def crack_init(spec_files):
com_args = {}
phases = {}
tasks = []
for spec_file in spec_files:
with open(spec_file, "r") as f:
specs = yaml.load(f)
if "with" in specs:
com_args = merge_dicts(com_args, specs["with"])
if "phases" in specs:
phases = merge_dicts(phases, specs["phases"])
format_args(phases, com_args)
if "do" in specs:
tasks.extend(specs["do"])
phases_index = {}
for i, task in enumerate(tasks):
tasks[i] = format_task(task, phases, phases_index, com_args, i)
phases_index["end"] = -1
return tasks, phases_index
def record_algos_stats(models,
records,
algo,
cut=None,
imb=None,
t=None,
operations=None,
**algopt):
stats = {
"algo": algo,
"cut": cut,
"imb": imb,
"time": t,
"operations": operations,
}
if t is not None:
records["time"] += t
if operations is not None:
records["operations"] += operations
records["per_algo"].append(merge_dicts(stats, algopt))
def format_task(task, phases, phases_index, com_args, i):
"""Get algorithm id, args and next phase.
"""
if isinstance(task, str):
if task in phases:
algo = phases[task]["algo"]
args = phases[task].get("args", {})
format_args(args, com_args)
next_phase = phases[task].get("next")
phases_index[task] = i
else:
algo = task
args = {}
next_phase = None
phases_index[algo] = i
elif isinstance(task, dict):
if "phase" in task:
phase_id = task["phase"]
if "algo" in task:
algo = task["algo"]
else:
algo = phases[phase_id]["algo"]
args = task.get("args", {})
format_args(args, com_args)
args = merge_dicts(phases[phase_id].setdefault("args", {}), args)
next_phase = task
phases_index[phase_id] = i
else: # task is of type {algo_name: {**args}}
algo = list(task)[0] # (should only be one key: the algo name)
args = task[algo]
format_args(args, com_args)
next_phase = None
phases_index[algo] = i
phase = {
"algo": algo,
"args": args,
"next": next_phase,
}
return phase
from crack.models.graph import INIT_GRAPH_FCTS, INIT_GRAPHGEOM_FCTS, OUTPUT_GRAPH_FCTS
from crack.models.hypergraph import INIT_HYPERGRAPH_FCTS
from crack.models.mesh import INIT_MESH_FCTS
from crack.models.partition import INIT_PARTITION_FCTS
from crack.models.nweights import INIT_NWGT_FCTS
from crack.models.eweights import INIT_EWGT_FCTS
from crack.models.cut import cut_lambda_minus_one, gain__cut_lambda_minus_one__graph, gain__cut_lambda_minus_one__hypergraph
from crack.models.imbalance import ConstraintsImbalance, imbalance
from crack.utils.errors import crack_error
from crack.utils.structures import merge_dicts
INIT_FCTS = merge_dicts(INIT_GRAPH_FCTS, INIT_GRAPHGEOM_FCTS,
INIT_HYPERGRAPH_FCTS, INIT_MESH_FCTS, INIT_NWGT_FCTS,
INIT_EWGT_FCTS, INIT_PARTITION_FCTS)
OUTPUT_FCTS = merge_dicts(OUTPUT_GRAPH_FCTS, )
CONSTRAINTS_OBJ = {
"imbalance": ConstraintsImbalance,
}
def get_obj_fcts(models, obj_name, obj_args):
"""How to compute the values (e.g. cut, imbalance) that the user
usually wants to minimize.
"""
obj_fct = None
if obj_name == "cut":
import random as rd
import sys
import yaml
from crack.algos.algos_fcts import ALGOS
from crack.analysis.analysis_fcts import ANALYZE_FCTS
from crack.models.models_fcts import INIT_FCTS, OUTPUT_FCTS
from crack.operators.coarsen import COARSEN_FCTS
from crack.operators.prolong import PROLONG_FCTS
from crack.utils.fork import FORK_FCTS
from crack.utils.structures import merge_dicts
from crack.utils.evaluate import eval_expr
from crack.utils.errors import crack_error
from crack.utils.algo_utils import init_algos_stats
NORMAL_FCTS = merge_dicts(ALGOS, ANALYZE_FCTS, INIT_FCTS, OUTPUT_FCTS)
def format_args(args, com_args):
if "with" in args:
for com_k, com_v in com_args[args["with"]].items():
args.setdefault(com_k, com_v)
del args["with"]
for k, v in args.items():
if isinstance(v, dict):
format_args(v, com_args)
def get_next_phase(l_models, records, tasks, phase_index, next_phase):
"""Analyse the fork conditions and return the next Phase.
"""