Merge branch 'main' into xiaowu/addOp(BatchNorm)

Author: xiaowuhu

onnxscript/function_libs/torch_aten/ops/core.py

@@ -3955,16 +3955,36 @@ def aten_negative(self: TensorType) -> TensorType:
     raise NotImplementedError()
 
 
-def aten_new_empty(self: TensorType, size: INT64) -> TensorType:
+@torch_op("aten::new_empty")
+def aten_new_empty(self: TTensor, size: INT64, dtype: int = -1) -> TTensor:
     # new_empty(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
 
-    raise NotImplementedError()
+    # using zero to simulate empty array
+    zero = op.Constant(value_float=0.0)
+    result = op.Expand(zero, size)
+    if dtype == -1:
+        result = op.CastLike(result, self)
+    else:
+        result = op.Cast(result, to=dtype)
+    return result
 
 
-def aten_new_empty_strided(self: TensorType, size: INT64, stride: INT64) -> TensorType:
+@torch_op("aten::new_empty_strided")
+def aten_new_empty_strided(
+    self: TTensor,
+    size: INT64,
+    stride: INT64,  # pylint: disable=unused-argument
+    dtype: int = -1,
+) -> TTensor:
     # new_empty_strided(Tensor self, SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
 
-    raise NotImplementedError()
+    # using zero to simulate empty array
+    zero = op.ConstantOfShape(size)
+    if dtype == -1:
+        result = op.CastLike(zero, self)
+    else:
+        result = op.Cast(zero, to=dtype)
+    return result
 
 
 @torch_op("aten::new_full")

onnxscript/tests/function_libs/torch_aten/ops_correctness_test.py

@@ -306,6 +306,8 @@ def _where_input_wrangler(
     # "native_dropout": core_ops.aten_native_dropout,  # native_dropout is not in OPS_DB
     "ne": core_ops.aten_ne,
     "neg": core_ops.aten_neg,
+    "new_empty": core_ops.aten_new_empty,
+    "new_empty_strided": core_ops.aten_new_empty_strided,
     "new_full": core_ops.aten_new_full,
     "nn.functional.adaptive_avg_pool1d": nn_ops.aten_adaptive_avg_pool1d,
     "nn.functional.adaptive_avg_pool2d": nn_ops.aten_adaptive_avg_pool2d,
@@ -400,6 +402,8 @@ def _where_input_wrangler(
     skip("empty_like", reason="Using zeros_like to simulate empty_like"),
     xfail("logcumsumexp", reason="naive implementation not numerically stable"),
     xfail("logsumexp", reason="ONNX Runtime 1.13 does not support ReduceLogSumExp-18"),
+    xfail("new_empty", reason="Using zeros to simulate empty"),
+    xfail("new_empty_strided", reason="Using zeros to simulate empty"),
     xfail(
         "nn.functional.upsample_nearest2d",
         reason="enable when ONNX Runtime does support opset18",