changes to optimize max_pool for kelvin

Change-Id: Id7a7d12c4a341deaa106c3a6ac00167dc237ec91

tensorflow/lite/micro/kernels/kelvin/pooling.cc

diff --git a/tensorflow/lite/micro/kernels/kelvin/pooling.cc b/tensorflow/lite/micro/kernels/kelvin/pooling.cc
new file mode 100644
index 0000000..47f1362
--- /dev/null
+++ b/tensorflow/lite/micro/kernels/kelvin/pooling.cc
@@ -0,0 +1,120 @@
+/* Copyright 2024 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/kernels/internal/reference/pooling.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/micro/kernels/kernel_util.h"
+#include "tensorflow/lite/micro/kernels/pooling.h"
+#include "tensorflow/lite/micro/micro_log.h"
+#include "tflm/opt/opt.h"
+
+namespace tflite {
+
+namespace {
+
+TfLiteStatus AverageEval(TfLiteContext* context, TfLiteNode* node) {
+  TFLITE_DCHECK(node->builtin_data != nullptr);
+  auto* params = reinterpret_cast<TfLitePoolParams*>(node->builtin_data);
+
+  TFLITE_DCHECK(node->user_data != nullptr);
+  const OpDataPooling* data =
+      static_cast<const OpDataPooling*>(node->user_data);
+
+  const TfLiteEvalTensor* input =
+      micro::GetEvalInput(context, node, kPoolingInputTensor);
+  TfLiteEvalTensor* output =
+      micro::GetEvalOutput(context, node, kPoolingOutputTensor);
+
+  // Inputs and outputs share the same type, guaranteed by the converter.
+  switch (input->type) {
+    case kTfLiteFloat32:
+      AveragePoolingEvalFloat(context, node, params, data, input, output);
+      break;
+    case kTfLiteInt8:
+      AveragePoolingEvalQuantized<int8_t>(context, node, params, data, input,
+                                          output);
+      break;
+    case kTfLiteInt16:
+      AveragePoolingEvalQuantized<int16_t>(context, node, params, data, input,
+                                           output);
+      break;
+    default:
+      MicroPrintf("Input type %s is not currently supported",
+                  TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus MaxEval(TfLiteContext* context, TfLiteNode* node) {
+  TFLITE_DCHECK(node->builtin_data != nullptr);
+  auto* params = reinterpret_cast<TfLitePoolParams*>(node->builtin_data);
+
+  TFLITE_DCHECK(node->user_data != nullptr);
+  const OpDataPooling* data =
+      static_cast<const OpDataPooling*>(node->user_data);
+
+  const TfLiteEvalTensor* input =
+      micro::GetEvalInput(context, node, kPoolingInputTensor);
+  TfLiteEvalTensor* output =
+      micro::GetEvalOutput(context, node, kPoolingOutputTensor);
+
+  switch (input->type) {
+    case kTfLiteFloat32:
+      MaxPoolingEvalFloat(context, node, params, data, input, output);
+      break;
+    case kTfLiteInt8:
+      tflite::PoolParams op_params;
+      op_params.stride_height = params->stride_height;
+      op_params.stride_width = params->stride_width;
+      op_params.filter_height = params->filter_height;
+      op_params.filter_width = params->filter_width;
+      op_params.padding_values.height = data->padding.height;
+      op_params.padding_values.width = data->padding.width;
+      op_params.quantized_activation_min = data->activation_min;
+      op_params.quantized_activation_max = data->activation_max;
+      kelvin::opt::MaxPoolGeneric(op_params, tflite::micro::GetTensorShape(input),
+                    input->data.int8, tflite::micro::GetTensorShape(output),
+                    output->data.int8);
+      break;
+    case kTfLiteInt16:
+      MaxPoolingEvalQuantized<int16_t>(context, node, params, data, input,
+                                       output);
+      break;
+    default:
+      MicroPrintf("Type %s not currently supported.",
+                  TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
+  return context->AllocatePersistentBuffer(context, sizeof(OpDataPooling));
+}
+
+}  // namespace
+
+TFLMRegistration Register_AVERAGE_POOL_2D() {
+  return tflite::micro::RegisterOp(Init, PoolingPrepare, AverageEval);
+}
+
+TFLMRegistration Register_MAX_POOL_2D() {
+  return tflite::micro::RegisterOp(Init, PoolingPrepare, MaxEval);
+}
+
+}  // namespace tflite