Fix bug: delete wrong check_type of paddle.concat and support LoDTensorArray (#29306)

python/paddle/fluid/layers/tensor.py

@@ -327,6 +327,10 @@ def concat(input, axis=0, name=None):
     out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())
 
     if input[0].desc.type() == core.VarDesc.VarType.LOD_TENSOR_ARRAY:
+        # NOTE(liym27): Don't remove this if branch!
+        # This feature is supported for Dynamic-to-Static, because after transformed, the type of inputs[0]
+        # is LOD_TENSOR_ARRAY in some scenarios. And this feature can be used in static mode.
+
         assert len(input) == 1, "If the elements of 'input' in concat are Variable(LoDTensorArray), " \
                 "number of the elements must be 1, but received %s." % len(input)
         out_index = helper.create_variable_for_type_inference(dtype="int32")

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

@@ -228,6 +228,7 @@ class TestConcatOpError(unittest.TestCase):
 
 class TestConcatAPI(unittest.TestCase):
     def test_fluid_api(self):
+        paddle.enable_static()
         x_1 = fluid.data(shape=[None, 1, 4, 5], dtype='int32', name='x_1')
         fluid.layers.concat([x_1, x_1], 0)
 
@@ -253,6 +254,7 @@ class TestConcatAPI(unittest.TestCase):
         assert np.array_equal(res_3, np.concatenate((input_2, input_3), axis=1))
 
     def test_api(self):
+        paddle.enable_static()
         x_1 = paddle.fluid.data(
             shape=[None, 1, 4, 5], dtype='int32', name='x_1')
         paddle.concat([x_1, x_1], 0)
@@ -338,21 +340,44 @@ class TestConcatAPIWithLoDTensorArray(unittest.TestCase):
         self.x = np.random.random(self.input_shape).astype("float32")
         self.place = fluid.CUDAPlace(0) \
             if fluid.is_compiled_with_cuda() else fluid.CPUPlace()
-        self.set_program()
 
-    def set_program(self):
-        self.program = fluid.Program()
-        with fluid.program_guard(self.program):
-            input = fluid.layers.assign(self.x)
-            tensor_array = fluid.layers.create_array(dtype='float32')
-            zero = fluid.layers.fill_constant(shape=[1], value=0, dtype="int64")
+    def set_program(self, use_fluid_api):
+        paddle.enable_static()
+        if use_fluid_api:
+            self.program = fluid.Program()
+            with fluid.program_guard(self.program):
+                input = fluid.layers.assign(self.x)
+                tensor_array = fluid.layers.create_array(dtype='float32')
+                zero = fluid.layers.fill_constant(
+                    shape=[1], value=0, dtype="int64")
+
+                for i in range(self.iter_num):
+                    fluid.layers.array_write(input, zero + i, tensor_array)
+
+                self.out_var = fluid.layers.concat(tensor_array, axis=self.axis)
+        else:
+            self.program = paddle.static.Program()
+            with paddle.static.program_guard(self.program):
+                input = paddle.assign(self.x)
+                tensor_array = fluid.layers.create_array(
+                    dtype='float32'
+                )  # Api create_array is not supported in paddle 2.0 yet.
+                zero = paddle.zeros(shape=[1], dtype="int64")
 
-            for i in range(self.iter_num):
-                fluid.layers.array_write(input, zero + i, tensor_array)
+                for i in range(self.iter_num):
+                    # Api array_write is not supported in paddle 2.0 yet.
+                    fluid.layers.array_write(input, zero + i, tensor_array)
+
+                self.out_var = paddle.concat(tensor_array, axis=self.axis)
+
+    def test_fluid_api(self):
+        self._run_static_mode(use_fluid_api=True)
 
-            self.out_var = fluid.layers.concat(tensor_array, axis=self.axis)
+    def test_paddle_api(self):
+        self._run_static_mode(use_fluid_api=False)
 
-    def test_case(self):
+    def _run_static_mode(self, use_fluid_api):
+        self.set_program(use_fluid_api)
         self.assertTrue(self.out_var.shape[self.axis] == -1)
         exe = fluid.Executor(self.place)
         res = exe.run(self.program, fetch_list=self.out_var)

python/paddle/tensor/manipulation.py

@@ -71,7 +71,7 @@ def concat(x, axis=0, name=None):
     This OP concatenates the input along the axis.
 
     Args:
-        x(list|tuple): ``x`` is a Tensor list or Tensor tuple which is with data type bool, float16, 
+        x(list|tuple): ``x`` is a Tensor list or Tensor tuple which is with data type bool, float16,
             float32, float64, int32, int64. All the Tensors in ``x`` must have same data type.
         axis(int|Tensor, optional): Specify the axis to operate on the input Tensors.
             It's a scalar with data type int or a Tensor with shape [1] and data type int32 
@@ -110,7 +110,6 @@ def concat(x, axis=0, name=None):
             #  [11 12 13]
             #  [14 15 16]]
     """
-    check_type(x, 'x', (list, tuple), 'concat')
     return paddle.fluid.layers.concat(input=x, axis=axis, name=name)