!3331 Add register information of BNInference.

Merge pull request !3331 from liuxiao93/Add-BNInference-opInfo

mindspore/ccsrc/backend/kernel_compiler/tbe/tbe_adapter.cc

@@ -64,6 +64,7 @@ static std::map<string, string> tbe_func_adapter_map = {
   {"b_n_training_update_grad", "bn_training_update_grad"},
   {"b_n_infer", "bn_infer"},
   {"b_n_infer_grad", "bn_infer_grad"},
+  {"b_n_inference", "bninference_d"},
   {"n_pu_clear_float_status", "n_p_u_clear_float_status"},
   {"n_pu_get_float_status", "n_p_u_get_float_status"},
   {"n_pu_alloc_float_status", "n_p_u_alloc_float_status"},

mindspore/ops/_op_impl/tbe/__init__.py

@@ -95,6 +95,7 @@ from .bn_training_update import _bn_training_update_tbe
 from .bn_training_update_grad import _bn_training_update_grad_tbe
 from .bn_infer import _bn_infer_tbe
 from .bn_infer_grad import _bn_infer_grad_tbe
+from .bn_inference import _bn_inference_tbe
 from .reciprocal import _reciprocal_tbe
 from .reverse_v2_d import _reverse_v2_d_tbe
 from .rint import _rint_tbe

mindspore/ops/_op_impl/tbe/bn_inference.py

@@ -0,0 +1,50 @@
+# 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.
+# ============================================================================
+
+"""BNInference op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+bn_inference_op_info = TBERegOp("BNInference") \
+    .fusion_type("OPAQUE") \
+    .async_flag(False) \
+    .binfile_name("bninference_d.so") \
+    .compute_cost(10) \
+    .kernel_name("bninference_d") \
+    .partial_flag(True) \
+    .attr("momentum", "optional", "float", "all", "0.999") \
+    .attr("epsilon", "optional", "float", "all", "0.00001") \
+    .attr("use_global_stats", "optional", "bool", "true,false", "true") \
+    .attr("mode", "optional", "int", "all", "1") \
+    .input(0, "x", False, "required", "all") \
+    .input(1, "mean", False, "required", "all") \
+    .input(2, "variance", False, "required", "all") \
+    .input(3, "scale", False, "optional", "all") \
+    .input(4, "offset", False, "optional", "all") \
+    .output(0, "y", False, "required", "all") \
+    .dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD,
+                  DataType.F16_5HD, DataType.F16_5HD) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD,
+                  DataType.F32_5HD, DataType.F32_5HD) \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default,
+                  DataType.F16_Default, DataType.F16_Default) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default,
+                  DataType.F32_Default, DataType.F32_Default) \
+    .get_op_info()
+
+
+@op_info_register(bn_inference_op_info)
+def _bn_inference_tbe():
+    """BNInference TBE register"""
+    return