coverage[toml] >= 6.5.0,< 8.0
mypy ==1.8.0
ruff ==0.2.0
dirty-equals ==0.6.0
# TODO: once removing databases from tutorial, upgrade SQLAlchemy
# probably when including SQLModel
sqlalchemy >=1.3.18,<1.4.43
databases[sqlite] >=0.3.2,<0.7.0
flask >=1.1.2,<3.0.0
anyio[trio] >=3.2.1,<4.0.0
PyJWT==2.8.0
pyyaml >=5.3.1,<7.0.0
passlib[bcrypt] >=1.7.2,<2.0.0

# types
types-ujson ==5.7.0.1

// RUN: json_to_flatbuffer %p/test_schema.fbs %s | flatbuffer_translate --tflite-flatbuffer-to-mlir -o - | FileCheck %s

// CHECK: %0 = "tfl.pseudo_const"() <{value = dense<2> : tensor<2xi32>}> : () -> tensor<2xi32>
// CHECK: %1 = "tfl.reshape"(%arg0, %0) : (tensor<1x4xf32>, tensor<2xi32>) -> tensor<2x2xf32>

{
  "version": 3,
  "operator_codes": [
    {
      "builtin_code": "RESHAPE"
    }
  ],
  "subgraphs": [
    {
      "tensors": [

// RUN: json_to_flatbuffer %p/test_schema.fbs %s | flatbuffer_translate --tflite-flatbuffer-to-mlir -o - | FileCheck %s

// CHECK: %[[CST:.*]] = "tfl.no_value"() <{value}> : () -> none
// CHECK: %[[RES0:.*]] = "tfl.conv_2d"(%arg0, %arg1, %[[CST]]) <{dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32}> : (tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, none) -> tensor<256x32x32x16xf32>

  let constructor = "mlir::odml::CreateUniformQuantizedStableHloToTflPass()";
  let description = [{
    Converts StableHLO ops that accept or return uniform quantized types to
    equivalent ops in the TFLite dialect.
  }];
  let dependentDialects = [
    "stablehlo::StablehloDialect",
    "quant::QuantizationDialect",
    "mlir::TFL::TFLDialect",
  ];
}

// There are four parts: a boolean negative flag, a form byte with three possible states
// (finite=0, infinite=1, NaN=2), a base-2 big-endian integer
// coefficient (also known as a significand) as a []byte, and an int32 exponent.
// These are composed into a final value as "decimal = (neg) (form=finite) coefficient * 10 ^ exponent".
// A zero length coefficient is a zero value.

//RUN: tf_tfl_translate --enable-stablehlo-conversion --input-mlir %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s


module {
func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> {
  %1 = arith.constant dense<1> : tensor<1xi32>
  %2 = arith.constant dense<2.0> : tensor<1x1x2xf32>
  %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""}
    : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32>

#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"

namespace mlir {
namespace lite {

// Sparsify the `input_model` and write the result to a flatbuffer `builder`.
absl::Status SparsifyModel(const tflite::ModelT& input_model,
                           flatbuffers::FlatBufferBuilder* builder);
}  // namespace lite
}  // namespace mlir

  private enum TimeoutsToUse {
    ANY(Timeout.values()),
    PAST(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO),
    FUTURE(Timeout.SMALL, Timeout.MAX),
    SMALL(Timeout.SMALL),
    FINITE(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO, Timeout.SMALL),
    INFINITE(Timeout.LARGE, Timeout.MAX);

    final ImmutableList<Timeout> timeouts;

    TimeoutsToUse(Timeout... timeouts) {

#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"  // IWYU pragma: keep
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/custom_call.h"
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/dot_general.h"  // IWYU pragma: keep
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/reduce.h"

    ],
    deps = [
        ":common",
        ":runtime_metadata_fbs",
        "//tensorflow/compiler/mlir/lite:tensorflow_lite",
        "//tensorflow/compiler/mlir/lite/experimental/tac/hardwares:target_hardware",
        "//tensorflow/compiler/mlir/lite/quantization/ir:QuantOps",
        "//tensorflow/compiler/mlir/tensorflow",
        "@flatbuffers",
        "@llvm-project//llvm:Support",
        "@llvm-project//mlir:ArithDialect",