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RegNet #16188

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FrancescoSaverioZuppichini merged 51 commits into main from modeling_regnet

Apr 7, 2022

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FrancescoSaverioZuppichini commented Mar 16, 2022 •

edited

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What does this PR do?

This WIP PR adds RegNet.

Currently, the model can be used as follows

from transformers import  RegNetConfig, RegNetForImageClassification
import requests
from io import BytesIO
res = requests.get('https://github.com/huggingface/transformers/blob/master/tests/fixtures/tests_samples/COCO/000000039769.png?raw=true')
image = Image.open(BytesIO(res.content))

feature_extractor = AutoFeatureExtractor.from_pretrained("zuppif/regnet-y-040")
model = RegNetForImageClassification.from_pretrained("zuppif/regnet-y-040").eval()

inputs = feature_extractor(image, return_tensors="pt")
outputs = model(**inputs)
print(model.config.id2label[torch.argmax(outputs.logits).item()])
# tiger cat

FrancescoSaverioZuppichini requested a review from NielsRogge

March 16, 2022 09:08

HuggingFaceDocBuilderDev commented Mar 16, 2022 •

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The documentation is not available anymore as the PR was closed or merged.

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+                      depths (`List[int]`, *optional*, defaults to `[3, 4, 6, 3]`):
+                          Depth (number of layers) for each stage.
+                      layer_type (`str`, *optional*, defaults to `"bottleneck"`):
+                          The layer to use, it can be either `"x" or `"y"` (like `x` but with squeeze and excitation).

Contributor

NielsRogge Mar 16, 2022

Can you clarify this?

Contributor

NielsRogge Mar 16, 2022

What is x?

Contributor Author

FrancescoSaverioZuppichini Mar 16, 2022

updated the doc

Collaborator

sgugger Mar 16, 2022

The default needs to be update (it's "y" not "bottleneck") and what "x" and "y" mean should be detailed here in the docstring for people who did not read the paper.

Contributor Author

FrancescoSaverioZuppichini Mar 21, 2022

Updated, let me know if it is better

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sgugger left a comment

Thanks for working on this new model. I left a few comments, but it's in good shape to be merged.

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+                      depths (`List[int]`, *optional*, defaults to `[3, 4, 6, 3]`):
+                          Depth (number of layers) for each stage.
+                      layer_type (`str`, *optional*, defaults to `"bottleneck"`):
+                          The layer to use, it can be either `"x" or `"y"` (like `x` but with squeeze and excitation).

Collaborator

sgugger Mar 16, 2022

The default needs to be update (it's "y" not "bottleneck") and what "x" and "y" mean should be detailed here in the docstring for people who did not read the paper.

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FrancescoSaverioZuppichini force-pushed the modeling_regnet branch from f135aee to 4025d7d Compare

March 21, 2022 16:05

FrancescoSaverioZuppichini force-pushed the modeling_regnet branch 2 times, most recently from 94ce99b to 4ff7b1a Compare

March 31, 2022 08:16

Contributor Author

FrancescoSaverioZuppichini commented Mar 31, 2022

Updated the codebase to use config when is possible. I had to update ResNetModel as well to make make fixup happy :)

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FrancescoSaverioZuppichini force-pushed the modeling_regnet branch 2 times, most recently from 303c1a6 to 45319dd Compare

April 5, 2022 17:21

FrancescoSaverioZuppichini requested a review from NielsRogge

April 5, 2022 18:41

Contributor Author

FrancescoSaverioZuppichini commented Apr 5, 2022

Conversion script for the 10B regnet model added + needed changes inside PretrainedModel._load_pretrained_model_low_mem

FrancescoSaverioZuppichini and others added 26 commits

April 7, 2022 21:17


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Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>


          removed unused code

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FrancescoSaverioZuppichini force-pushed the modeling_regnet branch from 123096e to fa5506e Compare

April 7, 2022 19:17

Contributor Author

FrancescoSaverioZuppichini commented Apr 7, 2022 •

edited

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Thanks to all reviewers, I've rebased and updated the code accordingly

FrancescoSaverioZuppichini merged commit af14c61 into main

FrancescoSaverioZuppichini deleted the modeling_regnet branch

April 7, 2022 19:58

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