Tensor t = Tensor(tensorflow::DT_FLOAT, tensorflow::TensorShape({50}));
        t.flat<float>().setZero();
        outputs->push_back(t);
      } else if (output_name == "dense/kernel") {
        Tensor t =
            Tensor(tensorflow::DT_FLOAT, tensorflow::TensorShape({100, 50}));
        t.flat<float>().setZero();
        outputs->push_back(t);
      } else {
        // Create a scalar float tensor.

      Tensor t = Tensor(tensorflow::DT_FLOAT, tensorflow::TensorShape({50}));
      t.flat<float>().setZero();
      outputs->push_back(t);
    } else if (output_name == "dense/kernel") {
      Tensor t =
          Tensor(tensorflow::DT_FLOAT, tensorflow::TensorShape({100, 50}));
      t.flat<float>().setZero();
      outputs->push_back(t);
    } else if (output_name == "var1") {

                                    Tensor* histogram_tensor) {
    const auto input_flat = input_tensor.flat<float>();
    auto histogram_flat = histogram_tensor->flat<int64_t>();
    histogram_flat.setZero();

    const float bin_width = CalculateBinWidth(min_value, max_value, num_bins);
    const float lower_bound = CalculateLowerBound(min_value, bin_width);
    for (int i = 0; i < input_flat.size(); ++i) {

  std::vector<Tensor> dy_datas(y_num);
  for (int i = 0; i < y_num; i++) {
    dy_datas[i] = Tensor(ys[i].type(), y_shapes[i]);
    auto dy_data_flat = dy_datas[i].flat<Y_T>();
    dy_data_flat.setZero();
  }

  // Create the feed list.
  ClientSession::FeedType feed_list;
  for (int i = 0; i < x_num; i++) {
    feed_list.insert({xs[i], x_datas[i]});
  }
  for (int i = 0; i < y_num; i++) {

		name := source.Type().Field(i).Name
		value := source.Field(i)
		zero := Zero(value.Type())
		b.Run(name+"/Direct", func(b *testing.B) {
			for i := 0; i < b.N; i++ {
				value.SetZero()
			}
		})
		b.Run(name+"/CachedZero", func(b *testing.B) {
			for i := 0; i < b.N; i++ {
				value.Set(zero)
			}
		})
		b.Run(name+"/NewZero", func(b *testing.B) {
			for i := 0; i < b.N; i++ {

			break
		}
		if d.opcode != scanArrayValue {
			panic(phasePanicMsg)
		}
	}

	if i < v.Len() {
		if v.Kind() == reflect.Array {
			for ; i < v.Len(); i++ {
				v.Index(i).SetZero() // zero remainder of array
			}
		} else {
			v.SetLen(i) // truncate the slice
		}
	}
	if i == 0 && v.Kind() == reflect.Slice {
		v.Set(reflect.MakeSlice(v.Type(), 0, 0))
	}
	return nil
}

			value, ok2 := sizedValue(concrete.Elem(), rand, size)
			if !ok1 || !ok2 {
				return reflect.Value{}, false
			}
			v.SetMapIndex(key, value)
		}
	case reflect.Pointer:
		if rand.Intn(size) == 0 {
			v.SetZero() // Generate nil pointer.
		} else {
			elem, ok := sizedValue(concrete.Elem(), rand, size)
			if !ok {
				return reflect.Value{}, false
			}
			v.Set(reflect.New(concrete.Elem()))
			v.Elem().Set(elem)

		key := decodeIntoValue(state, keyOp, keyIsPtr, keyP.Elem(), keyInstr)
		elem := decodeIntoValue(state, elemOp, elemIsPtr, elemP.Elem(), elemInstr)
		value.SetMapIndex(key, elem)
		keyP.Elem().SetZero()
		elemP.Elem().SetZero()
	}
}

// ignoreArrayHelper does the work for discarding arrays and slices.
func (dec *Decoder) ignoreArrayHelper(state *decoderState, elemOp decOp, length int) {

	//
	// This also allows scanning into user defined types such as "type Int int64".
	// For symmetry, also check for string destination types.
	switch dv.Kind() {
	case reflect.Pointer:
		if src == nil {
			dv.SetZero()
			return nil
		}
		dv.Set(reflect.New(dv.Type().Elem()))
		return convertAssignRows(dv.Interface(), src, rows)
	case reflect.Int, reflect.Int8, reflect.Int16, reflect.Int32, reflect.Int64:
		if src == nil {

				v.Set(reflect.ValueOf(x).Elem())
				for i := 0; i < v.NumField(); i++ {
					if !listJsonFields.needAny(v.Type().Field(i).Name) {
						v.Field(i).SetZero()
					}
				}
				x = v.Interface()
			}
			b, err := json.MarshalIndent(x, "", "\t")
			if err != nil {
				out.Flush()
				base.Fatalf("%s", err)
			}
			out.Write(b)
			out.Write(nl)