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PaddlePaddle · Nov 2, 2024 · 9ac124d · 9ac124d
1 parent 33efec7
commit 9ac124d
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Showing 2 changed files with 75 additions and 12 deletions.
diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py
@@ -3814,8 +3814,16 @@ def clip(
         min_n = check_clip_tensor(x, min, min_, value_dtype, 'min')
         max_n = check_clip_tensor(x, max, max_, value_dtype, 'max')
 
-        min_n = paddle.broadcast_to(min_n, x.shape) if min_n.shape != x.shape else min_n
-        max_n = paddle.broadcast_to(max_n, x.shape) if max_n.shape != x.shape else max_n
+        min_n = (
+            paddle.broadcast_to(min_n, x.shape)
+            if min_n.shape != x.shape
+            else min_n
+        )
+        max_n = (
+            paddle.broadcast_to(max_n, x.shape)
+            if max_n.shape != x.shape
+            else max_n
+        )
 
         output_min = paddle.where(x < min_n, min_n, x)
         output = paddle.where(output_min > max_n, max_n, output_min)
@@ -3921,8 +3929,16 @@ def clip_(
             max = check_clip_tensor(x, max, fmin, x.dtype, 'max')
             min = check_clip_tensor(x, min, fmin, x.dtype, 'min')
 
-            max_expand = paddle.broadcast_to(max, x.shape) if max.shape != x.shape else max
-            min_expand = paddle.broadcast_to(min, x.shape) if min.shape != x.shape else min
+            max_expand = (
+                paddle.broadcast_to(max, x.shape)
+                if max.shape != x.shape
+                else max
+            )
+            min_expand = (
+                paddle.broadcast_to(min, x.shape)
+                if min.shape != x.shape
+                else min
+            )
 
             paddle.where_(x > min_expand, x, min_expand)
             return paddle.where_(x < max_expand, x, max_expand)

diff --git a/test/legacy_test/test_clip_tensor_op.py b/test/legacy_test/test_clip_tensor_op.py
@@ -117,17 +117,13 @@ def test_static_clip(self):
         )
         data = np.random.random(data_shape).astype('float32')
         min_data = np.random.random([1]).astype('float32')
-        max_data = min_data + 10.
+        max_data = min_data + 10.0
         paddle.enable_static()
         with paddle.static.program_guard(paddle.static.Program()):
             x = paddle.static.data(name='x', shape=data_shape, dtype='float32')
-            min = paddle.static.data(
-                name='min', shape=[1], dtype='float32'
-            )
-            max = paddle.static.data(
-                name='max', shape=[1], dtype='float32'
-            )
-            out = paddle.clip(x, min)
+            min = paddle.static.data(name='min', shape=[1], dtype='float32')
+            max = paddle.static.data(name='max', shape=[1], dtype='float32')
+            out = paddle.clip(x, min, max)
             exe = base.Executor(self.place)
             res = exe.run(
                 feed={"x": data, 'min': min_data, 'max': max_data},
@@ -137,6 +133,34 @@ def test_static_clip(self):
             np.testing.assert_allclose(res_np, res[0], rtol=1e-05)
         paddle.disable_static()
 
+        if base.core.is_compiled_with_cuda():
+            paddle.enable_static()
+            data_shape = [1, 9, 9, 4]
+            data = np.random.random(data_shape).astype('float16')
+
+            with paddle.static.program_guard(paddle.static.Program()):
+                images = paddle.static.data(
+                    name='image1', shape=data_shape, dtype='float16'
+                )
+                min = paddle.static.data(
+                    name='min1', shape=[1], dtype='float16'
+                )
+                max = paddle.static.data(
+                    name='max1', shape=[1], dtype='float16'
+                )
+                out = paddle.clip(images, min, max)
+                place = paddle.CUDAPlace(0)
+                exe = paddle.static.Executor(place)
+                res1 = exe.run(
+                    feed={
+                        "image1": data,
+                        "min1": np.array([0.2]).astype('float16'),
+                        "max1": np.array([0.8]).astype('float16'),
+                    },
+                    fetch_list=[out],
+                )
+            paddle.disable_static()
+
     def test_dygraph_clip(self):
         self.place = (
             base.CUDAPlace(0)
@@ -197,6 +221,29 @@ def test_dygraph_clip(self):
         out = paddle.clip(data, min_data, max_data)
         np.testing.assert_allclose(out.numpy(), out_np, rtol=1e-05)
 
+        if base.core.is_compiled_with_cuda():
+            data_shape = [1, 2, 3, 4]
+            data = np.random.random(data_shape).astype('float16')
+            min_data = np.random.random(data_shape[-2:]).astype('float16')
+            max_data = np.random.random(data_shape[-1:]).astype('float16')
+            out_np = np.clip(data, min_data, max_data)
+            data = paddle.to_tensor(data)
+            min_data = paddle.to_tensor(min_data)
+            max_data = paddle.to_tensor(max_data)
+            out = paddle.clip(data, min_data, max_data)
+            np.testing.assert_allclose(out.numpy(), out_np, rtol=1e-05)
+
+            data_shape = [1, 2, 3, 4]
+            data = np.random.random(data_shape).astype('float16')
+            min_data = -10.0
+            max_data = 10.0
+            out_np = np.clip(data, min_data, max_data)
+            data = paddle.to_tensor(data)
+            min_data = paddle.to_tensor(min_data)
+            max_data = paddle.to_tensor(max_data)
+            out = paddle.clip(data, min_data, max_data)
+            np.testing.assert_allclose(out.numpy(), out_np, rtol=1e-05)
+
         paddle.enable_static()
 
     def test_shapeerror_clip(self):