From 7e8132ea8ef86afb04581ec2d6a58de90c934607 Mon Sep 17 00:00:00 2001
From: carlosgmartin <cgmartin@andrew.cmu.edu>
Date: Tue, 15 Jul 2025 13:20:27 -0400
Subject: [PATCH] Fix tree_min and tree_max to handle zero-size array leafs.

---
 optax/tree_utils/_tree_math.py      | 20 ++++++++++++++------
 optax/tree_utils/_tree_math_test.py | 16 ++++++++++++++++
 2 files changed, 30 insertions(+), 6 deletions(-)

diff --git a/optax/tree_utils/_tree_math.py b/optax/tree_utils/_tree_math.py
index 9387a0976..d0de50470 100644
--- a/optax/tree_utils/_tree_math.py
+++ b/optax/tree_utils/_tree_math.py
@@ -176,9 +176,13 @@ def tree_max(tree: Any) -> chex.Numeric:
   Returns:
     a scalar value.
   """
-  maxes = jax.tree.map(jnp.max, tree)
-  # initializer=-jnp.inf should work but pytype wants a jax.Array.
-  return jax.tree.reduce(jnp.maximum, maxes, initializer=jnp.array(-jnp.inf))
+  def f(array):
+    if jnp.size(array) == 0:
+      return None
+    else:
+      return jnp.max(array)
+  maxes = jax.tree.map(f, tree)
+  return jax.tree.reduce(jnp.maximum, maxes, initializer=-float("inf"))
 
 
 def tree_min(tree: Any) -> chex.Numeric:
@@ -190,9 +194,13 @@ def tree_min(tree: Any) -> chex.Numeric:
   Returns:
     a scalar value.
   """
-  mins = jax.tree.map(jnp.min, tree)
-  # initializer=jnp.inf should work but pytype wants a jax.Array.
-  return jax.tree.reduce(jnp.minimum, mins, initializer=jnp.array(jnp.inf))
+  def f(array):
+    if jnp.size(array) == 0:
+      return None
+    else:
+      return jnp.min(array)
+  mins = jax.tree.map(f, tree)
+  return jax.tree.reduce(jnp.minimum, mins, initializer=float("inf"))
 
 
 def tree_size(tree: Any) -> int:
diff --git a/optax/tree_utils/_tree_math_test.py b/optax/tree_utils/_tree_math_test.py
index f17857423..bd860220e 100644
--- a/optax/tree_utils/_tree_math_test.py
+++ b/optax/tree_utils/_tree_math_test.py
@@ -162,6 +162,22 @@ def test_tree_min(self, key):
     got = tu.tree_min(tree)
     np.testing.assert_allclose(expected, got)
 
+  def test_tree_min_empty(self):
+    tree = [jnp.ones([2, 3]), jnp.zeros([4, 0, 5])]
+    got = tu.tree_min(tree)
+    expected = 1.0
+    assert expected == got
+
+  @parameterized.product(
+      expected=(0, 10000, -10000, float("inf"), -float("inf")),
+      dtype=('int8', 'uint8', 'float32'),
+      which=(tu.tree_min, tu.tree_max),
+  )
+  def test_tree_max_min_empty_dtype(self, expected, dtype, which):
+    tree = [expected, jnp.zeros(0, dtype)]
+    got = which(tree)
+    assert expected == got
+
   @parameterized.parameters(
       'array_a', 'tree_a', 'tree_a_dict', 'tree_b', 'tree_b_dict'
   )