text: /* Copyright 2019 The TensorFlow Authors. 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 "tensorflow/lite/delegates/gpu/cl/kernels/softmax1x1.h"
  
  #include <string>
  
  #include "tensorflow/lite/delegates/gpu/cl/kernels/util.h"
  #include "tensorflow/lite/delegates/gpu/common/status.h"
  
  namespace tflite {
  namespace gpu {
  namespace cl {
  
  Softmax1x1::Softmax1x1(const OperationDef& definition)
      : GPUOperation(definition) {
    work_group_size_ = int3(32, 1, 1);
    code_ = GetSoftmaxKernelCode(definition_);
  }
  
  Softmax1x1::Softmax1x1(Softmax1x1&& kernel) : GPUOperation(std::move(kernel)) {}
  
  Softmax1x1& Softmax1x1::operator=(Softmax1x1&& kernel) {
    if (this != &kernel) {
      GPUOperation::operator=(std::move(kernel));
    }
    return *this;
  }
  
  std::string Softmax1x1::GetSoftmaxKernelCode(const OperationDef& op_def) {
    AddSrcTensor("src_tensor", op_def.src_tensors[0]);
    AddDstTensor("dst_tensor", op_def.dst_tensors[0]);
    args_.AddFloat("mask_x");
    args_.AddFloat("mask_y");
    args_.AddFloat("mask_z");
    args_.AddFloat("mask_w");
    args_.AddInt("slices_x32");
  
    std::string c = GetCommonDefines(op_def.precision);
    c += "__kernel void main_function(\n";
    c += "$0) {\n";
    if (op_def.IsBatchSupported()) {
      c += "  int batch_id = get_global_id(1);\n";
      c += "  if (batch_id >= args.dst_tensor.Batch()) return;\n";
      c += "  args.dst_tensor.SetBatchRef(batch_id);\n";
      c += "  args.src_tensor.SetBatchRef(batch_id);\n";
    }
    c += "  float4 mask = (float4)(args.mask_x, args.mask_y, args.mask_z, "
         "args.mask_w);\n";
    c += "  int offset = 0;\n";
    c += "  float sum = 0.0f;\n";
    c += "  int s = 0;\n";
    c += "  int tid = get_local_id(0);\n";
    c += "  do {\n";
    c += "    int z = offset + tid;\n";
    c += "    if (z < args.dst_tensor.Slices()) {\n";
    c += "      float4 mask_temp = z == args.dst_tensor.Slices() - 1 ? mask : "
         "(float4)(1.0f);\n";
    c += "      float4 src = args.src_tensor.Read<float>(0, 0, z);\n";
    c += "      sum += dot(mask_temp, exp(src));\n";
    c += "      offset += 32;\n";
    c += "    }\n";
    c += "    s++;\n";
    c += "  } while (s < args.slices_x32);\n";
    c += "\n";
    c += "  __local float4 tmp[8];\n";
    c += "  __local float* tmpx1 = (__local float*)tmp;\n";
    c += "  tmpx1[tid] = sum;\n";
    c += "  barrier(CLK_LOCAL_MEM_FENCE);\n";
    c += "  if (tid == 0) {\n";
    c += "    sum = dot((float4)(1.0f), tmp[0]);\n";
    c += "    sum += dot((float4)(1.0f), tmp[1]);\n";
    c += "    sum += dot((float4)(1.0f), tmp[2]);\n";
    c += "    sum += dot((float4)(1.0f), tmp[3]);\n";
    c += "    sum += dot((float4)(1.0f), tmp[4]);\n";
    c += "    sum += dot((float4)(1.0f), tmp[5]);\n";
    c += "    sum += dot((float4)(1.0f), tmp[6]);\n";
    c += "    sum += dot((float4)(1.0f), tmp[7]);\n";
    c += "    tmpx1[0] = 1.0f / sum;\n";
    c += "  }\n";
    c += "  barrier(CLK_LOCAL_MEM_FENCE);\n";
    c += "  sum = tmpx1[0];\n";
    c += "\n";
    c += "  offset = 0;\n";
    c += "  s = 0;\n";
    c += "  do {\n";
    c += "    int z = offset + tid;\n";
    c += "    if (z < args.dst_tensor.Slices()) {\n";
    c += "      FLT4 res = TO_FLT4(exp(args.src_tensor.Read<float>(0, 0, "
         "z))*sum);\n";
    c += "      args.dst_tensor.Write(res, 0, 0, z);\n";
    c += "      offset += 32;\n";
    c += "    }\n";
    c += "    s++;\n";
    c += "  } while (s < args.slices_x32);\n";
    c += "}\n";
    return c;
  }
  
  absl::Status Softmax1x1::BindArguments(ArgumentsBinder* args) {
    float4 mask = GetMaskForLastPlane(src_[0]->Channels());
    RETURN_IF_ERROR(args->SetFloat("mask_x", mask.x));
    RETURN_IF_ERROR(args->SetFloat("mask_y", mask.y));
    RETURN_IF_ERROR(args->SetFloat("mask_z", mask.z));
    RETURN_IF_ERROR(args->SetFloat("mask_w", mask.w));
    RETURN_IF_ERROR(
        args->SetInt("slices_x32", DivideRoundUp(src_[0]->Slices(), 32)));
    return absl::OkStatus();
  }
  
  int3 Softmax1x1::GetGridSize() const { return int3(32, dst_[0]->Batch(), 1); }
  
  Softmax1x1 CreateSoftmax1x1(const OperationDef& definition) {
    return Softmax1x1(definition);
  }
  
  }  // namespace cl
  }  // namespace gpu
  }  // namespace tflite
  