Question

我试图使用tensorboard查看我的线性回归代码图，但它给出了许多我找不到解决方法的错误。另外，我还在使用Intel M5 CPU和Intel HD 5300 GPU的MacBook上运行代码。

程序运行正常，因此我重新检查了在创建和存储图形的部分中任何错字的代码。我什至重新安装了tensorflow（1.12.2），但弹出了相同的错误。另外，我在运行代码后就可以看到正在创建目录（在其中图形存储为“ logdir”）。

import tensorflow as tf

W = tf.Variable([.3], tf.float32)
b = tf.Variable([-.3], tf.float32)

x = tf.placeholder(tf.float32)
y = tf.placeholder(tf.float32)

lm = x * W + b

squared_delta = tf.square(lm - y)
cost = tf.reduce_sum(squared_delta)

optimize = tf.train.GradientDescentOptimizer(0.01)

train = optimize.minimize(cost)

init = tf.global_variables_initializer()

with tf.Session() as sess:
    sess.run(init)

    fw = tf.summary.FileWriter('./event_logs', sess.graph)

    for i in range(100):
        sess.run(train, {x: [1, 2, 3, 4], y: [0, -1, -2, -3]})
        #print(' cost : ', sess.run(cost, {x: [1, 2, 3, 4], y: [0, -1, -2, -3]}))

    print("Variables W and b: {} & {}".format(sess.run(W)[0], sess.run(b)[0]))

    test_data = 3
    print("Value for {} is {}".format(test_data, round((test_data * sess.run(W) + sess.run(b))[0])))

我希望看到一个简单的图形，但是...

Sarthaks-MacBook:PycharmProjects Xcalibre$ tensorboard --logdir="machine_learning/"
Traceback (most recent call last):
  File "/Users/Xcalibre/anaconda3/bin/tensorboard", line 7, in <module>
    from tensorboard.main import run_main
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/tensorboard/main.py", line 45, in <module>
    from tensorboard import default
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/tensorboard/default.py", line 34, in <module>
    import tensorflow as tf
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/tensorflow/__init__.py", line 24, in <module>
    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/tensorflow/python/__init__.py", line 47, in <module>
    import numpy as np
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/numpy/__init__.py", line 142, in <module>
    from . import core
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/numpy/core/__init__.py", line 59, in <module>
    from . import numeric
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/numpy/core/numeric.py", line 3093, in <module>
    from . import fromnumeric
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/numpy/core/fromnumeric.py", line 17, in <module>
    from . import _methods
  File "/Users/Xcalibre/anaconda3/lib/python3.7/site-packages/numpy/core/_methods.py", line 158, in <module>
    _NDARRAY_ARRAY_FUNCTION = mu.ndarray.__array_function__
AttributeError: type object 'numpy.ndarray' has no attribute '__array_function__'

Answer 1

运行：

tensorboard --logdir="event_logs/"

那是您存储张量板应该加载的文件的地方。看看代码中的这一行：

fw = tf.summary.FileWriter('./event_logs', sess.graph)

我想您的项目目录名为machine_learning，这就是您尝试运行的原因：

tensorboard --logdir="machine_learning/"

但这完全是错误的。

当我尝试在构建图的终端上运行时，如何修复弹出的张量板错误

1 个答案: