Update with compiling optimization and DT_UINT32 support for HDF5 (#379)

* Update README.md

* Update with compiling optimization

For compilation optimization flags, the default (-march=native) optimizes the generated code for your machine's CPU type. [see here](https://www.tensorflow.org/install/source#configuration_options)

* add DT_UINT32 support

Author: CaptainDuke

README.md

@@ -134,8 +134,8 @@ $ docker build -f dev/Dockerfile -t tfio-dev .
 $ docker run -it --rm --net=host -v ${PWD}:/v -w /v tfio-dev
 $ # In Docker, configure will install TensorFlow or use existing install
 $ ./configure.sh
-$ # Build TensorFlow I/O C++
-$ bazel build -s --verbose_failures //tensorflow_io/...
+$ # Build TensorFlow I/O C++. For compilation optimization flags, the default (-march=native) optimizes the generated code for your machine's CPU type. [see here](https://www.tensorflow.org/install/source#configuration_options)
+$ bazel build -c opt --copt=-match=native -s --verbose_failures //tensorflow_io/...
 $ # Run tests with PyTest, note: some tests require launching additional containers to run (see below)
 $ pytest tests/
 $ # Build the TensorFlow I/O package

tensorflow_io/hdf5/kernels/hdf5_input.cc

@@ -105,7 +105,11 @@ class HDF5InputStream{
           Tensor tensor(ctx->allocator({}), DT_INT32, shape);
           dataset_[i].read(tensor.flat<int32>().data(), H5::PredType::NATIVE_INT, memoryspace, dataspace_[i]);
           out_tensors->emplace_back(std::move(tensor));
-        } else if (H5Tequal(native_type, H5T_NATIVE_LONG)) {
+        } else if (H5Tequal(native_type, H5T_NATIVE_UINT32)) {
+          Tensor tensor(ctx->allocator({}), DT_UINT32, shape);
+          dataset_[i].read(tensor.flat<uint32>().data(), H5::PredType::NATIVE_UINT32, memoryspace, dataspace_[i]);
+          out_tensors->emplace_back(std::move(tensor));
+        }else if (H5Tequal(native_type, H5T_NATIVE_LONG)) {
           Tensor tensor(ctx->allocator({}), DT_INT64, shape);
           dataset_[i].read(tensor.flat<int64>().data(), H5::PredType::NATIVE_LONG, memoryspace, dataspace_[i]);
           out_tensors->emplace_back(std::move(tensor));