Provide full path for buck hipification (pytorch#30746)

Summary: Pull Request resolved: pytorch#30746 This diff should be safe as long as open source build succeeds and should have no impact to cuda. Differential Revision: D18811302 fbshipit-source-id: a7adab993816cba51842701898fac5019438b664
luxe · Dec 5, 2019 · c4e9748 · c4e9748
1 parent f2a2fec
commit c4e9748
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Showing 5 changed files with 10 additions and 10 deletions.
diff --git a/aten/src/ATen/hip/impl/HIPGuardImplMasqueradingAsCUDA.h b/aten/src/ATen/hip/impl/HIPGuardImplMasqueradingAsCUDA.h
@@ -1,6 +1,6 @@
 #pragma once
 
-#include <ATen/hip/HIPConfig.h>
+#include <aten/src/ATen/hip/HIPConfig.h>
 
 // The includes of HIPGuard.h
 #include <c10/hip/impl/HIPGuardImpl.h>

diff --git a/aten/src/ATen/miopen/Utils.h b/aten/src/ATen/miopen/Utils.h
@@ -1,7 +1,7 @@
 #pragma once
 
 #include <ATen/ATen.h>
-#include <THH/THH.h>
+#include <aten/src/THH/THH.h>
 #include <ATen/miopen/miopen-wrapper.h>
 #include <ATen/miopen/Handle.h>
 

diff --git a/aten/src/ATen/native/SharedReduceOps.h b/aten/src/ATen/native/SharedReduceOps.h
@@ -9,8 +9,8 @@
 #include <THC/THCDeviceUtils.cuh>
 #include <ATen/native/cuda/DeviceSqrt.cuh>
 #elif defined(__HIPCC__)
-#include <THH/THHDeviceUtils.cuh>
-#include <ATen/native/hip/DeviceSqrt.cuh>
+#include <aten/src/THH/THHDeviceUtils.cuh>
+#include <aten/src/ATen/native/hip/DeviceSqrt.cuh>
 #endif
 #if defined(__CUDACC__) || defined(__HIPCC__)
 #include <thrust/tuple.h>

diff --git a/aten/src/ATen/native/miopen/Conv_miopen.cpp b/aten/src/ATen/native/miopen/Conv_miopen.cpp
@@ -105,7 +105,7 @@ std::tuple<at::Tensor,at::Tensor,at::Tensor> miopen_depthwise_convolution_backwa
 
 #else  // AT_ROCM_ENABLED
 
-#include <THH/THH.h>
+#include <aten/src/THH/THH.h>
 
 #include <ATen/miopen/miopen-wrapper.h>
 #include <ATen/miopen/Descriptors.h>

diff --git a/aten/src/ATen/native/miopen/RNN_miopen.cpp b/aten/src/ATen/native/miopen/RNN_miopen.cpp
@@ -27,7 +27,7 @@ namespace at { namespace native {
             const Tensor& input, TensorList weight, int64_t weight_stride0, const Tensor& weight_buf, const Tensor& hx, const Tensor& cx,
             const Tensor& output, const Tensor& grad_output_r, const Tensor& grad_hy_r,
             const Tensor& grad_cy_r, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first,
-            double dropout, bool train, bool bidirectional, IntArrayRef batch_sizes, const Tensor& dropout_state, 
+            double dropout, bool train, bool bidirectional, IntArrayRef batch_sizes, const Tensor& dropout_state,
             const Tensor& reserve, std::array<bool, 4> output_mask
             ) {
         AT_ERROR("miopen_rnn_backward: ATen not compiled with MIOpen support.");
@@ -37,7 +37,7 @@ namespace at { namespace native {
 
 #else // AT_ROCM_ENABLED()
 
-#include <THH/THH.h>
+#include <aten/src/THH/THH.h>
 
 #include <ATen/miopen/miopen-wrapper.h>
 #include <ATen/miopen/Descriptors.h>
@@ -517,7 +517,7 @@ std::tuple<Tensor, Tensor, Tensor, Tensor, Tensor> miopen_rnn(
                 w_desc.desc(), weight_buf.data_ptr(),
                 y_descs_arr.data(), y.data_ptr(),
                 descs.hy_desc.desc(), hy.data_ptr(),
-                descs.cy_desc.desc(), cy.defined() ? cy.data_ptr() : nullptr, 
+                descs.cy_desc.desc(), cy.defined() ? cy.data_ptr() : nullptr,
                 workspace.data_ptr(), workspace_size, reserve.data_ptr(), reserver_size ));
     } else { //Inference.
         reserve = at::empty({0}, input.options().dtype(kByte));
@@ -751,7 +751,7 @@ std::tuple<Tensor, Tensor, Tensor, std::vector<Tensor>> miopen_rnn_backward(
         const Tensor& input, TensorList weight, int64_t weight_stride0, const Tensor& weight_buf, const Tensor& hx, const Tensor& cx,
         const Tensor& output, const Tensor& grad_output_r, const Tensor& grad_hy_r,
         const Tensor& grad_cy_r, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first,
-        double dropout, bool train, bool bidirectional, IntArrayRef batch_sizes, const Tensor& dropout_state, 
+        double dropout, bool train, bool bidirectional, IntArrayRef batch_sizes, const Tensor& dropout_state,
         const Tensor& reserve, std::array<bool, 4> output_mask
         ) {
     auto grad_output = grad_output_r.defined() ? grad_output_r : at::zeros_like(output, LEGACY_CONTIGUOUS_MEMORY_FORMAT);
@@ -894,4 +894,4 @@ REGISTER_CUDA_DISPATCH(lstm_packed_miopen_stub, &lstm_packed_miopen);
 } // anonymous namepsace
 }} //namespace native.
 
-#endif 
+#endif