!3331 Add register information of BNInference.

Merge pull request !3331 from liuxiao93/Add-BNInference-opInfo
This commit is contained in:
mindspore-ci-bot 2020-07-23 10:32:33 +08:00 committed by Gitee
commit 322c24e6c5
3 changed files with 52 additions and 0 deletions

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@ -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"},

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@ -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

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@ -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