Merge branch 'master' of https://github.com/pytorch/pytorch

.github/actions/setup-rocm/action.yml

@@ -36,7 +36,12 @@ runs:
       run: |
         ngpu=$(rocminfo | grep -c -E 'Name:.*\sgfx')
         if [[ "x$ngpu" != "x2" && "x$ngpu" != "x4" ]]; then
-            echo "Failed to detect GPUs on the runner"
+            if [[ $ngpu -eq 0 ]]; then
+              echo "Error: Failed to detect any GPUs on the runner"
+            else
+              echo "Error: Detected $ngpu GPUs on the runner, when only 2 or 4 were expected"
+            fi
+            echo "Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified"
             exit 1
         fi
 

.github/templates/common.yml.j2

@@ -78,7 +78,12 @@ concurrency:
         run: |
           ngpu=$(rocminfo | grep -c -E 'Name:.*\sgfx')
           if [[ "x$ngpu" != "x2" && "x$ngpu" != "x4" ]]; then
-              echo "Failed to detect GPUs on the runner"
+              if [[ $ngpu -eq 0 ]]; then
+                echo "Error: Failed to detect any GPUs on the runner"
+              else
+                echo "Error: Detected $ngpu GPUs on the runner, when only 2 or 4 were expected"
+              fi
+              echo "Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified"
               exit 1
           fi
       - name: Runner health check disconnect on failure

.jenkins/pytorch/test.sh

@@ -249,7 +249,7 @@ test_inductor_distributed() {
 }
 
 test_inductor() {
-  python test/run_test.py --include test_modules --verbose
+  python test/run_test.py --include test_modules test_ops --verbose
   # TODO: investigate "RuntimeError: CUDA driver API confirmed a leak"
   # seen intest_ops_gradients.py
   # pytest test/test_ops_gradients.py --verbose -k "not _complex and not test_inplace_grad_acos_cuda_float64"

aten/src/ATen/native/ComplexHelper.h

@@ -18,19 +18,18 @@ namespace at { namespace native {
 // View tensor with new dtype, storage offset, sizes and strides
 inline Tensor view_tensor(
     const Tensor &tensor, ScalarType dtype,
-    int64_t offset, IntArrayRef sizes, IntArrayRef strides) {
+    c10::SymInt offset, SymIntArrayRef sizes, SymIntArrayRef strides) {
   Storage storage = tensor.storage();
   auto key_set = tensor.key_set().remove(DispatchKey::Conjugate);
   auto new_tensor = detail::make_tensor<TensorImpl>(
       c10::TensorImpl::VIEW, std::move(storage), key_set, scalarTypeToTypeMeta(dtype));
   auto * impl = new_tensor.unsafeGetTensorImpl();
-  impl->set_storage_offset(offset);
-  impl->set_sizes_and_strides(sizes, strides);
+  impl->set_sizes_and_strides(sizes, strides, offset);
   return new_tensor;
 }
 
-inline DimVector computeStrideForViewAsReal(IntArrayRef oldstride) {
-  DimVector res(oldstride.size() + 1);
+inline SymDimVector computeStrideForViewAsReal(SymIntArrayRef oldstride) {
+  SymDimVector res(oldstride.size() + 1);
   for (const auto i : c10::irange(oldstride.size())) {
     res[i] = oldstride[i] * 2;
   }
@@ -40,13 +39,13 @@ inline DimVector computeStrideForViewAsReal(IntArrayRef oldstride) {
 
 Tensor _view_as_real_physical(const Tensor& self) {
   TORCH_CHECK(self.is_complex(), "view_as_real is only supported for complex tensors");
-  auto old_sizes = self.sizes();
-  DimVector new_sizes(old_sizes.size() + 1);
+  auto old_sizes = self.sym_sizes();
+  SymDimVector new_sizes(old_sizes.size() + 1);
   std::copy(old_sizes.begin(), old_sizes.end(), new_sizes.begin());
   // last dimension will always have two elements containing the real and imag vals
   new_sizes.back() = 2;
-  auto new_strides = computeStrideForViewAsReal(self.strides());
-  auto new_storage_offset = 2 * self.storage_offset();
+  auto new_strides = computeStrideForViewAsReal(self.sym_strides());
+  auto new_storage_offset = self.sym_storage_offset() * 2;
   const auto float_type = c10::toRealValueType(self.scalar_type());
   auto real_tensor = view_tensor(self, float_type, new_storage_offset, new_sizes, new_strides);
   return real_tensor;
@@ -60,11 +59,11 @@ Tensor view_as_real(const Tensor& self) {
   return _view_as_real_physical(self);
 }
 
-inline DimVector computeStrideForViewAsComplex(IntArrayRef oldstride) {
+inline SymDimVector computeStrideForViewAsComplex(SymIntArrayRef oldstride) {
   const int64_t dim = oldstride.size();
   TORCH_CHECK(oldstride[dim-1] == 1, "Tensor must have a last dimension with stride 1");
 
-  DimVector res(dim - 1);
+  SymDimVector res(dim - 1);
   for (const auto i : c10::irange(res.size())) {
     TORCH_CHECK(oldstride[i] % 2 == 0, "Tensor must have a stride divisible by 2 for all but last dimension");
     res[i] = oldstride[i] / 2;
@@ -79,16 +78,16 @@ Tensor view_as_complex(const Tensor& self) {
     self.scalar_type() == kFloat || self.scalar_type() == kDouble || self.scalar_type() == kHalf,
     "view_as_complex is only supported for half, float and double tensors, but got a tensor of scalar type: ", self.scalar_type());
 
-  auto old_sizes = self.sizes();
+  auto old_sizes = self.sym_sizes();
   TORCH_CHECK(old_sizes.size() != 0, "Input tensor must have one or more dimensions");
   TORCH_CHECK(old_sizes[old_sizes.size()-1] == 2, "Tensor must have a last dimension of size 2");
-  DimVector new_sizes(old_sizes.begin(), old_sizes.end() - 1);
+  SymDimVector new_sizes(old_sizes.begin(), old_sizes.end() - 1);
 
-  const auto new_strides = computeStrideForViewAsComplex(self.strides());
+  const auto new_strides = computeStrideForViewAsComplex(self.sym_strides());
   const auto complex_type = c10::toComplexType(self.scalar_type());
 
-  TORCH_CHECK(self.storage_offset() % 2 == 0, "Tensor must have a storage_offset divisible by 2");
-  const auto new_storage_offset = self.storage_offset() / 2;
+  TORCH_CHECK(self.sym_storage_offset() % 2 == 0, "Tensor must have a storage_offset divisible by 2");
+  const auto new_storage_offset = self.sym_storage_offset() / 2;
 
   return view_tensor(self, complex_type, new_storage_offset, new_sizes, new_strides);
 }