I have installed tensorflow-cpu and it takes around 5 seconds to import.
Command used to install tensorflow:
pip install tensorflow-cpu
I have found other related articles on stackoverflow and github but none of them seems to help.
Note: I am using intel i7 8th gen with windows.
5 seconds is about the time the import needs on my system as well.
If you are interested in specifics, you can use
import cProfile
cProfile.run('import tensorflow')
to profile the call.
Related: import tensorflow is very slow?, What can cause the tensorflow import to be so slow?, How to speed up import tensorflow?(Older)
Related
import tensorflow.compat.v1 as tf
Error displayed in vscode
output in jupyter
Despite trying all the possible options, I am not able to fix this error.
I am trying to learn machine learning to create a simple sign language detection system. In my VSCode, the above image is displayed.
You need to follow the instructions mentioned in this link to install the tensorflow then open the VS code in the same virtual environment.
Please check these similar issues for your reference.
I am a university professor trying to learn deep learning for a possible class in the future. I have been using google colab with GPU support for the past couple of months. Just recently, the GPU device is not found. But, I am doing everything that I have done in the past. I can't imagine that I have done anything wrong because I am just working through tutorials from books and the tensorflow 2.0 tutorials site.
tensorflow 2 on Colab GPU was broken recently due to an upgrade from CUDA 10.0 to CUDA 10.1. As of this afternoon, the issue should be resolved for the tensorflow builds bundled with Colab. That is, if you run the following magic command:
%tensorflow_version 2.x
then import tensorflow will import a working, GPU-compatible tensorflow 2.0 version.
Note, however, if you attempt to install a version of tensorflow using pip install tensorflow-gpu or similar, the result may not work in Colab due to system incompatibilities.
See https://colab.research.google.com/notebooks/tensorflow_version.ipynb for more information.
I have just installed the stable version of TensorFlow 2.0 (released on October 1st 2019) in PyCharm.
The problem is that the keras package is unavailable.
The actual error is :
"cannot import name 'keras' from tensorflow"
I have installed via pip install tensorflow==2.0.0 the CPU version, and then uninstalled the CPU version and installed the GPU version , via pip install tensorflow-gpu==2.0.0.
Neither of the above worked versions of TensorFlow were working properly(could not import keras or other packages via from tensorflow.package_X import Y).
If I revert TensorFlow to version 2.0.0.b1, keras is available as a package (PyCharm recognises it) and everything runs smoothly.
Is there a way to solve this problem? Am I making a mistake in the installation process?
UPDATE --- Importing from the Python Console works and allows the imports without any error.
For PyCharm Users
For those who use PyCharm. Install future (EAP) release 2019.3 EAP build 193.3793.14 from here. With that, you will be able to use autocomplete for the current stable release of TensorFlow (i.e. 2.0). I have tried it and it works :).
For other IDEs
For users with other IDEs, this will be resolved only after the stable version is released, which is anyways the case now. But this might take some more time for a fix. See the comment here. I assume it will be wise to wait and keep using version 2.0.0.b1. On the other hand avoid imports from tensorflow_core if you do not want to refactor your code in the future.
Note: for autocomplete to work use import statement as below
import tensorflow.keras as tk
# this does not work for autocomplete
# from tensorflow import keras as tk
The autocomplete works for TensorFlow 2.0.0 on CPU version, but the autocomplete does not work for the GPU version.
SOLVED --- See the answers to this problem below.
SOLUTION 1 (best solution)
Is the accepted answer provided above. It works on EAP version, I tested it on several machines with Windows.
SOLUTION 2
Although PyCharm does not recognise the modules, running the .py file works. I still do not know if this is a problem of TensorFlow or PyCharm, but this is the solution that I have found, many people have run into this problem.
SOLUTION 3
Import the modules from tensorflow_core instead of tensorflow
Example: from tensorflow_core.python.keras.preprocessing.image import ImageDataGenerator
However, as mentioned by #Nagabhushan S N in the comment below and above in the accepted answer:
On the other hand avoid imports from tensorflow_core if you do not
want to refactor your code in the future.
I have installed the Tensorflow r1.14 and want to use TF-TRT. However, the following error occurs:
"ModuleNotFoundError: No module named 'tensorflow.contrib.tensorrt'"
when running the sample code. The same error occurs with Tensorflow r1.13. So my question is do I need to install the tensorflow.contrib.tensorrt library separately? If yes, how?
Additionally, I can run the sample code of the TensorRT, e.g. sampleINT8, successfully. Click here to see my successful sample code run.
This leads me to believe that TensorRT is installed properly. However, the TF-TRT still doesn't work.
Any help would be greatly appreciated!
In TF 1.14, TF-TRT was moved to the core from contrib.
You need to import it like this: from tensorflow.python.compiler.tensorrt import > trt_convert as trt
https://github.com/tensorflow/tensorrt/blob/master/tftrt/examples/image-classification/image_classification.py#L22
This is the correct answer for Linux.
However, if you're using Windows: the TensorRT Python API (and therefore TF-TRT) is not supported for Windows at the moment, so the TensorFlow python packages aren't built with TensorRT.
In TF 1.14, TF-TRT was moved to the core from contrib.
You need to import it like this:
from tensorflow.python.compiler.tensorrt import trt_convert as trt
https://github.com/tensorflow/tensorrt/blob/master/tftrt/examples/image-classification/image_classification.py#L22
In order to be able to import tensorflow.contrib.tensorrt you need to have tensorflow-gpu version >= 1.7 installed on your system. Maybe you could try installing the tensorflow-gpu library with a:
pip install tensorflow-gpu
Check out the Windows section of the GPU documentation as well. Also, I would try updating your tensorflow version with a:
pip install --upgrade tensorflow
to ensure you're up to date there as well. Check out this section of the TensorFlow documentation for additional support.
Hopefully that helps!
2 possibilities
Have you installed tensorflow-gpu instead of tensorflow?
From your screenshot it looks like you're using Windows. I had the same problem. There seems no tensorrt module under contrib in TF windows distribution however linux has it (I tried 1.13.1).
I am trying to test NVIDIA's Style GAN and am encountering an error when trying to run the pretrained_example.py file.
I get an import error from the line from tensorflow.python.ops import nccl_ops
ImportError: cannot import name 'nccl_ops'
I think I installed all the prerequisites properly and am using python 3.6. It could be a mac tensorflow issue possibly because it doesn't mention OSX on the github project. Any help would be appreciated. It might be a matter of installing a different version of tensorflow or something else, I'm not sure.
I updated tensorflow and it solved this issue