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/*
* 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 __LOCO_IR_DOMAIN_H__
#define __LOCO_IR_DOMAIN_H__
namespace loco
{
/**
* @brief Describe the kind of (N-dimensional) loco values
*
* loco is an intermediate representation for neural network compiler, which mainly focuses on
* N-dimensional values (usually referred to as Tensor).
*
* There are several special cases for N-dimensional values according to its usage. For example,
* vision community often refers to 4D array as "FeatureMap".
*
* It is definitely possible to represent all of these special cases using Tensor, but that scheme
* may introduces some confusion (e.g. NCHW vs NHWC issue).
*
* loco distinguishes these special cases from Tensor in order to reduce such confusion.
*
* This "Domain" enum class enumerates all of these special cases that loco supports.
*/
enum class Domain
{
Unknown,
Tensor,
Feature,
Filter, /* 2D Convolution Filter */
DepthwiseFilter, /* Depthwise 2D Convolution Filter */
Bias,
Matrix,
/* ... */
};
} // namespace loco
#endif // __LOCO_IR_DOMAIN_H__
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