|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
from dataclasses import dataclass, field |
|
|
from typing import Any, Dict, List, Tuple |
|
|
from functools import reduce |
|
|
|
|
|
import torch |
|
|
from torch.fx import Graph, Node |
|
|
|
|
|
from .fx import get_output_node |
|
|
from .util import get_param_nodes |
|
|
|
|
|
|
|
|
@dataclass |
|
|
class DSGraphParam: |
|
|
name: str |
|
|
shape: torch.Size |
|
|
dtype: torch.dtype |
|
|
device: torch.device |
|
|
node: Node |
|
|
allgather_node: Node |
|
|
release_node: Node |
|
|
param: torch.Tensor |
|
|
numel: int = field(init=False) |
|
|
|
|
|
def __post_init__(self): |
|
|
self.numel = reduce(lambda x, y: x * y, self.shape) |
|
|
|
|
|
|
|
|
class DSGraphParamManager: |
|
|
|
|
|
def __init__(self, fw_graph: Graph, sample_inputs: Any, index_to_ds_ids: List[Tuple[int, int, int]]): |
|
|
self._fw_graph = fw_graph |
|
|
self._bw_graph = None |
|
|
self._params: Dict[str, DSGraphParam] = {} |
|
|
self._param_name_to_grad: Dict[str, Node] = {} |
|
|
self._ds_ids: Dict[str, int] = {} |
|
|
|
|
|
param_nodes = get_param_nodes(fw_graph, index_to_ds_ids) |
|
|
self._param_names = [pn.name for pn in param_nodes] |
|
|
self._param_indices = [i for i, _, _ in index_to_ds_ids] |
|
|
|
|
|
param_inputs = [sample_inputs[i] for i, _, _ in index_to_ds_ids] |
|
|
ds_ids = [ds_id for _, ds_id, _ in index_to_ds_ids] |
|
|
ds_shapes = [ds_shape for _, _, ds_shape in index_to_ds_ids] |
|
|
|
|
|
for pn, pi, ds_id, ds_shape in zip(param_nodes, param_inputs, ds_ids, ds_shapes): |
|
|
self._params[pn.name] = DSGraphParam(name=pn.name, |
|
|
shape=ds_shape, |
|
|
dtype=pi.dtype, |
|
|
device=pi.device, |
|
|
node=pn, |
|
|
allgather_node=None, |
|
|
release_node=None, |
|
|
param=pi) |
|
|
self._ds_ids[pn.name] = ds_id |
|
|
|
|
|
def get_bwd_mapping(self, bw_graph: Graph): |
|
|
self._bw_graph = bw_graph |
|
|
|
|
|
output_node = get_output_node(bw_graph) |
|
|
param_nodes_bw = [n for n in self._bw_graph.nodes if n.name in self.param_names] |
|
|
grad_outputs = [output_node.args[0][i] for i in self._param_indices] |
|
|
param_name_to_grad = {param_name: grad for param_name, grad in zip(self.param_names, grad_outputs)} |
|
|
return param_nodes_bw, param_name_to_grad |
|
|
|
|
|
@property |
|
|
def param_names(self) -> List[str]: |
|
|
return self._param_names |
|
|
|
|
|
@property |
|
|
def params(self) -> Dict[str, DSGraphParam]: |
|
|
return self._params |
|
|
|
|
|
@property |
|
|
def ds_ids(self) -> Dict[str, int]: |
|
|
return self._ds_ids |
|
|
|
|
|
def get_grad_name(self, param_name) -> str: |
|
|
assert self._param_name_to_grad is not None, "Backward graph is not added yet" |
|
|
return self._param_name_to_grad[param_name] |
|
|
|
