Perceiver

tests/test_models.py

@@ -17,7 +17,7 @@
 # transformer models don't support many of the spatial / feature based model functionalities
 NON_STD_FILTERS = [
     'vit_*', 'tnt_*', 'pit_*', 'swin_*', 'coat_*', 'cait_*', '*mixer_*', 'gmlp_*', 'resmlp_*', 'twins_*',
-    'convit_*', 'levit*', 'visformer*', 'deit*', 'jx_nest_*', 'nest_*', 'xcit_*']
+    'convit_*', 'levit*', 'visformer*', 'deit*', 'jx_nest_*', 'nest_*', 'xcit_*', 'perceiver*']
 NUM_NON_STD = len(NON_STD_FILTERS)
 
 # exclude models that cause specific test failures
@@ -26,7 +26,7 @@
     EXCLUDE_FILTERS = [
         '*efficientnet_l2*', '*resnext101_32x48d', '*in21k', '*152x4_bitm', '*101x3_bitm', '*50x3_bitm',
         '*nfnet_f3*', '*nfnet_f4*', '*nfnet_f5*', '*nfnet_f6*', '*nfnet_f7*', 
-        '*resnetrs350*', '*resnetrs420*', 'xcit_large_24_p8*']
+        '*resnetrs350*', '*resnetrs420*', 'xcit_large_24_p8*', 'perceiver_l*']
 else:
     EXCLUDE_FILTERS = []
 
@@ -218,11 +218,12 @@ def test_model_default_cfgs_non_std(model_name, batch_size):
 
     # check first conv(s) names match default_cfg
     first_conv = cfg['first_conv']
-    if isinstance(first_conv, str):
-        first_conv = (first_conv,)
-    assert isinstance(first_conv, (tuple, list))
-    for fc in first_conv:
-        assert fc + ".weight" in state_dict.keys(), f'{fc} not in model params'
+    if first_conv is not None:
+        if isinstance(first_conv, str):
+            first_conv = (first_conv,)
+        assert isinstance(first_conv, (tuple, list))
+        for fc in first_conv:
+            assert fc + ".weight" in state_dict.keys(), f'{fc} not in model params'
 
 
 if 'GITHUB_ACTIONS' not in os.environ:

timm/models/__init__.py

@@ -22,6 +22,7 @@
 from .nasnet import *
 from .nest import *
 from .nfnet import *
+from .perceiver import *
 from .pit import *
 from .pnasnet import *
 from .regnet import *
@@ -36,6 +37,7 @@
 from .swin_transformer import *
 from .tnt import *
 from .tresnet import *
+from .twins import *
 from .vgg import *
 from .visformer import *
 from .vision_transformer import *
@@ -44,7 +46,6 @@
 from .xception import *
 from .xception_aligned import *
 from .xcit import *
-from .twins import *
 
 from .factory import create_model, split_model_name, safe_model_name
 from .helpers import load_checkpoint, resume_checkpoint, model_parameters

timm/models/nfnet.py

@@ -8,12 +8,6 @@
 
 Official Deepmind JAX code: https://github.com/deepmind/deepmind-research/tree/master/nfnets
 
-Status:
-* These models are a work in progress, experiments ongoing.
-* Pretrained weights for two models so far, more to come.
-* Model details updated to closer match official JAX code now that it's released
-* NF-ResNet, NF-RegNet-B, and NFNet-F models supported
-
 Hacked together by / copyright Ross Wightman, 2021.
 """
 import math