Merge pull request #28672 from ROCmSoftwarePlatform:google_upstream_rocm_platform_fix_190513
PiperOrigin-RevId: 248009969
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43343ce22a
@ -36,10 +36,10 @@ limitations under the License.
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#include "tensorflow/core/util/padding.h"
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#include "tensorflow/core/util/tensor_format.h"
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#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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#if GOOGLE_CUDA
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#include "tensorflow/core/kernels/maxpooling_op_gpu.h"
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#include "tensorflow/core/kernels/pooling_ops_common_gpu.h"
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#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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#endif // GOOGLE_CUDA
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namespace tensorflow {
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@ -112,7 +112,7 @@ REGISTER_KERNEL_BUILDER(
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Name("AvgPool").Device(DEVICE_CPU).TypeConstraint<Eigen::half>("T"),
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AvgPoolingOp<CPUDevice, Eigen::half>);
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#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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#if GOOGLE_CUDA
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template <typename T>
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class AvgPoolingOp<GPUDevice, T> : public UnaryOp<T> {
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public:
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@ -205,7 +205,7 @@ REGISTER_KERNEL_BUILDER(
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REGISTER_KERNEL_BUILDER(
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Name("AvgPool").Device(DEVICE_GPU).TypeConstraint<double>("T"),
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AvgPoolingOp<GPUDevice, double>);
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#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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#endif // GOOGLE_CUDA
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// The operation to compute AvgPool gradients.
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// It takes two inputs:
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@ -368,7 +368,7 @@ TF_CALL_float(REGISTER_CPU_KERNEL);
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TF_CALL_double(REGISTER_CPU_KERNEL);
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TF_CALL_half(REGISTER_CPU_KERNEL);
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#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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#if GOOGLE_CUDA
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// A CUDNN based AvgPoolingGrad implementation. It includes the padding as the
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// candidates for the pooling operation.
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@ -577,6 +577,6 @@ REGISTER_KERNEL_BUILDER(Name("AvgPoolGrad")
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.HostMemory("orig_input_shape"),
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AvgPoolingGradOpCustomGPUKernel<Eigen::half>);
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#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
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#endif // GOOGLE_CUDA
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} // namespace tensorflow
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@ -19,16 +19,13 @@ limitations under the License.
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#define TENSORFLOW_STREAM_EXECUTOR_GPU_GPU_DRIVER_H_
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#include <stddef.h>
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#include "tensorflow/stream_executor/platform/port.h"
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#include "third_party/gpus/cuda/include/cuda.h"
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#include "tensorflow/stream_executor/device_options.h"
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#include "tensorflow/stream_executor/gpu/gpu_types.h"
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#include "tensorflow/stream_executor/lib/status.h"
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#include "tensorflow/stream_executor/lib/statusor.h"
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#include "tensorflow/stream_executor/platform/port.h"
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#include "tensorflow/stream_executor/gpu/gpu_types.h"
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namespace stream_executor {
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namespace gpu {
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