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-rw-r--r--runtimes/neurun/src/backend/cpu/InitializerGenerator.cc208
1 files changed, 0 insertions, 208 deletions
diff --git a/runtimes/neurun/src/backend/cpu/InitializerGenerator.cc b/runtimes/neurun/src/backend/cpu/InitializerGenerator.cc
deleted file mode 100644
index 7b08c7131..000000000
--- a/runtimes/neurun/src/backend/cpu/InitializerGenerator.cc
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@@ -1,208 +0,0 @@
-/*
- * Copyright (c) 2018 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.
- */
-
-#include "InitializerGenerator.h"
-
-#include "internal/nnapi/kernel/Reader.h"
-#include "internal/nnapi/kernel/View.h"
-#include "util/kernel/IndexIterator.h"
-
-#include "NeuralNetworks.h"
-
-namespace neurun
-{
-namespace backend
-{
-namespace cpu
-{
-
-InitializerGenerator::InitializerGenerator(const neurun::graph::operand::Set &ctx) : _ctx(ctx)
-{
- // DO NOTHING
-}
-
-Initializer
-InitializerGenerator::generateWeight(const graph::operation::Conv2D::Implicit::Node &node)
-{
- const ::neurun::graph::operand::Index ker_index{node.getInputs().at(1)};
-
- const auto ker_shape = _ctx.at(ker_index).shape().asKernel();
- auto ker_base = _ctx.at(ker_index).data().base();
- auto ker_size = _ctx.at(ker_index).data().size();
-
- return [ker_shape, ker_base, ker_size](::arm_compute::ITensor &tensor) {
- const ::internal::nnapi::kernel::Reader<float> from{ker_shape, ker_base, ker_size};
- ::internal::nnapi::kernel::View<float> into{&tensor};
-
- ::nnfw::util::kernel::iterate(ker_shape)
- << [&](uint32_t nth, uint32_t ch, uint32_t row, uint32_t col) {
- const auto value = from.at(nth, ch, row, col);
- into.at(nth, row, col, ch) = value;
- };
- };
-}
-
-Initializer InitializerGenerator::generateWeight(const graph::operation::FullyConnected::Node &node)
-{
- const ::neurun::graph::operand::Index weight_index{node.getInputs().at(1)};
- const ::neurun::graph::operand::Index input_index{node.getInputs().at(0)};
-
- const auto num_output = _ctx.at(weight_index).shape().dim(0);
- auto weight_base = _ctx.at(weight_index).data().base();
- auto weight_size = _ctx.at(weight_index).data().size();
- auto weight_type = _ctx.at(weight_index).typeInfo().type();
-
- // NOTE We assume that input is a feature map
- // TODO Remove this restriction!
- const auto ifm_shape = _ctx.at(input_index).shape().asFeature();
-
- switch (weight_type)
- {
- case ::neurun::graph::operand::DataType::TENSOR_FLOAT32:
- {
- return [num_output, ifm_shape, weight_base, weight_size](::arm_compute::ITensor &tensor) {
- const ::nnfw::util::kernel::Shape ker_shape{num_output, ifm_shape.C, ifm_shape.H,
- ifm_shape.W};
- const ::internal::nnapi::kernel::Reader<float> from{ker_shape, weight_base, weight_size};
-
- ::nnfw::util::kernel::iterate(ker_shape)
- << [&](uint32_t nth, uint32_t ch, uint32_t row, uint32_t col) {
- const auto value = from.at(nth, ch, row, col);
-
- uint32_t offset = 0;
-
- // NNAPI uses NHWC ordering
- offset += nth * ifm_shape.H * ifm_shape.W * ifm_shape.C;
- offset += row * ifm_shape.W * ifm_shape.C;
- offset += col * ifm_shape.C;
- offset += ch;
-
- const ::arm_compute::Coordinates coordinate{offset};
-
- auto into = reinterpret_cast<float *>(tensor.ptr_to_element(coordinate));
-
- *into = value;
- };
- };
- }
- case ::neurun::graph::operand::DataType::TENSOR_QUANT8_ASYMM:
- {
- return [num_output, ifm_shape, weight_base, weight_size](::arm_compute::ITensor &tensor) {
- const ::nnfw::util::kernel::Shape ker_shape{num_output, ifm_shape.C, ifm_shape.H,
- ifm_shape.W};
- const ::internal::nnapi::kernel::Reader<uint8_t> from{ker_shape, weight_base, weight_size};
- ::nnfw::util::kernel::iterate(ker_shape)
- << [&](uint32_t nth, uint32_t ch, uint32_t row, uint32_t col) {
- const auto value = from.at(nth, ch, row, col);
- uint32_t offset = 0;
-
- // NNAPI uses NHWC ordering
- offset += nth * ifm_shape.H * ifm_shape.W * ifm_shape.C;
- offset += row * ifm_shape.W * ifm_shape.C;
- offset += col * ifm_shape.C;
- offset += ch;
-
- const ::arm_compute::Coordinates coordinate{offset};
-
- auto into = reinterpret_cast<uint8_t *>(tensor.ptr_to_element(coordinate));
-
- *into = value;
- };
- };
- }
- default:
- {
- throw std::runtime_error("Not supported weight type");
- }
- }
-}
-
-Initializer InitializerGenerator::generateBias(const graph::operation::Conv2D::Implicit::Node &node)
-{
- // TODO Refactor so we can reuse the common code
-
- const ::neurun::graph::operand::Index bias_index{node.getInputs().at(2)};
-
- auto bias_base = _ctx.at(bias_index).data().base();
- const auto bias_size = _ctx.at(bias_index).shape().asVector();
-
- return [bias_base, bias_size](::arm_compute::ITensor &tensor) {
- for (int32_t n = 0; n < bias_size; ++n)
- {
- const ::arm_compute::Coordinates coordinate{n};
-
- float *into = reinterpret_cast<float *>(tensor.ptr_to_element(coordinate));
-
- const float *from = reinterpret_cast<const float *>(bias_base) + n;
- const auto value = *from;
-
- *into = value;
- }
- };
-}
-
-Initializer InitializerGenerator::generateBias(const graph::operation::FullyConnected::Node &node)
-{
- const ::neurun::graph::operand::Index bias_index{node.getInputs().at(2)};
-
- auto bias_base = _ctx.at(bias_index).data().base();
- auto bias_type = _ctx.at(bias_index).typeInfo().type();
- const auto bias_size = _ctx.at(bias_index).shape().asVector();
-
- switch (bias_type)
- {
- case ::neurun::graph::operand::DataType::TENSOR_FLOAT32:
- {
- return [bias_base, bias_size](::arm_compute::ITensor &tensor) {
- for (int32_t n = 0; n < bias_size; ++n)
- {
- const ::arm_compute::Coordinates coordinate{n};
-
- float *into = reinterpret_cast<float *>(tensor.ptr_to_element(coordinate));
-
- const float *from = reinterpret_cast<const float *>(bias_base) + n;
- const auto value = *from;
-
- *into = value;
- }
- };
- }
- case ::neurun::graph::operand::DataType::TENSOR_QUANT8_ASYMM:
- {
- return [bias_base, bias_size](::arm_compute::ITensor &tensor) {
- for (int32_t n = 0; n < bias_size; ++n)
- {
- const ::arm_compute::Coordinates coordinate{n};
-
- uint8_t *into = reinterpret_cast<uint8_t *>(tensor.ptr_to_element(coordinate));
-
- const uint8_t *from = reinterpret_cast<const uint8_t *>(bias_base) + n;
- const auto value = *from;
-
- *into = value;
- }
- };
- }
- default:
- {
- throw std::runtime_error("Not supported bias type");
- }
- }
-}
-
-} // namespace cpu
-} // namespace backend
-} // namespace neurun
generated by cgit v1.2.3 (git 2.25.1) at 2024-04-23 10:32:40 +0000