return &data_.func == &o.data_.func;
        break;
      case FLOAT32:
        return data_.f32 == o.data_.f32;
        break;
      case INT64:
        return data_.i64 == o.data_.i64;
        break;
      case STRING:
        return data_.s == o.data_.s;
        break;
      case TENSOR:
        return data_.tensor == o.data_.tensor;
      case TENSOR_SPEC:

  // If `data_.size() + len` is greater than `SIZE_MAX` then the left hand side
  // will overflow to something less than max_length_. After checking `len <=
  // max_length_` we can use this subtraction to check for overflow.
  if (len > max_length_ || data_.size() >= max_length_ - len)
    return absl::ResourceExhaustedError("Buffer overflow");
  data_.resize(data_.size() + len);

    int64_t element_count = 1;
    for (int64_t i = 0, e = shape.size(); i < e; ++i) {
      element_count *= shape[i];
    }
    assert(data.getNumElements() == element_count);
  }

  using StridedArrayViewBase::NextTensorIndex;
  using StridedArrayViewBase::size;

  int64_t operator[](int64_t i) const {
    return data_.getValues<APInt>()[OffsetForIndex(i)].getSExtValue();

                               tensorflow::DataType dtype, void* data,
                               TFE_CustomDeviceTensorHandleMethods methods)
      : tensorflow::CustomDeviceTensorHandle(context, device, dtype),
        data_(data),
        methods_(methods) {}

  ~CAPICustomDeviceTensorHandle() override { methods_.deallocator(data_); }
  void* DevicePointer() const override { return data_; }
  Status NumDims(int* num_dims) const override {

  absl::Status AddString(const char* str, size_t len);

  // Fill content into a buffer and returns the number of bytes stored.
  // The function allocates space for the buffer but does NOT take ownership.
  int WriteToBuffer(char** buffer);

 private:
  // Data buffer to store contents of strings, not including headers.
  std::vector<char> data_;

    volumes:
      - data2-1:/data1
      - data2-2:/data2
      - data2-3:/data3

  minio3:
    <<: *minio-common
    hostname: minio3
    volumes:
      - data3-1:/data1
      - data3-2:/data2
      - data3-3:/data3

  minio4:
    <<: *minio-common
    hostname: minio4
    volumes:
      - data4-1:/data1
      - data4-2:/data2
      - data4-3:/data3

  nginx:

    <<: *minio-common
    hostname: minio1
    volumes:
      - data1-1:/data1
      - data1-2:/data2

  minio2:
    <<: *minio-common
    hostname: minio2
    volumes:
      - data2-1:/data1
      - data2-2:/data2

  minio3:
    <<: *minio-common
    hostname: minio3
    volumes:
      - data3-1:/data1
      - data3-2:/data2

  minio4:
    <<: *minio-common
    hostname: minio4
    volumes:

	if string(data1) != string(data2) {
		t.errorf("%s: %s: different data returned\n\t%q\n\t%q", file, desc, data1, data2)
		return
	}
}

// checkBadPath checks that various invalid forms of file's name cannot be opened using t.fsys.Open.
func (t *fsTester) checkOpen(file string) {
	t.checkBadPath(file, "Open", func(file string) error {
		f, err := t.fsys.Open(file)
		if err == nil {
			f.Close()

	data[len(prefix)+1] = 0
	if ctxt.Arch.ByteOrder == binary.BigEndian {
		data[len(prefix)+1] = 1
	}
	data[len(prefix)+1] |= 2 // signals new pointer-free format
	data = appendString(data, strdata["runtime.buildVersion"])
	data = appendString(data, strdata["runtime.modinfo"])
	// MacOS linker gets very upset if the size os not a multiple of alignment.
	for len(data)%16 != 0 {
		data = append(data, 0)
	}

  },
  "tags": {
    "objectLocation": {
      "name": "hosts",
      "poolId": 1,
      "setId": 1,
      "drives": [
        "/mnt/data1",
        "/mnt/data2",
        "/mnt/data3",
        "/mnt/data4"
      ]
    }
  },
  "accessKey": "minioadmin"
}
```

### Kafka Target

Assuming that you already have Apache Kafka configured and running.

```