diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py index e3d764b892fc209a9339faea9ac9b15032d33dd5..aabb288d45a99efeea70a44add4b1a3d75b0cf50 100644 --- a/python/paddle/fluid/framework.py +++ b/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) diff --git a/python/paddle/fluid/layer_helper_base.py b/python/paddle/fluid/layer_helper_base.py index 7e904ff31e247aa922fb918a6191f251ecde4342..adfeedac3121f6e97cef89c9254b63f447b4bfb7 100644 --- a/python/paddle/fluid/layer_helper_base.py +++ b/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. diff --git a/python/paddle/fluid/optimizer.py b/python/paddle/fluid/optimizer.py index aa8f9291a37859b4e9aecd37e705b4d1a7c4033e..c4df68e2e1a89b55c617b65c68830eda42c1d575 100644 --- a/python/paddle/fluid/optimizer.py +++ b/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) diff --git a/python/paddle/fluid/tests/unittests/test_variable.py b/python/paddle/fluid/tests/unittests/test_variable.py index f4f4749e0c0a562ee91564af68b74554f765b2e7..5023d0e87d50eb7e34ccadc2455cbe7250d16f9f 100644 --- a/python/paddle/fluid/tests/unittests/test_variable.py +++ b/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()