def execute(cls, ctx, op):
if op.merge:
return super().execute(ctx, op)
from xgboost import train, rabit
dtrain = ToDMatrix.get_xgb_dmatrix(ctx[op.dtrain.key])
evals = tuple()
if op.evals is not None:
eval_dmatrices = [ToDMatrix.get_xgb_dmatrix(ctx[t[0].key]) for t in op.evals]
evals = tuple((m, ev[1]) for m, ev in zip(eval_dmatrices, op.evals))
params = op.params
params['nthread'] = ctx.get_ncores() or -1
if op.tracker is None:
# non distributed
local_history = dict()
kwargs = dict() if op.kwargs is None else op.kwargs
bst = train(params, dtrain, evals=evals,
evals_result=local_history, **kwargs)
ctx[op.outputs[0].key] = {'booster': pickle.dumps(bst), 'history': local_history}
else:
# distributed
rabit_args = ctx[op.tracker.key]
rabit.init(rabit_args)
try:
local_history = dict()
bst = train(params, dtrain, evals=evals, evals_result=local_history,
**op.kwargs)
ret = {'booster': pickle.dumps(bst), 'history': local_history}
if rabit.get_rank() != 0:
ret = {}
ctx[op.outputs[0].key] = ret
finally:
rabit.finalize()
def stop(self):
"""Shutdown parameter server.
If current host is master host, also join the background thread that is running the master host.
"""
self.logger.debug("Shutting down parameter server.")
# This is the call that actually shuts down the rabit server; and when
# all of the slaves have been shut down then the RabitTracker will close
# /shutdown itself.
rabit.finalize()
if self.is_master_host:
self.rabit_context.join()
def execute(cls, ctx, op):
if op.merge:
return super().execute(ctx, op)
from xgboost import train, rabit
dtrain = ToDMatrix.get_xgb_dmatrix(ensure_own_data(ctx[op.dtrain.key]))
evals = tuple()
if op.evals is not None:
eval_dmatrices = [
ToDMatrix.get_xgb_dmatrix(ensure_own_data(ctx[t[0].key]))
for t in op.evals
]
evals = tuple(
(m, ev[1]) for m, ev in zip(eval_dmatrices, op.evals))
params = op.params
if op.tracker is None:
# non distributed
local_history = dict()
kwargs = dict() if op.kwargs is None else op.kwargs
bst = train(params,
dtrain,
evals=evals,
evals_result=local_history,
**kwargs)
ctx[op.outputs[0].key] = {
'booster': pickle.dumps(bst),
'history': local_history
}
else:
# distributed
rabit_args = ctx[op.tracker.key]
rabit.init([
arg.tobytes() if isinstance(arg, memoryview) else arg
for arg in rabit_args
])
try:
local_history = dict()
bst = train(params,
dtrain,
evals=evals,
evals_result=local_history,
**op.kwargs)
ret = {'booster': pickle.dumps(bst), 'history': local_history}
if rabit.get_rank() != 0:
ret = {}
ctx[op.outputs[0].key] = ret
finally:
rabit.finalize()
def __exit__(self, *args):
rabit.finalize()