Revert "Fix some more core aten ops (pytorch#6342)" (pytorch#6377)

Author: wonjoo-wj

codegen/xla_native_functions.yaml

@@ -77,7 +77,6 @@ full_codegen:
   - rsqrt
   - selu
   - sgn
-  - sigmoid
   - sign
   - silu
   - silu_backward
@@ -303,6 +302,7 @@ supported:
   - select_scatter
   - selu_
   - set_.source_Tensor
+  - sigmoid
   - sigmoid_backward
   - slice_copy.Tensor
   - slice_scatter

test/test_core_aten_ops.py

@@ -1904,17 +1904,11 @@ def test_aten_gelu_0(self):
     kwargs = dict()
     run_export_and_compare(self, torch.ops.aten.gelu, args, kwargs)
 
+  @unittest.skip
   def test_aten_gelu_1(self):
     args = (torch.randn((10, 10)).to(torch.float16),)
     kwargs = dict()
-    run_export_and_compare(
-        self,
-        torch.ops.aten.gelu,
-        args,
-        kwargs,
-        rtol=0.001,
-        atol=0.01,
-    )
+    run_export_and_compare(self, torch.ops.aten.gelu, args, kwargs)
 
   def test_aten_glu_0(self):
     args = (
@@ -3091,6 +3085,7 @@ def test_aten_native_group_norm_0(self):
     kwargs = dict()
     run_export_and_compare(self, torch.ops.aten.native_group_norm, args, kwargs)
 
+  @unittest.skip
   def test_aten_native_group_norm_1(self):
     args = (
         torch.randn((1, 3, 2, 10)).to(torch.float16),
@@ -3103,14 +3098,7 @@ def test_aten_native_group_norm_1(self):
         0.0,
     )
     kwargs = dict()
-    run_export_and_compare(
-        self,
-        torch.ops.aten.native_group_norm,
-        args,
-        kwargs,
-        rtol=0.001,
-        atol=0.01,
-    )
+    run_export_and_compare(self, torch.ops.aten.native_group_norm, args, kwargs)
 
   def test_aten_native_layer_norm_0(self):
     args = (
@@ -3417,6 +3405,7 @@ def test_aten_reciprocal_1(self):
     kwargs = dict()
     run_export_and_compare(self, torch.ops.aten.reciprocal, args, kwargs)
 
+  @unittest.skip
   def test_aten_reciprocal_2(self):
     args = (torch.randint(0, 10, (10, 10)).to(torch.int32),)
     kwargs = dict()
@@ -4014,6 +4003,7 @@ def test_aten_sigmoid_1(self):
     kwargs = dict()
     run_export_and_compare(self, torch.ops.aten.sigmoid, args, kwargs)
 
+  @unittest.skip
   def test_aten_sigmoid_2(self):
     args = (torch.randint(0, 10, (10, 10)).to(torch.int32),)
     kwargs = dict()

torch_xla/csrc/aten_xla_type.cpp

@@ -2758,6 +2758,12 @@ at::Tensor& XLANativeFunctions::set_(at::Tensor& self,
   return self;
 }
 
+at::Tensor XLANativeFunctions::sigmoid(const at::Tensor& self) {
+  TORCH_LAZY_FN_COUNTER_TIMED_TRACING("xla::");
+  return bridge::AtenFromXlaTensor(
+      tensor_methods::sigmoid(bridge::GetXlaTensor(self)));
+}
+
 at::Tensor XLANativeFunctions::sigmoid_backward(const at::Tensor& grad_output,
                                                 const at::Tensor& output) {
   TORCH_LAZY_FN_COUNTER_TIMED_TRACING("xla::");

torch_xla/csrc/ops/ops_lower_fn.cpp

@@ -684,10 +684,6 @@ torch_xla::XlaOpVector NeTensor::Lower(LoweringContext* loctx) const {
 
 torch_xla::XlaOpVector Reciprocal::Lower(LoweringContext* loctx) const {
   xla::XlaOp xla_input = loctx->GetOutputOp(operand(0));
-  if (xla::primitive_util::IsIntegralType(XlaHelpers::TypeOfXlaOp(xla_input))) {
-    xla::PrimitiveType input_type = XlaHelpers::TypeOfXlaOp(xla_input);
-    xla_input = ConvertTo(xla_input, input_type, xla::PrimitiveType::F32);
-  }
   return ReturnOp(BuildReciprocal(xla_input), loctx);
 }
 
@@ -730,14 +726,6 @@ torch_xla::XlaOpVector Sgn::Lower(LoweringContext* loctx) const {
   return ReturnOp(BuildSgn(xla_input), loctx);
 }
 
-torch_xla::XlaOpVector Sigmoid::Lower(LoweringContext* loctx) const {
-  xla::XlaOp xla_input = loctx->GetOutputOp(operand(0));
-  if (xla::primitive_util::IsIntegralType(XlaHelpers::TypeOfXlaOp(xla_input))) {
-    xla_input = xla::ConvertElementType(xla_input, xla::PrimitiveType::F32);
-  }
-  return ReturnOp(xla::Logistic(xla_input), loctx);
-}
-
 torch_xla::XlaOpVector Sign::Lower(LoweringContext* loctx) const {
   xla::XlaOp xla_input = loctx->GetOutputOp(operand(0));
   return ReturnOp(BuildSign(xla_input), loctx);

torch_xla/csrc/ops/ops_xla_shape_fn.cpp

@@ -762,11 +762,7 @@ xla::Shape NeTensorOutputShape(const torch::lazy::Value& self,
 }
 
 xla::Shape ReciprocalOutputShape(const torch::lazy::Value& input) {
-  xla::Shape result_shape = GetXlaShape(input);
-  if (xla::primitive_util::IsIntegralType(result_shape.element_type())) {
-    result_shape.set_element_type(xla::PrimitiveType::F32);
-  }
-  return result_shape;
+  return GetXlaShape(input);
 }
 
 xla::Shape ReluOutputShape(const torch::lazy::Value& input) {
@@ -808,14 +804,6 @@ xla::Shape SgnOutputShape(const torch::lazy::Value& input) {
   return GetXlaShape(input);
 }
 
-xla::Shape SigmoidOutputShape(const torch::lazy::Value& input) {
-  xla::Shape result_shape = GetXlaShape(input);
-  if (xla::primitive_util::IsIntegralType(result_shape.element_type())) {
-    result_shape.set_element_type(xla::PrimitiveType::F32);
-  }
-  return result_shape;
-}
-
 xla::Shape SignOutputShape(const torch::lazy::Value& input) {
   return GetXlaShape(input);
 }

torch_xla/csrc/ops/ops_xla_shape_fn.h

@@ -248,8 +248,6 @@ xla::Shape SeluOutputShape(const torch::lazy::Value& input);
 
 xla::Shape SgnOutputShape(const torch::lazy::Value& input);
 
-xla::Shape SigmoidOutputShape(const torch::lazy::Value& input);
-
 xla::Shape SignOutputShape(const torch::lazy::Value& input);
 
 xla::Shape SiluOutputShape(const torch::lazy::Value& input);