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Update with compiling optimization and DT_UINT32 support for HDF5 #379

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Merged
merged 3 commits into from
Jul 25, 2019
Merged

Update with compiling optimization and DT_UINT32 support for HDF5 #379

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c4aee1f
Update README.md
CaptainDuke Jul 25, 2019
102966c
Update with compiling optimization
CaptainDuke Jul 25, 2019
39a86f2
add DT_UINT32 support
CaptainDuke Jul 25, 2019
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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -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
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6 changes: 5 additions & 1 deletion tensorflow_io/hdf5/kernels/hdf5_input.cc
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Expand Up @@ -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));
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