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.
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文本中如果有数字读不出来
This is a nice first issue:
Add types/docments to the Learner.get_preds
function. This function is essential to any fastai
user and has almost no documentation. Add types and text to the variables as we have in many places now.
What happened + What you expected to happen
When initializing a Ray Trainer, we provide a logdir
argument, and the __init__
method of the Trainer stores it as a logdir
class variable.
Then, when creating a Trainable with Trainer.to_tune_trainable()
, it in-turn calls _create_tune_trainable()
, which does not use self.logdir
. So when tune_function
is defined inside `_create_tu
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.
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Hi, I see that is_last_batch
trainer property isn't documented in https://pytorch-lightning.readthedocs.io/en/stable/common/trainer.html#properties.
I was lucky to find it here.
I feel it would be helpful to have all properties listed there.
Thanks.
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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
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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
Adding a Dataset
- Name: Stanford dog dataset
- Description: The dataset is about 120 classes for a total of 20.580 images. You can find the dataset here http://vision.stanford.edu/aditya86/ImageNetDogs/
- Paper: http://vision.stanford.edu/aditya86/ImageNetDogs/
- Data: *[link to the Github repository or current dataset location](http://vision.stanford.edu/aditya86/Ima
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We should sort imports with isort to keep the import section clean
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Created by Facebook's AI Research lab (FAIR)
Released September 2016
Latest release 11 days ago
- Repository
- pytorch/pytorch
- Website
- pytorch.org
- Wikipedia
- Wikipedia
What does this PR do?