Fixed hypot bug on nan/inf pairings, began deprecation of non-real values

CHANGELOG.md

@@ -30,6 +30,9 @@ Remember to align the itemized text with the first line of an item within a list
   * In {func}`jax.jit`, passing invalid `static_argnums` or `static_argnames`
     now leads to an error rather than a warning.
   * The minimum jaxlib version is now 0.4.23.
+  * The {func}`jax.numpy.hypot` function now issues a deprecation warning when
+    passing complex-valued inputs to it. This will raise an error when the
+    deprecation is completed.
 
 ## jaxlib 0.4.27
 

jax/_src/numpy/ufuncs.py

@@ -22,6 +22,7 @@ from functools import partial
 import operator
 from textwrap import dedent
 from typing import Any, Callable, overload
+import warnings
 
 import numpy as np
 
@@ -730,12 +731,22 @@ def heaviside(x1: ArrayLike, x2: ArrayLike, /) -> Array:
 @implements(np.hypot, module='numpy')
 @jit
 def hypot(x1: ArrayLike, x2: ArrayLike, /) -> Array:
-  check_arraylike("hypot", x1, x2)
-  x1, x2 = promote_dtypes_inexact(x1, x2)
-  x1 = lax.abs(x1)
-  x2 = lax.abs(x2)
+  x1, x2 = promote_args_inexact("hypot", x1, x2)
+
+  # TODO(micky774): Promote to ValueError when deprecation is complete
+  # (began 2024-4-14).
+  if dtypes.issubdtype(x1.dtype, np.complexfloating):
+    warnings.warn(
+      "Passing complex-valued inputs to hypot is deprecated and will raise a "
+      "ValueError in the future. Please convert to real values first, such as "
+      "by using jnp.real or jnp.imag to take the real or imaginary components "
+      "respectively.",
+      DeprecationWarning, stacklevel=2)
+  x1, x2 = lax.abs(x1), lax.abs(x2)
+  idx_inf = lax.bitwise_or(isposinf(x1), isposinf(x2))
   x1, x2 = maximum(x1, x2), minimum(x1, x2)
-  return lax.select(x1 == 0, x1, x1 * lax.sqrt(1 + lax.square(lax.div(x2, lax.select(x1 == 0, lax._ones(x1), x1)))))
+  x = _where(x1 == 0, x1, x1 * lax.sqrt(1 + lax.square(lax.div(x2, _where(x1 == 0, lax._ones(x1), x1)))))
+  return _where(idx_inf, _lax_const(x, np.inf), x)
 
 
 @implements(np.reciprocal, module='numpy')

jax/experimental/array_api/__init__.py

@@ -124,6 +124,7 @@ from jax.experimental.array_api._elementwise_functions import (
     floor_divide as floor_divide,
     greater as greater,
     greater_equal as greater_equal,
+    hypot as hypot,
     imag as imag,
     isfinite as isfinite,
     isinf as isinf,

jax/experimental/array_api/_elementwise_functions.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 import jax
+from jax._src.dtypes import issubdtype
 from jax.experimental.array_api._data_type_functions import (
     result_type as _result_type,
     isdtype as _isdtype,
@@ -210,6 +211,20 @@ def greater_equal(x1, x2, /):
   return jax.numpy.greater_equal(x1, x2)
 
 
+def hypot(x1, x2, /):
+  """Computes the square root of the sum of squares for each element x1_i of the input array x1 with the respective element x2_i of the input array x2."""
+  x1, x2 = _promote_dtypes("hypot", x1, x2)
+
+  # TODO(micky774): Remove when jnp.hypot deprecation is completed
+  # (began 2024-4-14) and default behavior is Array API 2023 compliant
+  if issubdtype(x1.dtype, jax.numpy.complexfloating):
+    raise ValueError(
+      "hypot does not support complex-valued inputs. Please convert to real "
+      "values first, such as by using jnp.real or jnp.imag to take the real "
+      "or imaginary components respectively.")
+  return jax.numpy.hypot(x1, x2)
+
+
 def imag(x, /):
   """Returns the imaginary component of a complex number for each element x_i of the input array x."""
   x, = _promote_dtypes("imag", x)

tests/array_api_test.py

@@ -88,6 +88,7 @@ MAIN_NAMESPACE = {
   'full_like',
   'greater',
   'greater_equal',
+  'hypot',
   'iinfo',
   'imag',
   'inf',

tests/lax_numpy_operators_test.py

@@ -221,7 +221,7 @@ JAX_COMPOUND_OP_RECORDS = [
     op_record("fmod", 2, default_dtypes, all_shapes, jtu.rand_some_nan, []),
     op_record("heaviside", 2, default_dtypes, all_shapes, jtu.rand_default, [],
               inexact=True),
-    op_record("hypot", 2, default_dtypes, all_shapes, jtu.rand_default, [],
+    op_record("hypot", 2, real_dtypes, all_shapes, jtu.rand_default, [],
               inexact=True),
     op_record("kron", 2, number_dtypes, nonempty_shapes, jtu.rand_default, []),
     op_record("outer", 2, number_dtypes, all_shapes, jtu.rand_default, []),

tests/lax_numpy_test.py

@@ -914,6 +914,26 @@ class LaxBackedNumpyTests(jtu.JaxTestCase):
         jnp.clip(x, max=jnp.array([-1+5j]))
 
 
+  # TODO(micky774): Check for ValueError instead of DeprecationWarning when
+  # jnp.hypot deprecation is completed (began 2024-4-2) and default behavior is
+  # Array API 2023 compliant
+  @jtu.sample_product(shape=all_shapes)
+  @jax.numpy_rank_promotion('allow')  # This test explicitly exercises implicit rank promotion.
+  @jax.numpy_dtype_promotion('standard')  # This test explicitly exercises mixed type promotion
+  def testHypotComplexInputDeprecation(self, shape):
+    rng = jtu.rand_default(self.rng())
+    x = rng(shape, dtype=jnp.complex64)
+    msg = "Passing complex-valued inputs to hypot"
+    # jit is disabled so we don't miss warnings due to caching.
+    with jax.disable_jit():
+      with self.assertWarns(DeprecationWarning, msg=msg):
+        jnp.hypot(x, x)
+
+      with self.assertWarns(DeprecationWarning, msg=msg):
+        y = jnp.ones_like(x)
+        jnp.hypot(x, y)
+
+
   @jtu.sample_product(
     [dict(shape=shape, dtype=dtype)
       for shape, dtype in _shape_and_dtypes(all_shapes, number_dtypes)],