Function ConvertAvgPoolOperator

tensorflow/lite/toco/import_tensorflow.cc:1252–1289

}

tensorflow::Status ConvertAvgPoolOperator(
    const NodeDef& node, const TensorFlowImportFlags& tf_import_flags,
    const ModelFlags& model_flags, Model* model) {
  CHECK_EQ(node.op(), "AvgPool");
  TF_QCHECK_OK(CheckInputsCount(node, tf_import_flags, 1));
  const auto& input_name = node.input(0);
  // We only support NHWC, which is the default data_format.
  // So if data_format is not defined, we're all good.
  if (node.attr().count("data_format")) {
    CHECK_EQ(GetStringAttr(node, "data_format"), "NHWC");
  }
  CHECK_EQ(GetDataTypeAttr(node, "T"), DT_FLOAT);
  auto* avgpool = new AveragePoolOperator;
  avgpool->inputs.push_back(input_name);
  avgpool->outputs.push_back(node.name());
  const auto& strides = GetListAttr(node, "strides");
  CHECK_EQ(strides.i_size(), 4);
  CHECK_EQ(strides.i(0), 1);
  CHECK_EQ(strides.i(3), 1);
  avgpool->stride_height = strides.i(1);
  avgpool->stride_width = strides.i(2);
  const auto& ksize = GetListAttr(node, "ksize");
  CHECK_EQ(ksize.i_size(), 4);
  CHECK_EQ(ksize.i(0), 1);
  CHECK_EQ(ksize.i(3), 1);
  avgpool->kheight = ksize.i(1);
  avgpool->kwidth = ksize.i(2);
  const auto& padding = GetStringAttr(node, "padding");
  if (padding == "SAME") {
    avgpool->padding.type = PaddingType::kSame;
  } else if (padding == "VALID") {
    avgpool->padding.type = PaddingType::kValid;
  } else {
    LOG(FATAL) << "Bad padding (only SAME and VALID are supported)";
  }
  model->operators.emplace_back(avgpool);
  return tensorflow::Status::OK();
}

tensorflow::Status ConvertBatchMatMulOperator(
    const NodeDef& node, const TensorFlowImportFlags& tf_import_flags,