https://github.com/alan-turing-institute/ocf-iam4vp

Application of the Implicit Stacked Autoregressive Model for Video Prediction (IAM4VP) to cloudcasting

https://github.com/alan-turing-institute/ocf-iam4vp

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Repository

Application of the Implicit Stacked Autoregressive Model for Video Prediction (IAM4VP) to cloudcasting

Basic Info
  • Host: GitHub
  • Owner: alan-turing-institute
  • Language: Python
  • Default Branch: main
  • Size: 144 KB
Statistics
  • Stars: 3
  • Watchers: 2
  • Forks: 0
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  • Releases: 15
Created over 1 year ago · Last pushed over 1 year ago
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Readme

README.md

ocf-iam4vp

Application of the Implicit Stacked Autoregressive Model for Video Prediction (IAM4VP) to cloudcasting

Model summary

The settings below are being used to train this model

``` - batch-size: 2 - hidden-channels-space: 32 - hidden-channels-time: 64 - num-convolutions-space: 4 - num-convolutions-time: 4 - num-forecast-steps: 12

- num-history-steps: 24

Layer (type:depth-idx) Output Shape Param #

IAM4VP [2, 11, 372, 614] 10,999,296 ├─Encoder: 1-1 [48, 32, 93, 154] -- │ └─Sequential: 2-1 -- -- │ │ └─ConvSC: 3-1 [48, 32, 372, 614] 3,264 │ │ └─ConvSC: 3-2 [48, 32, 186, 307] 9,312 │ │ └─ConvSC: 3-3 [48, 32, 186, 307] 9,312 │ │ └─ConvSC: 3-4 [48, 32, 93, 154] 9,312 ├─TimeMLP: 1-2 [2, 32] -- │ └─SinusoidalPosEmb: 2-2 [2, 32] -- │ └─Linear: 2-3 [2, 128] 4,224 │ └─GELU: 2-4 [2, 128] -- │ └─Linear: 2-5 [2, 32] 4,128 ├─Predictor: 1-3 [2, 24, 32, 93, 154] -- │ └─Conv2d: 2-6 [2, 64, 93, 154] 98,368 │ └─Sequential: 2-7 -- -- │ │ └─ConvNextTimeEmbed: 3-5 [2, 64, 93, 154] 38,592 │ │ └─ConvNextTimeEmbedLKA: 3-6 [2, 64, 93, 154] 47,616 │ │ └─ConvNextTimeEmbedLKA: 3-7 [2, 64, 93, 154] 47,616 │ │ └─ConvNextTimeEmbedLKA: 3-8 [2, 64, 93, 154] 47,616 │ └─Conv2d: 2-8 [2, 768, 93, 154] 49,920 ├─Decoder: 1-4 [48, 11, 372, 614] -- │ └─Sequential: 2-9 -- -- │ │ └─ConvSC: 3-9 [48, 32, 186, 308] 37,056 │ │ └─ConvSC: 3-10 [48, 32, 186, 308] 9,312 │ │ └─ConvSC: 3-11 [48, 32, 372, 616] 37,056 │ │ └─ConvSC: 3-12 [48, 32, 372, 614] 18,528 │ └─Conv2d: 2-10 [48, 11, 372, 614] 363 ├─SpatioTemporalRefinement: 1-5 [2, 11, 372, 614] -- │ └─Attention: 2-11 [2, 264, 372, 614] -- │ │ └─Conv2d: 3-13 [2, 264, 372, 614] 69,960 │ │ └─GELU: 3-14 [2, 264, 372, 614] -- │ │ └─LargeKernelAttention: 3-15 [2, 264, 372, 614] 90,024 │ │ └─Conv2d: 3-16 [2, 264, 372, 614] 69,960 │ └─Conv2d: 2-12 [2, 11, 372, 614] 2,915

├─Sigmoid: 1-6 [2, 11, 372, 614] --

Total params: 11,706,950 Trainable params: 11,706,950 Non-trainable params: 0

Total mult-adds (Units.GIGABYTES): 565.48

Input size (MB): 482.40 Forward/backward pass size (MB): 29351.09 Params size (MB): 2.78

Estimated Total Size (MB): 29836.27

```

Owner

  • Name: The Alan Turing Institute
  • Login: alan-turing-institute
  • Kind: organization
  • Email: info@turing.ac.uk

The UK's national institute for data science and artificial intelligence.

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