Shape error of the actor forward function in DeepTrader task

import os
import sys
from pathlib import Path
import warnings
warnings.filterwarnings("ignore")
ROOT = os.path.dirname(os.path.abspath("."))
sys.path.append(ROOT)
import torch
import argparse
import os.path as osp
from mmcv import Config
from trademaster.utils import replace_cfg_vals
from trademaster.nets.builder import build_net
from trademaster.environments.builder import build_environment
from trademaster.datasets.builder import build_dataset
from trademaster.agents.builder import build_agent
from trademaster.optimizers.builder import build_optimizer
from trademaster.losses.builder import build_loss
from trademaster.trainers.builder import build_trainer
from trademaster.transition.builder import build_transition
from trademaster.utils import plot
from trademaster.utils import set_seed
set_seed(2023)

parser = argparse.ArgumentParser(description='Download dj30 Datasets')
parser.add_argument("--config", default=osp.join(ROOT, "configs", "portfolio_management", "portfolio_management_dj30_deeptrader_deeptrader_adam_mse.py"),
                    help="download datasets config file path")
parser.add_argument("--task_name", type=str, default="train")

args, _= parser.parse_known_args()
cfg = Config.fromfile(args.config)
task_name = args.task_name
cfg = replace_cfg_vals(cfg)

dataset = build_dataset(cfg)

train_environment = build_environment(cfg, default_args=dict(dataset=dataset, task="train"))
valid_environment = build_environment(cfg, default_args=dict(dataset=dataset, task="valid"))
test_environment = build_environment(cfg, default_args=dict(dataset=dataset, task="test"))

action_dim = train_environment.action_dim # 29
state_dim = train_environment.state_dim # 16
input_dim = len(train_environment.tech_indicator_list)

act = build_net(cfg.act_net)
cri = build_net(cfg.cri_net)
market = build_net(cfg.market_net)
act_optimizer = build_optimizer(cfg, default_args=dict(params=act.parameters()))
cri_optimizer = build_optimizer(cfg, default_args=dict(params=cri.parameters()))
market_optimizer = build_optimizer(cfg, default_args=dict(params=market.parameters()))
criterion = build_loss(cfg)

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
agent = build_agent(cfg, default_args=dict(action_dim=action_dim, 
                        state_dim=state_dim,act=act,cri=cri,
                        market=market,act_optimizer=act_optimizer, \
                        cri_optimizer = cri_optimizer, criterion = criterion,\
                        market_optimizer = market_optimizer,device = device))

trainer = build_trainer(cfg,
                        default_args=dict(train_environment=train_environment,
                                          valid_environment=valid_environment,
                                          test_environment=test_environment,
                                          agent=agent,device=device))
work_dir = os.path.join(ROOT, cfg.trainer.work_dir)

if not os.path.exists(work_dir):
    os.makedirs(work_dir)
cfg.dump(osp.join(work_dir, osp.basename(args.config)))

trainer.train_and_valid()

And I got the error :

Traceback (most recent call last):
  File "C:\Users\HuZetian\Desktop\TradeMaster\tutorial\Tutorial_DeepTrader.py", line 72, in <module>
    trainer.train_and_valid()
  File "C:\Users\HuZetian\Desktop\TradeMaster\trademaster\trainers\portfolio_management\deeptrader_trainer.py", line 173, in train_and_valid
    buffer_items = self.agent.explore_env(self.train_environment, self.horizon_len)
  File "C:\Users\HuZetian\Desktop\TradeMaster\trademaster\agents\portfolio_management\deeptrader.py", line 216, in explore_env    
    action = get_action(state,market_state,corr_matrix)
  File "C:\Users\HuZetian\Desktop\TradeMaster\trademaster\agents\portfolio_management\deeptrader.py", line 173, in get_action 
    asset_scores = self.act(state, corr_matrix)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl     
    return forward_call(*input, **kwargs)
  File "C:\Users\HuZetian\Desktop\TradeMaster\trademaster\nets\deeptrader.py", line 221, in forward
    H_L = self.TCN(x)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl     
    return forward_call(*input, **kwargs)
  File "C:\Users\HuZetian\Desktop\TradeMaster\trademaster\nets\deeptrader.py", line 135, in forward
    return self.network(x)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl     
    return forward_call(*input, **kwargs)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\container.py", line 139, in forward      
    input = module(input)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl     
    return forward_call(*input, **kwargs)
  File "C:\Users\HuZetian\Desktop\TradeMaster\trademaster\nets\deeptrader.py", line 89, in forward
    out = self.net(x)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl     
    return forward_call(*input, **kwargs)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\container.py", line 139, in forward      
    input = module(input)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\module.py", line 1148, in _call_impl     
    result = forward_call(*input, **kwargs)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\conv.py", line 307, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "C:\ProgramData\Anaconda3\envs\TradeMaster\lib\site-packages\torch\nn\modules\conv.py", line 303, in _conv_forward     
    return F.conv1d(input, weight, bias, self.stride,
RuntimeError: Expected 2D (unbatched) or 3D (batched) input to conv1d, but got input of size: [1, 29, 16, 10]

Can help me with it?

TradeMaster-NTU / TradeMaster

Shape error of the actor forward function in DeepTrader task #158