【发布时间】：2022-11-20 23:01:02
【问题描述】：
你好，我正在为 cartpole 上的强化学习构建一个 DQN 模型，并想像 keras model.summary() 函数一样打印我的模型摘要
这是我的模型类。
class DQN():
''' Deep Q Neural Network class. '''
def __init__(self, state_dim, action_dim, hidden_dim=64, lr=0.05):
super(DQN, self).__init__()
self.criterion = torch.nn.MSELoss()
self.model = torch.nn.Sequential(
torch.nn.Linear(state_dim, hidden_dim),
torch.nn.ReLU(),
torch.nn.Linear(hidden_dim, hidden_dim*2),
torch.nn.ReLU(),
torch.nn.Linear(hidden_dim*2, action_dim)
)
self.optimizer = torch.optim.Adam(self.model.parameters(), lr)
def update(self, state, y):
"""Update the weights of the network given a training sample. """
y_pred = self.model(torch.Tensor(state))
loss = self.criterion(y_pred, Variable(torch.Tensor(y)))
self.optimizer.zero_grad()
loss.backward()
self.optimizer.step()
def predict(self, state):
""" Compute Q values for all actions using the DQL. """
with torch.no_grad():
return self.model(torch.Tensor(state))
这是传递了参数的模型实例。
# Number of states = 4
n_state = env.observation_space.shape[0]
# Number of actions = 2
n_action = env.action_space.n
# Number of episodes
episodes = 150
# Number of hidden nodes in the DQN
n_hidden = 50
# Learning rate
lr = 0.001
simple_dqn = DQN(n_state, n_action, n_hidden, lr)
我尝试使用 torchinfo summary
from torchinfo import summary
simple_dqn = DQN(n_state, n_action, n_hidden, lr)
summary(simple_dqn, input_size=(4, 2, 50))
但我收到以下错误
NotImplementedError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/torchinfo/torchinfo.py in forward_pass(model, x, batch_dim, cache_forward_pass, device, mode, **kwargs)
286 if isinstance(x, (list, tuple)):
--> 287 _ = model.to(device)(*x, **kwargs)
288 elif isinstance(x, dict):
4 frames
/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1147
-> 1148 result = forward_call(*input, **kwargs)
1149 if _global_forward_hooks or self._forward_hooks:
/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _forward_unimplemented(self, *input)
200 """
--> 201 raise NotImplementedError(f"Module [{type(self).__name__}] is missing the required \"forward\" function")
202
NotImplementedError: Module [DQN] is missing the required "forward" function
The above exception was the direct cause of the following exception:
RuntimeError Traceback (most recent call last)
<ipython-input-24-ee921f7e5cb5> in <module>
1 from torchinfo import summary
2 simple_dqn = DQN(n_state, n_action, n_hidden, lr)
----> 3 summary(simple_dqn, input_size=(4, 2, 50))
/usr/local/lib/python3.7/dist-packages/torchinfo/torchinfo.py in summary(model, input_size, input_data, batch_dim, cache_forward_pass, col_names, col_width, depth, device, dtypes, mode, row_settings, verbose, **kwargs)
216 )
217 summary_list = forward_pass(
--> 218 model, x, batch_dim, cache_forward_pass, device, model_mode, **kwargs
219 )
220 formatting = FormattingOptions(depth, verbose, columns, col_width, rows)
/usr/local/lib/python3.7/dist-packages/torchinfo/torchinfo.py in forward_pass(model, x, batch_dim, cache_forward_pass, device, mode, **kwargs)
297 "Failed to run torchinfo. See above stack traces for more details. "
298 f"Executed layers up to: {executed_layers}"
--> 299 ) from e
300 finally:
301 if hooks:
RuntimeError: Failed to run torchinfo. See above stack traces for more details. Executed layers up to: []
任何帮助表示赞赏。
【问题讨论】：