def __init__(self, args):
# real MemNN model architecture
self.memnn_model = MemNNModel(args)
self.args = args
exp_name = args.data_set + '_' + args.exp_name
# create experiment dir
self.exp_dir= os.path.join(args.checkpoints_dir, exp_name)
helper_fn.makedirs(self.exp_dir)
hist_name = exp_name + '.hist'
model_name = exp_name + '_final_model.h5'
encoder_model_name = exp_name + '_encoder_model.h5'
decoder_model_name = exp_name + '_decoder_model.h5'
self.history_path = os.path.join(self.exp_dir, hist_name)
self.model_path = os.path.join(self.exp_dir, model_name)
self.encoder_model_path = os.path.join(self.exp_dir, encoder_model_name)
self.decoder_model_path = os.path.join(self.exp_dir, decoder_model_name)
outputs_dir = args.outputs_dir
helper_fn.makedirs(outputs_dir)
self.src_out_name = exp_name + '.src'
self.src_out_path = os.path.join(outputs_dir, self.src_out_name)
self.pred_out_name = exp_name + '.pred'
self.pred_out_path = os.path.join(outputs_dir, self.pred_out_name)
self.tar_out_name = exp_name + '.tgt'
self.tar_out_path = os.path.join(outputs_dir, self.tar_out_name)
def __init__(self, args):
# real Transformer model architecture
self.transformer_model = TransformerModel(
args=args,
transformer_dropout=0.05,
embedding_dropout=0.05,
use_same_embedding=False,
)
self.args = args
exp_name = args.data_set + '_' + args.exp_name
# create experiment dir
self.exp_dir = os.path.join(args.checkpoints_dir, exp_name)
helper_fn.makedirs(self.exp_dir)
hist_name = exp_name + '.hist'
model_name = exp_name + '_final_model.h5'
self.history_path = os.path.join(self.exp_dir, hist_name)
self.model_path = os.path.join(self.exp_dir, model_name)
outputs_dir = args.outputs_dir
helper_fn.makedirs(outputs_dir)
self.src_out_name = exp_name + '.src'
self.src_out_path = os.path.join(outputs_dir, self.src_out_name)
self.pred_out_name = exp_name + '.pred'
self.pred_out_path = os.path.join(outputs_dir, self.pred_out_name)
self.tar_out_name = exp_name + '.tgt'
self.tar_out_path = os.path.join(outputs_dir, self.tar_out_name)
def __init__(self, args):
self.tau = K.variable(0.5, name='temperature')
self.dssm_model = AutoPointerDssmModel(args=args, tau=self.tau, use_same_embedding=False)
self.args = args
exp_names = []
exp_names.append(args.data_set)
exp_names.append(args.exp_name)
exp_names.append('pos')
exp_names.append(str(args.positive_number))
exp_names.append('neg')
exp_names.append(str(args.negative_number))
exp_names.append('qr')
exp_names.append(str(args.query_retrieval_number))
exp_names.append('apr')
exp_names.append(str(args.auto_pointer_rate))
#exp_names.append('layers')
#exp_names.append(str(args.transformer_depth))
exp_name = '_'.join(exp_names)
# create experiment dir
self.exp_dir= os.path.join(args.checkpoints_dir, exp_name)
helper_fn.makedirs(self.exp_dir)
hist_name = exp_name + '.hist'
model_name = exp_name + '_final_model.h5'
self.history_path = os.path.join(self.exp_dir, hist_name)
self.model_path = os.path.join(self.exp_dir, model_name)
outputs_dir = args.outputs_dir
helper_fn.makedirs(outputs_dir)
self.out_name = exp_name + '.dssm'
self.out_path = os.path.join(outputs_dir, self.out_name)
def __init__(self, args):
# real Transformer model architecture
self.multi_task_model= MultiTaskModel(args=args)
self.args = args
exp_name = args.data_set + '_' + args.exp_name
# create experiment dir
self.exp_dir= os.path.join(args.checkpoints_dir, exp_name)
helper_fn.makedirs(self.exp_dir)
hist_name = exp_name + '.hist'
model_name = exp_name + '_final_model.h5'
self.history_path = os.path.join(self.exp_dir, hist_name)
self.model_path = os.path.join(self.exp_dir, model_name)
outputs_dir = args.outputs_dir
helper_fn.makedirs(outputs_dir)
self.src_out_name = exp_name + '.src'
self.src_out_path = os.path.join(outputs_dir, self.src_out_name)
self.pred_out_name = exp_name + '.pred'
self.pred_out_path = os.path.join(outputs_dir, self.pred_out_name)
self.tar_out_name = exp_name + '.tgt'
self.tar_out_path = os.path.join(outputs_dir, self.tar_out_name)
def __init__(self, args):
self.args = args
exp_name = args.data_set + '_' + args.exp_name
self.checkpoints_dir = os.path.join(args.checkpoints_dir, exp_name)
helper_fn.makedirs(self.checkpoints_dir)
self.checkpoint_prefix = os.path.join(self.checkpoints_dir, 'ckpt')
self.tensorboard_dir = args.tensorboard_dir
helper_fn.makedirs(self.tensorboard_dir)
outputs_dir = args.outputs_dir
helper_fn.makedirs(outputs_dir)
self.src_out_name = exp_name + '.src'
self.src_out_path = os.path.join(outputs_dir, self.src_out_name)
self.pred_out_name = exp_name + '.pred'
self.pred_out_path = os.path.join(outputs_dir, self.pred_out_name)
self.tar_out_name = exp_name + '.tgt'
self.tar_out_path = os.path.join(outputs_dir, self.tar_out_name)