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- # -*- coding: utf-8 -*-
- # MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
- #
- # Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
- #
- # Unless required by applicable law or agreed to in writing,
- # software distributed under the License is distributed on an
- # "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- import abc
- import weakref
- from typing import Any, Dict, List, Tuple, Type
-
- import numpy
-
- from ...core._imperative_rt.core2 import Tensor as RawTensor
- from ...module import Module
- from ...tensor import Tensor
-
-
- class Node:
- """
- ``Node`` represents the variables (Tensor/Module/other python object) used in Module's forward method. They are inputs/outputs of Expr(the operations on variables).
-
- param expr: the Expr which produces the node
- param name: the name of the node
- """
-
- expr = None
- __total_id = 0
- _id = None
- _name = None
- _top_graph = None # type: weakref.ReferenceType
-
- def __init__(self, expr: "Expr", name: str = None):
- self.expr = expr
- self.users = [] # List[Expr]
- self._id = Node.__total_id
- Node.__total_id += 1
- self._name = name
-
- def __setstate__(self, d):
- self.__dict__ = d
- Node.__total_id = max(Node.__total_id, self._id) + 1
-
- def __repr__(self):
- if self._name is None:
- return "%{}".format(self._id)
- else:
- return "%{}".format(self._name)
-
- @property
- def top_graph(self):
- if self._top_graph:
- return self._top_graph()
- return None
-
-
- class ModuleNode(Node):
- """
- ``ModuleNode`` represents the Module objects.
-
- Attributes:
- module_type: type of the Module correspending to the ModuleNode
- graph: the InternalGraph which will be interpreted when call Module's forward method
- attr_type_map: record the type of Module's attributes
- """
-
- module_type = Module # type: Type[Module]
- _owner = None # type: weakref.ReferenceType
-
- def __init__(self, expr: "Expr", name: str = None):
- super().__init__(expr, name)
- self.actual_mnode = []
-
- def __repr__(self):
- if self._name is None:
- return "%{}_({})".format(self._id, self.module_type.__name__)
- else:
- return "%{}_{}({})".format(self._id, self._name, self.module_type.__name__)
-
- def __getstate__(self):
- return {
- "expr": self.expr,
- "users": self.users,
- "_id": self._id,
- "_name": self._name,
- "module_type": self.module_type,
- }
-
- @property
- def owner(self):
- if self._owner:
- return self._owner()
- return None
-
-
- class TensorNode(Node):
- """
- ``TensorNode`` represents the Tensor objects.
- """
-
- shape = None # type: Tuple[int]
- dtype = None # type: numpy.dtype
- qparam = None
- device = None
-
- def __repr__(self):
- if self._name is None:
- return "%{}_(Tensor)".format(self._id)
- else:
- return "%{}_{}(Tensor)".format(self._id, self._name)
-
- def __getstate__(self):
- return {
- "expr": self.expr,
- "users": self.users,
- "_id": self._id,
- "qparam": self.qparam,
- "shape": self.shape,
- "dtype": self.dtype,
- "device": self.device,
- }
-
-
- class NodeMixin(abc.ABC):
- __node = None
-
- @abc.abstractmethod
- def _record_wrapped_nodes(self, node):
- # record the nodes which had been bound to this NodeMixin
- pass
-
- @classmethod
- def _record_tensornode_property(cls, node, value):
- assert isinstance(node, TensorNode)
- assert isinstance(value, RawTensor)
- if isinstance(value, RawTensor):
- node.dtype = value.dtype
- node.shape = (
- value._tuple_shape if isinstance(value, Tensor) else value.shape
- )
- node.device = value.device
- if hasattr(value, "_qparams") and value._qparams is not None:
- node.qparams = value.qparams
-
- @classmethod
- def wrap(cls, value, node):
- if isinstance(value, (NodeMixin, RawTensor)):
- if isinstance(node, Node):
- if isinstance(value, RawTensor):
- cls._record_tensornode_property(node, value)
- if isinstance(value, NodeMixin):
- value._record_wrapped_nodes(node)
- setattr(value, "_NodeMixin__node", node)
- else:
- assert callable(node)
- n = node()
- assert isinstance(n, Node)
- if isinstance(value, RawTensor):
- cls._record_tensornode_property(n, value)
- if isinstance(value, NodeMixin):
- value._record_wrapped_nodes(n)
- setattr(value, "_NodeMixin__node", n)
-
- @classmethod
- def wrap_safe(cls, value, node):
- assert isinstance(value, (NodeMixin, RawTensor))
- if isinstance(value, RawTensor):
- cls._record_tensornode_property(node, value)
- setattr(value, "_NodeMixin__node", node)
- if isinstance(value, NodeMixin):
- value._record_wrapped_nodes(node)
-
- @classmethod
- def get(cls, value, *default):
- return getattr(value, "_NodeMixin__node", *default)
-
- @classmethod
- def get_wrapped_type(cls, value):
- if isinstance(value, RawTensor):
- return TensorNode
- if isinstance(value, (Module, NodeMixin)):
- return ModuleNode
- return Node
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