%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"]} {

    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"

// 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

  %output_1 = "tf.TensorArrayGatherV3"(%handle_3, %indices, %res_1#3) {device = "/job:localhost/replica:0/task:0/device:CPU:0", element_shape = #tf_type.shape<?x512>} : (tensor<2x!tf_type.resource<tensor<?x512xf32>>>, tensor<?xi32>, tensor<f32>) -> tensor<?x?x512xf32>
  func.return %output_0, %output_1 : tensor<?x?x512xf32>, tensor<?x?x512xf32>
}

  TF_OpDefinitionBuilderAddInput(builder, "input1: uint8");
  TF_OpDefinitionBuilderAddInput(builder, "input2: uint32");
  TF_OpDefinitionBuilderAddOutput(builder, "output1: uint8");
  TF_OpDefinitionBuilderAddOutput(builder, "output2: uint8");
  TF_OpDefinitionBuilderSetShapeInferenceFunction(
      builder, &TF_ShapeInferenceContextSetUnknownShape);
  TF_Status* status = TF_NewStatus();

        %0 = tf_executor.graph {
          %output_0, %control_0 = tf_executor.island wraps "tf.Const"() <{value = dense<1.0> : tensor<1x2xf32>}> : () -> tensor<1x2xf32>

	}
	if entry, err := c1.Get(dummyID(1)); err != nil || entry.OutputID != dummyID(2) || entry.Size != 3 {
		t.Fatalf("c1.Get(1) = %x, %v, %v, want %x, %v, nil", entry.OutputID, entry.Size, err, dummyID(2), 3)
	}

	c2, err := Open(cdir)
	if err != nil {
		t.Fatalf("Open(c2) (reuse): %v", err)
	}
	if entry, err := c2.Get(dummyID(1)); err != nil || entry.OutputID != dummyID(2) || entry.Size != 3 {