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Sheldonfrith
Sheldonfrith commented Oct 1, 2021

🚀 Feature

Add information to this error message which will help an end-user actually figure out what is wrong:
RuntimeError: Expected from <= to to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)

Motivation

The error message itself told me to ask for an improvement... I cannot find any useful info on thi

nickhuangxinyu
nickhuangxinyu commented Sep 25, 2021

usually, after trained model. i save model in cpp format with code:

cat_model.save_model('a', format="cpp")
cat_model.save_model('b', format="cpp")

but when my cpp need to use multi models.

in my main.cpp

#include "a.hpp"
#include "b.hpp"

int main() {
  // do something
  double a_pv = ApplyCatboostModel({1.2, 2.3});  // i want to a.hpp's model here
  double b_pv 
rsn870
rsn870 commented Aug 21, 2020

Hi ,

I have tried out both loss.backward() and model_engine.backward(loss) for my code. There are several subtle differences that I have observed , for one retain_graph = True does not work for model_engine.backward(loss) . This is creating a problem since buffers are not being retained every time I run the code for some reason.

Please look into this if you could.

odddozen
odddozen commented Aug 27, 2021

the .pcd file format allows for fields to be extended. this means it can neatly hold data about the label or object of a point. this can be very handy for ML tasks. However, the open3d file io does not appear to be able to read other fields other than the xyz, rgb, normals etc . I haven't been able to find where in the open3d structure the code for the file io pcd loading is implemented to att

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

  • Updated Oct 15, 2021
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solardiz
solardiz commented Jul 19, 2019

Our users are often confused by the output from programs such as zip2john sometimes being very large (multi-gigabyte). Maybe we should identify and enhance these programs to output a message to stderr to explain to users that it's normal for the output to be very large - maybe always or maybe only when the output size is above a threshold (e.g., 1 million bytes?)

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