// RUN: odml-converter --shlo-simplify %s -split-input-file | FileCheck %s

func.func @foldDiv() -> tensor<2xf32> {
  %0 = stablehlo.constant dense<[2.0, 3.0]> : tensor<2xf32>
  %1 = stablehlo.constant dense<[4.0, 6.0]> : tensor<2xf32>
  %2 = stablehlo.divide %0, %1 : tensor<2xf32>
  return %2 : tensor<2xf32>
}

// CHECK-LABEL: foldDiv
// CHECK: stablehlo.constant dense<5.000000e-01> : tensor<2xf32>

// -----

config.test_source_root = config.mlir_test_dir

# test_exec_root: The root path where tests should be run.
config.test_exec_root = os.environ['RUNFILES_DIR']

if platform.system() == 'Windows':
  tool_patterns = [
      ToolSubst('FileCheck.exe', unresolved='fatal'),
      #  Handle these specially as they are strings searched for during testing.
      ToolSubst('count.exe', unresolved='fatal'),
      ToolSubst('not.exe', unresolved='fatal')
  ]

// RUN: tf-opt %s -tfl-prepare-quantize-dynamic-range="enable-dynamic-range-per-channel-quantization=false" | FileCheck --check-prefix=PerTensor %s
// RUN: tf-opt %s -tfl-prepare-quantize-dynamic-range="enable-float16-quantization" | FileCheck --check-prefix=Float16 %s
// RUN: tf-opt %s -tfl-prepare-quantize-dynamic-range="enable-custom-op-quantization=CustomTestOp=1-3,CustomTestOp3=3" | FileCheck --check-prefix=CustomOp %s

// RUN: odml-to-stablehlo-opt %s -constant-fold-broadcast-pass -cse -verify-diagnostics | FileCheck %s

// CHECK-LABEL: @foldBroadcastInDimBeforeMulOp_bcast_dim_1D_float
func.func @foldBroadcastInDimBeforeMulOp_bcast_dim_1D_float() -> (tensor<1x1x2x4xf32>) {
  // CHECK-DAG: %[[RES:.*]] = mhlo.constant dense<{{\[\[\[\[}}1.000000e+00, 4.000000e+00, 9.000000e+00, 1.600000e+01], [5.000000e+00, 1.200000e+01, 2.100000e+01, 3.200000e+01]]]]> : tensor<1x1x2x4xf32>

// RUN: tf-opt %s -tf-replicated-clustering-bridge-v1 | FileCheck %s

module attributes {tf.devices = ["/job:localhost/replica:0/task:0/device:CPU:0", "/job:localhost/replica:0/task:0/device:TPU:0", "/job:localhost/replica:0/task:0/device:TPU:1", "/job:localhost/replica:0/task:0/device:TPU_SYSTEM:0"], tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 296 : i32}} {
  func.func @main() {
// CHECK: arith.constant
// CHECK: TPUCompile
// CHECK: TPUExecute

  let description = [{
    This test-only pass is the same as `LiftQuantizableSpotsAsFunctionsPass` but
    has predefined `QuantizationSpecs` to make FileCheck testing easier.
  }];
  let options = [
    Option<"quantization_specs_", "quantization-specs",
      "mlir::quant::stablehlo::testing::TestQuantizationSpecs",

// RUN: tf-opt %s -tf-replicated-clustering-bridge-v2 -tfrt-lower-cluster-to-runtime-ops-tpu 2>&1 | FileCheck %s

// TPUReshardVariables should be inserted even when While functions' shapes are
// different than While operand shapes. Test the whole tf-tpu-bridge because
// correct insertion of TPUReshardVariables depends on multiple passes including
// TPUVariableRuntimeReformatting, ShapeInference, WhileRegion canonicalization,
// and TPUMergeVariablesWithExecute.

// RUN: tf-quant-opt %s -split-input-file -quant-add-dump-tensor-op='debugger_type=whole_model' | FileCheck --check-prefix=WholeModel %s
// RUN: tf-quant-opt %s -split-input-file -quant-add-dump-tensor-op='debugger_type=int_per_layer' | FileCheck --check-prefix=IntPerLayer %s
// RUN: tf-quant-opt %s -split-input-file -quant-add-dump-tensor-op='debugger_type=float_per_layer' | FileCheck --check-prefix=FloatPerLayer %s

module {

// RUN: tf-tfrt-opt -split-input-file -pass-pipeline='builtin.module(tf-to-mlrt, inline)' %s | FileCheck %s -dump-input=fail

// Test generated tf_mlrt while body and predicate is inlined.

func.func @then(%x: tensor<i1>, %y: tensor<i1>, %z: tensor<i32>) -> tensor<i1> {
  return %x: tensor<i1>
}

func.func @else(%x: tensor<i1>, %y: tensor<i1>, %z: tensor<i32>) -> tensor<i1> {
  return %y: tensor<i1>
}

// CHECK-LABEL: func @while_cond_if

// RUN: tf-opt "-tfxla-verify-legalization=legalize-chlo=true" -verify-diagnostics -split-input-file %s | FileCheck -dump-input=fail %s
// Tests the VerifyTFXLALegalization Pass, that just ensures we don't have
// any illegal ops at the end of the pipeline.

// CHECK-LABEL: allowsMHLO
func.func @allowsMHLO() -> (tensor<8x64x32x4xcomplex<f32>> {mhlo.sharding = ""}) {
  %0 = mhlo.constant dense<(1.000000e+00,-1.000000e+00)> : tensor<128x32x4xcomplex<f32>>