py:解决循环import

Author: miaobyte

front/py/deepx/autograd/_tensornode.py

@@ -1,5 +1,4 @@
 from .node import Node, NodeType
-from deepx import Tensor
 
 class TensorNode(Node):
     def __init__(self, name=None):
@@ -10,6 +9,7 @@ def tensor(self):
         return self._tensor
 
     def set_tensor(self, tensor):
+        from deepx import Tensor
         if not isinstance(tensor, Tensor):
             raise TypeError("tensor must be an instance of Tensor")
         self._tensor = tensor

front/py/deepx/autograd/node.py

@@ -6,23 +6,35 @@ class NodeType(IntEnum):
     CONST_ARG = 2
 
 class Node:
-    def __init__(self, name=None, ntype=NodeType.TENSOR):
-        self.ntype = ntype
-        self.name = name
+    def __init__(self, 
+                 ntype:NodeType=NodeType.TENSOR,
+                   name:str=None,
+                   graph =None):
+        from .graph import Graph
+        if graph == None:
+            self._graph = Graph.get_default()
+        else:
+            self._graph = graph
+
+        self._ntype = ntype
+        self._name = name
         self._inputs = {}
         self.attrs = {}
 
+    @property
     def ntype(self):
-        return self.ntype
+        return self._ntype
 
+    @property
     def name(self):
-        return self.name
-    
-    def inputs(self):
-        return self._inputs
-    
-    def input(self, name):
-        return self._inputs.get(name)
+        return self._name
+ 
+    @property
+    def input(self, name=None):
+        if name is None:
+            return self._inputs
+        else:
+            return self._inputs.get(name)
 
     def add_input(self, name, input_node):
         self._inputs[name] = input_node

front/py/deepx/autograd/op.py

@@ -1,6 +1,5 @@
 from typing import Any, Tuple, List, Optional
-from deepx  import Tensor
-from deepx.autograd.graph import Graph  
+from .graph import Graph  
 
 class Op:
     def __init__(self,args:List[str],returns:List[str],grad:bool,args_grad:List[str],returns_grad:List[str]):
@@ -11,9 +10,11 @@ def __init__(self,args:List[str],returns:List[str],grad:bool,args_grad:List[str]
         self._grad=grad
         self._args_grad=args_grad
         self._returns_grad=returns_grad
-    def forward(self, *input:Tensor) -> Tuple[Tensor, ...]:
+
+    def forward(self, *input) -> Tuple:
         raise NotImplementedError
-    def backward(self, *grad_outputs: Tensor) -> Tuple[Optional[Tensor], ...]:
+ 
+    def backward(self, *grad_outputs) -> Tuple:
         raise NotImplementedError
 
     def to_ir(self, dtype: str, is_backward: bool = False) -> str: