To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.

Question

2024-03-29 09:59:11.164507: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.

import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
TF_ENABLE_ONEDNN_OPTS = 0

boston_housing = tf.keras.datasets.boston_housing
(train_x, train_y), (_, _) = boston_housing.load_data(test_split = 0)

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

titles = ["CRIN", "ZN", "INDUS", "CHAS", "NOX", "RM", "AGE", "DIS", "RAD", "TAX", "PTRATIO", "B-1000", "LSTAT", "MEDV"]
plt.figure(figsize=(12, 12))

for i in range(13):
    plt.subplot(4, 4, (i + 1))
    plt.scatter(train_x[:, i], train_y)
    plt.xlabel(titles[i])
    plt.ylabel("Price($1000's)")
    plt.title(str(i + 1) + "." + titles[i] + " - Price")

plt.tight_layout()
plt.suptitle("各个属性与房价的关系", x = 0.5, y = 1.02, fontsize = 20)
plt.show

运行波士顿房价绘图 出现错误

Answer 1

【以下回答由 GPT 生成】

解决方案:

这个错误提示是由于在TensorFlow中启用了oneDNN操作引起的。要解决这个问题，可以根据错误提示设置环境变量 TF_ENABLE_ONEDNN_OPTS=0。

以下是具体的解决步骤：

1. 在代码中添加以下行，设置环境变量 TF_ENABLE_ONEDNN_OPTS=0：

import os
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'

1. 将上述代码放在导入TensorFlow库之前，确保在使用TensorFlow之前设置了该环境变量。

修改后的完整代码示例如下：

import os
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'

import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf

boston_housing = tf.keras.datasets.boston_housing
(train_x, train_y), (_, _) = boston_housing.load_data(test_split = 0)

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

titles = ["CRIN", "ZN", "INDUS", "CHAS", "NOX", "RM", "AGE", "DIS", "RAD", "TAX",
          "PTRATIO", "B-1000", "LSTAT", "MEDV"]
plt.figure(figsize=(12, 12))

for i in range(13):
    plt.subplot(4, 4, (i + 1))
    plt.scatter(train_x[:, i], train_y)
    plt.xlabel(titles[i])
    plt.ylabel("Price($1000's)")
    plt.title(str(i + 1) + '.' + titles[i] + ' - Price')

plt.tight_layout()
plt.suptitle("Relationship between various attributes and house prices", x=0.5, y=1.02, fontsize=20)
plt.show()

通过上述步骤设置环境变量，您应该能够解决在运行Boston房价图表时出现的错误。如果问题仍然存在，请让我知道。

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