Add support for _unsafe_index. (#5707)

* Add support for `_unsafe_index`. * Fix lint issues. * Add tests.
pytorch · Oct 19, 2023 · bccbb5a · bccbb5a
1 parent 6ea9947
commit bccbb5a
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diff --git a/codegen/xla_native_functions.yaml b/codegen/xla_native_functions.yaml
@@ -130,6 +130,7 @@ supported:
   - _to_cpu
   - _to_copy
   - _unsafe_view
+  - _unsafe_index.Tensor
   - adaptive_max_pool2d
   - adaptive_max_pool2d_backward
   - add.Scalar

diff --git a/test/cpp/test_aten_xla_tensor_1.cpp b/test/cpp/test_aten_xla_tensor_1.cpp
@@ -2033,6 +2033,34 @@ TEST_F(AtenXlaTensorTest, TestScatterReduceMaxInPlace) {
   ExpectCounterChanged("xla::scatter_reduce", cpp_test::GetIgnoredCounters());
 }
 
+TEST_F(AtenXlaTensorTest, TestUnsafeIndex) {
+  for (torch::ScalarType scalar_type :
+       {torch::kFloat, torch::kByte, torch::kChar, torch::kShort, torch::kInt,
+        torch::kLong}) {
+    torch::Tensor a =
+        isFloatingType(scalar_type)
+            ? torch::rand({3, 4}, torch::TensorOptions(scalar_type))
+            : torch::randint(100, {3, 4}, torch::TensorOptions(scalar_type));
+    for (torch::ScalarType index_scalar_type : {torch::kInt, torch::kLong}) {
+      torch::List<torch::optional<torch::Tensor>> indices{
+          torch::tensor({0, 1}, torch::TensorOptions(index_scalar_type)),
+          torch::tensor({2, 3}, torch::TensorOptions(index_scalar_type))};
+      torch::Tensor c0 = torch::_unsafe_index(a, indices);
+      ForEachDevice([&](const torch::Device& device) {
+        torch::Tensor xla_a = CopyToDevice(a, device);
+        torch::List<torch::optional<torch::Tensor>> xla_indices{
+            CopyToDevice(*indices.get(0), device),
+            CopyToDevice(*indices.get(1), device)};
+        torch::Tensor xla_c0 = torch::_unsafe_index(xla_a, xla_indices);
+        AllEqual(c0, xla_c0);
+      });
+    }
+  }
+  ExpectCounterNotChanged("aten::.*", cpp_test::GetIgnoredCounters());
+  ExpectCounterChanged("xla::index", cpp_test::GetIgnoredCounters());
+  ExpectCounterChanged("xla::_unsafe_index", cpp_test::GetIgnoredCounters());
+}
+
 TEST_F(AtenXlaTensorTest, TestIndexSelect) {
   for (torch::ScalarType scalar_type :
        {torch::kFloat, torch::kByte, torch::kChar, torch::kShort, torch::kInt,

diff --git a/test/dynamo/test_bridge.py b/test/dynamo/test_bridge.py
@@ -78,6 +78,19 @@ def get_random_inputs(self):
     return (torch.randn(10), torch.randn(10))
 
 
+class UpsampleModule(nn.Module):
+
+  def __init__(self):
+    super().__init__()
+    self.upsample = nn.Upsample(scale_factor=2)
+
+  def forward(self, x):
+    return self.upsample(x)
+
+  def get_random_inputs(self):
+    return (torch.randn((1, 1, 5)),)
+
+
 def allclose(expected, actual):
 
   def unwrap(cont):
@@ -179,6 +192,7 @@ def test_wrapper(self):
 
     model = model.to(device=xla_dev)
     inputs = tuple(inp.to(device=xla_dev) for inp in inputs)
+    inputs = tuple(inp.requires_grad_() for inp in inputs)
 
     # do baseline
     baseline_model = copy.deepcopy(model)
@@ -206,6 +220,7 @@ class TorchXLAReuseGraphTest(torch._dynamo.test_case.TestCase):
 
   test_training_linear = make_training_test(LinearModule)
   test_training_maxpool = make_training_test(MaxPoolModule)
+  test_training_upsample = make_training_test(UpsampleModule)
 
   def test_non_tensor_args_for_partition(self):
 

diff --git a/torch_xla/csrc/aten_xla_type.cpp b/torch_xla/csrc/aten_xla_type.cpp
@@ -626,6 +626,13 @@ at::Tensor XLANativeFunctions::_unsafe_view(const at::Tensor& self,
   return view_copy_symint(self, c10::fromIntArrayRefSlow(size));
 }
 
+at::Tensor XLANativeFunctions::_unsafe_index(
+    const at::Tensor& self,
+    const c10::List<c10::optional<at::Tensor>>& indices) {
+  TORCH_LAZY_FN_COUNTER("xla::");
+  return index(self, indices);
+}
+
 at::Tensor XLANativeFunctions::add(const at::Tensor& self,
                                    const at::Tensor& other,
                                    const at::Scalar& alpha) {