diff options
author | openvino-pushbot <openvino_pushbot@intel.com> | 2018-10-16 13:45:03 +0300 |
---|---|---|
committer | openvino-pushbot <openvino_pushbot@intel.com> | 2018-10-16 13:45:03 +0300 |
commit | 866530fb047cd17af6bd2dbbde5f5cb35f876840 (patch) | |
tree | 91451785d290a2481d82ed8dfe175aade3a0f727 /inference-engine/thirdparty/clDNN/src/include/batch_norm_inst.h | |
parent | c37d4661a27afb408a45f7752acea968032afcc0 (diff) | |
download | dldt-866530fb047cd17af6bd2dbbde5f5cb35f876840.tar.gz dldt-866530fb047cd17af6bd2dbbde5f5cb35f876840.tar.bz2 dldt-866530fb047cd17af6bd2dbbde5f5cb35f876840.zip |
Publishing R3
Diffstat (limited to 'inference-engine/thirdparty/clDNN/src/include/batch_norm_inst.h')
-rw-r--r-- | inference-engine/thirdparty/clDNN/src/include/batch_norm_inst.h | 66 |
1 files changed, 66 insertions, 0 deletions
diff --git a/inference-engine/thirdparty/clDNN/src/include/batch_norm_inst.h b/inference-engine/thirdparty/clDNN/src/include/batch_norm_inst.h new file mode 100644 index 000000000..1973b739d --- /dev/null +++ b/inference-engine/thirdparty/clDNN/src/include/batch_norm_inst.h @@ -0,0 +1,66 @@ +/* +// Copyright (c) 2016 Intel Corporation +// +// 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. +*/ + +/////////////////////////////////////////////////////////////////////////////////////////////////// +#pragma once +#include "api/CPP/batch_norm.hpp" +#include "primitive_inst.h" + +namespace cldnn +{ + +template <> +struct typed_program_node<batch_norm> : public typed_program_node_base<batch_norm> +{ + using parent = typed_program_node_base<batch_norm>; + +public: + using parent::parent; + + decltype(auto) input() const { return get_dependency(0); } + decltype(auto) mean() const { return get_dependency(1); } + decltype(auto) variance() const { return get_dependency(2); } + decltype(auto) inv_variance() const { return get_dependency(1); }; + bool variance_term() const { return !get_primitive()->variance.empty(); } + bool use_global_stats() const { return !get_primitive()->mean.empty() && !get_primitive()->variance.empty(); }; + bool forwad_pass() const { return !get_primitive()->inv_variance.empty(); }; + +}; + +using batch_norm_node = typed_program_node<batch_norm>; + +template <> +class typed_primitive_inst<batch_norm> : public typed_primitive_inst_base<batch_norm> +{ + using parent = typed_primitive_inst_base<batch_norm>; + +public: + static layout calc_output_layout(batch_norm_node const& node); + static std::string to_string(batch_norm_node const& node); + +public: + typed_primitive_inst(network_impl& network, batch_norm_node const& node); + + decltype(auto) mean_memory() const { return dep_memory(1); } + decltype(auto) variance_memory() const { return dep_memory(2); } + decltype(auto) inv_variance_memory() const { return dep_memory(1); }; + bool use_global_stats() const { return !argument.mean.empty() && !argument.variance.empty(); }; + bool forwad_pass() const { return !argument.inv_variance.empty(); }; +}; + +using batch_norm_inst = typed_primitive_inst<batch_norm>; + +} |