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This repository has been archived by the owner on Nov 17, 2023. It is now read-only.
For bugs or installation issues, please provide the following information.
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The text was updated successfully, but these errors were encountered:
I also noticed that, i think i have fixed the cifar10 one, please check this pull request: #5064
Am working on the mnist one, but am stuck with a mxnet error that i am unable to fix atm. So, i have code that i think removes some errors but it does not work yet. Should i make a pull request or post to another branch or? check here: repo matt32106:R-examples branch
train_model.fit(args, net, get_iterator(data_shape))
Arguments batch_size data_dir kv_store lr_factor momentum network num_examples num_round
"128" "data/mnist/" "local" "0.05" "0.9" "mlp" "60000" "10"
[11:34:56] src/io/iter_mnist.cc:91: MNISTIter: load 60000 images, shuffle=1, shape=(128,784)
[11:34:56] src/io/iter_mnist.cc:91: MNISTIter: load 10000 images, shuffle=1, shape=(128,784)
Start training with 1 devices Error in mx.nd.internal.dispatch.Ops(.Generic, e1, e2) :
ndarray.cc:500: MXNDArray binary operations only support NDArray and numeric values as operands
Called from: mx.nd.internal.dispatch.Ops(.Generic, e1, e2)
For bugs or installation issues, please provide the following information.
The more information you provide, the more likely people will be able to help you.
Environment info
Operating System:
Compiler:
Package used (Python/R/Scala/Julia):
MXNet version:
Or if installed from source:
MXNet commit hash (
git rev-parse HEAD
):If you are using python package, please provide
Python version and distribution:
If you are using R package, please provide
R
sessionInfo()
:Error Message:
Please paste the full error message, including stack trace.
Minimum reproducible example
if you are using your own code, please provide a short script that reproduces the error.
Steps to reproduce
or if you are running standard examples, please provide the commands you have run that lead to the error.
What have you tried to solve it?
The text was updated successfully, but these errors were encountered: