我在Tensorflow v2.1.0中遇到一个错误: AttributeError: module 'tensorflow_core.summary' has no attribute 'FileWriter 我的代码是: import tensorflow as tf
a = tf.constant(5.0)
b = tf.constant(6.0)
c = a*b
sess = tf.compat.v1.Session()
File_Writer = tf.summary.FileWriter(r"C:\Users\Name\Desktop\Te
我在Python3上运行了版本1.8的TensorFlow。
我得到了以下例外:
import tensorflow as tf
Matrix_one = tf.constant([[2,3],[3,4]])
with tf.Session() as session:
print(session.run(tf.math.log(Matrix_one)))
AttributeError: module 'tensorflow.tools.api.generator.api.math' has no attribute 'log'
源代码
import tensorflow as tf
constant_a = tf.constant('Hello World!')
with tf.Session() as session:
print(session.run(constant_a))
问题日志
2022-04-14 16:26:07.486097: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Librar
我在conda环境中运行tf2.0,并希望在图中显示张量。
plt.imshow(tmp)
TypeError: Image data of dtype object cannot be converted to float
tmp.dtype
tf.float32
所以我试着把它转换成一个numpy数组,但是.
print(tmp.numpy())
AttributeError: 'Tensor' object has no attribute 'numpy'
tmp.eval()
ValueError: Cannot evaluate tensor us
我正在使用Tensorflow==2.0.0a0,希望运行以下脚本:
import tensorflow as tf
import tensorboard
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import tensorflow_probability as tfp
from tensorflow_model_optimization.sparsity import keras as sparsity
from tensorflow import keras
tfd = tfp.distr
我在R中的keras tensorflow会话中得到了可变的结果。我希望在训练我的模型时更加一致。我曾尝试使用use_session_with_seed(),但出现以下错误 2019-12-15 17:46:31.057595: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll
Error in py_get_attr_impl(x, name, silent) :
AttributeError: mod
我需要用少量的节点创建一个简单的神经网络模型,对其进行训练,然后评估得到的已经训练好的网络中的某些参数。 我需要重复几次(>100)。因此,我只想重新初始化权重,而不是每次都创建一个新模型。 以下是我的代码中有问题的部分: import tensorflow as tf
from tensorflow import keras
from keras import backend as K
def reinitLayers(model):
session = K.get_session()
for layer in model.layers:
我想在执行pip install keras之后执行import keras,但它显示如下所示的消息。我甚至不能调用keras库中的任何函数。有人知道这件事吗? import keras 错误: AttributeError: module 'tensorflow.compat.v2.__internal__' has no attribute 'register_clear_session_function'
我正在尝试使用ELMO嵌入在Keras中构建一个NER模型。所以我偶然发现了并开始实现。我收到了很多错误,其中一些错误如下:
import tensorflow as tf
import tensorflow_hub as hub
from keras import backend as K
sess = tf.Session()
K.set_session(sess)
elmo_model = hub.Module("https://tfhub.dev/google/elmo/2", trainable=True)
sess.run(tf.global_variable
摘自https://www.tensorflow.org/api_docs/python/tf/broadcast_to import tensorflow as tf
with tf.Session() as sess:
x = tf.constant([1, 2, 3])
y = tf.broadcast_to(x, [3, 3]).eval()
print(y) 当我运行这段代码时,我得到 Traceback (most recent call last):
File "tf_play.py", line 5, in <module&
发生此错误的原因是我使用了from astroNN.models import Galaxy10CNN并将Tensorflow降级到1.15.2以防止ImportError: cannot import name 'get_default_session',但请参阅与属性'Wrapper‘AttributeError: module 'keras.layers' has no attribute 'Wrapper'相关的新错误 请给我建议。谢谢!
当我尝试使用TensorFlow2.1导入tensorflow_addons时,我看到以下错误 > import tensorflow_addons as tfa
AttributeError: module 'tensorflow_core._api.v2.random' has no attribute 'Generator'
Anaconda3.7버전을다운받고tensorfow버전을다운받았습니다(그전에CUDA v.10,cuDNN도다운받았어요。)
그런데tensorflow설치과정에서에러가하나발생했네요。
ERROR: astroid 2.3.1 requires typed-ast<1.5,>=1.4.0; implementation_name == "cpython" and python_version < "3.8", which is not installed.
위문제가중요한가요?중요하다면어떻게해결할수있나요?
그리고jupyter no
你好,我的tensorflow脚本有问题。在过去的几年里,这个脚本运行得很顺利。现在我在重新安装tensorflow后得到错误:
AttributeError: module 'tensorflow' has no attribute 'placeholder'
我试过了:
import tensorflow as tf
使用
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior ()
替换,这反过来会带来错误:
AttributeError: module 'tensorflow' h
我正在关注:
我的导入看起来像这样:
import tensorflow as tf
import tensorflow.python.debug as tf_debug
我有最新的tensorflow:
tensorflow==1.8.0
但我得到以下错误:
File "/home/lpp/Desktop/minion-basecaller/mincall/train/_train.py", line 16, in <module>
import tensorflow.python.debug as tf_debug
AttributeError: m
import tensorflow.contrib.learn.python.learn as learn
home/michael/miniconda3/lib/python3.6/importlib/_bootstrap.py:219:
RuntimeWarning: compiletime version 3.5 of module
'tensorflow.python.framework.fast_tensor_util' does not match runtime
version 3.6
return f(*args, **kwds)
-----------
我已经安装了tensorflow版本r0.11。
在我的文件名cartpole.py中,我导入了tensorflow
import tensorflow as tf
并使用它:
tf.reset_default_graph()
试图在PyCharm中运行我的项目,我得到了以下错误:
in <module>
tf.reset_default_graph()
AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
如何纠正此错误?
我正在尝试运行以下代码行:
import tensorflow as tf
physical_devices = tf.config.list_physical_devices("GPU")
for i in range(len(physical_devices)):
tf.config.experimental.set_memory_growth(physical_devices[i], True)
我也在尝试运行这几行代码:
import tensorflow as tf
physical_devices = tf.test.gpu_device_name(