While trying to perform object detection on raspberry pi I need tflite-support.task library which is present in version greater than 0.4 but I am unable to upgrade it.
ERROR: Could not find a version that satisfies the requirement tflite-support==0.4 (from versions: 0.1.0a0.dev3, 0.1.0a0.dev4, 0.1.0a0.dev5, 0.1.0a0, 0.1.0a1) ERROR: No matching distribution found for tflite-support==0.4
I tried upgrading it using pip but it was of no help. I am currently having python3.9.2 and raspberry pi OS version 11.
Related
I'm currently trying to compile Darknet on the latest CUDA toolkit which is version 11.1. I have a GPU capable of running CUDA version 5 which is a GeForce 940M. However, while rebuilding darknet using the latest CUDA toolkit, it said
nvcc fatal : Unsupported GPU architecture 'compute_30'
compute_30 is for version 3, how can it fail while my GPU can run version 5
Is it possible that my code detected my intel graphics card instead of my Nvidia GPU? if that's the case, is it possible to change its detection?
Support for compute_30 has been removed for versions after CUDA 10.2. So if you are using nvcc make sure to use this flag to target the correct architecture in the build system for darknet
-gencode=arch=compute_50,code=sm_50
You may also need to use this one to avoid a warning of architectures are deprecated.
-Wno-deprecated-gpu-targets
I added the following:
makefiletemp = open('Makefile','r+')
list_of_lines = makefiletemp.readlines()
list_of_lines[15] = list_of_lines[14]
list_of_lines[16] = "ARCH= -gencode arch=compute_35,code=sm_35 \\\n"
makefiletemp = open('Makefile','w')
makefiletemp.writelines(list_of_lines)
makefiletemp.close()
right before the
#Compile Darknet
!make
command. That seemed to work!
Im trying to run a simulation (done in matlab 2020a I guess) but when running it , it gives the next error
Failed to find 'Power Electronics/Full-Bridge Converter' in library 'powerlib' referenced by Full-Bridge Converter'
But in my install it already has the toolboxes installed
SimElectronics Version 2.5 (R2014a)
SimMechanics Version 4.4 (R2014a)
SimPowerSystems Version 6.1 (R2014a)
Simscape Version 3.11 (R2014a)
I have been told these are necessary,but then what? the needed toolboxes are supposed to be installed. What more is needed?
PD
Some friend told me the simpowersystems were merged alongside the simelectronics, into SimscapePowerSystems, so guessing the model is writen in that, whats the lower version with comes with these toolbox?, 2017?, 2016?
I am following a server side swift tutorial and I am currently trying to dockerize my project.
when running the command docker run -v $PWD:/swift-project -w /swift-project server-build /swift-utils/tools-utils.sh build release to run the build image and Im getting the following error:
/swift-project: error: package at '/swift-project' is using Swift tools version 5.2.0 but the installed version is 5.0.0
If I wanted to keep the swift-tools-version at 5.2 in my Package.swift, how would I update from version 5.0 to 5.2?
When i try to install turicreate in my mac machine its showing the following error:
Collecting turicreate
Could not fetch URL https://pypi.python.org/simple/turicreate/: There was a problem confirming the ssl certificate: [SSL: TLSV1_ALERT_PROTOCOL_VERSION] tlsv1 alert protocol version (_ssl.c:661) - skipping
Could not find a version that satisfies the requirement turicreate (from versions: )
No matching distribution found for turicreate
please help me to resolve it?
Probably there is a Python version mismatch. At the moment TuriCreate supports only 2.7, 3.5 and 3.6.
Here is more on setting up Python environment for popular ML packages on Mac -
Machine Learning Compass
Ok,this is something am having problems with. I recently installed Matlab R2013a on a x86_64 Linux system running RHEL 5, attached to a Tesla S2050. I have never used the GPU functionality in Matlab itself (but have tried some of it using Jacket that lets one
program GPUs in Matlab).
The Tesla is working fine with all the drivers ,CUDA installed (Jacket v1.8.2 is running fine without complaints).
** Driver Version: 270.41.34 (the last version from 2011, supporting S2050) **
CUDA: v5.0.35
nvcc -V : Cuda compilation tools, release 5.0, V0.2.1221
But the Matlab r2013a complains:
gpuDevice errors:
Caused by:
The CUDA driver was found, but it is too old. The CUDA driver on your system supports CUDA version 4. The required CUDA version is 5 or greater.
Now, I understand the error that Matlab has problems with the Driver version. But, I have installed the latest CUDA toolkit and the latest driver that nVidia has to offer for the Tesla S2050 that I have.
Is there a later driver version available for this Tesla (i downloaded the latest driver & when trying to install, it simply complains that I don't have the compatible nVidia hardware).
How do I tell Matlab to consider the relevant CUDA ? (where to set PATH, CUDA_PATH etc., if any ? )
Are there any other checks i need to perform the evaluate the working of the attached Tesla ?
Thanks in advance for help.
You cannot use CUDA 5.0 with driver 270.41.34. CUDA 5 requires 304.54 or newer. This is not a MATLAB issue.
Newer drivers that support CUDA 5 will also support Tesla S2050.
For example this recent 319.17 driver lists Tesla S2050 on the supported products tab. Or use the 304.54 that comes with cuda 5.0.