Adding these ops to enable the use of uint32 for indices in sparse matrices, since int32 has issues on GPU. Adding support for uint32 for:

1. VariableV2
2. Assign
3. Identity
4. TopKV2
5. Roll
6. Sub
7. RefSwitch/Switch

PiperOrigin-RevId: 298692513
Change-Id: I1209fb79ee9f8fca450b7a086a9dbc11945030ea

tensorflow/core/kernels/control_flow_ops.cc

@@ -109,6 +109,8 @@ TF_CALL_NUMBER_TYPES_NO_INT32(REGISTER_GPU_REF_SWITCH);
 TF_CALL_QUANTIZED_TYPES(REGISTER_GPU_REF_SWITCH);
 REGISTER_GPU_SWITCH(uint64);
 TF_CALL_variant(REGISTER_GPU_SWITCH);
+TF_CALL_uint32(REGISTER_GPU_SWITCH);
+TF_CALL_uint32(REGISTER_GPU_REF_SWITCH);
 
 #undef REGISTER_CPU_SWITCH
 #undef REGISTER_CPU_REF_SWITCH

tensorflow/core/kernels/cwise_op_gpu_sub.cu.cc

@@ -19,7 +19,8 @@ limitations under the License.
 
 namespace tensorflow {
 namespace functor {
-DEFINE_BINARY6(sub, Eigen::half, float, double, int64, complex64, complex128);
+DEFINE_BINARY7(sub, Eigen::half, float, double, int64, complex64, complex128,
+               uint32);
 }  // namespace functor
 }  // namespace tensorflow
 

tensorflow/core/kernels/cwise_op_sub.cc

@@ -20,7 +20,8 @@ REGISTER8(BinaryOp, CPU, "Sub", functor::sub, float, Eigen::half, double, int32,
           int64, bfloat16, complex64, complex128);
 #if !defined(__ANDROID_TYPES_SLIM__)
 // Sub op for int8, uint8, int16, uint16
-REGISTER4(BinaryOp, CPU, "Sub", functor::sub, int8, uint8, int16, uint16);
+REGISTER5(BinaryOp, CPU, "Sub", functor::sub, int8, uint8, int16, uint16,
+          uint32);
 #else
 // We only register the first type when we have multi-argument calls in the
 // case where we're trying to reduce executable size, but it turns out that the
@@ -29,8 +30,8 @@ REGISTER(BinaryOp, CPU, "Sub", functor::sub, int32);
 #endif  // __ANDROID_TYPES_SLIM__
 
 #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
-REGISTER6(BinaryOp, GPU, "Sub", functor::sub, float, Eigen::half, double, int64,
-          complex64, complex128);
+REGISTER7(BinaryOp, GPU, "Sub", functor::sub, float, Eigen::half, double, int64,
+          complex64, complex128, uint32);
 
 // A special GPU kernel for int32.
 // TODO(b/25387198): Also enable int32 in device memory. This kernel

tensorflow/core/kernels/dense_update_functor_gpu.cu.cc

@@ -68,6 +68,7 @@ TF_CALL_GPU_ALL_TYPES(DEFINE_GPU_KERNELS);
 TF_CALL_int32(DEFINE_GPU_KERNELS);
 TF_CALL_int64(DEFINE_GPU_KERNELS);
 TF_CALL_int8(DEFINE_GPU_KERNELS);
+TF_CALL_uint32(DEFINE_GPU_KERNELS);
 #undef DEFINE_GPU_KERNELS
 
 }  // end namespace tensorflow

tensorflow/core/kernels/dense_update_ops.cc

@@ -97,6 +97,8 @@ typedef Eigen::SyclDevice SYCLDevice;
       AssignOpT<CPUDevice, type>);
 
 TF_CALL_ALL_TYPES(REGISTER_KERNELS);
+// uint32 not included in ALL_TYPES
+TF_CALL_uint32(REGISTER_KERNELS);
 TF_CALL_QUANTIZED_TYPES(REGISTER_KERNELS);
 // quint16 not included in QUANTIZIED_TYPES
 TF_CALL_quint16(REGISTER_KERNELS);
@@ -112,6 +114,7 @@ TF_CALL_quint16(REGISTER_KERNELS);
 
 TF_CALL_GPU_ALL_TYPES(REGISTER_GPU_KERNELS);
 TF_CALL_int64(REGISTER_GPU_KERNELS);
+TF_CALL_uint32(REGISTER_GPU_KERNELS);
 #undef REGISTER_GPU_KERNELS
 #endif  // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
 

tensorflow/core/kernels/identity_op.cc

@@ -122,6 +122,7 @@ REGISTER_SYCL_HOST_KERNEL(bool);
 
 TF_CALL_NUMBER_TYPES_NO_INT32(REGISTER_GPU_KERNEL);
 REGISTER_GPU_KERNEL(Variant);
+TF_CALL_uint32(REGISTER_GPU_KERNEL);
 
 #undef REGISTER_GPU_KERNEL
 

tensorflow/core/kernels/roll_op.cc

@@ -400,6 +400,7 @@ TF_CALL_int64(REGISTER_KERNEL);
 TF_CALL_GPU_NUMBER_TYPES(REGISTER_KERNEL);
 TF_CALL_complex64(REGISTER_KERNEL);
 TF_CALL_complex128(REGISTER_KERNEL);
+TF_CALL_uint32(REGISTER_KERNEL);
 
 #undef REGISTER_KERNEL
 #endif  // GOOGLE_CUDA || TENSORFLOW_USE_ROCM

tensorflow/core/kernels/roll_op_gpu.cu.cc

@@ -96,6 +96,7 @@ TF_CALL_int64(DEFINE_GPU_SPECS);
 TF_CALL_GPU_NUMBER_TYPES(DEFINE_GPU_SPECS);
 TF_CALL_complex64(DEFINE_GPU_SPECS);
 TF_CALL_complex128(DEFINE_GPU_SPECS);
+TF_CALL_uint32(DEFINE_GPU_SPECS)
 
 #undef DEFINE_GPU_SPECS
 }  // namespace functor

tensorflow/core/kernels/topk_op.cc

@@ -258,6 +258,7 @@ namespace functor {
 
 TF_CALL_GPU_NUMBER_TYPES(DECLARE_GPU_SPEC);
 TF_CALL_INTEGRAL_TYPES(DECLARE_GPU_SPEC);
+TF_CALL_uint32(DECLARE_GPU_SPEC);
 
 #undef DECLARE_GPU_SPEC
 
@@ -275,7 +276,7 @@ TF_CALL_INTEGRAL_TYPES(DECLARE_GPU_SPEC);
 
 TF_CALL_GPU_NUMBER_TYPES(REGISTER_KERNELS);
 TF_CALL_INTEGRAL_TYPES(REGISTER_KERNELS);
-
+TF_CALL_uint32(REGISTER_KERNELS)
 #undef REGISTER_KERNELS
 
 #endif  // end GOOGLE_CUDA

tensorflow/core/kernels/topk_op_gpu_uint16.cu.cc

@@ -23,6 +23,8 @@ namespace tensorflow {
 using Eigen::GpuDevice;
 
 template struct functor::TopKFunctor<GPUDevice, uint16>;
+template struct functor::TopKFunctor<GPUDevice, uint32>;
+
 }  // namespace tensorflow
 
 #endif  // GOOGLE_CUDA

tensorflow/core/kernels/variable_ops.cc

@@ -236,6 +236,7 @@ TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SYCL_KERNEL);
 
 TF_CALL_GPU_NUMBER_TYPES(REGISTER_GPU_KERNELS);
 TF_CALL_int64(REGISTER_GPU_KERNELS);
+TF_CALL_uint32(REGISTER_GPU_KERNELS);
 #undef REGISTER_GPU_KERNELS
 #endif  // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
 

tensorflow/core/ops/math_ops.cc

@@ -435,8 +435,14 @@ Returns `x` + `y` element-wise.
 )doc");
 #endif  // INTEL_MKL
 
-REGISTER_OP("Sub").BINARY_MORE().SetShapeFn(
-    shape_inference::BroadcastBinaryOpShapeFn);
+REGISTER_OP("Sub")
+    .Input("x: T")
+    .Input("y: T")
+    .Output("z: T")
+    .Attr(
+        "T: {bfloat16, half, float, double, uint8, int8, uint16, int16, int32, "
+        "int64, complex64, complex128, uint32}")
+    .SetShapeFn(shape_inference::BroadcastBinaryOpShapeFn);
 
 REGISTER_OP("_MklSub")
     .BINARY_FEWER()