I am using the code below
profile = ProfileReport(df, title='Pandas Profiling Report', html={'style':{'full_width':True}})
to run a profile report but getting this error
"TypeError: describe_boolean_1d() got an unexpected keyword argument 'title'"
And when I remove the title, I get this error
"TypeError: describe_boolean_1d() got an unexpected keyword argument 'html'"
I got the same error
I run this code in Google Colab:
profile = ProfileReport(df, title="Pandas Profiling Report")
Then, got the same error. Because, somehow, in Colab, below code to install pandas_profilling didn't work well:
pip install pandas-profiling[notebook]
Installation by it makes the error.
Solution
Instead, I use an alternative:
pip install https://github.com/pandas-profiling/pandas-profiling/archive/master.zip
Then, restart the kernel and done. Errors gone.
I have conda on my machine, so first tried installing pandas-profiling with conda, but had the same error as you.
I have removed it: conda remove pandas-profiling
and then reinstall it with pip: pip install pandas-profiling[notebook,html]
And it worked fine.
Note: The visualization doesn't work on EDGE browser, Chrome is ok.
Best,
Victor
3 steps only:
pip install -U https://github.com/pandas-profiling/pandas-profiling/archive/master.zip
pip install -U pandas-profiling
import pandas_profiling as pp
from pandas_profiling import ProfileReport
Source: Kaggle notebook
Attribute error:- TensorFlow has no attribute "Session".
How should I solve this error?
Please look at the image in the link
Tensorflow error
Once I had similar problems after I had installed tensorflow-estimator. I reinstalled tensorflow and everything went back to normal again.
pip install --force-reinstall tensorflow
or
pip install --force-reinstall tensorflow-gpu
I am trying to train my own custom object detector using Tensorflow Object-Detection-API
I installed the tensorflow using "pip install tensorflow" in my google compute engine. Then I followed all the instructions on this site: https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html
When I try to use train.py I am getting this error message:
Traceback (most recent call last):
File "train.py", line 49, in
from object_detection.builders import dataset_builder
File "/usr/local/lib/python3.6/dist-packages/object_detection-0.1->py3.6.egg/object_detection/builders/dataset_builder.py", line 27, in
from object_detection.data_decoders import tf_example_decoder
File "/usr/local/lib/python3.6/dist-packages/object_detection-0.1-py3.6.egg/object_detection/data_decoders/tf_example_decoder.py", line 27, in
slim_example_decoder = tf.contrib.slim.tfexample_decoder
AttributeError: module 'tensorflow' has no attribute 'contrib'
Also I am getting different results when I try to learn version of tensorflow.
python3 -c 'import tensorflow as tf; print(tf.version)' : 2.0.0-dev20190422
and when I use
pip3 show tensorflow:
Name: tensorflow
Version: 1.13.1
Summary: TensorFlow is an open source machine learning framework for everyone.
Home-page: https://www.tensorflow.org/
Author: Google Inc.
Author-email: opensource#google.com
License: Apache 2.0
Location: /usr/local/lib/python3.6/dist-packages
Requires: gast, astor, absl-py, tensorflow-estimator, keras-preprocessing, grpcio, six, keras-applications, wheel, numpy, tensorboard, protobuf, termcolor
Required-by:
sudo python3 train.py --logtostderr --train_dir=training/ --
pipeline_config_path=training/ssd_inception_v2_coco.config
What should I do to solve this problem? I couldn't find anything about this error message except this: tensorflow 'module' object has no attribute 'contrib'
tf.contrib has moved out of TF starting TF 2.0 alpha.
Take a look at these tf 2.0 release notes https://github.com/tensorflow/tensorflow/releases/tag/v2.0.0-alpha0
You can upgrade your TF 1.x code to TF 2.x using the tf_upgrade_v2 script
https://www.tensorflow.org/alpha/guide/upgrade
This issue might be helpful for you, it explains how to achieve TPUStrategy, a popular functionality of tf.contrib in TF<2.0.
So, in TF 1.X you could do the following:
resolver = tf.contrib.cluster_resolver.TPUClusterResolver('grpc://' + os.environ['COLAB_TPU_ADDR'])
tf.contrib.distribute.initialize_tpu_system(resolver)
strategy = tf.contrib.distribute.TPUStrategy(resolver)
And in TF>2.0, where tf.contrib is deprecated, you achieve the same by:
tf.config.experimental_connect_to_host('grpc://' + os.environ['COLAB_TPU_ADDR'])
resolver = tf.distribute.cluster_resolver.TPUClusterResolver('grpc://' + os.environ['COLAB_TPU_ADDR'])
tf.tpu.experimental.initialize_tpu_system(resolver)
strategy = tf.distribute.experimental.TPUStrategy(resolver)
One easy way is you can pass your code written in TensorFlow 1.x to the below code to automatically upgrade it to TensorFlow 2.x.
$tf_upgrade_v2 \
--intree my_project/ \
--outtree my_project_v2/ \
--reportfile report.txt
The above code will replace all the commands which are deprecated in 2.x with the onces that are actually working in 2.x. And then you can run your code in TensorFlow 2.x.
In case if it throws an error and is unable to convert the complete code and then don't panic. Please open the "report.txt" file that is generated by the above code. In this file, you will find commands that are deprecated and their alternative commands that can be used in TensorFlow 2.x.
Taadaa, just replace the commands that are throwing errors with the new ones.
Example:
If the command in TensorFlow 1.x is:
tf.contrib
Then the same command in Tensorflow 2.x is:
tf.compat.v1.estimator
In the above example replace "tf.contrib" with "tf.compat.v1.estimator" and that should solve the problem.
I used google colab to run my models and everything was perfect untill i used inline tesorboard. With tensorboard inline, I had the same issue of "Module 'tensorflow' has no attribute 'contrib'".
It was able to run training when rebuild and reinstall the model using setup.py(research folder) after initialising tensorboard.
I used tensorflow 1.8 to train my model and there is no problem for now. Tensorflow 2.0 alpha is not suitable with object detection API
I'm using Google Colab as well. A comment suggested to put
%tensorflow_version 1.x
in the first (code) cell, and it worked!
If you want to use tf.contrib, you need to now copy and paste the source code from github into your script/notebook. It's annoying and doesn't always work. But that's the only workaround I've found. For example, if you wanted to use tf.contrib.opt.AdamWOptimizer, you have to copy and paste from here. https://github.com/tensorflow/tensorflow/blob/590d6eef7e91a6a7392c8ffffb7b58f2e0c8bc6b/tensorflow/contrib/opt/python/training/weight_decay_optimizers.py#L32
I face the same error and solve it by install python version 3.7 then i can install tensorflow 1.15 and it work.
I used tensorflow==2.9 but tensorflow-probability==0.6.0 so I met this error too. tensorflow-probability==0.6.0 seems to be compatible with tf 1
this is solution: pip install tensorflow_probability==0.12.2
This version of TensorFlow Probability requires TensorFlow version >= 2.3
if there are still some errors pip install tensorflow_probability==0.17.0
For me it worked using the latest release of tensorflow: pip install tensorflow==2.2.0
I was running tensorFlow in CPU version and with native pip in Windows. While running TensorFlow for the check "Hello TensorFlow" is output with some warnings.
on Running Premade_estimator I got errors:
How can I fix this?
Assuming you have a recent version of Tensorflow, it seems that it is not imported correctly.
I faced this error when I was running a script and in the same folder I have downloaded tensorflow, so that when importing "tensorflow" it imports the tensorflow folder where I was located instead of the tensorflow library installed.
I am new to tensorflow and tried to install into Anaconda. I followed the instruction to the dot from tensorflow.org. I encountered no problem encountered but in python shell when i perform import tensorflow as tf, I got this error message, "ModuleNotFoundError: No module named 'tensorflow'".
Please advise what to do to install tensorflow.
I already followed the previous post on conda create -n tensorflow python=3.6 but to no avail.