line-height: 18px;
  cursor: default;
  font-family: "Google Sans", Arial, sans-serif;
  font-size: 12pt;
  z-index: 2;
}
/* Box highlighting via shadows to avoid size changes */
.hilite { box-shadow: 0px 0px 0px 2px #000; z-index: 1; }
.hilite2 { box-shadow: 0px 0px 0px 2px #000; z-index: 1; }
/* Gap left between callers and callees */
.separator {
  position: absolute;
  text-align: center;
  font-size: 12pt;
  font-weight: bold;

}
#top table tr td:nth-child(6) {
  width: 100%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
}
#flathdr1, #flathdr2, #cumhdr1, #cumhdr2, #namehdr {
  cursor: ns-resize;
}
.hilite {
  background-color: #ebf5fb;
  font-weight: bold;

2)  Reference [TensorFlow Lite Model Colab](https://colab.research.google.com/gist/ymodak/0dfeb28255e189c5c48d9093f296e9a8/tensorflow-lite-debugger-colab.ipynb): Demonstrate how to convert your TF model to a TF Lite model (with quantization, if used) and run TFLite Inference (if possible).

```
(You can paste links or attach files by dragging & dropping them below)

name: TensorFlow Lite Other Issue description: Use this template to report any
issue in TensorFlow Lite that is not about Converters, Play Services or Ops
body: - type: dropdown id: issue-type attributes: label: Issue Type description:
What type of issue would you like to report? multiple: false options: - Bug -
Build/Install - Performance - Support - Feature Request - Documentation Feature
Request - Documentation Bug - Others validations: required: true - type:

#include "tensorflow/compiler/mlir/lite/common/tfl_pass_config.h"
#include "tensorflow/compiler/mlir/lite/debug/debug.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_export.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_import.h"
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/compiler/mlir/lite/tf_tfl_passes.h"

#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/lite/core/model_builder.h"
#include "tensorflow/lite/tools/optimize/reduced_precision_support.h"

namespace mlir {
namespace lite {
namespace {


TEST(SparsifyModelTest, MetadataIsAddedToOutputModel) {
  std::string expected_key = tflite::optimize::kTfLiteReducedPrecisionKey;

#include "absl/container/flat_hash_set.h"
#include "flatbuffers/flatbuffer_builder.h"  // from @flatbuffers
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/lite/c/c_api_types.h"
#include "tensorflow/lite/model.h"

namespace mlir {
namespace lite {

// Supported resulting types from quantization process.
enum class BufferType { QUANTIZED_INT8, QUANTIZED_FLOAT16 };

#include "mlir/Parser/Parser.h"  // from @llvm-project
#include "mlir/Support/FileUtilities.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/flatbuffer_export.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_import.h"
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"

namespace mlir {
namespace TFL {
namespace tac {

absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> ImportFlatbufferOrMlir(

#include "tensorflow/compiler/mlir/lite/metrics/error_collector.h"
#include "tensorflow/compiler/mlir/lite/metrics/types_util.h"
#include "tensorflow/lite/python/metrics/converter_error_data.pb.h"

namespace mlir {
namespace TFL {

// Collects errors when running the pass manager.
class ErrorCollectorInstrumentation : public PassInstrumentation {
  using ConverterErrorData = tflite::metrics::ConverterErrorData;

#include "mlir/Pass/PassManager.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/common/tfl_pass_config.h"
#include "tensorflow/lite/toco/toco_flags.pb.h"

namespace tensorflow {

// Add the TF to TFLite passes, specified in the pass_config, into a
// pass_manager. The session object will be provided when the TF MLIR is