I have a flask application that I would like to run it on an EC2 instance and TensorFlow is needed cause it is image classification. However, after the necessary updates and upgrades, I try to install TensorFlow but after the progress bar completes, I don't see the successfully installed tensorflow==2.7.0. Images are attached, is there any reason for why it is not letting me install TensorFlow, or does the instance have limitations that won't let me install it. Please help and thanks in advance.
installing the TensorFlow on the EC2 instance
Increase the storage on the hard disk (30 GB on my case_
pip install tensorflow-cpu
link
I also faced the same error and apparently the storage was not the reason. I tried using large instance with large memory and I was able to install tensorflow in the anaconda environment successfully.
Related
I am using Google Colab and am experiencing an issue when installing packages with python/pip following this TensorFlow guide. It loads forever then I get a timeout error when running the TensorFlow 2 setup script.
So then I tried to open their own notebook, which results in the same error. It just loads forever then throws a timeout. It is this line that loads forever: python -m pip install .
I am new to TensorFlow and Google Colab so I'm not sure how to debug this properly. How do I install the TensorFlow Object Detection API on Google Colab?
This is apparently a known issue as seen here.
I have just started using the Amazon Deeplens device. I got the demo face detection application working. I have a custom trained tensorflow model (.pb) that I want to deploy on Deeplens. I followed an online guide to create a new project with lambda (python 3.7) and uploaded and imported my model from a s3 bucket. Now, my issue is that I need to install tensorflow on the device for python 3. I tried installing various versions and was even successful it once but I still get an error in the logs saying Tensorflow Module not found
I have a couple of questions regarding this:
My Lambda has python 3.7 execution environment. Is this correct or should I match the one on deeplens (3.5)?
Can I upgrade python on Deeplens to the latest version?
If not, what is the Tensorflow version that is supported for python 3.5 on Deeplens and what is the correct command to install it: pip or pip3?
Any help or insight is appreciated.
I'm trying to write to GCS bucket via Beam (and TF Transform). But I keep getting the following error:
ValueError: Unable to get the Filesystem for path [...]
The answer here and some other sources suggest that I need to pip install aache-beam[gcp] to get a different variant of Apache Beam that works with GCP.
So, I tried changing the setup.py of my training package as:
REQUIRED_PACKAGES = ['apache_beam[gcp]==2.14.0', 'tensorflow-ranking', 'tensorflow_transform==0.14.0']
which didn't help. I also tried adding the following to the beginning of my code:
subprocess.check_call('pip uninstall apache-beam'.split())
subprocess.check_call('pip install apache-beam[gcp]'.split())
which didn't work either.
The logs of the failed GCP job is here. The traceback and the error message appear on row 276.
I should mention that running the same code using Beam's DirectRunner and writing the outputs to local disk runs fine. But I'm now trying to switch to DataflowRunner.
Thanks.
It turns out that you need to uninstall google-cloud-dataflow in addition to installing apache-beam with the gcp option. I guess this happens because google-cloud-dataflow is installed on GCP instances by default. Not sure if the same would be true on other platforms like AWS. But anyway, here are the commands I used:
pip uninstall -y google-cloud-dataflow
pip install apache-beam[gcp]
I noticed this in the very first cell of [this notebook] (https://github.com/GoogleCloudPlatform/training-data-analyst/blob/master/courses/machine_learning/deepdive/10_recommend/wals_tft.ipynb).
I'm trying to install the package sodapy using Pip on a fresh instance of Google Datalab but I'm receiving the error 'No space left on device.' I created this instance with over 100 GB of disk space so I'm a bit confused why I would be getting this error and I've tried deleting instances and creating new ones with no luck.
I'm using the command
!pip install sodapy
as is explained in the documentation- https://cloud.google.com/datalab/docs/how-to/adding-libraries
Thanks in advance for your help!
You may have run into a bug where the Disk was not being attached: https://github.com/googledatalab/datalab/issues/1898
(If that is the case, reseting the VM once should fix it and you should update to gcloud version 186.0.0 or later.)
Try adding the --user flag to the pip install command. This switches to using your persistent disk, which is the 100GB disk, instead of your VM's boot disk for the installed package.
I'm using an Ipython2.7 notebook to run some code. Recently discovered that all my data was corrupted and I need to do it all again (meaning I am very very behind schedule) I figured I could half the time required if I could run it on a second computer. So I've gone into a uni computer cluster where the computers have python 2.7 installed. I can open the notebook, but it won't run as the first line is
import mlpy.wavelet
And it gives me an import error. I've tried downloading and installing it from sourceforge, but it seems to install it to the a Q drive, which I don't have access to. I am completely lost on what to do here, I can't even remember how I first installed it on my laptop. I have a feeling I pip installed it but I have no clue how to do this on a uni comp.
Any rapid responses would be greatly appreciated
You can use pip to install packages in your user's home directory.
Run pip install --user mply to install mply and your other dependencies.
See this answer for reference.