!1724 add bntrainingupdatev3 for vm

Merge pull request !1724 from JichenZhao/bnops_for_vm

mindspore/ccsrc/kernel/tbe/tbe_adapter.cc

@@ -55,6 +55,7 @@ static std::map<string, string> tbe_func_adapter_map = {
   {"b_n_training_reduce", "bn_training_reduce"},
   {"b_n_training_update", "bn_training_update"},
   {"b_n_training_update_v2", "bn_training_update_v2"},
+  {"b_n_training_update_v3", "bn_training_update_v3"},
   {"b_n_training_reduce_grad", "bn_training_reduce_grad"},
   {"b_n_training_update_grad", "bn_training_update_grad"},
   {"b_n_infer", "bn_infer"},

mindspore/ops/_op_impl/tbe/__init__.py

@@ -194,6 +194,7 @@ from .sgd import _sgd_tbe
 from .lars_update import _lars_update_tbe
 from .arg_min import _arg_min_tbe
 from .bn_training_update_v2 import _bn_training_update_v2_tbe
+from .bn_training_update_v3 import _bn_training_update_v3_tbe
 from .square_sum_all import _square_sum_all_tbe
 from .pack import _pack_tbe
 from .unpack import _unpack_tbe

mindspore/ops/_op_impl/tbe/bn_training_update_v3.py

@@ -0,0 +1,51 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# 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.
+# ============================================================================
+
+"""BNTrainingUpdateV3 op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+bn_training_update_v3_op_info = TBERegOp("BNTrainingUpdateV3") \
+    .fusion_type("OPAQUE") \
+    .async_flag(False) \
+    .binfile_name("bn_training_update_v3.so") \
+    .compute_cost(10) \
+    .kernel_name("bn_training_update_v3") \
+    .partial_flag(True) \
+    .attr("epsilon", "required", "float", "all") \
+    .input(0, "x", False, "required", "all", reshape_type="NC") \
+    .input(1, "sum", False, "required", "all") \
+    .input(2, "square_sum", False, "required", "all") \
+    .input(3, "scale", False, "required", "all") \
+    .input(4, "offset", False, "required", "all") \
+    .output(0, "y", False, "required", "all", reshape_type="NC") \
+    .output(1, "batch_mean", False, "required", "all") \
+    .output(2, "batch_variance", False, "required", "all") \
+    .output(3, "reserve_1", False, "required", "all") \
+    .output(4, "reserve_2", False, "required", "all") \
+    .dtype_format(DataType.F16_5HD, DataType.F32_5HD, DataType.F32_5HD,
+                  DataType.F32_5HD, DataType.F32_5HD, DataType.F16_5HD,
+                  DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD,
+                  DataType.F32_5HD) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD,
+                  DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD,
+                  DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD,
+                  DataType.F32_5HD) \
+    .get_op_info()
+
+
+@op_info_register(bn_training_update_v3_op_info)
+def _bn_training_update_v3_tbe():
+    """BNTrainingUpdateV3 TBE register"""
+    return