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Merged
merged 7 commits into from
Nov 20, 2024
Merged

EfficientNet: Add lite0 variant #1968

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6a120f7
add lite0 variant
pkgoogle Oct 31, 2024
f50510d
format pass
pkgoogle Oct 31, 2024
84b1dee
added to preset file, fix uri
pkgoogle Nov 4, 2024
e1e4aad
fix parameter regression
pkgoogle Nov 7, 2024
ef09bee
Merge branch 'master' into add_efficientnet_lite0_preset
pkgoogle Nov 18, 2024
d7028d4
format fix
pkgoogle Nov 18, 2024
9ba8e42
fix merge regression
pkgoogle Nov 18, 2024
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13 changes: 13 additions & 0 deletions keras_hub/src/models/efficientnet/efficientnet_presets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -163,4 +163,17 @@
},
"kaggle_handle": "kaggle://keras/efficientnet/keras/efficientnet_es_ra_imagenet/1",
},
"efficientnet_lite0_ra_imagenet": {
"metadata": {
"description": (
"EfficientNet-Lite model fine-trained on the ImageNet 1k dataset "
"with RandAugment recipe."
),
"params": 4652008,
"official_name": "EfficientNet",
"path": "efficientnet",
"model_card": "https://arxiv.org/abs/1905.11946",
},
"kaggle_handle": "kaggle://keras/efficientnet/keras/efficientnet_lite0_ra_imagenet",
},
}
42 changes: 26 additions & 16 deletions keras_hub/src/utils/timm/convert_efficientnet.py
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Expand Up @@ -20,6 +20,32 @@
"depth_coefficient": 1.1,
"stackwise_squeeze_and_excite_ratios": [0.25] * 7,
},
"b2": {
"width_coefficient": 1.1,
"depth_coefficient": 1.2,
"stackwise_squeeze_and_excite_ratios": [0.25] * 7,
},
"b3": {
"width_coefficient": 1.2,
"depth_coefficient": 1.4,
"stackwise_squeeze_and_excite_ratios": [0.25] * 7,
},
"b4": {
"width_coefficient": 1.4,
"depth_coefficient": 1.8,
"stackwise_squeeze_and_excite_ratios": [0.25] * 7,
},
"b5": {
"width_coefficient": 1.6,
"depth_coefficient": 2.2,
"stackwise_squeeze_and_excite_ratios": [0.25] * 7,
},
"lite0": {
"width_coefficient": 1.0,
"depth_coefficient": 1.0,
"stackwise_squeeze_and_excite_ratios": [0] * 7,
"activation": "relu6",
},
"el": {
"width_coefficient": 1.2,
"depth_coefficient": 1.4,
Expand Down Expand Up @@ -65,22 +91,6 @@
"stackwise_nores_option": [True] + [False] * 5,
"activation": "relu",
},
"b2": {
"width_coefficient": 1.1,
"depth_coefficient": 1.2,
},
"b3": {
"width_coefficient": 1.2,
"depth_coefficient": 1.4,
},
"b4": {
"width_coefficient": 1.4,
"depth_coefficient": 1.8,
},
"b5": {
"width_coefficient": 1.6,
"depth_coefficient": 2.2,
},
}


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3 changes: 3 additions & 0 deletions tools/checkpoint_conversion/convert_efficientnet_checkpoints.py
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Expand Up @@ -19,6 +19,8 @@
--preset efficientnet_b5_sw_imagenet --upload_uri kaggle://keras/efficientnet/keras/efficientnet_b5_sw_imagenet
python tools/checkpoint_conversion/convert_efficientnet_checkpoints.py \
--preset efficientnet_b5_sw_ft_imagenet --upload_uri kaggle://keras/efficientnet/keras/efficientnet_b5_sw_ft_imagenet
python tools/checkpoint_conversion/convert_efficientnet_checkpoints.py \
--preset efficientnet_lite0_ra_imagenet --upload_uri kaggle://keras/efficientnet/keras/efficientnet_lite0_ra_imagenet
python tools/checkpoint_conversion/convert_efficientnet_checkpoints.py \
--preset efficientnet_el_ra_imagenet --upload_uri kaggle://keras/efficientnet/keras/efficientnet_el_ra_imagenet
python tools/checkpoint_conversion/convert_efficientnet_checkpoints.py \
Expand Down Expand Up @@ -50,6 +52,7 @@
"efficientnet_b4_ra2_imagenet": "timm/efficientnet_b4.ra2_in1k",
"efficientnet_b5_sw_imagenet": "timm/efficientnet_b5.sw_in12k",
"efficientnet_b5_sw_ft_imagenet": "timm/efficientnet_b5.sw_in12k_ft_in1k",
"efficientnet_lite0_ra_imagenet": "timm/efficientnet_lite0.ra_in1k",
"efficientnet_el_ra_imagenet": "timm/efficientnet_el.ra_in1k",
"efficientnet_em_ra2_imagenet": "timm/efficientnet_em.ra2_in1k",
"efficientnet_es_ra_imagenet": "timm/efficientnet_es.ra_in1k",
Expand Down
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