RuntimeError:无法在需要 grad 的张量上调用 numpy()
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【中文标题】RuntimeError:无法在需要 grad 的张量上调用 numpy()【英文标题】:RuntimeError: Can't call numpy() on Tensor that requires grad 【发布时间】:2021-11-11 07:56:35 【问题描述】:我开始学习机器学习,张量。一切正常,直到我开始显示图表。当我使用二次方程时,我输出它,使用log后,我开始输出错误。目前,我是 python 新手,很高兴得到任何帮助。
import torch
import numpy as np
import matplotlib.pyplot as plt
x = torch.tensor([[5., 10.],
[1., 2.]], requires_grad=True)
var_history = []
fn_history = []
alpha = 0.001
optimizer = torch.optim.SGD([x], lr=alpha)
def function_parabola(variable):
return (variable + 7).log().log().prod()
def make_gradient_step(function, variable):
function_result = function(variable)
function_result.backward()
optimizer.step()
optimizer.zero_grad()
for i in range(500):
var_history.append(x.data.numpy().copy())
fn_history.append(function_parabola(x).data.cpu().numpy().copy())
make_gradient_step(function_parabola, x)
print(x)
def show_contours(objective,
x_lims=[-10.0, 10.0],
y_lims=[-10.0, 10.0],
x_ticks=100,
y_ticks=100):
x_step = (x_lims[1] - x_lims[0]) / x_ticks
y_step = (y_lims[1] - y_lims[0]) / y_ticks
X, Y = np.mgrid[x_lims[0]:x_lims[1]:x_step, y_lims[0]:y_lims[1]:y_step]
res = []
for x_index in range(X.shape[0]):
res.append([])
for y_index in range(X.shape[1]):
x_val = X[x_index, y_index]
y_val = Y[x_index, y_index]
res[-1].append(objective(np.array([[x_val, y_val]]).T))
res = np.array(res)
plt.figure(figsize=(7,7))
plt.contour(X, Y, res, 100)
plt.xlabel('$x_1$')
plt.ylabel('$x_2$')
show_contours(function_parabola)
plt.scatter(np.array(var_history)[:,0], np.array(var_history)[:,1], s=10, c='r');
plt.show()
Traceback (most recent call last):
File "C:\Users\KP\PycharmProjects\pythonProject\HomeWork\ClassWork.py", line 25, in <module>
fn_history.append(function_parabola(x).data.cpu().detach().numpy().copy())
File "C:\Users\KP\PycharmProjects\pythonProject\HomeWork\ClassWork.py", line 13, in function_parabola
return np.prod(np.log(np.log(variable + 7)))
File "C:\Users\KP\PycharmProjects\pythonProject\venv\lib\site-packages\torch\_tensor.py", line 643, in __array__
return self.numpy()
RuntimeError: Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead.
【问题讨论】:
【参考方案1】:尝试将function_parabola
更改为:
def function_parabola(variable):
return np.prod(np.log(np.log(variable + 7)))
prod
和 log
函数在 numpy 模块中。
【讨论】:
非常感谢您的回答,它解决了我的问题,但又出现了一个新问题。RuntimeError: Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead.
@Альберт 导致错误的行是什么?
` 文件“C:\Users\KP\PycharmProjects\pythonProject\HomeWork\ClassWork.py”,第 25 行,在 fn_history.append(function_parabola(x).data.cpu().numpy().copy())
替换为fn_history.append(function_parabola(x).data.cpu().detach().numpy().copy())
很遗憾,这并没有解决问题。以上是关于RuntimeError:无法在需要 grad 的张量上调用 numpy()的主要内容,如果未能解决你的问题,请参考以下文章
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