added enum support for tabulate

flax/linen/summary.py

@@ -15,6 +15,7 @@
 """Flax Module summary library."""
 
 import dataclasses
+import enum
 import io
 from abc import ABC, abstractmethod
 from types import MappingProxyType
@@ -42,7 +43,7 @@
 import yaml
 
 import flax.linen.module as module_lib
-from flax.core import meta, unfreeze
+from flax.core import FrozenDict, meta, unfreeze
 from flax.core.scope import (
   CollectionFilter,
   DenyList,
@@ -709,12 +710,17 @@ def _normalize_structure(obj):
   if isinstance(obj, (tuple, list)):
     return tuple(map(_normalize_structure, obj))
   elif isinstance(obj, Mapping):
-    return {k: _normalize_structure(v) for k, v in obj.items()}
+    return {
+      _normalize_structure(k): _normalize_structure(v) for k, v in obj.items()
+    }
   elif dataclasses.is_dataclass(obj):
     return {
       f.name: _normalize_structure(getattr(obj, f.name))
       for f in dataclasses.fields(obj)
     }
+  elif isinstance(obj, enum.Enum):
+    # `yaml.safe_dump` does not support Enum key types so extract the underlying value
+    return obj.value
   else:
     return obj
 

tests/linen/summary_test.py

@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+
+import enum
 from typing import List
 
 import jax
@@ -735,6 +737,26 @@ def __call__(self, x):
     lines = rep.splitlines()
     self.assertIn('Total Parameters: 50', lines[-2])
 
+  def test_tabulate_enum(self):
+    class Net(nn.Module):
+      @nn.compact
+      def __call__(self, inputs):
+        x = inputs['x']
+        x = nn.Dense(features=2)(x)
+        return jnp.sum(x)
+
+    class InputEnum(str, enum.Enum):
+      x = 'x'
+
+    inputs = {InputEnum.x: jnp.ones((1, 1))}
+    # test args
+    lines = Net().tabulate(jax.random.key(0), inputs).split('\n')
+    self.assertIn('x: \x1b[2mfloat32\x1b[0m[1,1]', lines[5])
+    # test kwargs
+    lines = Net().tabulate(jax.random.key(0), inputs=inputs).split('\n')
+    self.assertIn('inputs:', lines[5])
+    self.assertIn('x: \x1b[2mfloat32\x1b[0m[1,1]', lines[6])
+
 
 if __name__ == '__main__':
   absltest.main()