support tuple/list init for VarBase (#25231)

* support tuple/list init for VarBase,test=develop

* fix doc of fluid.dygraph.to_variable,test=develop

* fix doc of fluid.dygraph.to_variable,test=develop

python/paddle/fluid/dygraph/base.py

@@ -23,6 +23,7 @@ from paddle.fluid.multiprocess_utils import CleanupFuncRegistrar
 from .tracer import Tracer
 import logging
 import objgraph
+from ..data_feeder import convert_dtype
 
 __all__ = [
     'no_grad',
@@ -539,28 +540,34 @@ def grad(outputs,
 
 
 @framework.dygraph_only
-def to_variable(value, name=None, zero_copy=None):
+def to_variable(value, name=None, zero_copy=None, dtype=None):
     """
     :api_attr: imperative
 
     The API will create a ``Variable`` or ``ComplexVariable`` object from 
-    numpy\.ndarray, Variable or ComplexVariable object.
+    tuple, list, numpy\.ndarray, Variable or ComplexVariable object.
 
     Parameters:
-        value(ndarray|Variable|Tensor|ComplexVariable): The numpy\.ndarray, Variable 
-            Tensor or ComplexVariable object that needs to be converted, it can be 
-            multi-dimension, and the data type is one of numpy\.{float16, 
-            float32, float64, int16, int32, int64, uint8, uint16, complex64, 
-            complex128}.
+        value(tuple|list|ndarray|Variable|Tensor|ComplexVariable): Initial data. 
+            Can be a list, tuple, NumPy ndarray, Variable, Tensor, ComplexVariable. 
+            The shape can be multi-dimensional. The data type is one of 
+            numpy\.{float16, float32, float64, int16, int32, int64, 
+            uint8, uint16, complex64, complex128}.
         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` .
         zero_copy(bool, optional): Whether to share memory with the input numpy 
             array. This parameter only works with CPUPlace and will be set to 
             True when it is None. Default: None.
+        dtype(str, optional): The desired data type of returned ``Variable`` .
+            Can be 'bool' , 'float16' , 'float32' , 'float64' , 'int8' , 'int16' , 
+            'int32' , 'int64' , 'uint8' . Default: None.
 
     Returns:
-        Variable or ComplexVariable: If ``value`` is a numpy\.ndarray object, return ``Tensor`` created from the specified numpy\.ndarray object, which has same data type and shape with ``value``. If ``value`` is a Variable or ComplexVariable object, just return ``value``.
+        Variable or ComplexVariable: If ``value`` is a tuple/list/numpy\.ndarray object, 
+            return ``Tensor`` created from the corresponding numpy\.ndarray object, which has 
+            same data type and shape with ``value``. If ``value`` is a Variable or ComplexVariable 
+            object, just return ``value``.
 
 
     Examples:
@@ -582,17 +589,41 @@ def to_variable(value, name=None, zero_copy=None):
             z = fluid.dygraph.to_variable(c)
             z.numpy() # array([2.+1.j, 2.+0.j])
             z.dtype # 'complex128'
+
+            y = fluid.dygraph.to_variable([[0.1, 1.2], [2.2, 3.1], [4.9, 5.2]])
+            y.shape     # [3L, 2L]
+
+            y = fluid.dygraph.to_variable(((0.1, 1.2), (2.2, 3.1), (4.9, 5.2)), dtype='int32')
+            y.shape     # [3L, 2L]
+
     """
-    if isinstance(value, np.ndarray):
-        assert framework.in_dygraph_mode(
-        ), "to_variable could only be called in dygraph mode"
+    support_type = (list, tuple, np.ndarray, core.VarBase, framework.Variable,
+                    framework.ComplexVariable, core.Tensor, core.LoDTensor)
+    if not isinstance(value, support_type):
+        raise TypeError(
+            "The type of 'value' in fluid.dygraph.to_variable must be %s, but received %s."
+            % (support_type, type(value)))
+    if isinstance(value, (core.VarBase, framework.Variable,
+                          framework.ComplexVariable)):
+        return value
+    elif isinstance(value, (core.Tensor, core.LoDTensor)):
+        return core.VarBase(value)
+    else:
         if isinstance(framework._current_expected_place(),
                       framework.core.CPUPlace):
             if zero_copy is None:
                 zero_copy = True
         else:
             assert not zero_copy, "zero_copy mode can only be used with CPUPlace"
-            zero_copy = False
+
+        if not isinstance(value, np.ndarray):
+            value = np.array(value)
+
+        if dtype is not None:
+            dtype = convert_dtype(dtype)
+            if value.dtype != dtype:
+                value = value.astype(dtype)
+
         if np.iscomplexobj(value):
             if not name:
                 name = framework.unique_name.generate('_generated_var')
@@ -617,12 +648,3 @@ def to_variable(value, name=None, zero_copy=None):
                 zero_copy=zero_copy,
                 name=name if name else '')
             return py_var
-    elif isinstance(value, (core.VarBase, framework.Variable,
-                            framework.ComplexVariable)):
-        return value
-    elif isinstance(value, (core.Tensor, core.LoDTensor)):
-        return core.VarBase(value)
-    else:
-        raise TypeError(
-            "The type of input value is invalid, expected type is 'ndarray', "
-            "'Variable' or 'ComplexVariable', but received %s." % type(value))

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

@@ -47,6 +47,24 @@ class TestVarBase(unittest.TestCase):
                 linear = fluid.dygraph.Linear(32, 64)
                 var = linear._helper.to_variable("test", name="abc")
 
+    def test_list_to_variable(self):
+        with fluid.dygraph.guard():
+            array = [[[1, 2], [1, 2], [1.0, 2]], [[1, 2], [1, 2], [1, 2]]]
+            var = fluid.dygraph.to_variable(array, dtype='int32')
+            self.assertTrue(np.array_equal(var.numpy(), array))
+            self.assertEqual(var.shape, [2, 3, 2])
+            self.assertEqual(var.dtype, core.VarDesc.VarType.INT32)
+            self.assertEqual(var.type, core.VarDesc.VarType.LOD_TENSOR)
+
+    def test_tuple_to_variable(self):
+        with fluid.dygraph.guard():
+            array = (((1, 2), (1, 2), (1, 2)), ((1, 2), (1, 2), (1, 2)))
+            var = fluid.dygraph.to_variable(array, dtype='float32')
+            self.assertTrue(np.array_equal(var.numpy(), array))
+            self.assertEqual(var.shape, [2, 3, 2])
+            self.assertEqual(var.dtype, core.VarDesc.VarType.FP32)
+            self.assertEqual(var.type, core.VarDesc.VarType.LOD_TENSOR)
+
     def test_tensor_to_variable(self):
         with fluid.dygraph.guard():
             t = fluid.Tensor()