小编Jor*_*Dik的帖子

我试图从强化学习算法中理解一些代码。为了做到这一点，我试图打印张量的值。

我做了一段简单的代码来说明我的意思。

import tensorflow as tf
from keras import backend as K

x = K.abs(-2.0)
tf.Print(x,[x], 'x')

目标是打印值“2”（-2 的绝对值）。但我只得到以下信息：

Using TensorFlow backend.

Process finished with exit code 0

什么都没有，我怎么能像 print('...') 语句那样打印值 '2' 呢？

我正在尝试运行以下代码：

import matplotlib.pylab as plt
import numpy as np
import torch
import torch.nn as nn

class LSTM(nn.Module):
    def __init__(self, input_shape, n_actions):
        super(LSTM, self).__init__()

        self.lstm = nn.LSTM(input_shape, 12)
        self.hidden2tag = nn.Linear(12, n_actions)

    def forward(self, x):
        out = self.lstm(x)
        out = self.hidden2tag(out)
        return out


state = [(1,2,3,4,5),(2,3,4,5,6),(3,4,5,6,7),(4,5,6,7,8),(5,6,7,8,9),(6,7,8,9,0)]

device = torch.device("cuda")
net = LSTM(5, 3).to(device)

state_v = torch.FloatTensor(state).to(device)

q_vals_v = net(state_v.view(1, state_v.shape[0], state_v.shape[1]))
_, action = int(torch.max(q_vals_v, dim=1).item())

并返回此错误：

import matplotlib.pylab as plt
import numpy as np
import torch
import torch.nn as nn …