[Relax] Support left_shift and right_shift op

Introduced left_shift and right_shift op in Relax with ONNX frontend
support.

Author: Siyuan Feng

python/tvm/relax/frontend/onnx/onnx_frontend.py

@@ -244,7 +244,7 @@ class BinaryBase(OnnxOpConverter):
     relax_op: Callable = None
 
     @classmethod
-    def _impl_v1(cls, bb, inputs, attr, params):
+    def base_impl(cls, bb, inputs, attr, params):
         if cls.numpy_op is None or cls.relax_op is None:
             raise ValueError("Numpy and Relax operators must be defined for BinaryBase.")
         if all([isinstance(inp, relax.Constant) for inp in inputs]):
@@ -274,83 +274,131 @@ class Add(BinaryBase):
     numpy_op = _np.add
     relax_op = relax.op.add
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Sub(BinaryBase):
     """Converts an onnx Sub node into an equivalent Relax expression."""
 
     numpy_op = _np.subtract
     relax_op = relax.op.subtract
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Mul(BinaryBase):
     """Converts an onnx Mul node into an equivalent Relax expression."""
 
     numpy_op = _np.multiply
     relax_op = relax.op.multiply
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Div(BinaryBase):
     """Converts an onnx Div node into an equivalent Relax expression."""
 
     numpy_op = _np.divide
     relax_op = relax.op.divide
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Pow(BinaryBase):
     """Converts an onnx Pow node into an equivalent Relax expression."""
 
     numpy_op = _np.power
     relax_op = relax.op.power
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class And(BinaryBase):
     """Converts an onnx And node into an equivalent Relax expression."""
 
     numpy_op = _np.logical_and
     relax_op = relax.op.logical_and
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Or(BinaryBase):
     """Converts an onnx Or node into an equivalent Relax expression."""
 
     numpy_op = _np.logical_or
     relax_op = relax.op.logical_or
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Xor(BinaryBase):
     """Converts an onnx Xor node into an equivalent Relax expression."""
 
     numpy_op = _np.logical_xor
     relax_op = relax.op.logical_xor
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Less(BinaryBase):
     """Converts an onnx Less node into an equivalent Relax expression."""
 
     numpy_op = _np.less
     relax_op = relax.op.less
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class LessOrEqual(BinaryBase):
     """Converts an onnx LessEqual node into an equivalent Relax expression."""
 
     numpy_op = _np.less_equal
     relax_op = relax.op.less_equal
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Greater(BinaryBase):
     """Converts an onnx Greater node into an equivalent Relax expression."""
 
     numpy_op = _np.greater
     relax_op = relax.op.greater
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class GreaterOrEqual(BinaryBase):
     """Converts an onnx GreaterEqual node into an equivalent Relax expression."""
 
     numpy_op = _np.greater_equal
     relax_op = relax.op.greater_equal
 
+    @classmethod
+    def _impl_v1(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
 
 class Equal(OnnxOpConverter):
     """Converts an onnx Equal node into an equivalent Relax expression."""
@@ -374,39 +422,77 @@ class BitwiseBase(BinaryBase):
     """Converts an onnx BitwiseBase node into an equivalent Relax expression."""
 
     @classmethod
-    def base_impl(cls, bb, inputs, attr, params, py_func, relax_op):
+    def base_impl(cls, bb, inputs, attr, params):
         valid_types = ["int8", "int16", "int32", "int64", "uint8", "uint16", "uint32", "uint64"]
         for num, inp in enumerate(inputs):
             if inp.struct_info.dtype not in valid_types:
                 raise ValueError(
                     f"Bitwise operations expect all inputs to have integer types, "
                     f"got {inp.struct_info.dtype} for input {num}"
                 )
-        return BinaryBase.base_impl(bb, inputs, attr, params, py_func, relax_op)
+        return super().base_impl(bb, inputs, attr, params)
 
 
 class BitwiseAnd(BitwiseBase):
     """Converts an onnx BitwiseAnd node into an equivalent Relax expression."""
 
+    numpy_op = _np.bitwise_and
+    relax_op = relax.op.bitwise_and
+
     @classmethod
     def _impl_v18(cls, bb, inputs, attr, params):
-        return cls.base_impl(bb, inputs, attr, params, lambda x, y: x & y, relax.op.bitwise_and)
+        return cls.base_impl(bb, inputs, attr, params)
 
 
 class BitwiseOr(BitwiseBase):
     """Converts an onnx BitwiseOr node into an equivalent Relax expression."""
 
+    numpy_op = _np.bitwise_or
+    relax_op = relax.op.bitwise_or
+
     @classmethod
     def _impl_v18(cls, bb, inputs, attr, params):
-        return cls.base_impl(bb, inputs, attr, params, lambda x, y: x | y, relax.op.bitwise_or)
+        return cls.base_impl(bb, inputs, attr, params)
 
 
 class BitwiseXor(BitwiseBase):
     """Converts an onnx BitwiseXor node into an equivalent Relax expression."""
 
+    numpy_op = _np.bitwise_xor
+    relax_op = relax.op.bitwise_xor
+
     @classmethod
     def _impl_v18(cls, bb, inputs, attr, params):
-        return cls.base_impl(bb, inputs, attr, params, lambda x, y: x ^ y, relax.op.bitwise_xor)
+        return cls.base_impl(bb, inputs, attr, params)
+
+
+class BitwiseNot(BitwiseBase):
+    """Converts an onnx BitwiseNot node into an equivalent Relax expression."""
+
+    numpy_op = _np.bitwise_not
+    relax_op = relax.op.bitwise_not
+
+    @classmethod
+    def _impl_v18(cls, bb, inputs, attr, params):
+        return cls.base_impl(bb, inputs, attr, params)
+
+
+class BitShift(BitwiseBase):
+    """Converts an onnx BitShift node into an equivalent Relax expression."""
+
+    @classmethod
+    def _impl_v11(cls, bb, inputs, attr, params):
+        direction = attr.get("direction", "LEFT").decode("ascii")
+        if direction == "LEFT":
+            cls.numpy_op = _np.left_shift
+            cls.relax_op = relax.op.left_shift
+        elif direction == "RIGHT":
+            cls.numpy_op = _np.right_shift
+            cls.relax_op = relax.op.right_shift
+        else:
+            raise ValueError("Unsupported Shift Direction: " + direction)
+
+        return cls.base_impl(bb, inputs, attr, params)
 
 
 class Sigmoid(OnnxOpConverter):
@@ -2652,8 +2738,8 @@ def _get_convert_map():
         "BitwiseAnd": BitwiseAnd,
         "BitwiseOr": BitwiseOr,
         "BitwiseXor": BitwiseXor,
-        # "BitwiseNot": BitwiseNot,
-        # "BitwiseShift": BitwiseShift,
+        "BitwiseNot": BitwiseNot,
+        "BitShift": BitShift,
         "And": And,
         "Or": Or,
         "Xor": Xor,

python/tvm/relax/op/__init__.py

@@ -52,6 +52,7 @@
     floor_divide,
     greater,
     greater_equal,
+    left_shift,
     less,
     less_equal,
     logical_and,
@@ -62,6 +63,7 @@
     multiply,
     not_equal,
     power,
+    right_shift,
     subtract,
 )
 from .create import (

python/tvm/relax/op/binary.py

@@ -386,3 +386,35 @@ def bitwise_xor(x1: Expr, x2: Expr) -> Expr:
         The computed result.
     """
     return _ffi_api.bitwise_xor(x1, x2)
+
+
+def left_shift(x1: Expr, x2: Expr) -> Expr:
+    """Bitwise Shift Left
+    Parameters
+    ----------
+    x1 : relax.Expr
+        The input tensor to be shifted.
+    x2 : relax.Expr
+        The number of positions to shift.
+    Returns
+    -------
+    result : relax.Expr
+        The computed result.
+    """
+    return _ffi_api.left_shift(x1, x2)
+
+
+def right_shift(x1: Expr, x2: Expr) -> Expr:
+    """Bitwise Shift Right
+    Parameters
+    ----------
+    x1 : relax.Expr
+        The input tensor to be shifted.
+    x2 : relax.Expr
+        The number of positions to shift.
+    Returns
+    -------
+    result : relax.Expr
+        The computed result.
+    """
+    return _ffi_api.right_shift(x1, x2)

python/tvm/relax/transform/legalize_ops/binary.py

@@ -62,6 +62,8 @@ def binary_call_te(bb: BlockBuilder, call: Call) -> Expr:
 register_legalize("relax.bitwise_and", _binary(topi.bitwise_and))
 register_legalize("relax.bitwise_or", _binary(topi.bitwise_or))
 register_legalize("relax.bitwise_xor", _binary(topi.bitwise_xor))
+register_legalize("relax.left_shift", _binary(topi.left_shift))
+register_legalize("relax.right_shift", _binary(topi.right_shift))
 
 # logical
 register_legalize("relax.logical_and", _binary(topi.logical_and))

python/tvm/script/ir_builder/relax/ir.py

@@ -102,6 +102,7 @@
     isinf,
     isnan,
     layout_transform,
+    left_shift,
     less,
     less_equal,
     linear,
@@ -133,6 +134,7 @@
     quantize,
     repeat,
     reshape,
+    right_shift,
     round,
     rsqrt,
     scatter_elements,
@@ -773,6 +775,7 @@ def dtype(value: Union[py_str, DataType]) -> Expr:
     "isinf",
     "isnan",
     "layout_transform",
+    "left_shift",
     "less",
     "less_equal",
     "linear",
@@ -809,6 +812,7 @@ def dtype(value: Union[py_str, DataType]) -> Expr:
     "repeat",
     "reshape",
     "rewriter",
+    "right_shift",
     "tensor_to_shape",
     "shape_to_tensor",
     "rocm",

src/relax/op/distributed/binary.cc

@@ -68,6 +68,8 @@ RELAX_REGISTER_BINARY_BROADCAST_DIST_INFER_STRUCT_INFO(logical_xor);
 RELAX_REGISTER_BINARY_BROADCAST_DIST_INFER_STRUCT_INFO(bitwise_and);
 RELAX_REGISTER_BINARY_BROADCAST_DIST_INFER_STRUCT_INFO(bitwise_or);
 RELAX_REGISTER_BINARY_BROADCAST_DIST_INFER_STRUCT_INFO(bitwise_xor);
+RELAX_REGISTER_BINARY_BROADCAST_DIST_INFER_STRUCT_INFO(left_shift);
+RELAX_REGISTER_BINARY_BROADCAST_DIST_INFER_STRUCT_INFO(right_shift);
 
 }  // namespace distributed
 }  // namespace relax

src/relax/op/tensor/binary.cc

@@ -207,6 +207,8 @@ RELAX_REGISTER_BINARY_BROADCAST_OP_AND_IMPL(logical_xor);
 RELAX_REGISTER_BINARY_BROADCAST_OP_AND_IMPL(bitwise_and);
 RELAX_REGISTER_BINARY_BROADCAST_OP_AND_IMPL(bitwise_or);
 RELAX_REGISTER_BINARY_BROADCAST_OP_AND_IMPL(bitwise_xor);
+RELAX_REGISTER_BINARY_BROADCAST_OP_AND_IMPL(left_shift);
+RELAX_REGISTER_BINARY_BROADCAST_OP_AND_IMPL(right_shift);
 
 }  // namespace relax
 }  // namespace tvm

src/relax/op/tensor/binary.h

@@ -129,6 +129,12 @@ Expr bitwise_or(Expr x1, Expr x2);
 /*! \brief Broadcasted element-wise bitwise xor */
 Expr bitwise_xor(Expr x1, Expr x2);
 
+/*! \brief Broadcasted element-wise bitwise shift left */
+Expr left_shift(Expr x1, Expr x2);
+
+/*! \brief Broadcasted element-wise bitwise shift right */
+Expr right_shift(Expr x1, Expr x2);
+
 }  // namespace relax
 }  // namespace tvm