// RUN: stablehlo-quant-opt %s -split-input-file -stablehlo-unfuse-mhlo-batch-norm | FileCheck %s

// CHECK-LABEL: @unfuse_batch_norm
// CHECK-SAME: %[[X:[^:[:space:]]+]]
// CHECK-SAME: %[[SCALE:[^:[:space:]]+]]
// CHECK-SAME: %[[OFFSET:[^:[:space:]]+]]
// CHECK-SAME: %[[MEAN:[^:[:space:]]+]]
// CHECK-SAME: %[[VARIANCE:[^:[:space:]]+]]
func.func @unfuse_batch_norm(
    %x: tensor<4x256xf32>, %scale: tensor<256xf32>, %offset: tensor<256xf32>,

// CHECK-DAG: %[[CONST:.*]] = "tf.Const"() <{value = dense<0.000000e+00> : tensor<512x512xf32>}> : () -> tensor<512x512xf32>
// CHECK: %[[PARTITIONEDCALL:.*]] = "tf.PartitionedCall"(%arg0, %[[CONST]])
// CHECK-SAME: <{config = "",
// CHECK-SAME: f = @composite_matmul_fn_1}>
// CHECK-NOT: {_tfl_quant_trait = "fully_quantizable"
// CHECK: %[[UNQUANTIZED_OUTPUT:.*]] = "tf.MatMul"(%arg0, %arg0)
// CHECK: }

// CHECK-LABEL: private @composite_matmul_fn_1

// CHECK-SAME: %[[ARG_0:.*]]: tensor<!tf_type.variant>, %[[ARG_1:.*]]: tensor<i64>
func.func @single_state_single_dataset_type_no_arguments(
      %arg0: tensor<!tf_type.variant>,
      %arg1: tensor<i64>
    ) {
    // CHECK:      %[[ANON_ITER:[0-9]*]] = "tf.AnonymousIteratorV3"
    // CHECK-SAME: output_shapes = [#tf_type.shape<32>]
    // CHECK-SAME: output_types = [f32]

        id.getDisplayName() == "original -> current (foo)"
    }

    def "equals and hash code differentiate between same and different instances"() {
        def componentId = newComponentId("foo")

        when:
        def id = new TransformedComponentFileArtifactIdentifier(componentId, "a", "b")
        def same = new TransformedComponentFileArtifactIdentifier(componentId, "a", "b")

Did you know?

  - [testing.T] is one doc link.
  - So is [testing.M].
  - So is [testing.B].
    This is the same list paragraph.

    There is [testing.PB] in this list item, too!
-- text --
Did you know?

  - testing.T is one doc link.

  - So is testing.M.

  - So is testing.B. This is the same list paragraph.

    There is testing.PB in this list item, too!
-- markdown --
Did you know?

# Tests different SignatureDef's with identical method_name string

# CHECK:      func {{@[a-zA-Z_0-9]+}}(
# CHECK-SAME:   {{.*}})
# CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["key"]

# CHECK:      func {{@[a-zA-Z_0-9]+}}(
# CHECK-SAME:   {{.*}})
# CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["key2"]


def Test():

  x = tf.constant(1.0, shape=(3, 3))

*/
package p

func f() {
	var x interface{}
	switch x.(type) { // should remain the same
	}
	switch x.(type) { // should become: switch x.(type) {
	}

	switch x.(type) { // should remain the same
	case int:
	}
	switch x.(type) { // should become: switch x.(type) {
	case int:
	}

	switch x.(type) { // should remain the same
	case []int:
	}

	// Parenthesized (x.(type)) in type switches containing cases

 They must not be standard packages (like fmt), meta-patterns (std, cmd,
 all), or relative or absolute file paths.

 - All arguments must have the same version suffix. Different queries are not
 allowed, even if they refer to the same version.

 - All arguments must refer to packages in the same module at the same version.

 - Package path arguments must refer to main packages. Pattern arguments
 will only match main packages.

// RUN: odml-to-stablehlo-opt %s --transpose-commute-ops | FileCheck %s
// CHECK-LABEL:   func.func @commute_transpose_pad(
// CHECK-SAME:          %[[INPUT:.*]]: tensor<1x112x112x64xf32>,
// CHECK-SAME:          %[[PAD_VAL:.*]]: tensor<f32>) -> tensor<1x64x114x114xf32> {
// CHECK:           %[[PAD:.*]] = stablehlo.pad %[[INPUT]], %[[PAD_VAL]],
// CHECK:               low = [0, 1, 1, 0], high = [0, 1, 1, 0], interior = [0, 0, 0, 0]

// CHECK: tfrt_fallback_async.set_resource
// CHECK-SAME: {device = "/device:CPU:0", index = 0 : i64}


// CHECK-LABEL: func @init
// CHECK-SAME: {tfrt.cost_threshold = 1 : i64}
func.func @func_init() attributes {tf_saved_model.exported_names = ["init"]} {
  func.return
}

// CHECK-LABEL: func @basic
// CHECK-SAME: ([[in_chain:%.*]]: !tfrt.chain
// CHECK-SAME: [[arg0:%.*]]: !tfrt_fallback.tf_tensor,