1. When running as follows:

%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
    "" "Use the SVG format to display the drawing in Jupyter." "" "
    display.set_matplotlib_formats('svg')
    
def set_figsize(figsize=(3.5, 2.5)):  #@save
    "" "Sets the chart size of Matplotlib." ""
    use_svg_display()
    d2l.plt.rcParams['figure.figsize'] = figsize
#@save
def set_axes(axes, xlabel, ylabel, xlim, ylim, xscale, yscale, legend):
    "" "Sets the axis of Matplotlib." ""
    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):
    "" "Draw data points." "" "
    if legend is None:
        legend = []

    set_figsize(figsize)
    axes = axes if axes else d2l.plt.gca()

    # If `x` There is a shaft, output 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. The result is as follows:

3. View Anaconda-Prompt Related messages is as follows:

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/.

It is roughly found on the Internet because it is not actually turned off after each opening of Jupyter Notebook, so it takes a lot of memory. According to the Anaconda-Prompt Tips: The following code needs to be increased in advance:

import os
os.environ["KMP_DUPLICATE_LIB_OK"]  =  "TRUE"

4. The correct code is as follows:

%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
    "" "Use the SVG format to display the drawing in Jupyter." "" "
    display.set_matplotlib_formats('svg')
    
def set_figsize(figsize=(3.5, 2.5)):  #@save
    "" "Sets the chart size of Matplotlib." ""
    use_svg_display()
    d2l.plt.rcParams['figure.figsize'] = figsize
#@save
def set_axes(axes, xlabel, ylabel, xlim, ylim, xscale, yscale, legend):
    "" "Sets the axis of Matplotlib." ""
    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):
    "" "Draw data points." "" "
    if legend is None:
        legend = []

    set_figsize(figsize)
    axes = axes if axes else d2l.plt.gca()

    # If `x` There is a shaft, output 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. After the new increase is:

So, finally, it is successfully displayed.