// RUN: stablehlo-quant-opt %s -split-input-file -stablehlo-quantize | FileCheck %s

// Test that hybrid quantized dot_general is produced when q/dq pair only exists
// for weight.

module attributes {tf_saved_model.semantics} {
  func.func private @quantize_dot_general_fn(%arg0: tensor<1x2xf32>) -> tensor<1x3xf32> attributes {tf._original_func_name = "main_0"} {
    %cst = stablehlo.constant dense<3.000000e-01> : tensor<2x3xf32>

// RUN: stablehlo-quant-opt %s -split-input-file -stablehlo-insert-calibration-statistics-saver='aggregator-ops-to-ignore=skipping_id' | FileCheck %s

func.func @serving_default(%arg0: tensor<1x3x4x3xf32>) -> (tensor<1x2x2x2xf32>) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_input_tensor:0", outputs = "PartitionedCall:0"}} {

// RUN: tf-tfrt-opt -split-input-file -tfrt-reconfig-batch-op="tfrt-min-num-batch-threads=2 tfrt-min-max-enqueued-batches=3" %s | FileCheck %s --dump-input=always

// -----

// The num_batch_threads is lowered bound to 2 from the original attribute of 1

// CHECK-LABEL: func private @batched_function
func.func private @batched_function(%arg0: tensor<1x3xf32>) -> tensor<1x3xf32> {
  %2 = "tf.Identity"(%arg0) : (tensor<1x3xf32>) -> tensor<1x3xf32>

// RUN: tf-opt %s --tf-decompose-optionals --split-input-file | FileCheck %s

// CHECK-LABEL: @from_value
func.func @from_value(%arg0: tensor<f32>) {
  // CHECK-NOT: Optional
  %0 = "tf.OptionalFromValue"(%arg0) : (tensor<f32>) -> tensor<!tf_type.variant<tensor<f32>>>
  return
}

// -----

// CHECK-LABEL: @get_value
func.func @get_value(%arg0: tensor<!tf_type.variant<tensor<f32>>>) {
  // CHECK-NOT: Optional

		// Neither namespace nor pod has ambient mode enabled
		return false
	}
	if podHasSidecar(pod) {
		// Ztunnel and sidecar for a single pod is currently not supported; opt out.
		return false
	}
	if pod.GetLabels()[constants.DataplaneModeLabel] == constants.DataplaneModeNone {
		// Pod explicitly asked to not have ambient redirection enabled
		return false
	}
	return true
}

contains the telemetry collection mode, and the `GOTELEMETRYDIR` value setting which contains
the directory telemetry data and configuration are written to.

<!-- go.dev/issue/58894 ("all: add opt-in transparent telemetry to Go toolchain") -->

// RUN: tf-tfrt-opt -split-input-file -tf-device-decompose-resource-ops -sink-variable-as-named-array %s | FileCheck %s

// -----
// Basic test: all variables tensors are for devices and sinked as named ifrt arrays
//
//
// CHECK-LABEL:  func.func @serving_default(%arg0: tensor<1x3xf32>) -> tensor<1x1xf32> {
// CHECK-NEXT:   [[HANDLE2:%.*]] = "tf.VarHandleOp"
// CHECK-NEXT:   [[KEY:%.*]], [[FUTURE:%.*]] = "tf.IfrtLoadVariable"([[HANDLE2]])

    # Example
    # cniConfFileName: 10-calico.conflist

    # CNI bin and conf dir override settings
    # defaults:
    cniBinDir: "" # Auto-detected based on version; defaults to /opt/cni/bin.
    cniConfDir: /etc/cni/net.d
    cniConfFileName: ""
    # This directory must exist on the node, if it does not, consult your container runtime
    # documentation for the appropriate path.

        "//tensorflow/core:core_cpu",
    ],
    alwayslink = 1,
)

# This should just be a wrapper around tf_mlir_opt_main. Don't add
# direct dependencies to this binary.
tf_cc_binary(
    name = "tf-opt",
    testonly = True,
    deps = [
        ":tf_mlir_opt_main",
    ],
)

tf_cc_binary(
    name = "tf-reduce",
    testonly = True,
    srcs = ["tf_mlir_reduce_main.cc"],
    deps = [

// RecordFlags contains all flags associated with the "--record" operation
type RecordFlags struct {
	// Record indicates the state of the recording flag.  It is a pointer so a caller can opt out or rebind
	Record *bool

	changeCause string
}

// ToRecorder returns a ChangeCause recorder if --record=false was not
// explicitly given by the user
func (f *RecordFlags) ToRecorder() (Recorder, error) {