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)
