Merge pull request #46741 from yongtang:46700-tf.math.reduce_prod-keepdims

PiperOrigin-RevId: 354991067
Change-Id: Ibf9c353042b49b5ffc8113aed99fb9f3cbf6eea2

tensorflow/python/kernel_tests/reduction_ops_test.py

@@ -116,6 +116,24 @@ class ReductionUnknownShape(test.TestCase):
           self.assertEqual(y.shape, ())
 
 
+class ReductionInvalidKeepdims(test.TestCase):
+
+  def testBasic(self):
+    # Test case for GitHub issue 46700.
+    for dtype, reductions in [
+        (dtypes.float32, (math_ops.reduce_sum, math_ops.reduce_mean,
+                          math_ops.reduce_prod, math_ops.reduce_max,
+                          math_ops.reduce_min, math_ops.reduce_euclidean_norm)),
+        (dtypes.bool, (math_ops.reduce_all, math_ops.reduce_any))
+    ]:
+      for reduction in reductions:
+        with self.assertRaisesRegex(ValueError, "The truth value"):
+          x = True if dtype == dtypes.bool else 1
+          y = reduction(
+              input_tensor=x, keepdims=np.array([63600, 1], dtype=np.float16))
+          self.evaluate(y)
+
+
 class BaseReductionTest(test.TestCase):
 
   def _tf_reduce(self, x, reduction_axes, keepdims):

tensorflow/python/ops/math_ops.py

@@ -2016,7 +2016,7 @@ def reduce_sum_with_dims(input_tensor,
                          keepdims=False,
                          name=None,
                          dims=None):
-  keepdims = False if keepdims is None else keepdims
+  keepdims = False if keepdims is None else bool(keepdims)
   return _may_reduce_to_scalar(
       keepdims, axis,
       gen_math_ops._sum(input_tensor, dims, keepdims, name=name))
@@ -2059,6 +2059,7 @@ def reduce_euclidean_norm(input_tensor, axis=None, keepdims=False, name=None):
   Returns:
     The reduced tensor, of the same dtype as the input_tensor.
   """
+  keepdims = bool(keepdims)
   return _may_reduce_to_scalar(
       keepdims, axis,
       gen_math_ops.euclidean_norm(
@@ -2331,7 +2332,7 @@ def reduce_mean(input_tensor, axis=None, keepdims=False, name=None):
 
   @end_compatibility
   """
-  keepdims = False if keepdims is None else keepdims
+  keepdims = False if keepdims is None else bool(keepdims)
   return _may_reduce_to_scalar(
       keepdims, axis,
       gen_math_ops.mean(
@@ -2491,7 +2492,7 @@ def reduce_prod(input_tensor, axis=None, keepdims=False, name=None):
   Equivalent to np.prod
   @end_compatibility
   """
-  keepdims = False if keepdims is None else keepdims
+  keepdims = False if keepdims is None else bool(keepdims)
   return _may_reduce_to_scalar(
       keepdims, axis,
       gen_math_ops.prod(
@@ -2678,7 +2679,7 @@ def reduce_min(input_tensor, axis=None, keepdims=False, name=None):
   Equivalent to np.min
   @end_compatibility
   """
-  keepdims = False if keepdims is None else keepdims
+  keepdims = False if keepdims is None else bool(keepdims)
   return _may_reduce_to_scalar(
       keepdims, axis,
       gen_math_ops._min(
@@ -2805,7 +2806,7 @@ def reduce_max_with_dims(input_tensor,
                          keepdims=False,
                          name=None,
                          dims=None):
-  keepdims = False if keepdims is None else keepdims
+  keepdims = False if keepdims is None else bool(keepdims)
   return _may_reduce_to_scalar(
       keepdims, axis,
       gen_math_ops._max(input_tensor, dims, keepdims, name=name))
@@ -2909,7 +2910,7 @@ def reduce_all(input_tensor, axis=None, keepdims=False, name=None):
   Equivalent to np.all
   @end_compatibility
   """
-  keepdims = False if keepdims is None else keepdims
+  keepdims = False if keepdims is None else bool(keepdims)
   return _may_reduce_to_scalar(
       keepdims, axis,
       gen_math_ops._all(
@@ -3015,7 +3016,7 @@ def reduce_any(input_tensor, axis=None, keepdims=False, name=None):
   Equivalent to np.any
   @end_compatibility
   """
-  keepdims = False if keepdims is None else keepdims
+  keepdims = False if keepdims is None else bool(keepdims)
   return _may_reduce_to_scalar(
       keepdims, axis,
       gen_math_ops._any(