dmlc--dgl
Lingfan Yu
deb653f8dc
* executor api * draft executor interface * WIP * revert changes to avoid conflict with api change * core scheduling logic * WIP: build graph adj * incidence matrix for in edges * support incidence matrix for partial recv nodes * improve * build adjmat in scheduler * graph store * get degree bucketing schedule * connect to c++ degree bucketing * conceptual executor creation code * executor comments * fix * more executor comments * WIP: full send_and_recv schedule * most schedulers * simplify scheduler * executors * runtime * builtin function base class * adj indices and shape * completely refactor scheduler * rename and move bundled out to function.py * use_edge_feature in msg func * rewrite scheduler * node edge executor * connect with graph api * handle zero degree * misc * fix test cases * fix a good many bugs... * remove old scheduler * push and pull * fix send recv * c++ lint * fix batched send recv * hot fix for mxnet * typo * write back executor * apply node edge * clean up, doc string * fix as requested * refactor * fix * WIP * WIP * ir draft * more on ir * WIP: spmv schedule * WIP * recv schedule * refactor * WIP * snr degree bucketing * snr scheduler * move prog to graph.py; rename * unittest for send/recv * remove some legacy codes * WIP: update_all * pass test_basics * passed all current utests * more utests; fix mx utest * WIP: fixing zero deg initial value * some tests * fix 0deg problem * fix mx * fix mx * some notes * fix as requested
70 行
1.5 KiB
Python
70 行
1.5 KiB
Python
from __future__ import absolute_import
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from .program import get_current_prog
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class VarType(object):
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# Types for symbolic objects (i.e, they might not be
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# concretized before evaluation.
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FEAT = 0
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FEAT_DICT = 1
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# Types for concrete objects (i.e, they must have values).
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SPMAT = 2
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IDX = 3
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STR = 4
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FUNC = 5
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VAR_TYPE_NAME_MAP = [
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'Feat',
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'FeatDict',
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'SpMat',
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'Idx',
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'Str',
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'Func',
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]
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class Var(object):
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"""Variable
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name : str
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type : int
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data : any, default=None (not concretized)
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"""
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__slots__ = ['name', 'type', 'data']
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def __init__(self, name, type, data):
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self.name = name
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self.type = type
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self.data = data
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def __str__(self):
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if self.type == VarType.STR:
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return '"%s"' % self.data
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else:
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return self.name
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def typestr(self):
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return VAR_TYPE_NAME_MAP[self.type]
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def new(type, data=None, name=None):
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if name is None:
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cur_prog = get_current_prog()
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name = '_z%d' % cur_prog.varcount
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cur_prog.varcount += 1
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return Var(name, type, data)
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def FEAT(data=None, name=None):
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return new(VarType.FEAT, data, name)
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def FEAT_DICT(data=None, name=None):
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return new(VarType.FEAT_DICT, data, name)
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def SPMAT(data=None, name=None):
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return new(VarType.SPMAT, data, name)
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def IDX(data=None, name=None):
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return new(VarType.IDX, data, name)
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def STR(data=None, name=None):
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return new(VarType.STR, data, name)
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def FUNC(data=None, name=None):
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return new(VarType.FUNC, data, name)
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