def METHOD_NAME():
    local_w = dict()
    local_w["linear.weight"] = torch.FloatTensor(
        [
            [-0.0003, 0.0192, -0.0294, 0.0219, 0.0037, 0.0021],
            [-0.0198, -0.0150, -0.0104, -0.0203, -0.0060, -0.0299],
            [-0.0201, 0.0149, -0.0333, -0.0203, 0.0012, 0.0080],
            [0.0237, 0.0103, -0.0219, 0.0088, -0.0009, 0.0009],
            [0.0144, -0.0336, -0.0346, -0.0222, -0.0025, -0.0138],
            [-0.0196, -0.0118, 0.0230, -0.0202, 0.0172, 0.0355],
        ]
    )
    local_w["linear.bias"] = torch.FloatTensor([-0.0753, -0.0589, -0.0907, -0.0672, 0.1159, 0.0290])
    global_w = dict()
    global_w["linear.weight"] = torch.FloatTensor(
        [
            [-0.0003, 0.0192, -0.0294, 0.0219, 0.0037, 0.0021],
            [-0.0198, -0.0150, -0.0104, -0.0203, -0.0060, -0.0299],
            [-0.0201, 0.0149, -0.0333, -0.0203, 0.0012, 0.0080],
            [0.0237, 0.0103, -0.0219, 0.0088, -0.0009, 0.0009],
            [0.0144, -0.0336, -0.0346, -0.0222, -0.0025, -0.0138],
            [-0.0196, -0.0118, 0.0230, -0.0202, 0.0172, 0.0355],
        ]
    )
    global_w["linear.bias"] = torch.FloatTensor([-0.0745, -0.0578, -0.0899, -0.0662, 0.1122, 0.0295])
    return local_w, global_w