126 lines
4.0 KiB
C++
126 lines
4.0 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/lite/delegates/gpu/gl/kernels/add.h"
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#include <algorithm>
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#include <cstdint>
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#include <cstring>
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#include <string>
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#include <vector>
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#include "absl/memory/memory.h"
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#include "absl/strings/str_cat.h"
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#include "tensorflow/lite/delegates/gpu/common/data_type.h"
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#include "tensorflow/lite/delegates/gpu/common/status.h"
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#include "tensorflow/lite/delegates/gpu/common/types.h"
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namespace tflite {
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namespace gpu {
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namespace gl {
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namespace {
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class Add : public NodeShader {
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public:
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Status GenerateCode(const GenerationContext& ctx,
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GeneratedCode* generated_code) const final {
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auto attr = absl::any_cast<AddAttributes>(ctx.node->operation.attributes);
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auto adds = absl::get_if<Tensor<Linear, DataType::FLOAT32>>(&attr.param);
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auto scalar = absl::get_if<float>(&attr.param);
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auto inputs = ctx.graph->FindInputs(ctx.node->id);
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if (!adds && !scalar) {
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// check if it is a broadcast
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if (inputs.size() == 2 &&
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inputs[0]->tensor.shape != inputs[1]->tensor.shape &&
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inputs[1]->tensor.shape.h == 1 && inputs[1]->tensor.shape.w == 1 &&
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inputs[0]->tensor.shape.c == inputs[1]->tensor.shape.c) {
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*generated_code = {
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/*parameters=*/{},
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/*objects=*/{},
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/*shared_variables=*/{},
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/*workload=*/uint3(),
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/*workgroup=*/uint3(),
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/*source_code=*/
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"value_0 = $input_data_1[gid.z]$ + $input_data_0[gid.x, gid.y, "
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"gid.z]$;",
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/*input=*/IOStructure::ONLY_DEFINITIONS,
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/*output=*/IOStructure::AUTO,
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};
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return OkStatus();
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}
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std::string code = "value_0 = value_0";
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for (int index = 1; index < inputs.size(); ++index) {
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if (inputs[index]->tensor.shape != inputs[0]->tensor.shape) {
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return InvalidArgumentError("Shapes are not equal");
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}
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absl::StrAppend(&code, " + value_", index);
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}
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absl::StrAppend(&code, ";");
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*generated_code = {
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/*parameters=*/{},
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/*objects=*/{},
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/*shared_variables=*/{},
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/*workload=*/uint3(),
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/*workgroup=*/uint3(),
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/*source_code=*/std::move(code),
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/*input=*/IOStructure::AUTO,
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/*output=*/IOStructure::AUTO,
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};
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return OkStatus();
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}
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if (scalar) {
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*generated_code = {
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/*parameters=*/{{"scalar", *scalar}},
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/*objects=*/{},
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/*shared_variables=*/{},
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/*workload=*/uint3(),
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/*workgroup=*/uint3(),
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/*source_code=*/"value_0 += $scalar$;",
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/*input=*/IOStructure::AUTO,
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/*output=*/IOStructure::AUTO,
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};
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} else {
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auto shape = inputs[0]->tensor.shape;
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*generated_code = {
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/*parameters=*/{},
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/*objects=*/{{"add_buffer", MakeReadonlyObject(adds->data)}},
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/*shared_variables=*/{},
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// Declare workload explicitly because shader depends on gid.z.
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/*workload=*/
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uint3(shape.w, shape.h, IntegralDivideRoundUp(shape.c, 4)),
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/*workgroup=*/uint3(),
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/*source_code=*/"value_0 += $add_buffer[gid.z]$;",
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/*input=*/IOStructure::AUTO,
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/*output=*/IOStructure::AUTO,
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};
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}
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return OkStatus();
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}
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};
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} // namespace
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std::unique_ptr<NodeShader> NewAddNodeShader() {
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return absl::make_unique<Add>();
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}
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} // namespace gl
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} // namespace gpu
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} // namespace tflite
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