Mengjiao Liu <******@****.***> 1693972533 +0800

// IntPerLayer-DAG: "tf.DumpTensor"(%[[output1_unquantized]]) <{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>) -> ()
// IntPerLayer-DAG: return %[[output0]], %[[output1_quantized]]

# Text form of tensorflow.tf2xla.Config proto.
feed {
  id { node_name: "x_hold" }
  shape {
    dim { size: <M> }
    dim { size: <K> }
  }
}
feed {
  id { node_name: "y_hold" }
  shape {
    dim { size: <K> }
    dim { size: <N> }
  }
}
fetch {
  id { node_name: "x_y_prod" }

  while (!nodes_to_visit.empty()) {
    const string node_name = nodes_to_visit.front();
    nodes_to_visit.pop();
    if (reachable_node_names->find(node_name) != reachable_node_names->end()) {
      continue;
    }
    reachable_node_names->insert(node_name);
    NodeDef* node = name_to_node_map.at(node_name);
    if (kVariableTypes->find(node->op()) != kVariableTypes->end()) {

    string file_name;
    string func_name;
    string node_name;
    OP_REQUIRES_OK(ctx, ctx->GetAttr("log_dir_path", &log_dir_path));
    OP_REQUIRES_OK(ctx, ctx->GetAttr("enabled", &enabled_));
    OP_REQUIRES_OK(ctx, ctx->GetAttr("file_name", &file_name));
    OP_REQUIRES_OK(ctx, ctx->GetAttr("func_name", &func_name));
    OP_REQUIRES_OK(ctx, ctx->GetAttr("node_name", &node_name));

    "tf.DumpTensor"(%4) {device = "", enabled = true, file_name = "quantized_tensor_data.pb", func_name = "conv_with_dump", log_dir_path = "/tmp/dumps/composite_conv2d_with_bias_and_relu6_fn_1", node_name = "Conv2D_1"} : (tensor<*xf32>) -> ()

  // Exercise kernel NodeDef name read
  TF_StringView name_string_view = TF_OpKernelConstruction_GetName(ctx);
  std::string node_name = "SomeNodeName";
  std::string candidate_node_name =
      std::string(name_string_view.data, name_string_view.len);
  EXPECT_EQ(node_name, candidate_node_name);
  return s;
}

static void MyComputeFunc(void* kernel, TF_OpKernelContext* ctx) {

    if log-dump-ssh "${node_name}" "command -v journalctl" &> /dev/null; then
        if [[ "${on_master}" == "true" ]]; then
          log-dump-ssh "${node_name}" "sudo journalctl --output=short-precise -u kube-master-installation.service" > "${dir}/kube-master-installation.log" || true

// WholeModel-DAG: %[[matmul1_q:.*]] = "tf.XlaCallModule"(%[[matmul0_q]], %[[w0]], %[[b0]]) <{Sout = [#tf_type.shape<?x2>], module = "", version = 9 : i64}> {_entry_function = @composite_dot_genera...

    const FlatSymbolRefAttr f_attr = GetFuncAttr(op);

    // In TF::PartitionedCallOp case, func_name and node_name are filled.
    // But in TF::XlaCallModuleOp case, node_name is `kEmptyNodeName` since
    // debugging and selective quantization of StableHLO Quantizer only uses
    // func_name for op matching.
    auto [func_name, node_name] = GetFuncNameAndNodeName(op, f_attr);
    std::string folder_name =