add-uint-support
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
What this skill does
# Add Unsigned Integer (uint) Support to Operators
This skill helps add support for unsigned integer types (uint16, uint32, uint64) to PyTorch operators by updating their AT_DISPATCH macros.
## When to use this skill
Use this skill when:
- Adding uint16, uint32, or uint64 support to an operator
- User mentions "unsigned types", "uint support", "barebones unsigned types"
- Enabling support for kUInt16, kUInt32, kUInt64 in kernels
- Working with operator implementations that need expanded type coverage
## Quick reference
**Add unsigned types to existing dispatch:**
```cpp
// Before
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES));
// After (method 1: add unsigned types explicitly)
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES));
// After (method 2: use V2 integral types if AT_INTEGRAL_TYPES present)
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES));
```
## Type group reference
**Unsigned type groups:**
- `AT_BAREBONES_UNSIGNED_TYPES`: kUInt16, kUInt32, kUInt64
- `AT_INTEGRAL_TYPES_V2`: AT_INTEGRAL_TYPES + AT_BAREBONES_UNSIGNED_TYPES
**Relationship:**
```cpp
AT_INTEGRAL_TYPES // kByte, kChar, kInt, kLong, kShort
AT_BAREBONES_UNSIGNED_TYPES // kUInt16, kUInt32, kUInt64
AT_INTEGRAL_TYPES_V2 // INTEGRAL_TYPES + BAREBONES_UNSIGNED_TYPES
```
## Instructions
### Step 1: Determine if conversion to V2 is needed
Check if the file uses AT_DISPATCH_V2:
**If using old AT_DISPATCH:**
- First convert to AT_DISPATCH_V2 using the at-dispatch-v2 skill
- Then proceed with adding uint support
**If already using AT_DISPATCH_V2:**
- Proceed directly to Step 2
### Step 2: Analyze the current dispatch macro
Identify what type groups are currently in use:
```cpp
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
// body
}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);
^^^^^^^^^^^^^^^^^^^^^^^^^
Current type coverage
```
Common patterns:
- `AT_EXPAND(AT_ALL_TYPES)` → includes AT_INTEGRAL_TYPES + AT_FLOATING_TYPES
- `AT_EXPAND(AT_INTEGRAL_TYPES)` → signed integers only
- `AT_EXPAND(AT_FLOATING_TYPES)` → floating point types
### Step 3: Choose the uint addition method
Two approaches:
**Method 1: Add AT_BAREBONES_UNSIGNED_TYPES explicitly**
- Use when: You want to be explicit about adding uint support
- Add `AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES)` to the type list
**Method 2: Substitute AT_INTEGRAL_TYPES with AT_INTEGRAL_TYPES_V2**
- Use when: The dispatch already uses `AT_EXPAND(AT_INTEGRAL_TYPES)`
- More concise: replaces one type group with its superset
- Only applicable if AT_INTEGRAL_TYPES is present
### Step 4: Apply the transformation
**Method 1 example:**
```cpp
// Before
AT_DISPATCH_V2(
dtype,
"min_values_cuda",
AT_WRAP([&]() {
kernel_impl<scalar_t>(iter);
}),
AT_EXPAND(AT_ALL_TYPES),
kBFloat16, kHalf, kBool
);
// After (add unsigned types)
AT_DISPATCH_V2(
dtype,
"min_values_cuda",
AT_WRAP([&]() {
kernel_impl<scalar_t>(iter);
}),
AT_EXPAND(AT_ALL_TYPES),
AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES),
kBFloat16, kHalf, kBool
);
```
**Method 2 example:**
```cpp
// Before
AT_DISPATCH_V2(
dtype,
"integral_op",
AT_WRAP([&]() {
kernel<scalar_t>();
}),
AT_EXPAND(AT_INTEGRAL_TYPES)
);
// After (substitute with V2)
AT_DISPATCH_V2(
dtype,
"integral_op",
AT_WRAP([&]() {
kernel<scalar_t>();
}),
AT_EXPAND(AT_INTEGRAL_TYPES_V2)
);
```
### Step 5: Handle AT_ALL_TYPES vs individual type groups
If the dispatch uses `AT_EXPAND(AT_ALL_TYPES)`:
- `AT_ALL_TYPES` = `AT_INTEGRAL_TYPES` + `AT_FLOATING_TYPES`
- To add uint: add `AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES)` to the list
If the dispatch separately lists INTEGRAL and FLOATING:
```cpp
// Before
AT_EXPAND(AT_INTEGRAL_TYPES), AT_EXPAND(AT_FLOATING_TYPES)
// After (Method 2 preferred)
AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES)
```
### Step 6: Verify all dispatch sites
Check the file for ALL dispatch macros that need uint support:
- Some operators have multiple dispatch sites (CPU, CUDA, different functions)
- Apply the transformation consistently across all sites
- Ensure each gets the same type coverage updates
### Step 7: Validate the changes
Check that:
- [ ] AT_DISPATCH_V2 format is used (not old AT_DISPATCH)
- [ ] Unsigned types are added via one of the two methods
- [ ] All relevant dispatch sites in the file are updated
- [ ] Type groups use `AT_EXPAND()`
- [ ] Arguments are properly formatted and comma-separated
## Common patterns
### Pattern 1: AT_ALL_TYPES + extras
```cpp
// Before
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);
// After
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kHalf, kBFloat16);
```
### Pattern 2: Separate INTEGRAL + FLOATING
```cpp
// Before
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_INTEGRAL_TYPES), AT_EXPAND(AT_FLOATING_TYPES));
// After
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES));
```
### Pattern 3: Old dispatch needs conversion first
```cpp
// Before (needs v2 conversion first)
AT_DISPATCH_ALL_TYPES_AND2(kHalf, kBFloat16, dtype, "op", [&]() {
kernel<scalar_t>();
});
// After v2 conversion
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);
// After adding uint support
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kHalf, kBFloat16);
```
## Multiple dispatch sites example
For a file with multiple functions:
```cpp
void min_values_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_V2(iter.dtype(), "min_values_cuda", AT_WRAP([&]() {
impl<scalar_t>(iter);
}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kBFloat16, kHalf);
// ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
// Added uint support
}
void min_launch_kernel(TensorIterator &iter) {
AT_DISPATCH_V2(iter.input_dtype(), "min_cuda", AT_WRAP([&]() {
gpu_reduce_kernel<scalar_t>(iter);
}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kBFloat16, kHalf);
// ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
// Added uint support here too
}
```
## Decision tree
Use this decision tree to determine the approach:
```
Is the file using AT_DISPATCH_V2?
├─ No → Use at-dispatch-v2 skill first, then continue
└─ Yes
└─ Does it use AT_EXPAND(AT_INTEGRAL_TYPES)?
├─ Yes → Replace with AT_EXPAND(AT_INTEGRAL_TYPES_V2)
└─ No → Add AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES) to type list
```
## Edge cases
### Case 1: Dispatch with only floating types
If the operator only supports floating point types, don't add uint support:
```cpp
// Leave as-is - floating point only operator
AT_DISPATCH_V2(dtype, "float_op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_FLOATING_TYPES), kHalf);
```
### Case 2: Complex types present
Unsigned types work alongside complex types:
```cpp
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES),
AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES),
AT_EXPAND(AT_COMPLEX_TYPES),
kHalf, kBFloat16);
```
### Case 3: Already has uint support
Check if uint types are already present:
- If `AT_INTEGRAL_TYPES_V2` is used → already has uint support
- If `AT_BAREBONES_UNSIGNED_TYPES` is already in list → already has uint support
- Skip the file if uint support is already present
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