autoparallel support dataset in gpu

mindspore/ccsrc/frontend/parallel/context.cc

@@ -44,7 +44,10 @@ std::shared_ptr<ParallelContext> ParallelContext::GetInstance() {
   return inst_context_;
 }
 
-ParallelContext::ParallelContext() { Reset(); }
+ParallelContext::ParallelContext() {
+  communication_backend_ = HCCL_BACKEND;
+  Reset();
+}
 
 void ParallelContext::Reset() {
   mirror_mean_ = false;
@@ -53,7 +56,6 @@ void ParallelContext::Reset() {
   loss_repeated_mean_ = true;
   device_num_ = 1;
   global_rank_ = 0;
-  communication_backend_ = HCCL_BACKEND;
   device_num_is_set_ = false;
   global_rank_is_set_ = false;
   parallel_mode_ = STAND_ALONE;

mindspore/train/model.py

@@ -30,6 +30,8 @@ from ..nn.metrics import Loss
 from .. import nn
 from ..nn.wrap.cell_wrapper import _VirtualDatasetCell
 from .parallel_utils import ParallelMode
+from ._utils import _to_full_tensor
+from ..parallel._utils import _need_to_full
 from ..common import dtype as mstype
 from .dataset_helper import DatasetHelper
 from . import amp
@@ -418,6 +420,8 @@ class Model:
 
             # for data sink dataset_helper only iter once, other wise iter epoch_size times.
             for inputs in dataset_helper:
+                if _need_to_full():
+                    inputs = _to_full_tensor(inputs, self._device_number, self._global_rank)
                 list_callback.step_begin(run_context)
                 outputs = self._train_network(*inputs)
                 cb_params.cur_step_num += dataset_helper.sink_size()