// 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"},

                inputDirectory = file("input")
                outputDirectory = file("build/output")
            }
        """
        def toBeModifiedPath = "in/some/subdir/input1.txt"
        def toBeRemovedPath = "in/some/subdir/input2.txt"
        def toBeAddedPath = "in/some/other/subdir/other-input.txt"
        file("input/$toBeModifiedPath").text = "input to copy"
        file("input/${toBeRemovedPath}").text = "input to copy"

    }

    def "can increase the quiet period"() {
        given:
        inputDir.createDir("input1")
        inputDir.createDir("input2")
        def inputFile1 = inputDir.file("input1/input.txt")
        def inputFile2 = inputDir.file("input2/input.txt")

        when:
        succeeds("theTask", "-D${StartParameterBuildOptions.ContinuousBuildQuietPeriodOption.PROPERTY_NAME}=5000")

  %weight_zps = "tf.Const"() { value = dense<3> : tensor<i32> } : () -> tensor<i32>

  // CHECK: "tf.AddV2"
  // CHECK: mhlo.constant
  // CHECK-SAME{LITERAL}: dense<[[1, 2], [3, 4]]> : tensor<2x2xi8>
  %0 = "tf.AddV2"(%input, %input) : (tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>

  // CHECK: "mhlo.dot"
  // CHECK-SAME: (tensor<?x?xf32>, tensor<2x2x!quant.uniform<i8:f32, 1.000000e+00:3>>) -> tensor<?x?xf32>

inputs-report.png...

  Init(2);
  // Create nested loop:
  //  while (input1 < 6) {
  //    inner_input1 = input1
  //    while (inner_input1 < 3) {
  //      input2 += 1
  //      inner_input1 += 2
  //    }
  //    input1 += input2
  //  }
  //
  // Expected execution with initial values input1 = input2 = 0:
  //
  // outer inner               inner_
  // step# step# input1 input2 input1
  // ------------------------------------

// CHECK-LABEL: @main_stream_0
// CHECK-SAME: ([[input0:%.*]]: !tf_mlrt.tensor, [[promise_b:%.*]]: !mlrt.promise)
func.func @main_stream_0(%input0: tensor<i32>, %promise_b: !mlrt.promise) {
  %const = "tf.Const"() {__op_key = 0 : i32, value = dense<1> : tensor<i32>} : () -> tensor<i32>
  // CHECK: [[a:%.*]] = tf_mlrt.executeop([[input0]],
  // CHECK-SAME: AddV2

  TFE_DeleteContextOptions(opts);

  TFE_TensorHandle* input1 = TestMatrixTensorHandle(ctx);
  TFE_TensorHandle* input2 = TestMatrixTensorHandle(ctx);
  TFE_Op* identityOp = TFE_NewOp(ctx, "IdentityN", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_TensorHandle* inputs[] = {input1, input2};
  TFE_OpAddInputList(identityOp, inputs, 2, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

			"spiffe://td/ns/ns/sa/sa/",
			nil,
		},
		{
			// wrong separator /
			"spiffe://td/ns/ns/foobar/sa/",
			nil,
		},
	}
	for _, tt := range cases {
		t.Run(tt.input, func(t *testing.T) {
			got, err := ParseIdentity(tt.input)
			if tt.expected == nil {
				if err == nil {
					t.Fatalf("expected error, got %#v", got)
				}
				return
			}
			if err != nil {
				t.Fatal(err)
			}

Anis Eleuch <******@****.***> 1712232280 +0100