cpu to support bitwise ops (#14197)

docs/OperatorKernels.md

@@ -44,6 +44,10 @@ Do not modify directly.*
 |||[9, 13]|**T** = tensor(double), tensor(float)|
 |||[7, 8]|**T** = tensor(double), tensor(float)|
 |BitShift|*in* X:**T**<br> *in* Y:**T**<br> *out* Z:**T**|11+|**T** = tensor(uint32), tensor(uint64), tensor(uint8)|
+|BitwiseAnd|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T**|18+|**T** = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|BitwiseNot|*in* X:**T**<br> *out* Y:**T**|18+|**T** = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|BitwiseOr|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T**|18+|**T** = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
+|BitwiseXor|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T**|18+|**T** = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |BlackmanWindow|*in* size:**T1**<br> *out* output:**T2**|17+|**T1** = tensor(int32), tensor(int64)<br/> **T2** = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |Cast|*in* input:**T1**<br> *out* output:**T2**|13+|**T1** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
 |||[6, 12]|**T1** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T2** = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|

onnxruntime/core/providers/cpu/cpu_execution_provider.cc

@@ -830,6 +830,38 @@ class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain,
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, float, ReduceSumSquare);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, double, ReduceSumSquare);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, ReduceSumSquare);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int8_t, BitwiseAnd);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int16_t, BitwiseAnd);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, BitwiseAnd);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int64_t, BitwiseAnd);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint8_t, BitwiseAnd);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint16_t, BitwiseAnd);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint32_t, BitwiseAnd);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint64_t, BitwiseAnd);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int8_t, BitwiseNot);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int16_t, BitwiseNot);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, BitwiseNot);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int64_t, BitwiseNot);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint8_t, BitwiseNot);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint16_t, BitwiseNot);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint32_t, BitwiseNot);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint64_t, BitwiseNot);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int8_t, BitwiseOr);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int16_t, BitwiseOr);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, BitwiseOr);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int64_t, BitwiseOr);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint8_t, BitwiseOr);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint16_t, BitwiseOr);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint32_t, BitwiseOr);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint64_t, BitwiseOr);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int8_t, BitwiseXor);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int16_t, BitwiseXor);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, BitwiseXor);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int64_t, BitwiseXor);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint8_t, BitwiseXor);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint16_t, BitwiseXor);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint32_t, BitwiseXor);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint64_t, BitwiseXor);
 class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, Pad);
 class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, ScatterND);
 class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, ScatterElements);
@@ -2131,6 +2163,38 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
                                                                 ReduceSumSquare)>,
     BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, double,
                                                                 ReduceSumSquare)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int8_t, BitwiseAnd)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int16_t, BitwiseAnd)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, BitwiseAnd)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int64_t, BitwiseAnd)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint8_t, BitwiseAnd)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint16_t, BitwiseAnd)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint32_t, BitwiseAnd)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint64_t, BitwiseAnd)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int8_t, BitwiseNot)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int16_t, BitwiseNot)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, BitwiseNot)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int64_t, BitwiseNot)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint8_t, BitwiseNot)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint16_t, BitwiseNot)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint32_t, BitwiseNot)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint64_t, BitwiseNot)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int8_t, BitwiseOr)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int16_t, BitwiseOr)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, BitwiseOr)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int64_t, BitwiseOr)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint8_t, BitwiseOr)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint16_t, BitwiseOr)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint32_t, BitwiseOr)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint64_t, BitwiseOr)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int8_t, BitwiseXor)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int16_t, BitwiseXor)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int32_t, BitwiseXor)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, int64_t, BitwiseXor)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint8_t, BitwiseXor)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint16_t, BitwiseXor)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint32_t, BitwiseXor)>,
+    BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, uint64_t, BitwiseXor)>,
     BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, Pad)>,
     BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, ScatterND)>,
     BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 18, ScatterElements)>,

onnxruntime/core/providers/cpu/math/element_wise_ops.cc

@@ -374,6 +374,42 @@ REG_ELEMENTWISE_TYPED_KERNEL(BitShift, 11, uint8_t, BitShift);
 REG_ELEMENTWISE_TYPED_KERNEL(BitShift, 11, uint32_t, BitShift);
 REG_ELEMENTWISE_TYPED_KERNEL(BitShift, 11, uint64_t, BitShift);
 
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseAnd, 18, int8_t, BitwiseAnd);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseAnd, 18, int16_t, BitwiseAnd);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseAnd, 18, int32_t, BitwiseAnd);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseAnd, 18, int64_t, BitwiseAnd);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseAnd, 18, uint8_t, BitwiseAnd);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseAnd, 18, uint16_t, BitwiseAnd);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseAnd, 18, uint32_t, BitwiseAnd);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseAnd, 18, uint64_t, BitwiseAnd);
+
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseNot, 18, int8_t, BitwiseNot);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseNot, 18, int16_t, BitwiseNot);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseNot, 18, int32_t, BitwiseNot);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseNot, 18, int64_t, BitwiseNot);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseNot, 18, uint8_t, BitwiseNot);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseNot, 18, uint16_t, BitwiseNot);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseNot, 18, uint32_t, BitwiseNot);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseNot, 18, uint64_t, BitwiseNot);
+
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseOr, 18, int8_t, BitwiseOr);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseOr, 18, int16_t, BitwiseOr);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseOr, 18, int32_t, BitwiseOr);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseOr, 18, int64_t, BitwiseOr);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseOr, 18, uint8_t, BitwiseOr);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseOr, 18, uint16_t, BitwiseOr);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseOr, 18, uint32_t, BitwiseOr);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseOr, 18, uint64_t, BitwiseOr);
+
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseXor, 18, int8_t, BitwiseXor);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseXor, 18, int16_t, BitwiseXor);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseXor, 18, int32_t, BitwiseXor);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseXor, 18, int64_t, BitwiseXor);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseXor, 18, uint8_t, BitwiseXor);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseXor, 18, uint16_t, BitwiseXor);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseXor, 18, uint32_t, BitwiseXor);
+REG_ELEMENTWISE_TYPED_KERNEL(BitwiseXor, 18, uint64_t, BitwiseXor);
+
 REG_ELEMENTWISE_VERSIONED_TYPED_KERNEL(Erf, 9, 12, float, Erf);
 // Supposed to add BFloat16 but we are not supporting now, however, separate registration
 REG_ELEMENTWISE_TYPED_KERNEL(Erf, 13, float, Erf);
@@ -1155,7 +1191,122 @@ Status BitShift<T>::Compute(OpKernelContext* context) const {
 }
 
 template <typename T>
-class Sin final : public OpKernel {
+Status BitwiseAnd<T>::Compute(OpKernelContext* context) const {
+  ProcessBroadcastSpanFuncs funcs {
+      [](BroadcastHelper& per_iter_bh) {
+        const T X = per_iter_bh.ScalarInput0<T>();
+        auto Y = per_iter_bh.SpanInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(Y.begin(), Y.end(), output.begin(),
+            [X](T y) {
+                return std::bit_and<T>()(X, y);
+            });
+      },
+      [](BroadcastHelper& per_iter_bh) {
+        auto X = per_iter_bh.SpanInput0<T>();
+        const T Y = per_iter_bh.ScalarInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(X.begin(), X.end(), output.begin(),
+            [Y](T x) {
+                return static_cast<T>(std::bit_and<T>()(x, Y));
+            });
+      },
+      [](BroadcastHelper& per_iter_bh) {
+        auto X = per_iter_bh.SpanInput0<T>();
+        auto Y = per_iter_bh.SpanInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(X.begin(), X.end(), Y.begin(), output.begin(), std::bit_and<T>());
+      }};
+  
+  UntypedBroadcastTwo(*context, funcs, 1.0f);
+  return Status::OK();
+}
+
+template <typename T>
+Status BitwiseNot<T>::Compute(OpKernelContext* context) const {
+  auto& input = *context->Input<Tensor>(0);
+  auto& output = *context->Output(0, input.Shape());
+
+  std::transform(EigenMap<T>(input).array().begin(), EigenMap<T>(input).array().end(), EigenMap<T>(output).array().begin(), std::bit_not<T>());
+
+  return Status::OK();
+}
+
+template <typename T>
+Status BitwiseOr<T>::Compute(OpKernelContext* context) const {
+  ProcessBroadcastSpanFuncs funcs{
+      [](BroadcastHelper& per_iter_bh) {
+        const T X = per_iter_bh.ScalarInput0<T>();
+        auto Y = per_iter_bh.SpanInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(Y.begin(), Y.end(), output.begin(),
+                       [X](T y) {
+                         return std::bit_or<T>()(X, y);
+                       });
+      },
+      [](BroadcastHelper& per_iter_bh) {
+        auto X = per_iter_bh.SpanInput0<T>();
+        const T Y = per_iter_bh.ScalarInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(X.begin(), X.end(), output.begin(),
+                       [Y](T x) {
+                         return static_cast<T>(std::bit_or<T>()(x, Y));
+                       });
+      },
+      [](BroadcastHelper& per_iter_bh) {
+        auto X = per_iter_bh.SpanInput0<T>();
+        auto Y = per_iter_bh.SpanInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(X.begin(), X.end(), Y.begin(), output.begin(), std::bit_or<T>());
+      }};
+
+  UntypedBroadcastTwo(*context, funcs, 1.0f);
+  return Status::OK();
+}
+
+template <typename T>
+Status BitwiseXor<T>::Compute(OpKernelContext* context) const {
+  ProcessBroadcastSpanFuncs funcs{
+      [](BroadcastHelper& per_iter_bh) {
+        const T X = per_iter_bh.ScalarInput0<T>();
+        auto Y = per_iter_bh.SpanInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(Y.begin(), Y.end(), output.begin(),
+                       [X](T y) {
+                         return std::bit_xor<T>()(X, y);
+                       });
+      },
+      [](BroadcastHelper& per_iter_bh) {
+        auto X = per_iter_bh.SpanInput0<T>();
+        const T Y = per_iter_bh.ScalarInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(X.begin(), X.end(), output.begin(),
+                       [Y](T x) {
+                         return static_cast<T>(std::bit_xor<T>()(x, Y));
+                       });
+      },
+      [](BroadcastHelper& per_iter_bh) {
+        auto X = per_iter_bh.SpanInput0<T>();
+        auto Y = per_iter_bh.SpanInput1<T>();
+        auto output = per_iter_bh.OutputSpan<T>();
+
+        std::transform(X.begin(), X.end(), Y.begin(), output.begin(), std::bit_xor<T>());
+      }};
+
+  UntypedBroadcastTwo(*context, funcs, 1.0f);
+  return Status::OK();
+}
+
+template <typename T>
+  class Sin final : public OpKernel {
  public:
   Sin(const OpKernelInfo& info) : OpKernel(info) {
   }

onnxruntime/core/providers/cpu/math/element_wise_ops.h

@@ -427,6 +427,42 @@ class BitShift final : public OpKernel {
   bool shift_left_;
 };
 
+template <typename T>
+class BitwiseAnd final : public OpKernel {
+ public:
+  explicit BitwiseAnd(const OpKernelInfo& info) : OpKernel(info) {
+  }
+
+  Status Compute(OpKernelContext* context) const override;
+};
+
+template <typename T>
+class BitwiseNot final : public OpKernel {
+ public:
+  explicit BitwiseNot(const OpKernelInfo& info) : OpKernel(info) {
+  }
+
+  Status Compute(OpKernelContext* context) const override;
+};
+
+template <typename T>
+class BitwiseOr final : public OpKernel {
+ public:
+  explicit BitwiseOr(const OpKernelInfo& info) : OpKernel(info) {
+  }
+
+  Status Compute(OpKernelContext* context) const override;
+};
+
+template <typename T>
+class BitwiseXor final : public OpKernel {
+ public:
+  explicit BitwiseXor(const OpKernelInfo& info) : OpKernel(info) {
+  }
+
+  Status Compute(OpKernelContext* context) const override;
+};
+
 // PRelu is activation function, but it's closer to binary elementwise ops in implementation
 template <typename T>
 class PRelu final : public OpKernel {

onnxruntime/test/testdata/onnx_backend_test_series_filters.jsonc

@@ -116,7 +116,6 @@
         "^test_div_uint8_cuda",
         "^test_add_uint8_cuda",
         "^test_roialign_aligned_*",
-        "^test_bitwise_*",
         "^test_clip_default_int8_max_expanded_cpu",
         "^test_clip_default_int8_min_expanded_cpu",
         "^test_col2im_*",