package norm

import "unicode/utf8"

type input struct {
	str   string
	bytes []byte
}

func inputBytes(str []byte) input {
	return input{bytes: str}
}

func inputString(str string) input {
	return input{str: str}
}

func (in *input) setBytes(str []byte) {
	in.str = ""
	in.bytes = str
}

func (in *input) setString(str string) {
	in.str = str
	in.bytes = nil
}

 * limitations under the License.
 */
package org.gradle.api.tasks;

import java.lang.annotation.*;

/**
 * <p>Attached to a task property to indicate that the property specifies some input value for the task.</p>
 *
 * <p>This annotation should be attached to the getter method in Java or the property in Groovy.
 * Annotations on setters or just the field in Java are ignored.</p>
 *

// RUN: tac-translate -input-mlir -output-mlir -device-specs=GPU %s -o - 2>&1 | FileCheck %s

module {
func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>, %arg2: tensor<1xf32>, %arg3: tensor<1xf32>) -> tensor<2x1xf32> attributes {tf.entry_function = {inputs = "input0,input1,input2,input3", outputs = "output"}} {
  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

  %10 = "tf.opK"() : () -> tensor<*xi16>
  %11 = "tf.opL"() : () -> tensor<*xi64>
  tf_device.replicate([%0, %1, %2] as %input0: tensor<*xi1>, %9 as %input1: tensor<*xi8>, %10 as %input2: tensor<*xi16>, [%3, %4, %5] as %input3: tensor<*xi32>, [%6, %7, %8] as %input4: tensor<*xf32>, %11 as %input5: tensor<*xi64>) {n = 3 : i32} {
    tf_device.return
  }
  func.return

// CHECK:      %[[OP_A:[a-z0-9]*]] = "tf.opA"

# RUN: tf_tfl_translate -tf-input-arrays=input0,input1 \
# RUN:                  -tf-input-shapes=4:4 \
# RUN:                  -tf-input-data-types=DT_FLOAT,DT_FLOAT \
# RUN:                  -tf-output-arrays=Add \
# RUN:                  -tf-inference-type=DT_QUINT8 \
# RUN:                  -tf-input-min-values='-2,-3' \
# RUN:                  -tf-input-max-values='2,3' \
# RUN:                  --quant-stats=%s.stats \

}

// CHECK:      node {
// CHECK-NEXT:   name: "input0"
// CHECK-NEXT:   op: "_Arg"
// CHECK:      node {
// CHECK-NEXT:   name: "input1"
// CHECK-NEXT:   op: "_Arg"
// CHECK:      node {
// CHECK-NEXT:   name: "Add{{_.*_1}}"
// CHECK-NEXT:   op: "Add"
// CHECK-NEXT:   input: "input0"
// CHECK-NEXT:   input: "input1"
// CHECK:      node {
// CHECK-NEXT:   name: "Add"
// CHECK-NEXT:   op: "_Retval"

    def setup() {
        INVOCATION_COUNT.set(0)
    }

    def "input artifact selection is restored when using the in-memory cache"() {
        def transform = registerTransform(IdentityTransform)

        def inputArtifact1 = file("input1/input.txt")
        inputArtifact1.text = "Hello"

        def inputArtifact2 = file("input2/input.txt")
        inputArtifact2.text = "Hello"

        expect:

        0 * calculated._
    }

    def "notifies each of the inputs of task start and complete"() {
        def input1 = Mock(LifecycleAwareValue)
        def input2 = "other"
        def input3 = Mock(LifecycleAwareValue)
        def fileCollection = new CalculatedTaskInputFileCollection(taskDependencyFactory, ":task", Stub(MinimalFileSet), input1, input2, input3)

        when:
        fileCollection.prepareValue()

    }

    def "out-of-date when input file changes"() {
        given:
        def inputFile = file("input.txt")
        inputFile.text = "foo"
        buildFile << """
            ${keyInfo.addAsPropertiesScript()}
            signing {
                ${signingConfiguration()}
            }
            task signCustomFile(type: Sign) {
                sign(file("input.txt"))
            }
        """

// RUN: tf-opt -split-input-file -verify-diagnostics -tf-tpu-annotate-dynamic-shape-inputs %s | FileCheck %s

// Test that annotate the inputs of the cluster func to be dynamic shaped.

module attributes {tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:TPU_SYSTEM:0", "/job:worker/replica:0/task:0/device:TPU:0"]} {
   func.func @main(
      %arg0: tensor<2048xi64> {tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"},