value {
      s: "cluster"
    }
  }
}
node {
  name: "output0"
  op: "TPUReplicatedOutput"
  input: "Identity"
  attr {
    key: "T"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "num_replicas"
    value {
      i: 1
    }
  }
}
node {
  name: "output1"
  op: "TPUReplicatedOutput"
  input: "Identity_1"
  attr {
    key: "T"

# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-unconditionally-use-set-output-shapes-on-import -tf-enable-shape-inference-on-import=false -tf-graph-as-function %s -o -  | FileCheck %s
# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-unconditionally-use-set-output-shapes-on-import -tf-enable-shape-inference-on-import=true -tf-graph-as-function %s -o - | FileCheck %s

# Verify importing with _output_shapes enabled works as expected.

node {
  name: "_Arg"

                @Override
                void transform(TransformOutputs outputs) {
                    def input = inputArtifact.get().asFile
                    def output1 = outputs.file(input.name + ".1." + target)
                    def output2 = outputs.file(input.name + ".2." + target)
                    if (showOutput) {

Benjamin Elder <******@****.***> 1547627953 -0800

Laura Kassovic <******@****.***> 1701107622 -0800

    }

    private static String[] customTaskWithOutputs(List<String> outputs) {
        (["customTask", "-PnumOutputs=${outputs.size()}"] + outputs.withIndex().collect { value, idx -> "-Poutput${idx}" + (value ? "=${value}" : '') }) as String[]
    }

    def "output files moved from one location to another marks task up-to-date"() {
        buildFile << """

  %outputs_2 = "tf.add"(%outputs_0, %outputs_1): (tensor<1x1xf32>, tensor<1x1xf32>) -> tensor<1x1xf32>
  return %outputs_2 : tensor<1x1xf32>
}

// CHECK-LABEL: @_func
func.func private @_func(%arg0: tensor<1x3xf32>, %arg1: tensor<3x1xf32>) -> (tensor<1x1xf32>) {

        }

        void createContents() {
            file.text = "output file"
            dir.file("some/dir/output1.txt") << "output1"
            dir.file("some/dir/output2.txt") << "output2"
            dir.file("some/output3.txt") << "output3"
            dir.file("some/another/output4.txt") << "output4"
            dir.createDir("some/lonelyDir")
        }
    }

                            const std::vector<Output>& outputs,
                            const std::vector<Output>& inputs,
                            std::vector<Output>* grad_outputs) {
  std::vector<Output> grad_inputs;
  grad_inputs.reserve(outputs.size());
  for (const Output& output : outputs) {
    grad_inputs.emplace_back(ops::OnesLike(scope, output));
  }

overlapping-outputs-timeline.png...