = 1; i <= checker_idxs[0]; i++) {
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if ( !((checker_idxs[i] <= from_idx) &&
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(checker_idxs[i] <= 6)) ) {
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free(checker_idxs);
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return 0;
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/* Check if moving backmost checker */
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if (checker_idxs[i] < from_idx) {
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moving_backmost_checker = 0;
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if (!bearing_directly_off) break;
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}
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} else {
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if (checker_idxs[i] > 6) {
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all_checkers_in_last_quadrant = 0;
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break;
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}
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if (checker_idxs[i] > from_idx) {
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moving_backmost_checker = 0;
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if (!bearing_directly_off) break;
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}
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}
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}
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free(checker_idxs);
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return 1;
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if (all_checkers_in_last_quadrant &&
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(bearing_directly_off || moving_backmost_checker)) return 1;
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else return 0;
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}
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@ -124,7 +144,7 @@ int is_move_valid(int board[], int player, int face_value, int move[]) {
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&& bear_in_if_checker_on_bar(board, player, from_idx)
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&& checkers_at_from_idx(from_state, player)
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&& no_block_at_to_idx(to_state, player)
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&& (!bearing_off || can_bear_off(board, player, from_idx))
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&& (!bearing_off || can_bear_off(board, player, from_idx, to_idx))
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;
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}
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|
|
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28
report_docs.txt
Normal file
28
report_docs.txt
Normal file
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@ -0,0 +1,28 @@
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<christoffer> Alexander og jeg skrev noget af vores bachelorprojekt om til C her i fredags.
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<christoffer> Man skal virkelig passe på sine hukommelsesallokeringer.
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<Jmaa> Ja, helt klart.
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<christoffer> Jeg fandt et memory leak, der lækkede 100 MiB hukommelse i sekundet.
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<Jmaa> Hvilken del blev C-ificeret?
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<Jmaa> Damned
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<christoffer> Årsagen var at vi gav et objekt med tilbage til Python uden at dekrementere dets ref-count, så fortolkeren stadig troede at nogen havde brug for det.
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<christoffer> Den del af spillogikken, der tjekker om træk er gyldige.
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<christoffer> Det bliver kaldt ret mange tusinde gange pr. spil, så vi tænkte at der måske kunne være lidt optimering at hente i at omskrive det til C.
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<Jmaa> Ok, så I har ikke selv brugt alloc og free. Det er alligevel noget.
|
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<christoffer> Metoden selv blev 7 gange hurtigere!
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<Jmaa> Wow!
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<christoffer> Jo. Det endte vi også med at gøre.
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||||
<christoffer> Vi havde brug for lister af variabel størrelse. Det endte med en struct med et "size" felt og et "list" felt.
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<Jmaa> Inkluderer det speedup, frem og tilbagen mellem C og python?
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<christoffer> Det burde det gøre, ja!
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<Jmaa> Gjorde det nogen stor effekt for hvor hurtigt I kan evaluere?
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<christoffer> Jeg tror ikke at der er særligt meget "frem og tilbage"-stads. Det ser ud til at det kode man skriver bliver kastet ret direkte ind i fortolkeren.
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<christoffer> Det gjorde en stor forskel for når vi laver 1-ply.
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<christoffer> "ply" er hvor mange træk man kigger fremad.
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<christoffer> Så kun at kigge på det umiddelbart næste træk er 0-ply, hvilket er det vi har gjort indtil nu
|
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<christoffer> 1-ply var for langsomt. Det tog ca. 6-7 sekunder at evaluere ét træk.
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<christoffer> Alexander lavede lidt omskrivninger, så TensorFlow udregnede det hurtigere og fik det ned på ca. 3-4 sekunder *pr. spil*.
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<christoffer> Så skrev vi noget af det om til C, og nu er vi så på ca. 2 sekunder pr. spil med 1-ply, hvilket er ret vildt.
|
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<christoffer> Det er så godt at Python-fortolkeren kan udvides med C!
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<christoffer> caspervk, kan I optimere jeres bachelorprojekt med et par C-moduler?
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<Jmaa> Det er en hel lille sektion til rapporten det der.
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<christoffer> Yeah. Kopierer bare det her verbatim ind.
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782
test.py
782
test.py
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|
@ -141,6 +141,56 @@ class TestIsMoveValid(unittest.TestCase):
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# TODO: More tests for bearing off are needed
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def test_bear_off_non_backmost(self):
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board = ( 0,
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0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 1, 1,
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0 )
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self.assertEqual(Board.is_move_valid(board, 1, 2, (23, 25)), True)
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self.assertEqual(Board.is_move_valid(board, 1, 1, (24, 25)), True)
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self.assertEqual(Board.is_move_valid(board, 1, 2, (24, 26)), False)
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def test_bear_off_quadrant_limits_white(self):
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board = ( 0,
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0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 1,
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1, 1, 1, 1, 1, 1,
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0 )
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self.assertEqual(Board.is_move_valid(board, 1, 2, (23, 25)), False)
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self.assertEqual(Board.is_move_valid(board, 1, 1, (24, 25)), False)
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def test_bear_off_quadrant_limits_black(self):
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board = ( 0,
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-1, -1, -1, -1, -1, -1,
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-1, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0,
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||||
0, 0, 0, 0, 0, 0,
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||||
0 )
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self.assertEqual(Board.is_move_valid(board, -1, 2, (2, 0)), False)
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self.assertEqual(Board.is_move_valid(board, -1, 1, (1, 0)), False)
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def test_bear_off_quadrant_limits_white_2(self):
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board = ( 0,
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0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0,
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||||
0, 0, 0, 0, 0, 0,
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||||
1, 0, 0, 0, 0, 1,
|
||||
0 )
|
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self.assertEqual(Board.is_move_valid(board, 1, 1, (24, 25)), True)
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def test_bear_off_quadrant_limits_black_2(self):
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board = ( 0,
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-1, 0, 0, 0, 0, -1,
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0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
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||||
0 )
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||||
self.assertEqual(Board.is_move_valid(board, -1, 1, (1, 0)), True)
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|
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class TestNumOfChecker(unittest.TestCase):
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def test_simple_1(self):
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board = ( 0,
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|
|
@ -552,372 +602,372 @@ class TestLegalMoves(unittest.TestCase):
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self.assertEqual(Board.calculate_legal_states(board, -1, (4,3)), expected_board_set)
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# class TestBoardFlip(unittest.TestCase):
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# def test_flip_board(self):
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# board = (0,
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# -14, -1, 0, 0, 0, 0,
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# 0, 0, 0, 0, 0, 0,
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# 0, 0, 0, 0, 0, 0,
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# 0, 0, 0, 0, 0, 1,
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# 0)
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|
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# expected_board = ( 0,
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# -1, 0, 0, 0, 0, 0,
|
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# 0, 0, 0, 0, 0, 0,
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# 0, 0, 0, 0, 0, 0,
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# 0, 0, 0, 0, 1, 14,
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# 0 )
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# self.assertEqual(Board.flip(board), expected_board)
|
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|
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# def test_flip_board_bar(self):
|
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# board = (2,
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# 0, 0, 0, 0, 0, 0,
|
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# 0, 0, 0, 0, 0, 0,
|
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# 0, 0, 0, 0, 0, 0,
|
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# 0, 0, 0, 0, 0, 0,
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# -7)
|
||||
|
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# expected_board = (7,
|
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# 0, 0, 0, 0, 0, 0,
|
||||
# 0, 0, 0, 0, 0, 0,
|
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# 0, 0, 0, 0, 0, 0,
|
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# 0, 0, 0, 0, 0, 0,
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# -2)
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|
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# self.assertEqual(Board.flip(board), expected_board)
|
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|
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# def test_flip_board_extensive(self):
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# board = (4,
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# -5, -1, 0, 4, 3, 0,
|
||||
# 0, -1, 0, -5, 0, 0,
|
||||
# 0, 3, 0, 0, 0, 0,
|
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# 0, 0, 0, -1, 0, 1,
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# -2)
|
||||
|
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# expected_board = (2,
|
||||
# -1, 0, 1, 0, 0, 0,
|
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# 0, 0, 0, 0, -3, 0,
|
||||
# 0, 0, 5, 0, 1, 0,
|
||||
# 0, -3, -4, 0, 1, 5,
|
||||
# -4)
|
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|
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# self.assertEqual(Board.flip(board), expected_board)
|
||||
|
||||
# def test_inverse(self):
|
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# board = (4,
|
||||
# -5, -1, 0, 4, 3, 0,
|
||||
# 0, -1, 0, -5, 0, 0,
|
||||
# 0, 3, 0, 0, 0, 0,
|
||||
# 0, 0, 0, -1, 0, 1,
|
||||
# -2)
|
||||
|
||||
# self.assertEqual(Board.flip(Board.flip(board)), board)
|
||||
|
||||
# def test_tesauro_initial(self):
|
||||
# board = Board.initial_state
|
||||
|
||||
# expected = (1,1,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,1,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1,1,1,1,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0.0,
|
||||
# 0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,1,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1,1,1,1,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,0,0,
|
||||
|
||||
# 0.0,
|
||||
# 0,
|
||||
|
||||
# 1,
|
||||
# 0
|
||||
# )
|
||||
|
||||
# import numpy as np
|
||||
# self.assertTrue((Board.board_features_tesauro(board, 1) ==
|
||||
# np.array(expected).reshape(1, 198)).all())
|
||||
|
||||
# def test_tesauro_bars(self):
|
||||
# board = list(Board.initial_state)
|
||||
# board[1] = 0
|
||||
# board[0] = 2
|
||||
# board[24] = 0
|
||||
# board[25] = -2
|
||||
|
||||
# board = tuple(board)
|
||||
|
||||
# expected = (0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,1,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1,1,1,1,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1.0,
|
||||
# 0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,1,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1,1,1,1,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1.0,
|
||||
# 0,
|
||||
|
||||
# 1,
|
||||
# 0
|
||||
# )
|
||||
|
||||
# import numpy as np
|
||||
# self.assertTrue((Board.board_features_tesauro(board, 1) ==
|
||||
# np.array(expected).reshape(1, 198)).all())
|
||||
|
||||
|
||||
# def test_tesauro_home(self):
|
||||
# board = list(Board.initial_state)
|
||||
|
||||
# board[1] = 0
|
||||
# board[24] = 0
|
||||
|
||||
# board = tuple(board)
|
||||
|
||||
# expected = (0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,1,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1,1,1,1,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0.0,
|
||||
# 2,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,1,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1,1,1,1,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0.0,
|
||||
# 2,
|
||||
|
||||
# 1,
|
||||
# 0
|
||||
# )
|
||||
|
||||
# import numpy as np
|
||||
# self.assertTrue((Board.board_features_tesauro(board, 1) ==
|
||||
# np.array(expected).reshape(1, 198)).all())
|
||||
|
||||
|
||||
# def test_tesauro_black_player(self):
|
||||
# board = Board.initial_state
|
||||
|
||||
# expected = (1,1,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,1,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1,1,1,1,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0.0,
|
||||
# 0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,1,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 1,1,1,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 1,1,1,1,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 0,0,0,0,
|
||||
# 1,1,0,0,
|
||||
|
||||
# 0.0,
|
||||
# 0,
|
||||
|
||||
# 0,
|
||||
# 1
|
||||
# )
|
||||
|
||||
# import numpy as np
|
||||
# self.assertTrue((Board.board_features_tesauro(board, -1) ==
|
||||
# np.array(expected).reshape(1, 198)).all())
|
||||
class TestBoardFlip(unittest.TestCase):
|
||||
def test_flip_board(self):
|
||||
board = (0,
|
||||
-14, -1, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 1,
|
||||
0)
|
||||
|
||||
expected_board = ( 0,
|
||||
-1, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 1, 14,
|
||||
0 )
|
||||
|
||||
self.assertEqual(Board.flip(board), expected_board)
|
||||
|
||||
def test_flip_board_bar(self):
|
||||
board = (2,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
-7)
|
||||
|
||||
expected_board = (7,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0,
|
||||
-2)
|
||||
|
||||
self.assertEqual(Board.flip(board), expected_board)
|
||||
|
||||
def test_flip_board_extensive(self):
|
||||
board = (4,
|
||||
-5, -1, 0, 4, 3, 0,
|
||||
0, -1, 0, -5, 0, 0,
|
||||
0, 3, 0, 0, 0, 0,
|
||||
0, 0, 0, -1, 0, 1,
|
||||
-2)
|
||||
|
||||
expected_board = (2,
|
||||
-1, 0, 1, 0, 0, 0,
|
||||
0, 0, 0, 0, -3, 0,
|
||||
0, 0, 5, 0, 1, 0,
|
||||
0, -3, -4, 0, 1, 5,
|
||||
-4)
|
||||
|
||||
self.assertEqual(Board.flip(board), expected_board)
|
||||
|
||||
def test_inverse(self):
|
||||
board = (4,
|
||||
-5, -1, 0, 4, 3, 0,
|
||||
0, -1, 0, -5, 0, 0,
|
||||
0, 3, 0, 0, 0, 0,
|
||||
0, 0, 0, -1, 0, 1,
|
||||
-2)
|
||||
|
||||
self.assertEqual(Board.flip(Board.flip(board)), board)
|
||||
|
||||
def test_tesauro_initial(self):
|
||||
board = Board.initial_state
|
||||
|
||||
expected = (1,1,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,1,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,0,
|
||||
0,0,0,0,
|
||||
|
||||
1,1,1,1,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0.0,
|
||||
0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,1,
|
||||
|
||||
0,0,0,0,
|
||||
1,1,1,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
1,1,1,1,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,0,0,
|
||||
|
||||
0.0,
|
||||
0,
|
||||
|
||||
1,
|
||||
0
|
||||
)
|
||||
|
||||
import numpy as np
|
||||
self.assertTrue((Board.board_features_tesauro(board, 1) ==
|
||||
np.array(expected).reshape(1, 198)).all())
|
||||
|
||||
def test_tesauro_bars(self):
|
||||
board = list(Board.initial_state)
|
||||
board[1] = 0
|
||||
board[0] = 2
|
||||
board[24] = 0
|
||||
board[25] = -2
|
||||
|
||||
board = tuple(board)
|
||||
|
||||
expected = (0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,1,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,0,
|
||||
0,0,0,0,
|
||||
|
||||
1,1,1,1,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
1.0,
|
||||
0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,1,
|
||||
|
||||
0,0,0,0,
|
||||
1,1,1,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
1,1,1,1,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
1.0,
|
||||
0,
|
||||
|
||||
1,
|
||||
0
|
||||
)
|
||||
|
||||
import numpy as np
|
||||
self.assertTrue((Board.board_features_tesauro(board, 1) ==
|
||||
np.array(expected).reshape(1, 198)).all())
|
||||
|
||||
|
||||
def test_tesauro_home(self):
|
||||
board = list(Board.initial_state)
|
||||
|
||||
board[1] = 0
|
||||
board[24] = 0
|
||||
|
||||
board = tuple(board)
|
||||
|
||||
expected = (0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,1,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,0,
|
||||
0,0,0,0,
|
||||
|
||||
1,1,1,1,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0.0,
|
||||
2,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,1,
|
||||
|
||||
0,0,0,0,
|
||||
1,1,1,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
1,1,1,1,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0.0,
|
||||
2,
|
||||
|
||||
1,
|
||||
0
|
||||
)
|
||||
|
||||
import numpy as np
|
||||
self.assertTrue((Board.board_features_tesauro(board, 1) ==
|
||||
np.array(expected).reshape(1, 198)).all())
|
||||
|
||||
|
||||
def test_tesauro_black_player(self):
|
||||
board = Board.initial_state
|
||||
|
||||
expected = (1,1,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,1,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,0,
|
||||
0,0,0,0,
|
||||
|
||||
1,1,1,1,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0.0,
|
||||
0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,1,1,
|
||||
|
||||
0,0,0,0,
|
||||
1,1,1,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
1,1,1,1,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
0,0,0,0,
|
||||
1,1,0,0,
|
||||
|
||||
0.0,
|
||||
0,
|
||||
|
||||
0,
|
||||
1
|
||||
)
|
||||
|
||||
import numpy as np
|
||||
self.assertTrue((Board.board_features_tesauro(board, -1) ==
|
||||
np.array(expected).reshape(1, 198)).all())
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user