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Diffstat (limited to 'compiler/moco-tf/src/BroadcastHelper.h')
-rw-r--r-- | compiler/moco-tf/src/BroadcastHelper.h | 76 |
1 files changed, 76 insertions, 0 deletions
diff --git a/compiler/moco-tf/src/BroadcastHelper.h b/compiler/moco-tf/src/BroadcastHelper.h new file mode 100644 index 000000000..6238ad269 --- /dev/null +++ b/compiler/moco-tf/src/BroadcastHelper.h @@ -0,0 +1,76 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * + * 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. + */ + +#ifndef __BROADCAST_HELPER_H__ +#define __BROADCAST_HELPER_H__ + +#include <loco/IR/Node.h> +#include <loco/IR/Dimension.h> +#include <loco/IR/TensorShape.h> + +#include <bino.h> +#include <fipe.h> // include "fipe.h" for clients + +namespace moco +{ +namespace tf +{ + +class BroadcastFunctor final +{ +public: + BroadcastFunctor(const loco::TensorShape &shape) : _shape{shape} + { + // DO NOTHING + } + +public: + loco::Node *build(loco::Node *in_node, const loco::TensorShape &in_shape) const; + + loco::Node *operator()(loco::Node *in_node, const loco::TensorShape &in_shape) const + { + return build(in_node, in_shape); + } + + // This method assumes the followings: + // - loco::shape_known(node) returns true, and + // - loco::shape_get(node).domain() is loco::Domain::Tensor + loco::Node *build(loco::Node *node) const; + + loco::Node *operator()(loco::Node *node) const { return build(node); } + +private: + loco::TensorShape _shape; +}; + +/** + * @brief Create a broadcasted node + * + * First, append canonical.FixedReshape if rank expansion is required. + * Then, append canonical.TensorBroadcast if dimension expansion is required + * + * This mimics "tf.broadcast_to" API in TensorFlow. + */ +static inline auto broadcast_to(const loco::TensorShape &shape) + -> decltype(bino::transform_both(std::declval<BroadcastFunctor>())) +{ + return bino::transform_both(BroadcastFunctor{shape}); +} + +} // namespace tf +} // namespace moco + +#endif // __BROADCAST_HELPER_H__ |