// RUN: tf-quant-opt %s -split-input-file -verify-diagnostics \
// RUN:   -quant-insert-restore-op | FileCheck %s
// RUN: tf-quant-opt %s -split-input-file -verify-diagnostics \
// RUN:   -mlir-print-debuginfo -mlir-print-local-scope \
// RUN:   -quant-insert-restore-op | FileCheck %s --check-prefix CHECK-LOC

// RestoreV2 op created for a single VarHandleOp.

module attributes {tf_saved_model.semantics} {

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Ensure constants roundtrip exactly

func.func @bool() -> tensor<4xi1> {
  // CHECK-LABEL: @bool
  // CHECK: value = dense<[false, true, true, false]> : tensor<4xi1>
  %0 = "tfl.pseudo_const"() { value = dense<[false, true, true, false]> : tensor<4xi1> } : () -> tensor<4xi1>
  func.return %0 : tensor<4xi1>
}

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s

// RUN:     -allow-unregistered-dialect -mlir-disable-threading \
// RUN:     -split-input-file -verify-diagnostics | FileCheck %s
// RUN: tf-quant-opt %s -quant-merge-initializer-function-ops-to-main \
// RUN:     -allow-unregistered-dialect -mlir-disable-threading \
// RUN:     -split-input-file -mlir-print-local-scope -mlir-print-debuginfo \
// RUN:     -verify-diagnostics | FileCheck %s --check-prefix CHECK-LOC

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Ensure lstm roundtrip exactly

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer --emit-stablehlo-ops=true %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir --disable-vhlo-to-stablehlo=true - -o - | FileCheck %s
// test stablehlo roundtrip

// Identity function to make the exporter happy
func.func @main(%arg0: tensor<4xi8>) -> tensor<4xi8> {
  func.return %arg0 : tensor<4xi8>
}

// RUN: tf-mlir-translate -mlir-tf-str-attr-to-mlir %s -mlir-print-debuginfo -mlir-print-local-scope | FileCheck %s

"\0A\0Amodule attributes {tf.versions = {producer = 888 : i32}} {\0A func.func @main(%arg0: tensor<?xi32>) -> tensor<?xi32> {\0A %0 = \22tf.Identity\22(%arg0) : (tensor<?xi32>) -> tensor<?xi32> loc(unknown)\0A return %0 : tensor<?xi32> loc(unknown)\0A } loc(unknown)\0A} loc(unknown)"

// Test simple serialized computation consisting of a function named `main`

func.func @main() {
  cf.br ^bb1
^bb1:
  func.return
}

// -----

// Tests main function is terminated with a non MLIR ReturnOp.

// expected-error@+1 {{expects function 'main' to have a MLIR ReturnOp}}
func.func @main() {
^bb0:
  tf_device.return
}

// -----

// Tests main function with invalid resource argument subtype.

  // expected-error @+1 {{'tfl.lstm' op attribute 'kernel_type' failed to satisfy constraint: lstm_kernel_type whose value is mlir::TFL::LSTMKernelType::FULL}}

    return %0 : tensor<i1>
  }
}

// -----
// This test verifies that the sequencing pass WAI even when tf.WriteSummaryOp is present. This is a complement to the logic/test for embedding_pipelining.cc/mlir
module {
  func.func @main(%arg0: tensor<*x!tf_type.resource>) {
    %cst_main = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>