def show_board(_boards, _pboards=None, show_float=False):
shstr = [' ', ' │ ', '─┘ ', ' └─', '─┐ ', ' ┌─', '───']
idx = 0
for z in range(board_z):
print 'LAYER {}'.format(z + 1)
for y in range(n_dims_half, board_y + n_dims_half):
for x in range(n_dims_half, board_x + n_dims_half):
# ビアを赤色で表示
if _pboards is not None and _boards[z][y][x]['type'] == 1 and _pboards[z][y][x]['type'] == 'via':
sys.stdout.write('\033[1;31;47m {} \033[0m'.format(nl.int2str(_boards[z][y][x]['data'], 36)))
elif _boards[z][y][x]['type'] == 1:
sys.stdout.write('\033[1;30;47m {} \033[0m'.format(nl.int2str(_boards[z][y][x]['data'], 36)))
else:
# 正しい配線形状
fr_color = '30'
# 途切れてないセル / 途切れてるセル
bg_color = '47'
if show_float:
if _boards[z][y][x]['float'] != None:
bg_color = '43'
sys.stdout.write('\033[1;{};{}m{}\033[0m'.format(fr_color, bg_color, shstr[_boards[z][y][x]['shape']]))
idx = idx + 1
print ''
def show_board(_board, show_float=False):
shstr = [' ', ' │ ', '─┘ ', ' └─', '─┐ ', ' ┌─', '───']
idx = 0
for y in range(n_dims_half, board_y + n_dims_half):
for x in range(n_dims_half, board_x + n_dims_half):
if _board[y][x]['type'] == 1:
sys.stdout.write('\033[1;30;47m {} \033[0m'.format(nl.int2str(_board[y][x]['data'], 36)))
else:
# 正しい配線形状
fr_color = '30'
# 途切れてないセル / 途切れてるセル
bg_color = '47'
if show_float:
if _board[y][x]['float'] != None:
bg_color = '43'
sys.stdout.write('\033[1;{};{}m{}\033[0m'.format(fr_color, bg_color, shstr[_board[y][x]['shape']]))
idx = idx + 1
print ''
loss_test, accuracy_test, result = forward(x_test, y_test, train=False)
# 訓練データ/テストデータの誤差と、正解精度を表示
if epoch % 100 == 0:
print 'epoch', epoch
print 'Train: mean loss={}, accuracy={}'.format(sum_loss / n_train, sum_accuracy / n_train)
if testfilename != 'none':
print 'Test: mean loss={}, accuracy={}'.format(loss_test.data, accuracy_test.data)
# テストデータの配線を表示
idx = 0
str = [' ', ' │ ', '─┘ ', ' └─', '─┐ ', ' ┌─', '───']
for y in range(n_dims_half, board_y + n_dims_half):
for x in range(n_dims_half, board_x + n_dims_half):
if board[y][x]['type'] == 1:
sys.stdout.write('\033[1;30;47m ' + nl.int2str(board[y][x]['data'], 36) + ' \033[0m')
else:
ex_shape = np.argmax(result.data[idx])
# 正しい配線形状
if (not args.show_wrong) or board[y][x]['shape'] == ex_shape:
sys.stdout.write('\033[1;30;47m' + str[ex_shape] + '\033[0m')
# 間違ってる配線形状
else:
sys.stdout.write('\033[1;31;47m' + str[ex_shape] + '\033[0m')
idx = idx + 1
print ''
# モデルをシリアライズ化して保存
with open(DIR_DUMP + '/s{}_u{}_e{}_d{}_t{}.pkl'.format(n_dims, n_units, n_epoch, args.dataset, testfilename_short), 'w') as f:
pickle.dump(model, f)