!3396 fix get dataset size error

Merge pull request !3396 from panfengfeng/fix_getdataset_size_error
This commit is contained in:
mindspore-ci-bot 2020-07-24 23:09:45 +08:00 committed by Gitee
commit dc64a3878a
6 changed files with 41 additions and 23 deletions

View File

@ -212,12 +212,12 @@ Status DeviceQueueOp::SendDataToGPU() {
RETURN_IF_NOT_OK(RetryPushGPUData(data_size, curr_row, handle));
total_batch++;
}
if (!TaskManager::FindMe()->Interrupted())
if (!TaskManager::FindMe()->Interrupted() && !GpuBufferMgr::GetInstance().IsClosed())
RETURN_IF_NOT_OK(GetNextInput(&current_buffer));
else
is_break_loop = true;
}
if (!TaskManager::FindMe()->Interrupted())
if (!TaskManager::FindMe()->Interrupted() && !GpuBufferMgr::GetInstance().IsClosed())
RETURN_IF_NOT_OK(GetNextInput(&current_buffer));
else
is_break_loop = true;

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@ -2401,7 +2401,7 @@ class TransferDataset(DatasetOp):
# need to keep iterator alive so the executionTree is not destroyed
if self._noop_mode():
return
self.iterator = TupleIterator(self, num_epochs=-1)
self.iterator = TupleIterator(self, num_epochs=num_epochs)
def stop_send(self):
self.iterator.depipeline.StopSend()

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@ -24,13 +24,18 @@ from ..nn.wrap import GetNextSingleOp
from ..parallel._utils import _get_device_num, _get_global_rank, _need_to_full
def _send_data(dataset):
def _send_data(dataset, epoch_num):
"""Engine dataset to write data to tdt queue."""
if not hasattr(dataset, '__has_sent__'):
exec_dataset = dataset.__TRANSFER_DATASET__
exec_dataset.send()
exec_dataset.send(epoch_num)
dataset.__has_sent__ = True
def _send_data_no_flag(dataset, epoch_num):
"""Engine dataset to write data to tdt queue directly."""
exec_dataset = dataset.__TRANSFER_DATASET__
exec_dataset.send(epoch_num)
class DatasetHelper:
"""
@ -54,7 +59,7 @@ class DatasetHelper:
>>> outputs = network(*inputs)
"""
def __init__(self, dataset, dataset_sink_mode=True, sink_size=-1):
def __init__(self, dataset, dataset_sink_mode=True, sink_size=-1, epoch_num=1):
check_bool(dataset_sink_mode)
check_int(sink_size)
if sink_size < -1 or sink_size == 0:
@ -74,7 +79,7 @@ class DatasetHelper:
iterclass = _DatasetIterMS
elif context.get_context("device_target") == "CPU":
raise RuntimeError("Currently dataset sink mode is not supported when the device target is CPU.")
self.iter = iterclass(dataset, sink_size)
self.iter = iterclass(dataset, sink_size, epoch_num)
else:
iterclass = _DatasetIterNormal
self.iter = iterclass(dataset)
@ -98,7 +103,7 @@ class DatasetHelper:
class _DatasetIter:
"""Base iter for dataset helper"""
def __init__(self, dataset, sink_size):
def __init__(self, dataset, sink_size, epoch_num):
self.dataset = dataset
self.sink_size = sink_size
self.sink_count = 1
@ -110,9 +115,9 @@ class _DatasetIter:
dataset.__ME_INITED__ = dataset.__TRANSFER_DATASET__.queue_name
if not hasattr(dataset, '__no_send__'):
_send_data(dataset)
_send_data(dataset, epoch_num)
else:
_send_data(dataset)
_send_data_no_flag(dataset, epoch_num)
self.stop_send = dataset.__TRANSFER_DATASET__.stop_send
self.dataset_types, self.dataset_shapes = _get_types_and_shapes(dataset)
@ -156,8 +161,8 @@ class _DatasetIter:
class _DatasetIterGE(_DatasetIter):
"""Iter for GE."""
def __init__(self, dataset, sink_size):
super().__init__(dataset, sink_size)
def __init__(self, dataset, sink_size, epoch_num):
super().__init__(dataset, sink_size, epoch_num)
self.sink_count = self.get_sink_count(dataset)
batch_expand_num = 1
if _need_to_full():
@ -172,8 +177,8 @@ class _DatasetIterGE(_DatasetIter):
class _DatasetIterMSLoopSink(_DatasetIter):
"""Iter for context (device_target=Ascend)"""
def __init__(self, dataset, sink_size):
super().__init__(dataset, sink_size)
def __init__(self, dataset, sink_size, epoch_num):
super().__init__(dataset, sink_size, epoch_num)
self.sink_count = self.get_sink_count(dataset)
ms_role = os.getenv("MS_ROLE")
if ms_role in ("MS_PSERVER", "MS_SCHED"):
@ -193,8 +198,8 @@ class _DatasetIterMSLoopSink(_DatasetIter):
class _DatasetIterMS(_DatasetIter):
"""Iter for MS(enable_loop_sink=False)."""
def __init__(self, dataset, sink_size):
super().__init__(dataset, sink_size)
def __init__(self, dataset, sink_size, epoch_num):
super().__init__(dataset, sink_size, epoch_num)
if sink_size > 0:
self.sink_count = sink_size
else:
@ -206,8 +211,8 @@ class _DatasetIterMS(_DatasetIter):
class _DatasetIterPSLite(_DatasetIter):
"""Iter for context (device_target=GPU) on MS_PSERVER or MS_SCHED"""
def __init__(self, dataset, sink_size):
super().__init__(dataset, sink_size)
def __init__(self, dataset, sink_size, epoch_num):
super().__init__(dataset, sink_size, epoch_num)
self.sink_count = 1
self.sink_size = 1
self.op = None

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@ -227,7 +227,7 @@ class Model:
scaling_sens /= self._device_number
return scaling_sens
def _exec_preprocess(self, network, is_train, phase, dataset, dataset_sink_mode, sink_size=-1):
def _exec_preprocess(self, network, is_train, phase, dataset, dataset_sink_mode, sink_size=-1, epoch_num=1):
"""Initializes dataset."""
need_wrap = False
if dataset_sink_mode:
@ -239,7 +239,7 @@ class Model:
if not is_train:
dataset.__loop_size__ = 1
dataset_helper = DatasetHelper(dataset, dataset_sink_mode, sink_size)
dataset_helper = DatasetHelper(dataset, dataset_sink_mode, sink_size, epoch_num)
# remove later to deal with loop sink
if need_wrap:
@ -399,12 +399,18 @@ class Model:
cb_params (_InternalCallbackParam): Callback parameters. Default: None.
sink_size (int): Control the amount of data each sink. Default: -1.
"""
if sink_size == -1:
epoch_num = epoch
else:
epoch_num = epoch * sink_size // train_dataset.get_dataset_size()
dataset_helper, train_network = self._exec_preprocess(self._train_network,
is_train=True,
phase='train',
dataset=train_dataset,
dataset_sink_mode=True,
sink_size=sink_size)
sink_size=sink_size,
epoch_num=epoch_num)
self._train_network = train_network
cb_params.train_network = self._train_network
cb_params.cur_step_num = 0
@ -621,6 +627,8 @@ class Model:
list_callback.step_end(run_context)
self._update_metrics(outputs)
valid_dataset.reset()
metrics = self._get_metrics()
cb_params.metrics = metrics
list_callback.end(run_context)

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@ -58,7 +58,7 @@ class MindData:
def create_tuple_iterator(self):
return self.__iter__()
def send(self):
def send(self, num_epochs=-1):
pass
def stop_send(self):

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@ -15,11 +15,16 @@
"""Dataset help for minddata dataset"""
from mindspore._checkparam import check_bool
from mindspore.parallel._utils import _get_device_num, _get_parallel_mode
from mindspore.train.dataset_helper import _send_data
from mindspore.train._utils import _exec_datagraph, _get_types_and_shapes, \
_to_full_shapes
from mindspore.train.parallel_utils import ParallelMode
def _send_data(dataset):
"""Engine dataset to write data to tdt queue."""
if not hasattr(dataset, '__has_sent__'):
exec_dataset = dataset.__TRANSFER_DATASET__
exec_dataset.send()
dataset.__has_sent__ = True
class DatasetHelper:
"""