name: tests

on:
  push:
    branches-ignore:
      - 'gh-pages'
  pull_request:
    branches-ignore:
      - 'gh-pages'

permissions:
  contents: read

jobs:
  # Label of the container job
  sqlite:
    strategy:
      matrix:
        go: ['1.22', '1.21', '1.20']
        platform: [ubuntu-latest] # can not run in windows OS
    runs-on: ${{ matrix.platform }}

    steps:
    - name: Set up Go 1.x

#
# There should be few tests in here and it should be rare where the execution
# tests are not tested by unit tests already. This is useful for verifying some
# runtime behavior, but the majority of runtime tests should be TFLite side and
# invariants only verified in the converter/compiler.

load("//tensorflow:tensorflow.default.bzl", "filegroup")
load("//tensorflow/compiler/mlir:glob_lit_test.bzl", "glob_lit_tests")

limitations under the License.
==============================================================================*/
#include "tensorflow/compiler/mlir/lite/schema/schema_conversion_utils.h"

#include <algorithm>

namespace tflite {

int8_t ConvertBuiltinCodeToDeprecatedBuiltinCode(
    const BuiltinOperator builtin_code) {
  return (builtin_code < BuiltinOperator_PLACEHOLDER_FOR_GREATER_OP_CODES)

  let options = [
    Option<"default_min_", "default-min", "double", "-1.0",
               "Default minimum value for TFLite quantization">,
    Option<"default_max_", "default-max", "double", "1.0",
               "Default maximum value for TFLite quantization">,
    Option<"is_signed_", "is-signed", "bool", "false",
               "Is the corresponding integer signed">,
  ];
}

==============================================================================*/

// This is the operation enums definition file for TensorFlow Lite.

#ifndef TFL_OP_ENUMS
#define TFL_OP_ENUMS

include "mlir/IR/AttrTypeBase.td"
include "mlir/IR/EnumAttr.td"
include "mlir/IR/OpBase.td"
include "tensorflow/compiler/mlir/lite/ir/tfl_op_interfaces.td"

// A string attribute whose value are one of the values in `cases`.

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// This only test the exporter and importer are working without min/max quantization parameters.

func.func @main(tensor<40x37xf32>, tensor<40x37xf32>) -> tensor<40x40xf32> {
^bb0(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>):
  %cst = arith.constant dense<1.0> : tensor<40xf32>

// is std::nullopt, all signatures will be imported. Otherwise, only names
// in `exported_names` are imported.
//
// Note that the word `Lite` means it is a lighter version compared to
// ConvertSavedModelV1ToMlir(), and is not related to TFLite.
//
// TODO(b/179683149): Rename this class to avoid confusion with TFLite.
absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> ConvertSavedModelV1ToMlirLite(

#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/op_or_arg_name_mapper.h"
#include "tensorflow/lite/toco/toco_flags.pb.h"

namespace tflite {
// Options for exporting to Flatbuffer.
struct FlatbufferExportOptions {
  // TocoFlags proto. The following fields are migrated.
  // bool emit_builtin_tflite_ops  -> !toco_flags.force_select_tf_ops()

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate -output-arrays=mul,div,exp --experimental-prune-unreachable-nodes-unconditionally --tflite-flatbuffer-to-mlir - -o - | FileCheck %s

// CHECK: (%[[ARG:.*]]: tensor<4xf32>) -> (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>)
func.func @main(%arg0: tensor<4xf32>) -> tensor<4xf32> attributes {tf.entry_function = {inputs = "mul"}} {

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate -output-arrays=mul,exp,div --experimental-prune-unreachable-nodes-unconditionally --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Confirm graph pruning.

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")