change shape of output in cross_entropy, test=develop (#29220)

python/paddle/fluid/tests/unittests/test_cross_entropy_loss.py

@@ -219,6 +219,47 @@ class CrossEntropyLoss(unittest.TestCase):
         self.assertTrue(np.allclose(static_ret, expected))
         self.assertTrue(np.allclose(dy_ret_value, expected))
 
+    def test_cross_entropy_loss_1d_with_weight_none_func(self):
+        input_np = np.random.random([100, 200]).astype(np.float64)  #N,C
+        label_np = np.random.randint(0, 100, size=(100)).astype(np.int64)  #N
+        weight_np = np.random.random([200]).astype(np.float64)  #C
+        paddle.enable_static()
+        prog = fluid.Program()
+        startup_prog = fluid.Program()
+        place = fluid.CUDAPlace(0) if fluid.core.is_compiled_with_cuda(
+        ) else fluid.CPUPlace()
+        with fluid.program_guard(prog, startup_prog):
+            input = fluid.data(name='input', shape=[100, 200], dtype='float64')
+            label = fluid.data(name='label', shape=[100], dtype='int64')
+            weight = fluid.data(name='weight', shape=[200], dtype='float64')
+            ret = paddle.nn.functional.cross_entropy(
+                input, label, weight=weight, reduction='none')
+
+            exe = fluid.Executor(place)
+            static_ret = exe.run(prog,
+                                 feed={
+                                     'input': input_np,
+                                     'label': label_np,
+                                     "weight": weight_np
+                                 },
+                                 fetch_list=[ret])
+            static_ret = np.squeeze(static_ret)
+            self.assertIsNotNone(static_ret)
+        with fluid.dygraph.guard():
+            dy_ret = paddle.nn.functional.cross_entropy(
+                fluid.dygraph.to_variable(input_np),
+                fluid.dygraph.to_variable(label_np),
+                weight=fluid.dygraph.to_variable(weight_np),
+                reduction='none')
+            dy_ret_value = dy_ret.numpy()
+            dy_ret_value = np.squeeze(dy_ret_value)
+            self.assertIsNotNone(dy_ret_value)
+        expected = cross_entropy_loss_1d(
+            input_np, label_np, weight=weight_np, reduction='none')
+        self.assertTrue(np.allclose(static_ret, dy_ret_value))
+        self.assertTrue(np.allclose(static_ret, expected))
+        self.assertTrue(np.allclose(dy_ret_value, expected))
+
     def test_cross_entropy_loss_1d_mean(self):
         input_np = np.random.random([100, 200]).astype(np.float64)  #N,C
         label_np = np.random.randint(0, 100, size=(100)).astype(np.int64)  #N,1

python/paddle/nn/functional/loss.py

@@ -1236,6 +1236,8 @@ def cross_entropy(input,
             else:
                 return core.ops.mean(out)
         else:
+            if input_dims - 1 == label_dims:
+                out = paddle.squeeze(out, axis=axis)
             return out
 
     fluid.data_feeder.check_variable_and_dtype(
@@ -1267,6 +1269,9 @@ def cross_entropy(input,
         else:
             return paddle.mean(out, name=name)
     else:
+        if input_dims - 1 == label_dims:
+            out = paddle.squeeze(out, axis=axis)
+
         return out