PyTorch

PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab.

The forward() method implementation of PerceiverAudioPreprocessor seems to be problematic because it has an extra required pos argument, whereas all other preprocessors do not (or it is optional). In fact, while it is passed to `_build_net

https://github.com/open-mmlab/mmdetection/blob/7a9bc498d5cc972171ec4f7332afcd70bb50e60e/tools/analysis_tools/coco_error_analysis.py#L43
This I believe is for coco format, but I couldn't find any files for plotting precision or precision vs recall chart for pascal voc format.

📚 Documentation

For typos and doc fixes, please go ahead and:

.. code-block:: python
   :emphasize-lines: 3,5

   def some_function():
       interesting = False
       print 'This line is highlighted.'
       print 'This one is not...'
       print '...but this one is.'

<img width="553" alt="Screenshot 2022-02-25 at 16 15 01" src="https://user-images.githubuserconte

Change tensor.data to tensor.detach() due to
pytorch/pytorch#6990 (comment)
tensor.detach() is more robust than tensor.data.

🚀 Feature

Motivation

paper "LEARNING TO REPRESENT PROGRAMS WITH GRAPHS" which encode computer programs as graphs, with rich semantic information, however, most code implementation on this dataset VarMisuse is based on TensorFlow, like [tf-gnn-samples](https://github.com/microsof

Although the results look nice and ideal in all TensorFlow plots and are consistent across all frameworks, there is a small difference (more of a consistency issue). The result training loss/accuracy plots look like they are sampling on a lesser number of points. It looks more straight and smooth and less wiggly as compared to PyTorch or MXNet.

It can be clearly seen in chapter 6([CNN Lenet](ht

New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.

Feb	MAR	Apr
	10
2021	2022	2023

PyTorch

Here are 20,487 public repositories matching this topic...

huggingface / transformers

CorentinJ / Real-Time-Voice-Cloning

GokuMohandas / MadeWithML

yunjey / pytorch-tutorial

ultralytics / yolov5

fastai / fastai

babysor / MockingBird

open-mmlab / mmdetection

TencentARC / GFPGAN

lutzroeder / netron

PyTorchLightning / pytorch-lightning

📚 Documentation

junyanz / pytorch-CycleGAN-and-pix2pix

rwightman / pytorch-image-models

pytorch / fairseq

zergtant / pytorch-handbook

ShusenTang / Dive-into-DL-PyTorch

pyg-team / pytorch_geometric

🚀 Feature

Motivation

Tencent / ncnn

JaidedAI / EasyOCR

bharathgs / Awesome-pytorch-list

huggingface / datasets

d2l-ai / d2l-en

dragen1860 / Deep-Learning-with-TensorFlow-book

horovod / horovod

onnx / onnx

New Operator

Describe the operator

Can this operator be constructed using existing onnx operators?

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

flairNLP / flair

deepinsight / insightface

microsoft / nni

allenai / allennlp

graykode / nlp-tutorial

Related Topics