jupyter notebook内核挂掉了，需要重启
1.在运行如下代码时：
%matplotlib inline
import numpy as np
from IPython import display
from d2l import torch as d2l
def f(x):
return 3*x**2-4*x
def numerical_lim(f, x, h):
return (f(x + h) - f(x)) / h
h = 0.1
for i in range(5):
print(f'h={h:.5f}, numerical limit={numerical_lim(f, 1, h):.5f}')
h *= 0.1
def use_svg_display(): #@save
"""使用svg格式在Jupyter中显示绘图。"""
display.set_matplotlib_formats('svg')
def set_figsize(figsize=(3.5, 2.5)): #@save
"""设置matplotlib的图表大小。"""
use_svg_display()
d2l.plt.rcParams['figure.figsize'] = figsize
#@save
def set_axes(axes, xlabel, ylabel, xlim, ylim, xscale, yscale, legend):
"""设置matplotlib的轴。"""
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
axes.set_xscale(xscale)
axes.set_yscale(yscale)
axes.set_xlim(xlim)
axes.set_ylim(ylim)
if legend:
axes.legend(legend)
axes.grid()
#@save
def plot(X, Y=None, xlabel=None, ylabel=None, legend=None, xlim=None,
ylim=None, xscale='linear', yscale='linear',
fmts=('-', 'm--', 'g-.', 'r:'), figsize=(3.5, 2.5), axes=None):
"""绘制数据点。"""
if legend is None:
legend = []
set_figsize(figsize)
axes = axes if axes else d2l.plt.gca()
# 如果 `X` 有一个轴，输出True
def has_one_axis(X):
return (hasattr(X, "ndim") and X.ndim == 1 or
isinstance(X, list) and not hasattr(X[0], "__len__"))
if has_one_axis(X):
X = [X]
if Y is None:
X, Y = [[]] * len(X), X
elif has_one_axis(Y):
Y = [Y]
if len(X) != len(Y):
X = X * len(Y)
axes.cla()
for x, y, fmt in zip(X, Y, fmts):
if len(x):
axes.plot(x, y, fmt)
else:
axes.plot(y, fmt)
set_axes(axes, xlabel, ylabel, xlim, ylim, xscale, yscale, legend)
x = np.arange(0, 3, 0.1)
plot(x, [f(x), 2 * x - 3], 'x', 'f(x)', legend=['f(x)', 'Tangent line (x=1)'])
2.显示结果如下：
3.查看anaconda-prompt相关消息如下：
OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized.
OMP: Hint This means that multiple copies of the OpenMP runtime have been linked into the program. That is dangerous, since it can degrade performance or cause incorrect results. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, e.g. by avoiding static linking of the OpenMP runtime in any library. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results. For more information, please see http://www.intel.com/software/products/support/.
网上大致查了下，是由于在每次打开jupyter notebook后没有实际上关掉，所以占据了大量的内存，根据anaconda-prompt的提示：需提前增加如下代码：
import os
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
4.正确代码如下：
%matplotlib inline
import numpy as np
from IPython import display
from d2l import torch as d2l
def f(x):
return 3*x**2-4*x
def numerical_lim(f, x, h):
return (f(x + h) - f(x)) / h
h = 0.1
for i in range(5):
print(f'h={h:.5f}, numerical limit={numerical_lim(f, 1, h):.5f}')
h *= 0.1
def use_svg_display(): #@save
"""使用svg格式在Jupyter中显示绘图。"""
display.set_matplotlib_formats('svg')
def set_figsize(figsize=(3.5, 2.5)): #@save
"""设置matplotlib的图表大小。"""
use_svg_display()
d2l.plt.rcParams['figure.figsize'] = figsize
#@save
def set_axes(axes, xlabel, ylabel, xlim, ylim, xscale, yscale, legend):
"""设置matplotlib的轴。"""
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
axes.set_xscale(xscale)
axes.set_yscale(yscale)
axes.set_xlim(xlim)
axes.set_ylim(ylim)
if legend:
axes.legend(legend)
axes.grid()
#@save
def plot(X, Y=None, xlabel=None, ylabel=None, legend=None, xlim=None,
ylim=None, xscale='linear', yscale='linear',
fmts=('-', 'm--', 'g-.', 'r:'), figsize=(3.5, 2.5), axes=None):
"""绘制数据点。"""
if legend is None:
legend = []
set_figsize(figsize)
axes = axes if axes else d2l.plt.gca()
# 如果 `X` 有一个轴，输出True
def has_one_axis(X):
return (hasattr(X, "ndim") and X.ndim == 1 or
isinstance(X, list) and not hasattr(X[0], "__len__"))
if has_one_axis(X):
X = [X]
if Y is None:
X, Y = [[]] * len(X), X
elif has_one_axis(Y):
Y = [Y]
if len(X) != len(Y):
X = X * len(Y)
axes.cla()
for x, y, fmt in zip(X, Y, fmts):
if len(x):
axes.plot(x, y, fmt)
else:
axes.plot(y, fmt)
set_axes(axes, xlabel, ylabel, xlim, ylim, xscale, yscale, legend)
x = np.arange(0, 3, 0.1)
import os
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
plot(x, [f(x), 2 * x - 3], 'x', 'f(x)', legend=['f(x)', 'Tangent line (x=1)'])
4.新增后如下：
所以，最后就成功显示上图。