From b9c7c66ea52952553a797ac86ff9045f0db9f3fd Mon Sep 17 00:00:00 2001
From: LielinJiang <50691816+LielinJiang@users.noreply.github.com>
Date: Fri, 9 Oct 2020 11:39:16 +0800
Subject: [PATCH] add type promotion (#27756)

---
 .../fluid/tests/unittests/test_kldiv_loss_op.py   | 15 +++++++++++++++
 python/paddle/nn/functional/loss.py               | 10 ++++++++++
 2 files changed, 25 insertions(+)

diff --git a/python/paddle/fluid/tests/unittests/test_kldiv_loss_op.py b/python/paddle/fluid/tests/unittests/test_kldiv_loss_op.py
index 3a3b7071e04..aaba571e1a6 100644
--- a/python/paddle/fluid/tests/unittests/test_kldiv_loss_op.py
+++ b/python/paddle/fluid/tests/unittests/test_kldiv_loss_op.py
@@ -115,5 +115,20 @@ class TestKLDivLossDygraph(unittest.TestCase):
         pred_loss = paddle.nn.functional.kl_div(input, label)
 
 
+class TestKLDivLossTypePromotion(unittest.TestCase):
+    def test_kl_div_promotion(self):
+
+        with paddle.fluid.dygraph.guard():
+            x1 = paddle.rand([5, 20], dtype='float32')
+            target1 = paddle.rand([5, 20], dtype='float64')
+
+            kldiv_criterion = paddle.nn.KLDivLoss()
+            pred_loss1 = kldiv_criterion(x1, target1)
+
+            x2 = paddle.rand([5, 20], dtype='float64')
+            target2 = paddle.rand([5, 20], dtype='float32')
+            pred_loss2 = paddle.nn.functional.kl_div(x2, target2)
+
+
 if __name__ == "__main__":
     unittest.main()
diff --git a/python/paddle/nn/functional/loss.py b/python/paddle/nn/functional/loss.py
index 76722f26007..05daf24ca24 100644
--- a/python/paddle/nn/functional/loss.py
+++ b/python/paddle/nn/functional/loss.py
@@ -800,6 +800,16 @@ def kl_div(input, label, reduction='mean', name=None):
             # shape=[5, 20]
 
     """
+    # ugly type promotion
+    if fluid.data_feeder.convert_dtype(
+            input.dtype) == 'float32' and fluid.data_feeder.convert_dtype(
+                label.dtype) == 'float64':
+        input = fluid.layers.cast(input, 'float64')
+    elif fluid.data_feeder.convert_dtype(
+            input.dtype) == 'float64' and fluid.data_feeder.convert_dtype(
+                label.dtype) == 'float32':
+        label = fluid.layers.cast(label, 'float64')
+
     if paddle.in_dynamic_mode():
         out = core.ops.kldiv_loss(input, label, 'reduction', reduction)
         return out
-- 
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