Update sotabench with new models

Author: rwightman

sotabench.py

@@ -78,7 +78,7 @@ def _entry(model_name, paper_model_name, paper_arxiv_id, batch_size=BATCH_SIZE,
     _entry('mixnet_m', 'MixNet-M', '1907.09595'),
     _entry('mixnet_s', 'MixNet-S', '1907.09595'),
     _entry('mnasnet_100', 'MnasNet-B1', '1807.11626'),
-    _entry('mobilenetv3_100', 'MobileNet V3-Large 1.0', '1905.02244',
+    _entry('mobilenetv3_rw', 'MobileNet V3-Large 1.0', '1905.02244',
            model_desc='Trained in PyTorch with RMSProp, exponential LR decay, and hyper-params matching '
                       'paper as closely as possible.'),
     _entry('resnet18', 'ResNet-18', '1812.01187'),
@@ -114,6 +114,30 @@ def _entry(model_name, paper_model_name, paper_arxiv_id, batch_size=BATCH_SIZE,
            model_desc='Ported from official Google AI Tensorflow weights'),
     _entry('tf_efficientnet_b7', 'EfficientNet-B7 (RandAugment)', '1905.11946', batch_size=BATCH_SIZE//8,
            model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b0_ap', 'EfficientNet-B0 (AdvProp)', '1911.09665',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b1_ap', 'EfficientNet-B1 (AdvProp)', '1911.09665',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b2_ap', 'EfficientNet-B2 (AdvProp)', '1911.09665',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b3_ap', 'EfficientNet-B3 (AdvProp)', '1911.09665', batch_size=BATCH_SIZE // 2,
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b4_ap', 'EfficientNet-B4 (AdvProp)', '1911.09665', batch_size=BATCH_SIZE // 2,
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b5_ap', 'EfficientNet-B5 (AdvProp)', '1911.09665', batch_size=BATCH_SIZE // 4,
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b6_ap', 'EfficientNet-B6 (AdvProp)', '1911.09665', batch_size=BATCH_SIZE // 8,
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b7_ap', 'EfficientNet-B7 (AdvProp)', '1911.09665', batch_size=BATCH_SIZE // 8,
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_b8_ap', 'EfficientNet-B8 (AdvProp)', '1911.09665', batch_size=BATCH_SIZE // 8,
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_cc_b0_4e', 'EfficientNet-CondConv-B0 4 experts', '1904.04971',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_cc_b0_8e', 'EfficientNet-CondConv-B0 8 experts', '1904.04971',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_efficientnet_cc_b1_8e', 'EfficientNet-CondConv-B1 8 experts', '1904.04971',
+           model_desc='Ported from official Google AI Tensorflow weights'),
     _entry('tf_efficientnet_es', 'EfficientNet-EdgeTPU-S', '1905.11946',
            model_desc='Ported from official Google AI Tensorflow weights'),
     _entry('tf_efficientnet_em', 'EfficientNet-EdgeTPU-M', '1905.11946',
@@ -124,6 +148,18 @@ def _entry(model_name, paper_model_name, paper_arxiv_id, batch_size=BATCH_SIZE,
     _entry('tf_mixnet_l', 'MixNet-L', '1907.09595', model_desc='Ported from official Google AI Tensorflow weights'),
     _entry('tf_mixnet_m', 'MixNet-M', '1907.09595', model_desc='Ported from official Google AI Tensorflow weights'),
     _entry('tf_mixnet_s', 'MixNet-S', '1907.09595', model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_mobilenetv3_large_100', 'MobileNet V3-Large 1.0', '1905.02244',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_mobilenetv3_large_075', 'MobileNet V3-Large 0.75', '1905.02244',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_mobilenetv3_large_minimal_100', 'MobileNet V3-Large Minimal 1.0', '1905.02244',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_mobilenetv3_small_100', 'MobileNet V3-Small 1.0', '1905.02244',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_mobilenetv3_small_075', 'MobileNet V3-Small 0.75', '1905.02244',
+           model_desc='Ported from official Google AI Tensorflow weights'),
+    _entry('tf_mobilenetv3_small_minimal_100', 'MobileNet V3-Small Minimal 1.0', '1905.02244',
+           model_desc='Ported from official Google AI Tensorflow weights'),
 
     ## Cadene ported weights (to remove if Cadene adds sotabench)
     _entry('inception_resnet_v2', 'Inception ResNet V2', '1602.07261'),