void transform(TransformOutputs outputs) {
                    def input = inputArtifact.get().asFile
                    println "processing [\${input.name}]"
                    def output = outputs.file(input.name + ".green")
                    output.text = input.text + ".green"
                }
            }
        """

        buildFile << """

    // Convert back to a C++ Tensor and ensure we get expected output.
    Tensor output;
    ASSERT_EQ(absl::OkStatus(), TF_TensorToTensor(dst, &output)) << line;
    ASSERT_EQ(src.NumElements(), output.NumElements()) << line;
    for (int64_t i = 0; i < src.NumElements(); ++i) {
      ASSERT_EQ(data[i], output.flat<tstring>()(i)) << line;
    }

    TF_DeleteTensor(dst);
  }
}

                void transform(TransformOutputs outputs) {
                    def input = inputArtifact.get().asFile
                    println "converting \${input.name} to red"
                    assert input.file
                    def output = outputs.file(input.name + ".red")
                    output.text = input.text + ".red"
                }
            }

        when:
        run("count")

        then:
        output.count("service:") == 6
        output.count("service: created with value = 10") == 2
        output.count("service: value is 11") == 2
        output.count("service: closed with value 11")

        when:
        run("count")

        then:
        output.count("service:") == 3
        outputContains("service: created with value = 10")

            dependencies { compile files('a.jar') }
            task fileProducer {
                outputs.file 'build/out.txt'
                doLast {
                    file('build/out.txt').text = 'some content'
                }
            }
            task dirProducer {
                outputs.dir 'build/outdir'
                doLast {
                    file('build/outdir').mkdirs()

  // Function with resources lifted. Can be nullptr if nothing needs to change.
  func::FuncOp lifted_callee;
  // Mapping from old resource outputs to their aliasing output inputs.
  llvm::SmallDenseMap<int64_t, int64_t> old_outputs_aliasing_old_inputs;
  // Mapping from old to new output indices in case any output is removed.
  llvm::SmallVector<int64_t, 4> old_to_new_output_indices;
  // ResourceArgUseInfo for each old resource argument.

  Scope root = Scope::NewRootScope().ExitOnError();
  Output variable = ops::Variable(root.WithOpName("variable"),
                                  PartialTensorShape{}, DT_FLOAT);
  Output read = ops::Identity(root.WithOpName("read"), variable);
  Output neg = ops::Negate(root.WithOpName("negate"), read);
  Output identity = ops::Negate(root.WithOpName("identity"), neg);
  Output add = ops::Add(root.WithOpName("add"), identity, neg);

  func.func @conv_with_filter_larger_than_1MB(%arg0: tensor<1x224x224x3xf32> {tf_saved_model.index_path = ["input"]}) -> (tensor<1x224x112x512xf32> {tf_saved_model.index_path = ["output"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_input:0", outputs = "PartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {
    %cst = "tf.Const"() {value = dense<2> : tensor<32x32x3x512xi8>} : () -> tensor<32x32x3x512xi8>

		// (This displays the logged output after the --- FAIL line.)
		format += "%s"
		args = append(args[:len(args):len(args)], c.output)
		c.output = c.output[:0]
	}

	if c.chatty != nil && (p.w == c.chatty.w || c.chatty.json) {
		// We're flushing to the actual output, so track that this output is
		// associated with a specific test (and, specifically, that the next output
		// is *not* associated with that test).
		//

		return regInfo{inputs: []inputInfo{{regs: m}}, outputs: []outputInfo{{regs: m}}}
	}
	if op == OpArgIntReg {
		reg := v.Block.Func.Config.intParamRegs[v.AuxInt8()]
		return regInfo{outputs: []outputInfo{{regs: 1 << uint(reg)}}}
	}
	if op == OpArgFloatReg {
		reg := v.Block.Func.Config.floatParamRegs[v.AuxInt8()]
		return regInfo{outputs: []outputInfo{{regs: 1 << uint(reg)}}}
	}
	if op.IsCall() {