add selected rows supported in framework (#21808)

* add selected rows supported in framework

python/paddle/fluid/framework.py

@@ -568,7 +568,6 @@ def _varbase_creator(type=core.VarDesc.VarType.LOD_TENSOR,
                      dtype=None,
                      persistable=None,
                      **kwargs):
-
     if dtype is not None:
         if not isinstance(dtype, core.VarDesc.VarType):
             dtype = convert_np_dtype_to_dtype_(dtype)
@@ -1398,6 +1397,10 @@ class Variable(object):
         # TODO(minqiyang): Support lod_level in dygraph mode
         if in_dygraph_mode():
             raise Exception("Dygraph model DO NOT supprt lod")
+
+        if self.type == core.VarDesc.VarType.SELECTED_ROWS:
+            raise Exception("SelectedRows DO NOT supprt lod")
+
         return self.desc.lod_level()
 
     @property
@@ -2445,7 +2448,7 @@ class Block(object):
                                    " is inited by multiple init ops " + str(
                                        init_ops))
             elif init_ops_len == 1:
-                #TODO already inited, do nothing, should log a warning
+                # TODO already inited, do nothing, should log a warning
                 pass
             else:
                 initializer(param, self)
@@ -3351,8 +3354,8 @@ class IrGraph(object):
             op_node(IrOpNode): the operator node that is needed to update input's link.
         """
         assert old_output_node.node in self.graph.nodes() and new_output_node.node in \
-        self.graph.nodes() and op_node.node in self.graph.nodes(), \
-        'The three arguments(old_output_node &new_output_node &op_node) must be in the graph nodes.'
+               self.graph.nodes() and op_node.node in self.graph.nodes(), \
+            'The three arguments(old_output_node &new_output_node &op_node) must be in the graph nodes.'
         old_output_node.remove_input(op_node)
         op_node.remove_output(old_output_node)
         new_output_node.append_input(op_node)
@@ -4525,7 +4528,12 @@ class Parameter(Variable):
             be applied on this parameter.
     """
 
-    def __init__(self, block, shape, dtype, **kwargs):
+    def __init__(self,
+                 block,
+                 shape,
+                 dtype,
+                 type=core.VarDesc.VarType.LOD_TENSOR,
+                 **kwargs):
         if shape is None:
             raise ValueError("The shape of Parameter should not be None")
         if dtype is None:
@@ -4542,7 +4550,13 @@ class Parameter(Variable):
                     % list(shape))
 
         Variable.__init__(
-            self, block, persistable=True, shape=shape, dtype=dtype, **kwargs)
+            self,
+            block,
+            persistable=True,
+            shape=shape,
+            dtype=dtype,
+            type=type,
+            **kwargs)
         self.trainable = kwargs.get('trainable', True)
 
         self.optimize_attr = kwargs.get('optimize_attr', {'learning_rate': 1.0})
@@ -4660,7 +4674,7 @@ class ParamBase(core.VarBase):
 
         self.is_distributed = False
 
-        #self.block = default_main_program().global_block()
+        # self.block = default_main_program().global_block()
 
         _dygraph_tracer().trace_var(name, self)
 

python/paddle/fluid/layer_helper_base.py

@@ -280,7 +280,8 @@ class LayerHelperBase(object):
                          dtype,
                          is_bias=False,
                          default_initializer=None,
-                         stop_gradient=False):
+                         stop_gradient=False,
+                         type=core.VarDesc.VarType.LOD_TENSOR):
         """Create parameters for this layers.
 
            Args:
@@ -334,15 +335,17 @@ class LayerHelperBase(object):
             return self.main_program.global_block().create_parameter(
                 dtype=dtype,
                 shape=shape,
+                type=type,
                 stop_gradient=stop_gradient,
                 **attr._to_kwargs(with_initializer=True))
         else:
             self.startup_program.global_block().create_parameter(
                 dtype=dtype,
                 shape=shape,
+                type=type,
                 **attr._to_kwargs(with_initializer=True))
             return self.main_program.global_block().create_parameter(
-                dtype=dtype, shape=shape, **attr._to_kwargs())
+                dtype=dtype, shape=shape, type=type, **attr._to_kwargs())
 
     def create_variable_for_type_inference(self, dtype, stop_gradient=False):
         """Create a temporary variable that should be type inferred layer.

python/paddle/fluid/optimizer.py

@@ -324,7 +324,8 @@ class Optimizer(object):
                          param,
                          dtype=None,
                          fill_value=0.0,
-                         shape=None):
+                         shape=None,
+                         type=None):
         """Utility function to add an accumulator for a parameter
 
         Args:
@@ -354,7 +355,7 @@ class Optimizer(object):
             name=var_name,
             persistable=True,
             dtype=dtype or param.dtype,
-            type=param.type,
+            type=param.type if type is None else type,
             shape=shape,
             belong_to_optimizer=True)
         self.helper.set_variable_initializer(
@@ -1635,13 +1636,15 @@ class AdamOptimizer(Optimizer):
                 param=p,
                 fill_value=0.9 if isinstance(self._beta1, Variable) \
                         else self._beta1,
-                shape=[1])
+                shape=[1],
+                type=core.VarDesc.VarType.LOD_TENSOR)
             self._add_accumulator(
                 name=self._beta2_pow_acc_str,
                 param=p,
                 fill_value=0.999 if isinstance(self._beta2, Variable) \
                         else self._beta2,
-                shape=[1])
+                shape=[1],
+                type=core.VarDesc.VarType.LOD_TENSOR)
 
     def _append_optimize_op(self, block, param_and_grad):
         assert isinstance(block, framework.Block)

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

@@ -206,6 +206,21 @@ class TestVariable(unittest.TestCase):
             self.assertIsNone(var.dtype)
             self.assertIsNone(var.type)
 
+    def test_create_selected_rows(self):
+        b = default_main_program().current_block()
+
+        var = b.create_var(
+            name="var",
+            shape=[1, 1],
+            dtype="float32",
+            type=fluid.core.VarDesc.VarType.SELECTED_ROWS,
+            persistable=True)
+
+        def _test():
+            var.lod_level()
+
+        self.assertRaises(Exception, _test)
+
 
 if __name__ == '__main__':
     unittest.main()