}
    tf_executor.fetch %outputs#0, %outputs#1 : tensor<i1>, tensor<i32>
  }
  return
}

// CHECK: [[OUTPUT_0:%.*]], {{%.*}} = tf_executor.island wraps "tf.opA"() {_parallel_execution_ids = "p0:0"}
// CHECK: [[OUTPUT_1:%.*]], {{%.*}} = tf_executor.island wraps "tf.opB"([[OUTPUT_0:%.*]]) {_parallel_execution_ids = "p0:0"}

    %cst = stablehlo.constant dense<0.000000e+00>: tensor<10x1024x3xf32>

        output.contains 'Output: nested.outputFiles$2 [output-nested-2.txt]'
        output.contains 'Output: outputDirectories$1 [outputs1]'
        output.contains 'Output: outputDirectories$2 [outputs2]'
        output.contains "Output: outputDirectory [outputs]"
        output.contains "Output: outputFile [output.txt]"
        output.contains 'Output: outputFiles$1 [output1.txt]'

                            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));
  }

                }
                outputs.files files(fileList) withPropertyName("out")
                def output1 = project.file("build/output1.txt")
                def output2 = project.file("build/output2.txt")
                doLast {
                    output1.parentFile.mkdirs()
                    output1 << "data"
                    if (!System.getProperty("changedCardinality")) {

    %cst = stablehlo.constant dense<0.000000e+00>: tensor<10x1024x3xf32>

  func.func @serving_default(%arg0: tensor<1x10xf32> {tf_saved_model.index_path = ["x"]}) ->
    (tensor<1x10xf32> {tf_saved_model.index_path = ["output_0"]}, tensor<1x10xi64> {tf_saved_model.index_path = ["output_1"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_x:0", outputs = "StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {

// WholeModel-DAG: "tf.DumpTensor"(%[[output1]]) <{enabled = true, file_name = "unquantized_tensor_data.pb", func_name = "conv", log_dir_path = "/tmp/dumps/composite_conv2d_with_bias_and_relu6_fn_1", node_name = "Conv2D_1"}> : (tensor<*xf32>) -> ()
// WholeModel-DAG: return %[[output0]], %[[output1]]

// IntPerLayer-LABEL: func @conv
// IntPerLayer-DAG: %[[w:.*]] = "tf.Const"() <{value = dense<{{\[\[\[\[}}1.600000e-01, 1.000000e-01

    %outputs_3, %control_3 = tf_executor.island wraps "tf.TPUReplicatedOutput"(%outputs_2) {T = "tfdtype$DT_FLOAT", device = "", name = "output0", num_replicas = 1 : i64} : (tensor<0xf32>) -> tensor<0xf32>
    %outputs_4, %control_4 = tf_executor.island wraps "tf.Identity"(%outputs_3) {T = "tfdtype$DT_FLOAT", device = "", name = "output_0_shard_0"} : (tensor<0xf32>) -> tensor<0xf32>

Xiaopeng Han <******@****.***> 1686064488 +0800