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Questions tagged [mxnet]

Apache MXNet is a fast, scalable, open source deep learning framework that supports Python, R, Scala, C++, Julia, Go, and Javascript. MXNet can run on multiple CPUs and multiple GPUs distributed across multiple hosts, with almost linear scalability.

Apache MXNet: Flexible and Efficient Library for Deep Learning

For more details see http://mxnet.io/

Flexible

Supports both imperative and symbolic programming

Portable

Runs on CPUs or GPUs, on clusters, servers, desktops, or mobile phones

Multiple Languages

Supports over 7 programming languages, including C++, Python, R, Scala, Julia, Matlab, Javascript and Perl.

Auto-Differentiation

Calculates the gradient automatically for training a model

Distributed on Cloud

Supports distributed training on multiple CPU/GPU machines, including AWS, GCE, Azure, and Yarn clusters

Performance

Optimized C++ backend engine parallelizes both I/O and computation

701 questions
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Limit MXNet GPU Memory Usage

Is there a way that we can limit the Memory Allocation used by this Model to allow for Concurrent Models to Run? I'm currently using InsightFace which is built on MXNet. After loading the first model the GPU Mem stats reflect: utilization.gpu 74…
njho
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How is log_softmax() implemented to compute its value (and gradient) with better speed and numerical stability?

Both MXNet and PyTorch provide special implementation for computing log(softmax()), which is faster and numerically more stable. However, I cannot find the actual Python implementation for this function, log_softmax(), in either package. Can anyone…
herrlich10
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Mxnet datatype is float64, but keeps saying that it's float32

I'm a pytorch and tensorflow user. I came across Mxnet in order to use AWS sagemaker's elastic inference. Mxnet gluon dataset api seems to be very similar to pytorch's dataset. class CustomDataset(mxnet.gluon.data.Dataset): def __init__(self): …
Piljae Chae
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Reduce the size of fasterRCNN array output, using Gluon, python

I'm using a faster rcnn model to run some object detection. The wrapper I'm using is gluon and the code is below: net = model_zoo.get_model('faster_rcnn_resnet50_v1b_coco', pretrained=True) im_fname =…
Dave
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SageMaker Image Classification: How to get an ordered list of classes corresponding to the output of the model

I'm training a model for multi-class image classification on AWS sagemaker using a custom dataset. The dataset has around 50 classes. I'm following this notebook: Image classification transfer learning demo According to my understanding, the final…
LucyDrops
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Wrong gpu order in mxnet and tensorflow

My desktop has 2 gpu installed: 1080 and 1080Ti nvidia-smi shows that gpu-0 is 1080 and gpu-1 is 1080Ti +-----------------------------------------------------------------------------+ | NVIDIA-SMI 410.79 Driver Version: 410.79 CUDA…
Ivan Kovtun
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Installing MXNet framework. on Raspberry Pi - SciPy hanging

I'm attempting to setup AWS Greengrass with mxnet for Machine Learning on a Raspberry Pi. When running ./mxnet_installer.sh from https://docs.aws.amazon.com/greengrass/latest/developerguide/ml-console.html#install-mxnet it takes ages and just…
L G
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How to install the R package for mxnet?

I used to work with the mxnet package in R. I have an old installation and I can use it in R 3.4x but now I want to switch to the newest R version (R 3.5 locally) and I would love to use it on rstudio.cloud. The package was on CRAN (wasn't it?) Now…
Richi W
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XOR neural network, the losses don't go down

I'm using Mxnet to train a XOR neural network, but the losses don't go down, they are always above 0.5. Below is my code in Mxnet 1.1.0; Python 3.6; OS X El Capitan 10.11.6 I tried 2 loss functions - squared loss and softmax loss, both didn't…
Kun Hu
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Training data in S3 in AWS Sagemaker

I've uploaded my own Jupyter notebook to Sagemaker, and am trying to create an iterator for my training / validation data which is in S3, as follow: train = mx.io.ImageRecordIter( path_imgrec = ‘s3://bucket-name/train.rec’ …… ) I…
Lakshay Sharma
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Advantages and Disadvantages of MXNet compared to other Deep Learning APIs

Recently I decided to learn MXNet, as some code I need to use, is written using this API. However, I would like to know which are the advantages and disadvantages of MXNet compared to the other Deep Learning Libraries out there.
obelix
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Model training fails with h2o deepwater

While trying to train a lenet model for multiclass classification using h2o deepwater using mxnet backed I am getting the following errors: Loading H2O mxnet bindings. Found CUDA_HOME or CUDA_PATH environment variable, trying to connect to GPU…
Sooraj
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How to load a trained MXnet model?

I have trained a network using MXnet, but am not sure how I can save and load the parameters for later use. First I define and train the network: dataIn = mx.sym.var('data') fc1 = mx.symbol.FullyConnected(data=dataIn, num_hidden=100) …
Nuclear Hoagie
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MXNetError: Shape inconsistent, Provided=(1,2), inferred shape=(1,1)

I am trying to train a LSTM like, from __future__ import print_function import mxnet as mx import numpy as np from mxnet import nd, autograd, sym from mxnet import gluon ctx = mx.cpu() LIMIT = 20 data = np.array([(s, 1) for s in…
user3002273
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MXNet: nn.Activation vs nd.relu?

I am new to MXNet (I am using it in Python3) Their tutorial series encourages you define your own gluon blocks. So lets say this is your block (a common convolution structure): class CNN1D(mx.gluon.Block): def __init__(self, **kwargs): …
SumNeuron
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