Add Op(built-in function ops) | feat(torchlib) (#1135)

Fix microsoft/onnx-converters-private#190

With pytorch/pytorch#112758, this PR moves
built-in function ops mapping into torchlib.
NOTE: module name of `operator.add` is _operator

onnxscript/function_libs/torch_lib/ops/core.py

@@ -124,7 +124,7 @@ def aten__softmax(
     return aten_softmax_no_dtype(self, dim)
 
 
-@torch_op("aten::abs")
+@torch_op(("aten::abs", "_operator::abs"))
 def aten_abs(self: TRealOrUInt8) -> TRealOrUInt8:
     """abs(Tensor self) -> Tensor"""
 
@@ -158,7 +158,7 @@ def aten_acosh(self: TFloat) -> TFloat:
     return op.Acosh(self)
 
 
-@torch_op(("aten::add", "aten::add.Tensor"))
+@torch_op(("aten::add", "aten::add.Tensor", "_operator::add"))
 def aten_add(self: TReal, other: TReal, alpha: float = 1.0) -> TReal:
     """add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor"""
     # TODO(microsoft/onnxruntime#15977): Improve fp16 precision
@@ -1163,6 +1163,7 @@ def aten_binomial(
         "aten::bitwise_and.Tensor",
         "aten::bitwise_and.Scalar",
         "aten::bitwise_and.Scalar_Tensor",
+        "_operator::and_",
     )
 )
 def aten_bitwise_and(self: TInt, other: TInt) -> TInt:
@@ -1234,6 +1235,7 @@ def aten_bitwise_not(self: TInt) -> TInt:
         "aten::bitwise_or.Tensor",
         "aten::bitwise_or.Scalar",
         "aten::bitwise_or.Scalar_Tensor",
+        "_operator::or_",
     )
 )
 def aten_bitwise_or(self: TInt, other: TInt) -> TInt:
@@ -1443,6 +1445,13 @@ def aten_ceil(self: TFloat) -> TFloat:
     return op.Ceil(self)
 
 
+@torch_op("math::ceil")
+def python_math_ceil(self: TFloat) -> TInt:
+    """ceil(Tensor self) -> Tensor"""
+    ceil = op.Ceil(self)
+    return op.Cast(ceil, to=INT64.dtype)
+
+
 def aten_chain_matmul(matrices: Sequence[TensorType]) -> TensorType:
     """chain_matmul(Tensor[] matrices) -> Tensor"""
 
@@ -2617,6 +2626,7 @@ def aten_dist(self: TensorType, other: TensorType, p: float = 2.0) -> TensorType
         "aten::div.Scalar_mode",
         "aten::divide",
         "aten::true_divide",
+        "_operator::truediv",
     )
 )
 def aten_div(self: TFloat, other: TFloat) -> TFloat:
@@ -3372,7 +3382,14 @@ def aten_floor(self: TFloatOrBFloat16) -> TFloatOrBFloat16:
     return op.Floor(self)
 
 
-@torch_op("aten::floor_divide")
+@torch_op("math::floor")
+def python_math_floor(self: TFloatOrBFloat16) -> TInt:
+    """floor(Tensor self) -> Tensor"""
+    floor = op.Floor(self)
+    return op.Cast(floor, to=INT64.dtype)
+
+
+@torch_op(("aten::floor_divide", "_operator::floordiv"))
 def aten_floor_divide(self: TFloat, other: TFloat) -> TFloat:
     """floor_divide(Tensor self, Tensor other) -> Tensor"""
 
@@ -3514,7 +3531,9 @@ def aten_gcd(self: TensorType, other: TensorType) -> TensorType:
     raise NotImplementedError()
 
 
-@torch_op(("aten::ge", "aten::ge.Tensor", "aten::ge.Scalar", "aten::greater_equal"))
+@torch_op(
+    ("aten::ge", "aten::ge.Tensor", "aten::ge.Scalar", "aten::greater_equal", "_operator::ge")
+)
 def aten_ge(self: TReal, other: TReal) -> BOOL:
     """ge.Tensor(Tensor self, Tensor other) -> Tensor"""
 
@@ -3670,7 +3689,7 @@ def aten_gru_cell(
     raise NotImplementedError()
 
 
-@torch_op(("aten::gt", "aten::gt.Scalar", "aten::greater"))
+@torch_op(("aten::gt", "aten::gt.Scalar", "aten::greater", "_operator::gt"))
 def aten_gt(self: TReal, other: TReal) -> BOOL:
     """gt.Tensor(Tensor self, Tensor other) -> Tensor"""
 
@@ -4382,7 +4401,7 @@ def aten_ldexp(self: TensorType, other: TensorType) -> TensorType:
     raise NotImplementedError()
 
 
-@torch_op(("aten::le", "aten::le.Tensor"))
+@torch_op(("aten::le", "aten::le.Tensor", "_operator::le"))
 def aten_le(self: TReal, other: TReal) -> BOOL:
     """le.Tensor(Tensor self, Tensor other) -> Tensor"""
 
@@ -4686,7 +4705,7 @@ def aten_lstm_mps_backward(
     raise NotImplementedError()
 
 
-@torch_op(("aten::lt", "aten::lt.Scalar", "aten::less"))
+@torch_op(("aten::lt", "aten::lt.Scalar", "aten::less", "_operator::lt"))
 def aten_lt(self: TReal, other: TReal) -> BOOL:
     """lt.Tensor(Tensor self, Tensor other) -> Tensor"""
 
@@ -5288,7 +5307,7 @@ def aten_msort(self: TensorType) -> TensorType:
     raise NotImplementedError()
 
 
-@torch_op(("aten::mul", "aten::mul.Tensor"))
+@torch_op(("aten::mul", "aten::mul.Tensor", "_operator::mul"))
 def aten_mul(self: TReal, other: TReal) -> TReal:
     """mul.Tensor(Tensor self, Tensor other) -> Tensor"""
     # FIXME(titaiwang): get rid of this when we have type_promotion
@@ -5739,14 +5758,14 @@ def aten_native_norm(self: TensorType, p: float = 2.0) -> TensorType:
     raise NotImplementedError()
 
 
-@torch_op(("aten::ne", "aten::ne.Scalar", "aten::ne.Tensor"))
+@torch_op(("aten::ne", "aten::ne.Scalar", "aten::ne.Tensor", "_operator::ne"))
 def aten_ne(self: TReal, other: TReal) -> BOOL:
     """ne.Tensor(Tensor self, Tensor other) -> Tensor"""
 
     return op.Not(op.Equal(self, other))
 
 
-@torch_op("aten::neg")
+@torch_op(("aten::neg", "_operator::neg"))
 def aten_neg(self: TReal) -> TReal:
     """neg(Tensor self) -> Tensor"""
 
@@ -6126,7 +6145,9 @@ def aten_positive(self: TensorType) -> TensorType:
     raise NotImplementedError()
 
 
-@torch_op(("aten::pow", "aten::pow.Tensor_Tensor", "aten::pow.Tensor_Scalar"))
+@torch_op(
+    ("aten::pow", "aten::pow.Tensor_Tensor", "aten::pow.Tensor_Scalar", "_operator::pow")
+)
 def aten_pow(self: TReal, exponent: TTensor) -> TReal:
     """pow(Tensor self, Tensor exponent) -> Tensor"""
 
@@ -7406,7 +7427,7 @@ def aten_stft(
     return result
 
 
-@torch_op(("aten::sub", "aten::sub.Tensor"))
+@torch_op(("aten::sub", "aten::sub.Tensor", "_operator::sub"))
 def aten_sub(self: TReal, other: TReal, alpha: float = 1.0) -> TReal:
     """sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor"""
     alpha = op.CastLike(alpha, other)