inception_v3 requires an input of (299, 299)
while other models requires an input of (224, 224).
Due to adaptive pooling used in some models,
they can run on varying sized intput without throwing errors
(but the results are usually not correct).
You have to resize/crop an image to be the right input size
(and then other necessary transformations, e.g., to_tensor
Data for NLP Research
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
The Multi-Genre NLI Corpus (MultiNLI)
General Language Understanding Evaluation (GLUE)
The Stanford Question Answering Dataset
SWAG (Situations With Adversarial Generations)
Reading Comprehension Dataset (RACE)
Heuristic Analysis for NLI Systems Data set …
SLIDE: Sub-Linear Deep Learning Engine
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
Hands on Tensor in PyTorch
Deep Learning Libraries for Dialog Systems and Chatbots
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
References
https://github.com/deepmipt/DeepPavlov
Device Managment in PyTorch
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
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Modules can hold parameters of different types on different devices, so it's not always possible to unambiguously determine the device. The recommended workflow in PyTorch is to create the device object …