// 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

// CHECK-LABEL: module attributes

// RUN: tfr-opt %s -canonicalize="test-convergence" -verify-diagnostics -split-input-file | FileCheck %s

// Tests for ops with canonicalization patterns.

// CHECK-LABEL: get_real_shape
func.func @get_real_shape(%arg0: tensor<1x2xf32>) -> tensor<2xindex> {
  %0 = "tfr.cast"(%arg0) : (tensor<1x2xf32>) -> !tfr.tensor
  %1 = tfr.get_shape %0 -> !shape.shape
  %2 = shape.to_extent_tensor %1 : !shape.shape -> tensor<2xindex>
  func.return %2 : tensor<2xindex>

// RUN: tf-opt %s -tfl-prepare-quantize -tfl-quantize  | FileCheck %s
// RUN: tf-opt %s -tfl-quantize="legacy-quantize=true" | FileCheck --check-prefix=LEGACY %s
// RUN: tf-opt %s -tfl-prepare-quantize -tfl-quantize="ops-blocklist=tfl.fully_connected,tfl.softmax locs-blocklist=Block,NullBlock" | FileCheck --check-prefix=BLOCK %s

// CHECK-LABEL: QuantizeFloatConst
func.func @QuantizeFloatConst() -> tensor<2x2x!quant.uniform<u8:f32, 7.8431372549019615E-4:128>> {

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

// Test to verify loop outlining.

// RUN: tf-opt --split-input-file --tfl-while-loop-outline %s | FileCheck %s
// Check that while loop outlining is nop if re-ran.
// RUN: tf-opt --tfl-while-loop-outline %s -o %t1
// RUN: tf-opt --tfl-while-loop-outline %t1 -o %t2
// RUN: diff %t1 %t2

// CHECK-LABEL: func @while
func.func @while() -> tensor<1xf32>
    attributes {tf.entry_function = {outputs = "result"}} {

// RUN: tfr-opt %s -verify-diagnostics -split-input-file | tfr-opt | FileCheck %s

// Tests for types, ops with custom constraints, verifiers, printer or parser
// methods.

// CHECK-LABEL: tensor_type_noconstraint
func.func private @tensor_type_noconstraint() -> !tfr.tensor

// -----

// CHECK-LABEL: tensor_type
func.func private @tensor_type() -> !tfr.tensor<T>

// -----

// CHECK-LABEL: tensor_list_type_noconstraint

# CHECK: fake/user/code/file_C.py:27:1: error: 'tf.Conv2D' op attribute 'data_format' failed to satisfy constraint: 'NHWC' or 'NCHW' convnet data format

node {
  name: "input"
  op: "Placeholder"
  attr {

// RUN: tf-opt %s -tf-functional-control-flow-to-cfg -split-input-file | FileCheck %s

func.func private @testIf1Then(tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
func.func private @testIf1Else(tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>

// CHECK-LABEL: func @testIf1Result(%arg0: tensor<i1>, %arg1: tensor<*xf32>, %arg2: tensor<*xf32>)
func.func @testIf1Result(tensor<i1>, tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32> {

// RUN: tf-tfrt-opt -verify-diagnostics -split-input-file -tfrt-fuse-tpu-compile-and-execute-ops -canonicalize %s | FileCheck %s --dump-input=fail --dump-input-filter=all

module attributes {tf_saved_model.semantics} {

// Test fusing _TPUCompileMlirOp and TPUExecuteOp into TPUCompileMlirAndExecuteOp.

// CHECK-LABEL: func private @test_fuse_tpu_ops
func.func private @test_fuse_tpu_ops(%arg0: tensor<*xi32>, %arg1: tensor<*x!tf_type.resource>) -> tensor<*xi32> {

// RUN: tf-opt %s -tf-fused-kernel-matcher | FileCheck %s

//===----------------------------------------------------------------------===//
// Conv2D + BiasAdd + <Activation> fusions.
//===----------------------------------------------------------------------===//

// CHECK-LABEL: conv2DBiasAdd_noActivation
func.func @conv2DBiasAdd_noActivation(%arg0: tensor<128xf32>, %arg1: tensor<1x1x3x128xf32>, %arg2: tensor<8x32x32x3xf32>) -> (tensor<*xf32>) {