def init_args(cls, params): work_dir = osp.join( params.work_dir, f'{params.proj_name}/{params.exp_name}/{params.exp_version}/experiment' ) try_set_attr(params, f'{cls.prefix_name()}_work_dir', work_dir) try_set_attr(params, f'{cls.prefix_name()}_log_dir', work_dir)
def init_args(cls, params, model_cls_name=None, model_cls=None): try_set_attr(params, 'q_net_cls_name', 'attn_film_q_net') try_set_attr(params, 'img_net_cls_name', 'film_img_net') try_set_attr(params, 'fusion_net_cls_name', 'film_fusion_net') try_set_attr(params, 'classifier_net_cls_name', 'concat_classifier_net') try_set_attr(params, 'net_modes', (True, True, True, True)) for net_name in ('q', 'img', 'fusion', 'classifier'): Net.init_args(params, getattr(params, f'{net_name}_net_cls_name', None)) return params
def init_args(cls, params, sub_cls=None): cls.default_init_args(params) try_set_attr(params, f'{cls.prefix_name()}_name', 'logger_group') try_set_attr( params, f'{cls.prefix_name()}_logger_dir', to_path(params.root_dir).joinpath(f'loggers/{params.proj_name}')) logger_cls = cls.load_cls( try_get_attr(params, f'{cls.prefix_name()}_logger_cls', check=False)) if logger_cls is not None: logger_cls.init_args(params) setattr( params, f'{cls.prefix_name()}_logger_kwargs', load_func_kwargs(params, logger_cls.__init__, cls.prefix_name()))
def init_args(cls, params, sub_cls=None): try_set_attr(params, f'{cls.prefix_name()}_layers', ('img_init_layer_a', 'dsod_layer', 'dsod_layer')) try_set_attr(params, f'{cls.prefix_name()}_layer_in_dims', (3, 64, 128)) try_set_attr(params, f'{cls.prefix_name()}_layer_out_dims', (64, 128, 128))
def init_args(cls, params, sub_cls=None): try_set_attr(params, f'{cls.prefix_name()}_q_net_cls', 'cgs_q_net') try_set_attr(params, f'{cls.prefix_name()}_graph_net_cls', 'cgs_graph_net') try_set_attr(params, f'{cls.prefix_name()}_cls_net_cls', 'cgs_cls_net') for net_name in cls.net_names: net_cls = Net.load_cls(try_get_attr(params, f'{cls.prefix_name()}_{net_name}_cls', check=False)) if net_cls is not None: net_cls.init_args(params)
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'fusion_layer_types', (None, 'film_fusion_layer', 'film_fusion_layer_f')) try_set_attr(params, 'fusion_layer_dims', (None, 128, 128)) try_set_attr(params, 'fusion_layer_hs', (112, 56, 28))
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'img_in_dim', 1024) try_set_attr(params, 'img_layer_dims', (128,)) if hasattr(params, 'img_layer_dims'): layer_num = len(params.img_layer_dims) try_set_attr(params, 'img_layer_norm_types', ('batch',) * layer_num) try_set_attr(params, 'img_layer_act_types', ('relu',) * layer_num) try_set_attr(params, 'img_layer_coord_types', ('default',) * layer_num) try_set_attr(params, 'img_layer_se_types', (None,) * layer_num)
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'question_query_dim', 128) super().init_args(params, cls_name, sub_cls)
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'classifier_answer_num', 28) try_set_attr(params, 'classifier_proj_dim', 512) try_set_attr(params, 'classifier_fc_dim', 1024) try_set_attr(params, 'classifier_norm_type', 'batch') try_set_attr(params, 'classifier_add_coord', True) try_set_attr(params, 'classifier_in_dim', 128)
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'question_vocab_num', 90) try_set_attr(params, 'question_embed_dim', 32) try_set_attr(params, 'question_feat_dim', 128) try_set_attr(params, 'question_is_bi', False)
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'img_in_dim', 3) try_set_attr(params, 'img_growth_rate', 32) try_set_attr(params, 'img_layer_types', ('img_init_layer', 'dsod_layer', 'dsod_layer', 'dsod_layer')) try_set_attr(params, 'img_layer_dims', (64, 128, 128, 128)) if hasattr(params, 'img_layer_types'): layer_num = len(params.img_layer_types) try_set_attr(params, 'img_layer_widens', (1,) * layer_num) try_set_attr(params, 'img_layer_coord_types', ('default',) * layer_num) try_set_attr(params, 'img_layer_depths', (4,) * layer_num) try_set_attr(params, 'img_layer_norm_types', ('batch',) * 4) try_set_attr(params, 'img_layer_se_types', ('None',) * 4) return params
def init_args(cls, params, sub_cls=None): try_set_attr(params, f'{cls.prefix_name()}_layers', ('sparse_graph_layer', )) try_set_attr(params, f'{cls.prefix_name()}_layer_obj_dims', (2048, )) try_set_attr(params, f'{cls.prefix_name()}_layer_q_dims', (1024, )) try_set_attr(params, f'{cls.prefix_name()}_layer_out_dims', (1024, )) try_set_attr(params, f'{cls.prefix_name()}_layer_kernel_sizes', (8, )) try_set_attr(params, f'{cls.prefix_name()}_layer_reduce_sizes', (16, )) try_set_attr(params, f'{cls.prefix_name()}_filter_method', 'not_eye')
def init_args(cls, params, sub_cls=None): cls.default_init_args(params) try_set_attr( params, f'{cls.prefix_name()}_work_dir', to_path(params.root_dir).joinpath(f'loggers/{params.proj_name}')) try_set_attr(params, f'{cls.prefix_name()}_env', params.proj_name)
def init_args(cls, params, sub_cls=None): try_set_attr(params, f'{cls.prefix_name()}_layers', ('dense_film_layer', 'dense_film_layer', 'dense_film_layer', 'dense_film_layer')) try_set_attr(params, f'{cls.prefix_name()}_layer_img_dims', (128, 256, 384, 512))
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'img_in_dim', 3) try_set_attr(params, 'img_layer_types', ('img_init_layer', 'dsod_fusion_layer_a', 'dsod_fusion_layer_a', 'dsod_fusion_layer_a')) try_set_attr(params, 'img_layer_dims', (64, 128, 128, 128)) try_set_attr(params, 'img_layer_feat_hs', (112, 56, 28, 14)) return params
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'classifier_answer_num', 29) try_set_attr(params, 'classifier_fc_dim', 512) try_set_attr(params, 'classifier_norm_type', 'batch') try_set_attr(params, 'classifier_in_dim', 128)
def init_args(cls, params): save_dir = osp.join( params.work_dir, f'{params.proj_name}/{params.exp_name}/{params.exp_version}/checkpoint' ) try_set_attr(params, f'{cls.prefix_name()}_save_dir', save_dir)
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'fusion_in_dim', 128) try_set_attr(params, 'fusion_layer_types', ('film_fusion_layer',) * 4) if hasattr(params, 'fusion_layer_types'): layer_num = len(params.fusion_layer_types) try_set_attr(params, 'fusion_layer_dims', (params.fusion_in_dim,) * layer_num) # try_set_attr(args, 'fusion_layer_dims', (256, 384, 512, 640)) try_set_attr(params, 'fusion_layer_norm_types', ('batch',) * layer_num) try_set_attr(params, 'fusion_layer_act_types', ('relu',) * layer_num) try_set_attr(params, 'fusion_layer_fusion_norm_types', ('batch',) * layer_num) try_set_attr(params, 'fusion_layer_coord_types', ('default',) * layer_num)
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'classifier_answer_num', 28) try_set_attr(params, 'classifier_proj_dim', 30) try_set_attr(params, 'classifier_fc_dim', 1024) try_set_attr(params, 'classifier_norm_type', 'batch') try_set_attr(params, 'classifier_attn_max', 50) try_set_attr(params, 'classifier_add_coord', True) try_set_attr(params, 'classifier_img_dim', 128) try_set_attr(params, 'classifier_query_dim', 128) try_set_attr(params, 'classifier_act_type', 'relu')
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'classifier_answer_num', 28) try_set_attr(params, 'classifier_proj_dim', 512) try_set_attr(params, 'classifier_fc_dim', 1024) try_set_attr(params, 'classifier_norm_type', 'batch') try_set_attr(params, 'classifier_feat_h', 14) try_set_attr(params, 'classifier_coord_type', 'default') try_set_attr(params, 'classifier_in_dim', 128) try_set_attr(params, 'classifier_act_type', 'relu')
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'question_vocab_num', 90) try_set_attr(params, 'question_embed_dim', 200) try_set_attr(params, 'question_feat_dim', 4096) try_set_attr(params, 'question_add_one', True) try_set_attr(params, 'question_info_dim', 1024) try_set_attr(params, 'question_is_bi', False)
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, 'classifier_answer_num', 29) try_set_attr(params, 'classifier_proj_dim', 512) try_set_attr(params, 'classifier_fc_dim', 1024) try_set_attr(params, 'classifier_norm_type', 'batch') try_set_attr(params, 'classifier_feat_h', 14) try_set_attr(params, 'classifier_add_coord', False) try_set_attr(params, 'classifier_img_dim', 128) try_set_attr(params, 'classifier_query_dim', 128) try_set_attr(params, 'classifier_act_type', 'relu')
def init_args(cls, params, cls_name=None, sub_cls=None): try_set_attr(params, f'{cls.prefix_name()}_vocab_num', 82) try_set_attr(params, f'{cls.prefix_name()}_embed_dim', 100) try_set_attr(params, f'{cls.prefix_name()}_out_dim', 2048) try_set_attr(params, f'{cls.prefix_name()}_is_bi', False)