I’m using a virtual machine on Windows 10 with this config: Memory 7.8 GiB Processor Intel® Core™ i5-6600K CPU @ 3.50GHz × 3 Graphics llvmpipe (LLVM 11.0.0, 256 bits) Disk Capcity 80.5 GB OS Ubuntu 20.10 64 Bit Virtualization Oracle I installed docker for Ubuntu as described in the official documentation. I pulled the docker ..
I have a docker image based on pytorch/pytorch:1.6.0-cuda10.1-cudnn7-devel image. It builds successfully on macOS Catalina but it fails to build on macOS Big Sur. It fails when running import encoding in python script (see stack trace below). Seems like the issue is related to python deep learning libraries that are wrapping c++ implementation. I don’t ..
Has anyone encountered issues with docker 3.2.2 on macOS Big Sur and knows how to fix them? Symptoms: images that build and run successfully on Catalina refuse to build on Big Sur with various errors. Seems like the issue is related to python deep learning libraries that are wrapping c++ implementation. For example, I had ..
I am using transformers pipeline to perform sentiment analysis on sample texts from 6 different languages. I tested the code in my local Jupyterhub and it worked fine. But when I wrap it in a flask application and create a docker image out of it, the execution is hanging at the pipeline inference line and ..
I’m trying to install some packages in a docker container, and there is a problem when installing from a requirements.txt file. This line: RUN python3.8 -m pip install -r requirements.txt fails with the error: … Collecting torch Downloading torch-1.8.0-cp38-cp38-manylinux1_x86_64.whl (735.5 MB) ERROR: THESE PACKAGES DO NOT MATCH THE HASHES FROM THE REQUIREMENTS FILE. If you ..
Recently, I have started working on using docker images. I want to deploy PyTorch based text classification model which requires GPU to run on. When the docker image is called upon, then it’s not able to detect GPU in the VM. Hence, my code is failing by throwing no Cuda device found error. This is ..
i am trying to create a docker image to make it run as a server for serving a model in pytorch i converted the .pt model file to .MAR file in my local machine and i copied the .MAR file inside the docker image i created a dockerfile FROM ubuntu:18.04 ENV TZ=Asia/Shanghai ENV DEBIAN_FRONTEND noninteractive ..
I have an inference code perfectely working (remove background from image) I want to deploy this to AWS to get API calls? My question is how can I deploy this code to AWS, I have a top-level class that handles everything. I have never used AWS before, what should I? P.S. – I am not ..
I tried the 4 commands those I got from this post: https://community.arm.com/developer/tools-software/tools/b/tools-software-ides-blog/posts/aarch64-docker-images-for-pytorch-and-tensorflow The last command does not complete and there seems to be an endless loop. git clone https://github.com/ARM-software/Tool-Solutions.git cd Tool-Solutions/docker/pytorch-aarch64 export DOCKER_BUILDKIT=1 ./build.sh –build-type full –tf_version 2 –bazel_memory_limit 30000 –jobs 16 This command never completes. How do I install pytorch on ARM? Source: Docker ..
I have two servers, with environments one NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 and another NVIDIA-SMI 455.45.01 Driver Version: 455.45.01 CUDA Version: 11.1 I installed docker, nvidia-docker and deepo (GPU version). Now let’s run a docker container shell: docker run -it –gpus all deepo bash. In the shell, nvidia-smi returns the correct info, ..