mindspore.rewrite.api.node 源代码

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"""Rewrite module api: Node."""

from typing import Union, Optional

from mindspore.nn import Cell
from mindspore.ops.primitive import Primitive
from mindspore import _checkparam as Validator
from ..node import Node as NodeImpl
from ..symbol_tree import SymbolTree as SymbolTreeImpl
from .node_type import NodeType
from .scoped_value import ScopedValue


[文档]class Node: """ A node is a data structure that expresses source code statements in a network. Each node usually corresponds to a statement in expanded forward evaluation process. Nodes can express a ``Cell`` call statement, a ``Primitive`` call statement, an arithmetic operation statement, a return statements, etc. of the forward calculation process. Args: node (NodeImpl): A handler of `NodeImpl`. It is recommended to call the specific methods in Node to create a Node, such as 'create_call_cell', rather than calling the Node's constructor directly. Don't care what `NodeImpl` is, just treat it as a handle. """ def __init__(self, node: NodeImpl): self._node = node def __eq__(self, other: 'Node'): if not isinstance(other, Node): return False return self._node == other._node
[文档] @staticmethod def create_call_cell(cell: Cell, targets: [Union[ScopedValue, str]], args: [ScopedValue] = None, kwargs: {str: ScopedValue}=None, name: str = "", is_sub_net: bool = False) -> 'Node': """ Create a node. Only support create from a `Cell` now. A node is corresponding to source code like: .. code-block:: `targets` = self.`name`(*`args`, **`kwargs`) Args: cell (Cell): Cell-operator of this forward-layer. targets (list[ScopedValue]): Indicate output names. Used as targets of an assign statement in source code. args (list[ScopedValue]): Indicate input names. Used as args of a call expression of an assign statement in source code. Default: ``None`` , which indicates the `cell` has no args inputs. kwargs (dict): Type of key must be `str` and type of value must be `ScopedValue`. Indicate keyword input names. Used as kwargs of a call expression of an assign statement in source code. Default: ``None`` , which indicates the `cell` has no kwargs inputs. name (str): Indicate the name of node. Used as field name in source code. Default is None. Rewrite will generate name from `targets` when name is None. Rewrite will check and ensure the uniqueness of `name` while node being inserted. Default: ``""`` . is_sub_net (bool): Indicate that is `cell` a network. If `is_sub_net` is true, Rewrite will try to parse the `cell` to a TreeNode, otherwise the `cell` is parsed to a CallCell node. Default: ``False`` . Returns: An instance of `Node`. Raises: TypeError: If `cell` is not a `Cell`. TypeError: If `targets` is not `list`. TypeError: If the type of `targets` is not in `[ScopedValue, str]`. TypeError: If arg in `args` is not a `ScopedValue`. TypeError: If key of `kwarg` is not a str or value of kwarg in `kwargs` is not a `ScopedValue`. Examples: >>> from mindspore.rewrite import SymbolTree, ScopedValue >>> import mindspore.nn as nn >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> node = stree.get_node("conv1") >>> position = stree.after(node) >>> new_node = node.create_call_cell(cell=nn.ReLU(), targets=['x'], ... args=[ScopedValue.create_naming_value('x')], name='new_relu') >>> stree.insert(position, new_node) >>> print(type(new_node)) <class 'mindspore.rewrite.api.node.Node'> """ Validator.check_value_type("cell", cell, [Cell, Primitive], "Node") Validator.check_element_type_of_iterable("targets", targets, [ScopedValue, str], "Node") Validator.check_value_type("name", name, [str], "Node") Validator.check_value_type("is_sub_net", is_sub_net, [bool], "Node") if args is not None: Validator.check_element_type_of_iterable("args", args, [ScopedValue], "Node") if kwargs is not None: Validator.check_element_type_of_dict("kwargs", kwargs, [str], [ScopedValue], "Node") return Node(NodeImpl.create_call_op(cell, None, targets, ScopedValue.create_naming_value(name, "self"), args, kwargs, name, is_sub_net))
def get_handler(self) -> NodeImpl: return self._node
[文档] def get_inputs(self) -> ['Node']: """ Gets a list of nodes whose output values are used as input values for the current node. Returns: A list of nodes. Examples: >>> from mindspore.rewrite import SymbolTree >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> node = stree.get_node("conv2") >>> inputs = node.get_inputs() >>> print([input.get_name() for input in inputs]) ['max_pool2d'] """ return [Node(node_impl) for node_impl in self._node.get_inputs()]
[文档] def get_users(self) -> ['Node']: """ Get a list of nodes that use the output of the current node as input. Returns: A list of nodes. Examples: >>> from mindspore.rewrite import SymbolTree >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> node = stree.get_node("conv1") >>> users = node.get_users() >>> print([user.get_name() for user in users]) ['relu'] """ belong_symbol_tree: SymbolTreeImpl = self._node.get_belong_symbol_tree() if belong_symbol_tree is None: return [] unique_results = [] for node_user in belong_symbol_tree.get_node_users(self._node): node = node_user[0] if node not in unique_results: unique_results.append(node) return [Node(node_impl) for node_impl in unique_results]
[文档] def set_arg(self, index: int, arg: Union[ScopedValue, str]): """ Set argument of current node. Args: index (int): Indicate which input being modified. arg (Union[ScopedValue, str]): New argument to been set. Raises: TypeError: If `index` is not a `int` number. TypeError: If the type of `arg` is not in [`ScopedValue`, `str`]. Examples: >>> from mindspore.rewrite import SymbolTree >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> node = stree.get_node("relu_3") >>> node.set_arg(0, "fc1") >>> print(node.get_args()) [fc1] """ Validator.check_value_type("index", index, [int], "Node") Validator.check_value_type("arg", arg, [ScopedValue, str], "Node") belong_symbol_tree: SymbolTreeImpl = self._node.get_belong_symbol_tree() if belong_symbol_tree is None: self._node.set_arg(arg, index) else: belong_symbol_tree.set_node_arg(self._node, index, arg)
[文档] def set_arg_by_node(self, arg_idx: int, src_node: 'Node', out_idx: Optional[int] = None): """ Set argument of current node by another Node. Args: arg_idx (int): Indicate which input being modified. src_node (Node): A `Node` as new input. Can be a node or name of node. out_idx (int, optional): Indicate which output of `src_node` as new input of current node. Default: ``None`` , which means use first output of `src_node` as new input. Raises: RuntimeError: If `src_node` is not belong to current `SymbolTree`. TypeError: If `arg_idx` is not a `int` number. ValueError: If `arg_idx` is out of range. TypeError: If `src_node` is not a `Node` instance. TypeError: If `out_idx` is not a `int` number. ValueError: If `out_idx` is out of range. ValueError: If `src_node` has multi-outputs while `out_idx` is None or `out_idx` is not offered. Examples: >>> from mindspore.rewrite import SymbolTree >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> src_node = stree.get_node("fc1") >>> dst_node = stree.get_node("relu_3") >>> dst_node.set_arg_by_node(0, src_node, 0) >>> print(dst_node.get_args()) [fc1] """ Validator.check_value_type("arg_idx", arg_idx, [int], "Node") Validator.check_value_type("src_node", src_node, [Node], "Node") if out_idx is not None: Validator.check_value_type("out_idx", out_idx, [int], "Node") belong_symbol_tree: SymbolTreeImpl = self._node.get_belong_symbol_tree() if belong_symbol_tree is None: self._node.set_arg_by_node(arg_idx, src_node._node, out_idx) else: belong_symbol_tree.set_node_arg_by_node(self._node, arg_idx, src_node.get_handler(), out_idx)
[文档] def get_targets(self) -> [ScopedValue]: """ Gets a list of output values for the current node. Returns: A list of outputs of type ``ScopedValue`` . """ return self._node.get_targets()
[文档] def get_name(self) -> str: """ Get the name of current node. When node has been inserted into `SymbolTree`, the name of node should be unique in `SymbolTree`. Returns: A string as name of node. Examples: >>> from mindspore.rewrite import SymbolTree >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> node = stree.get_node("conv1") >>> name = node.get_name() >>> print(name) conv1 """ return self._node.get_name()
[文档] def get_node_type(self) -> NodeType: """ Get the node_type of current node. See :class:`mindspore.rewrite.NodeType` for details on node types. Returns: A NodeType as node_type of node. Examples: >>> from mindspore.rewrite import SymbolTree >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> node = stree.get_node("conv1") >>> node_type = node.get_node_type() >>> print(node_type) NodeType.CallCell """ return self._node.get_node_type()
[文档] def get_instance_type(self) -> type: """ Gets the instance type called in the code corresponding to the current node. - When `node_type` of current node is `CallCell`, the code for that node calls an instance of type ``Cell`` . - When `node_type` of current node is `CallPrimitive`, the code for that node calls an instance of type ``Primitive`` . - When `node_type` of current node is `Tree`, the code for that node calls an instance of network type. - When `node_type` of current node is `Python`, `Input`, `Output` or `CallMethod`, the instance type is ``NoneType`` . Returns: The type of instance called in the statement corresponding to the current node. Examples: >>> from mindspore.rewrite import SymbolTree >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> node = stree.get_node("conv1") >>> instance_type = node.get_instance_type() >>> print(instance_type) <class 'mindspore.nn.layer.conv.Conv2d'> """ return self._node.get_instance_type()
def get_instance(self): return self._node.get_instance()
[文档] def get_args(self) -> [ScopedValue]: """ Get arguments of current node. Returns: A list of arguments of type ``ScopedValue`` . Examples: >>> from mindspore.rewrite import SymbolTree >>> # Define the network structure of LeNet5. Refer to >>> # https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/code/lenet.py >>> net = LeNet5() >>> stree = SymbolTree.create(net) >>> node = stree.get_node("conv1") >>> print(node.get_args()) [x] """ return self._node.get_args()
def get_kwargs(self) -> {str: ScopedValue}: return self._node.get_kwargs() def set_attribute(self, key: str, value): Validator.check_value_type("key", key, [str], "Node attribute") self._node.set_attribute(key, value) def get_attributes(self) -> {str: object}: return self._node.get_attributes() def get_attribute(self, key: str): Validator.check_value_type("key", key, [str], "Node attribute") return self._node.get_attribute(key)