from options.base_options import BaseOptions


class TestOptions(BaseOptions):
    def initialize(self):
        BaseOptions.initialize(self)
        self.parser.add_argument('--batch_size', type=int, default=1, help='Batch size')
        self.parser.add_argument('--start_mov_len', type=int, default=10)
        self.parser.add_argument('--est_length', action="store_true", help="Whether to use sampled motion length")
        self.parser.add_argument('--num_layers', type=int, default=8, help='num_layers of transformer')
        self.parser.add_argument('--latent_dim', type=int, default=512, help='latent_dim of transformer')
        self.parser.add_argument('--diffusion_steps', type=int, default=1000, help='diffusion_steps of transformer')
        self.parser.add_argument('--no_clip', action='store_true', help='whether use clip pretrain')
        self.parser.add_argument('--no_eff', action='store_true', help='whether use efficient attention')


        self.parser.add_argument('--repeat_times', type=int, default=3, help="Number of generation rounds for each text description")
        self.parser.add_argument('--split_file', type=str, default='test.txt')
        self.parser.add_argument('--text', type=str, default="", help='Text description for motion generation')
        self.parser.add_argument('--motion_length', type=int, default=0, help='Number of framese for motion generation')
        self.parser.add_argument('--text_file', type=str, default="", help='Path of text description for motion generation')
        self.parser.add_argument('--which_epoch', type=str, default="latest", help='Checkpoint that will be used')
        self.parser.add_argument('--result_path', type=str, default="./eval_results/", help='Path to save generation results')
        self.parser.add_argument('--num_results', type=int, default=40, help='Number of descriptions that will be used')
        self.parser.add_argument('--ext', type=str, default='default', help='Save file path extension')

        self.is_train = False