Add dygraph implementation for multiplex op (#29049)

python/paddle/fluid/layers/nn.py

@@ -5719,7 +5719,7 @@ def row_conv(input, future_context_size, param_attr=None, act=None):
 
 
 @templatedoc()
-def multiplex(inputs, index):
+def multiplex(inputs, index, name=None):
     """
 
     Based on the given index parameter, the OP selects a specific row from each input Tensor to construct the output Tensor.
@@ -5748,35 +5748,30 @@ def multiplex(inputs, index):
 
 
     Args:
-       inputs (list): The input Tensor list. The list elements are N-D Tensors of data types float32, float64, int32, int64. All input Tensor shapes should be the same and rank must be at least 2.
-       index (Variable): Used to select some rows in the input Tensor to construct an index of the output Tensor. It is a 2-D Tensor with data type int32 or int64 and shape [M, 1], where M is the number of input Tensors.
-
+        inputs (list): The input Tensor list. The list elements are N-D Tensors of data types float32, float64, int32, int64. All input Tensor shapes should be the same and rank must be at least 2.
+        index (Tensor): Used to select some rows in the input Tensor to construct an index of the output Tensor. It is a 2-D Tensor with data type int32 or int64 and shape [M, 1], where M is the number of input Tensors.
+        name(str, optional): The default value is None. Normally there is no
+            need for user to set this property. For more information, please
+            refer to :ref:`api_guide_Name`.
     Returns:
-        Variable(Tensor): Output of multiplex OP, with data type being float32, float64, int32, int64.
+        Tensor: Output of multiplex OP, with data type being float32, float64, int32, int64.
 
     Examples:
 
         .. code-block:: python
 
-            import paddle.fluid as fluid
+            import paddle
             import numpy as np
-
-            x1 = fluid.data(name='x1', shape=[None, 2], dtype='float32')
-            x2 = fluid.data(name='x2', shape=[None, 2], dtype='float32')
-            index = fluid.data(name='index', shape=[None, 1], dtype='int32')
-            out = fluid.layers.multiplex(inputs=[x1, x2], index=index)
-
-            exe = fluid.Executor(fluid.CPUPlace())
-            exe.run(fluid.default_startup_program())
-
             img1 = np.array([[1, 2], [3, 4]]).astype(np.float32)
             img2 = np.array([[5, 6], [7, 8]]).astype(np.float32)
-            index = np.array([[1], [0]]).astype(np.int32)
-
-            res = exe.run(fluid.default_main_program(), feed={'x1':img1, 'x2':img2, 'index':index}, fetch_list=[out])
+            inputs = [paddle.to_tensor(img1), paddle.to_tensor(img2)]
+            index = paddle.to_tensor(np.array([[1], [0]]).astype(np.int32))
+            res = paddle.multiplex(inputs, index)
             print(res) # [array([[5., 6.], [3., 4.]], dtype=float32)]
 
     """
+    if in_dygraph_mode():
+        return core.ops.multiplex(index, inputs)
     helper = LayerHelper('multiplex', **locals())
 
     check_type(inputs, 'inputs', (list), 'multiplex')

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

@@ -17,6 +17,7 @@ from __future__ import print_function
 import unittest
 import numpy as np
 from op_test import OpTest
+import paddle
 import paddle.fluid as fluid
 
 
@@ -91,5 +92,16 @@ class TestMultiplexOpError(unittest.TestCase):
             self.assertRaises(TypeError, test_type2)
 
 
+class TestMultiplexODygrap(unittest.TestCase):
+    def test_multiplex_dygraph(self):
+        paddle.disable_static()
+        img1 = np.array([[1, 2], [3, 4]]).astype(np.float32)
+        img2 = np.array([[5, 6], [7, 8]]).astype(np.float32)
+        inputs = [paddle.to_tensor(img1), paddle.to_tensor(img2)]
+        index = paddle.to_tensor(np.array([[1], [0]]).astype(np.int32))
+        res = paddle.multiplex(inputs, index)
+        paddle.enable_static()
+
+
 if __name__ == '__main__':
     unittest.main()