!5019 raise RuntimeError when set different mode after Initializer created

Merge pull request !5019 from yihuaijie/dev

mindspore/ccsrc/frontend/parallel/context.cc

@@ -81,8 +81,6 @@ void ParallelContext::set_mirror_mean(bool mirror_mean) { mirror_mean_ = mirror_
 
 void ParallelContext::set_full_batch(bool full_batch) { full_batch_ = full_batch; }
 
-void ParallelContext::set_has_initializer(bool has_initializer) { has_initializer_ = has_initializer; }
-
 void ParallelContext::set_cast_before_mirror(bool cast_before_mirror) { cast_before_mirror_ = cast_before_mirror; }
 
 void ParallelContext::set_loss_repeated_mean(bool loss_repeated_mean) { loss_repeated_mean_ = loss_repeated_mean; }

mindspore/ccsrc/frontend/parallel/context.h

@@ -58,9 +58,6 @@ class ParallelContext {
   void set_full_batch(bool full_batch);
   bool full_batch() const { return full_batch_; }
 
-  void set_has_initializer(bool has_initializer);
-  bool has_initializer() const { return has_initializer_; }
-
   void set_cast_before_mirror(bool cast_before_mirror);
   bool cast_before_mirror() const { return cast_before_mirror_; }
 
@@ -115,7 +112,6 @@ class ParallelContext {
   static std::shared_ptr<ParallelContext> inst_context_;
   bool mirror_mean_;
   bool full_batch_;
-  bool has_initializer_ = false;
   bool cast_before_mirror_;
   bool loss_repeated_mean_;
   int32_t device_num_;

mindspore/ccsrc/pipeline/jit/init.cc

@@ -198,8 +198,6 @@ PYBIND11_MODULE(_c_expression, m) {
     .def("get_strategy_ckpt_save_file", &ParallelContext::strategy_ckpt_save_file, "Get strategy checkpoint save file.")
     .def("set_full_batch", &ParallelContext::set_full_batch, "Set whether load full batch on each device.")
     .def("get_full_batch", &ParallelContext::full_batch, "Get whether load full batch on each device.")
-    .def("set_has_initializer", &ParallelContext::set_has_initializer, "Set whether any Initializer has been created.")
-    .def("get_has_initializer", &ParallelContext::has_initializer, "Get whether any Initializer has been created.")
     .def("set_enable_parallel_optimizer", &ParallelContext::set_enable_parallel_optimizer,
          "Set enable/disable parallel optimizer.")
     .def("get_enable_parallel_optimizer", &ParallelContext::enable_parallel_optimizer,

mindspore/common/api.py

@@ -24,7 +24,7 @@ from mindspore import log as logger
 from .._c_expression import generate_key, Executor_, Tensor, MetaTensor, PynativeExecutor_
 from .._c_expression import verify_inputs_signature, init_exec_dataset, _set_dataset_mode_config, init_backend
 from .tensor import Tensor as MsTensor
-from ..parallel._utils import _get_device_num, _get_global_rank, _need_to_full, _to_full_tensor, _set_has_initializer
+from ..parallel._utils import _get_device_num, _get_global_rank, _need_to_full, _to_full_tensor
 # store ms_function class compiled pipeline cache
 ms_compile_cache = {}
 
@@ -383,7 +383,6 @@ class _Executor:
             Str, the full phase of the cell.
             Bool, if the graph has been compiled before, return False, else return True.
         """
-        _set_has_initializer(False)
         obj.check_names()
         args_names, args_list = _generate_pip_args(obj, *args)
         dic = dict(zip(args_names, args_list))

mindspore/common/initializer.py

@@ -24,7 +24,6 @@ from mindspore import log as logger
 from . import dtype as mstype
 from .tensor import Tensor
 from .._c_expression import random_normal
-from ..parallel._utils import _set_has_initializer
 
 _INITIALIZER_ALIAS = dict()
 
@@ -43,7 +42,6 @@ class Initializer:
         self._kwargs = kwargs
         self.shape = None
         self.dtype = None
-        _set_has_initializer(True)
 
     def _initialize(self, *kwargs):
         raise NotImplementedError('Must be overridden!')

mindspore/common/parameter.py

@@ -90,6 +90,9 @@ class Parameter(MetaTensor):
         input_class.__init__(obj, *class_init_args)
         # it's better to make the Initializer a kind of metatensor.
         obj.init_mode = None
+        obj.is_default_input_initializer = False
+        if isinstance(default_input, Initializer):
+            obj.is_default_input_initializer = True
         if not isinstance(obj, Tensor):
             obj.init_mode = default_input
         return obj
@@ -118,6 +121,7 @@ class Parameter(MetaTensor):
         self.is_param_ps = False
         self._cast_type = None
         self.init_in_server = False
+        self.is_in_parallel = _is_in_parallel_mode()
 
     @staticmethod
     def _get_base_class(input_class):
@@ -372,10 +376,17 @@ class Parameter(MetaTensor):
             set_sliced (bool): True if the parameter is set sliced after initializing the data.
                 Default: False.
 
+        Raises:
+            RuntimeError: If it is from Initializer, and parallel mode has changed after the Initializer created.
+
         Returns:
             Parameter, the `Parameter` after initializing data. If current `Parameter` was already initialized before,
             returns the same initialized `Parameter`.
         """
+        if self.is_default_input_initializer:
+            is_current_in_parallel = _is_in_parallel_mode()
+            if self.is_in_parallel != is_current_in_parallel:
+                raise RuntimeError("Must set or change parallel mode before any Initializer created.")
         if self.init_mode is None:
             return self
         if layout is not None:

mindspore/context.py

@@ -449,7 +449,7 @@ def set_auto_parallel_context(**kwargs):
         next task, interface mindspore.context.reset_auto_parallel_context() needs to be called to reset
         the configuration.
         Setting or changing parallel modes must be called before any Initializer created, or RuntimeError
-        will be raised.
+        may be raised when compile network.
 
     Args:
         device_num (int): Available device number, the value must be in [1, 4096]. Default: 1.
@@ -491,7 +491,6 @@ def set_auto_parallel_context(**kwargs):
 
     Raises:
         ValueError: If input key is not attribute in auto parallel context.
-        RuntimeError: If there is any Initializer created before setting or changing parallel_mode.
 
     Examples:
         >>> context.set_auto_parallel_context(device_num=8)

mindspore/parallel/_auto_parallel_context.py

@@ -176,12 +176,8 @@ class _AutoParallelContext:
 
         Raises:
             ValueError: If parallel mode is not supported.
-            RuntimeError: If there is any Initializer created before setting or changing parallel_mode.
         """
         self.check_context_handle()
-        if self.get_has_initializer():
-            self.set_has_initializer(False)
-            raise RuntimeError("Must set or change parallel mode before any Initializer created.")
         ret = self._context_handle.set_parallel_mode(parallel_mode)
         if ret is False:
             raise ValueError("Parallel mode does not support {}".format(parallel_mode))
@@ -253,21 +249,6 @@ class _AutoParallelContext:
         self.check_context_handle()
         return self._context_handle.get_full_batch()
 
-    def set_has_initializer(self, has_initializer):
-        """
-        Set whether any Initializer has been created.
-
-        Args:
-            has_initializer (bool): True if a Initializer created.
-        """
-        self.check_context_handle()
-        self._context_handle.set_has_initializer(has_initializer)
-
-    def get_has_initializer(self):
-        """Get whether any Initializer has been created."""
-        self.check_context_handle()
-        return self._context_handle.get_has_initializer()
-
     def set_strategy_ckpt_save_file(self, strategy_ckpt_save_file):
         """
         Set strategy checkpoint save path.
@@ -562,7 +543,6 @@ def _set_auto_parallel_context(**kwargs):
 
     Raises:
         ValueError: If input key is not attribute in auto parallel context.
-        RuntimeError: If there is any Initializer created before setting or changing parallel_mode.
     """
     for key, value in kwargs.items():
         if key not in _set_auto_parallel_context_func_map:

mindspore/parallel/_utils.py

@@ -32,19 +32,6 @@ def _get_full_batch():
     """Get whether to use full_batch."""
     return auto_parallel_context().get_full_batch()
 
-def _get_has_initializer():
-    """Get whether any Initializer has been created."""
-    return auto_parallel_context().get_has_initializer()
-
-def _set_has_initializer(has_initializer):
-    """
-    Set whether any Initializer has been created.
-
-    Args:
-        has_initializer (bool): True if a Initializer created.
-    """
-    auto_parallel_context().set_has_initializer(has_initializer)
-
 
 def _need_to_full():
     """Check whether to convert input to full shape or tensor."""

tests/ut/python/communication/test_data_parallel_lenet.py

@@ -24,7 +24,6 @@ import mindspore.nn as nn
 from mindspore import Tensor, Model, ParallelMode
 from mindspore.nn.optim import Momentum
 from mindspore.ops import operations as P
-from mindspore.parallel._utils import _set_has_initializer
 
 _current_dir = os.path.dirname(os.path.realpath(__file__)) + "/../test_data"
 
@@ -90,4 +89,3 @@ def test_lenet5_train_step_training_pynative():
     Model(network=network, loss_fn=loss_fn, optimizer=optimizer)
     context.set_context(mode=context.GRAPH_MODE)
     context.reset_auto_parallel_context()
-    _set_has_initializer(False)

tests/ut/python/nn/test_parameter.py

@@ -21,7 +21,6 @@ from mindspore import context, Tensor, Parameter, ParameterTuple
 from mindspore._checkparam import _check_str_by_regular
 from mindspore.common import dtype as mstype
 from mindspore.common.initializer import initializer
-from mindspore.parallel._utils import _set_has_initializer
 
 def test_parameter_init():
     dat = np.array([[1, 2, 3], [2, 3, 4]])
@@ -191,7 +190,6 @@ def test_scalar_parameter_update():
 
 
 def test_parameter_lazy_init():
-    _set_has_initializer(False)
     # support lazy init in SEMI_AUTO_PARALLEL mode
     context.reset_auto_parallel_context()
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8)

tests/ut/python/parallel/test_add_relu_redistribution.py

@@ -20,7 +20,6 @@ from mindspore import context
 from mindspore.common.api import _executor
 from mindspore.ops import composite as C
 from mindspore.ops import operations as P
-from mindspore.parallel._utils import _set_has_initializer
 from tests.ut.python.ops.test_math_ops import VirtualLoss
 
 
@@ -61,7 +60,6 @@ def compile_net(net, x, y):
 
 
 def test_add_relu_stride_slice():
-    _set_has_initializer(False)
     context.set_auto_parallel_context(device_num=8, global_rank=7)
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel")
 
@@ -75,7 +73,6 @@ def test_add_relu_stride_slice():
 
 
 def test_add_relu_all_gather():
-    _set_has_initializer(False)
     context.set_auto_parallel_context(device_num=8, global_rank=7)
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel")
 

tests/ut/python/parallel/test_allreduce_fusion.py

@@ -23,7 +23,6 @@ from mindspore.nn.optim.momentum import Momentum
 from mindspore.parallel import _cost_model_context as cost_model_context
 from mindspore.parallel._auto_parallel_context import auto_parallel_context
 from mindspore.train import Model, ParallelMode
-from mindspore.parallel._utils import _set_has_initializer
 from tests.dataset_mock import MindData
 
 
@@ -182,7 +181,6 @@ def test_allreduce_fusion_parameters():
 
 
 def test_allreduce_fusion1():
-    _set_has_initializer(False)
     cost_model_context.set_cost_model_context(costmodel_allreduce_fusion_algorithm=1)
     cost_model_context.set_cost_model_context(costmodel_allreduce_fusion_times=2)
     cost_model_context.set_cost_model_context(costmodel_allreduce_fusion_tail_percent=0.5)

tests/ut/python/parallel/test_alltoall.py

@@ -23,7 +23,7 @@ from mindspore.common.parameter import Parameter
 from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
 from mindspore.nn.optim.momentum import Momentum
 from mindspore.ops import operations as P
-from mindspore.parallel._utils import _reset_op_id, _set_has_initializer
+from mindspore.parallel._utils import _reset_op_id
 from mindspore.train import Model, ParallelMode
 from tests.dataset_mock import MindData
 
@@ -90,7 +90,6 @@ def all_to_all_common(strategy1):
 
 
 def test_all_to_all():
-    _set_has_initializer(False)
     strategy1 = ((8, 1),)
     context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     _reset_op_id()

tests/ut/python/parallel/test_arithmetic.py

@@ -20,7 +20,6 @@ from mindspore import Parameter, Tensor, context
 from mindspore.common.api import _executor
 from mindspore.ops import composite as C
 from mindspore.ops import operations as P
-from mindspore.parallel._utils import _set_has_initializer
 from tests.ut.python.ops.test_math_ops import VirtualLoss
 
 
@@ -61,7 +60,6 @@ def test_matmul_sub():
             out = self.sub(out, b)
             return out
 
-    _set_has_initializer(False)
     context.set_auto_parallel_context(device_num=8, global_rank=0)
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel")
     strategy1 = ((2, 2), (2, 2))

tests/ut/python/parallel/test_initializer_weight_slice.py

@@ -84,11 +84,23 @@ def test_wrong_order_set_parallel_mode_with_initializer():
     net = Net(strategy1, strategy2, weight)
     exe = me._executor
     x = Tensor(np.ones([32, 32]), dtype=ms.float32)
+    context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    net.set_auto_parallel()
     with pytest.raises(RuntimeError):
-        context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
-        net.set_auto_parallel()
         exe.compile(net, x, auto_parallel_mode=True, phase='train')
 
+def test_wrong_order_set_same_parallel_mode_with_initializer():
+    context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    weight = initializer("Normal", [64, 32], ms.float32)
+    strategy1 = ((2, 1), (4, 1))
+    strategy2 = ((2, 4),)
+    net = Net(strategy1, strategy2, weight)
+    exe = me._executor
+    x = Tensor(np.ones([32, 32]), dtype=ms.float32)
+    context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, global_rank=0)
+    net.set_auto_parallel()
+    exe.compile(net, x, auto_parallel_mode=True, phase='train')
+
 def test_wrong_order_set_parallel_mode_without_initializer():
     weight = Tensor(np.ones([64, 32]), ms.float32)
     strategy1 = ((2, 1), (4, 1))

tests/ut/python/parallel/test_using_seed_for_initializer.py

@@ -18,7 +18,6 @@ from numpy import allclose
 import mindspore.common.initializer as init
 import mindspore.nn as nn
 from mindspore import Parameter
-from mindspore.parallel._utils import _set_has_initializer
 
 parameter_shape = [16, 4]
 
@@ -47,7 +46,6 @@ def test_using_same_seed_for_initializer():
     np.random.seed(0)
     net2 = ParameterNet()
     net2.init_parameters_data()
-    _set_has_initializer(False)
     for key in net1.parameters_dict():
         if key not in net2.parameters_dict():
             assert False
@@ -62,7 +60,6 @@ def test_using_diffserent_seed_for_initializer():
     np.random.seed(1)
     net2 = ParameterNet()
     net2.init_parameters_data()
-    _set_has_initializer(False)
     for key in net1.parameters_dict():
         if key not in net2.parameters_dict():
             assert False