def __init__(self):
super(SendNet, self).__init__()
self.x = Parameter(initializer(Tensor(x), x.shape), name='x')
self.depend = P.Depend()
self.send = Send(sr_tag=0,
dest_rank=rank + size // 2,
group=NCCL_WORLD_COMM_GROUP)
def __init__(self):
super().__init__()
self.parameter1 = Parameter(Tensor([199.0], ms.float32), name="parameter1")
self.assign = P.Assign()
self.assignadd = P.AssignAdd()
self.addn = P.AddN()
self.depend = P.Depend()
def __init__(self, var, accum):
super().__init__()
self.depend = P.Depend()
self.sparse_apply_proximal_adagrad = P.SparseApplyProximalAdagrad()
self.var = Parameter(var, name="var")
self.accum = Parameter(accum, name="accum")
self.const = Tensor(9999, mstype.float32)
def test_elim_depend_value(tag):
""" test_elim_depend_value """
fns = FnDict()
depend = P.Depend()
@fns
def before(x):
return depend(x, None)
@fns
def after(x):
return x
return fns[tag]
def __init__(self):
super(Net2, self).__init__()
self.relu1 = P.ReLU()
self.relu2 = P.ReLU().add_prim_attr("primitive_target", "CPU")
self.mul = P.Mul()
self.depend = P.Depend()
def __init__(self):
super(Net1, self).__init__()
self.relu1 = P.ReLU()
self.relu2 = P.ReLU()
self.mul = P.Mul()
self.depend = P.Depend()
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
from mindspore.ops import Primitive
from mindspore.ops import operations as P
from mindspore.ops import _constants as Constants
depend = P.Depend()
all_reduce = P.AllReduce()
broadcast = P.Broadcast(1)
tensor_move = Primitive('TensorMove')
make_tuple = Primitive('MakeTuple')
tuple_getitem = Primitive(Constants.kTupleGetItem)
assign_add = P.AssignAdd()
apply_momentun = P.ApplyMomentum()
relu = P.ReLU()
class FnDict:
def __init__(self):
self.fnDict = {}
def __call__(self, fn):
