Reapply "[FRONTEND] added support for tuples (#5220)" (#3043)

This reverts commit 492ea92.

Summary of changes:
* support for tuples
* `constexprs` are now also part of the signature. The format is:
`signature={..., 'o': "*fp32", '[Name of constexpr]': 'constexpr'}`
* For `ASTSource` there is parameter name change: `constants` ->
`constexprs`
* New nesting level has appeared for the main properties (defined in
`_add_common_properties`): `divisibility_16`, `equal_to_1` and
`equal_to_none`.

---------

Signed-off-by: Anatoly Myachev <[email protected]>
Co-authored-by: Pavel Chekin <[email protected]>

Author: anmyachev

.pre-commit-config.yaml

@@ -6,6 +6,7 @@ repos:
       - id: check-symlinks
       - id: destroyed-symlinks
       - id: trailing-whitespace
+        exclude: .*.patch
       - id: end-of-file-fixer
       - id: check-yaml
       - id: check-toml

python/src/ir.cc

@@ -605,6 +605,7 @@ void init_triton_ir(py::module &&m) {
                    "Function argument index out of range");
              return self.getArgument(idx);
            })
+      .def("get_num_args", &FuncOp::getNumArguments)
       .def(
           "add_entry_block",
           [](FuncOp &self) -> Block * { return self.addEntryBlock(); },

python/test/unit/language/test_compile_errors.py

@@ -17,7 +17,7 @@ def kernel():
         a += 1  # noqa
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
     try:
         assert "is not defined" in str(e.value), "error should mention the undefined variable"
@@ -32,7 +32,7 @@ def kernel():
         0 + "a"
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
     try:
         assert "at 2:4:" in str(e.value), "error should point to the 0"
@@ -47,7 +47,7 @@ def kernel():
         tl.static_assert(isinstance(0, tl.tensor))
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
     try:
         assert isinstance(e.value, CompileTimeAssertionFailure)
@@ -66,7 +66,7 @@ def kernel():
         not (0, 0)
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
     try:
         assert e.value.__cause__ is None
@@ -83,7 +83,7 @@ def kernel():
         1.0 << 1
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
     try:
         assert "at 2:4:" in str(e.value), "error should point to the 1.0"
@@ -107,7 +107,7 @@ def kernel():
         nested_call()
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
     try:
         inner = e.value.__cause__
@@ -130,7 +130,7 @@ def kernel():
         tl.expand_dims(None, -1)
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
     try:
         inner = e.value.__cause__
@@ -157,7 +157,7 @@ def kernel():
         a = two_returns()
         a + tl.arange(0, 4)  # only works if we took the first return
 
-    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
 
 def test_not_const_annotate_no_err():
@@ -166,7 +166,7 @@ def test_not_const_annotate_no_err():
     def kernel(N: int = 1):
         pass
 
-    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={'N': 'i32'}, constants={}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={'N': 'i32'}, constexprs={}))
 
 
 @triton.jit
@@ -186,14 +186,14 @@ def kernel1(N: tl.constexpr):
         a = returns_branched_on_constexpr(N)
         a + tl.arange(0, 4)
 
-    triton.compile(triton.compiler.ASTSource(fn=kernel1, signature={}, constants={"N": 0}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel1, signature={"N": "constexpr"}, constexprs={"N": 0}))
 
     @triton.jit
     def kernel2(N: tl.constexpr):
         a = returns_branched_on_constexpr(N)
         a + tl.arange(0, 8)
 
-    triton.compile(triton.compiler.ASTSource(fn=kernel2, signature={}, constants={"N": 1}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel2, signature={"N": "constexpr"}, constexprs={"N": 1}))
 
 
 @triton.jit
@@ -211,7 +211,7 @@ def kernel(N: int):
         returns_branched_on_non_constexpr(N)
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={'N': 'i32'}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={'N': 'i32'}, constexprs={}))
 
     try:
         assert "at 2:4:" in str(e.value), "error should point to the function call"
@@ -227,7 +227,7 @@ def kernel():
         tl.arange(2, 7)
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
     assert str(e.value.__cause__) == "arange's range must be a power of 2"
 
 
@@ -238,7 +238,7 @@ def kernel():
         tl.full((33, ), 0, dtype=tl.int64)
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
     assert str(e.value.__cause__) == "Shape element 0 must be a power of 2"
 
 
@@ -251,7 +251,7 @@ def kernel():
         a = CAPTURED  # noqa
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
     assert "CAPTURED is not defined" in str(e.value)
 
 
@@ -265,7 +265,7 @@ def kernel():
         a = GLOBAL  # noqa
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
     assert "global variable" in str(e.value)
 
 
@@ -279,7 +279,7 @@ def kernel():
         a = CONSTEXPR_ANNOTATED_GLOBAL  # noqa
 
     # No error.
-    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
 
 CONSTEXPR_GLOBAL = tl.constexpr(42)
@@ -292,7 +292,7 @@ def kernel():
         a = CONSTEXPR_GLOBAL  # noqa
 
     # No error.
-    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
 
 TYPE_ALIAS = tl.pointer_type(tl.int32)
@@ -305,7 +305,7 @@ def kernel():
         a = TYPE_ALIAS  # noqa
 
     # No error.
-    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
 
 def test_global_access_in_fn_default_arg():
@@ -315,7 +315,7 @@ def kernel(a=GLOBAL):
         pass
 
     # No error.
-    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={'a': "i32"}, constants={}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={'a': "i32"}, constexprs={}))
 
 
 def test_defaults_assign_no_err():
@@ -324,7 +324,7 @@ def test_defaults_assign_no_err():
     def kernel(a=1, B: tl.constexpr = ""):
         pass
 
-    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={'a': 'i32'}, constants={'B': ""}))
+    triton.compile(triton.compiler.ASTSource(fn=kernel, signature={'a': 'i32', 'B': 'constexpr'}, constexprs={'B': ""}))
 
 
 def test_where_warning(fresh_triton_cache):
@@ -337,7 +337,7 @@ def kernel():
         tl.where(a, b, c)
 
     with pytest.warns(UserWarning):
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
 
 
 @pytest.mark.parametrize("dtype", [tl.float8e5, tl.float8e5b16, tl.float8e4nv, tl.float8e4b8, tl.float8e4b15])
@@ -371,7 +371,8 @@ def dtype_kernel(dtype: tl.constexpr):
         ctx = pytest.raises(CompilationError, match="")
 
     with ctx as e:
-        triton.compile(triton.compiler.ASTSource(fn=dtype_kernel, signature={}, constants={"dtype": dtype}))
+        triton.compile(
+            triton.compiler.ASTSource(fn=dtype_kernel, signature={"dtype": "constexpr"}, constexprs={"dtype": dtype}))
 
     if dtype not in supported_dtypes:
         try:
@@ -426,7 +427,7 @@ def dot_kernel():
         tl.dot(a, b, max_num_imprecise_acc=128)
 
     with pytest.raises(CompilationError) as e:
-        triton.compile(triton.compiler.ASTSource(fn=dot_kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=dot_kernel, signature={}, constexprs={}))
     try:
         assert (str(e.value.__cause__) == "max_num_imprecise_acc (128) must be <= K (64)")
     except AssertionError as assertion_err:

python/test/unit/language/test_core.py

@@ -4494,15 +4494,17 @@ def kernel(x):
 def test_value_specialization(value: int, value_type: str, device) -> None:
 
     def repr(specialization):
-        spec_type = specialization.signature["VALUE"]
-        return f"kernel_{spec_type}"
+        ty = specialization.signature["value1"]
+        cst = '_'.join([k for k, v in specialization.constants.items() if v == 1])
+        return f"kernel_{ty}_{cst}"
 
     @triton.jit(repr=repr)
-    def kernel(VALUE, X):
+    def kernel(value1, is_one, X):
         pass
 
     x = torch.tensor([3.14159], device=device)
-    h = kernel[(1, )](value, x)
+    h = kernel[(1, )](value, 1, x)
+    assert "is_one" in h.name
     assert value_type in h.name
 
 
@@ -6346,6 +6348,19 @@ def sanitize_sum_2d_kernel(Z, X, BLOCK_0: tl.constexpr, BLOCK_1: tl.constexpr, r
     torch.testing.assert_close(Z, X.sum(reduce_dim).to(torch.int32))
 
 
+def test_dtype(device):
+
+    @triton.jit
+    def kernel(X):
+        dtype_x: tl.constexpr = X.dtype.element_ty
+        tl.static_assert(dtype_x == tl.int32)
+        tl.static_assert(dtype_x == tl.constexpr(tl.int32))
+        tl.static_assert(dtype_x == tl.int8 or (dtype_x == tl.int16 or dtype_x == tl.int32))
+
+    X = torch.zeros(1, dtype=torch.int32, device=device)
+    kernel[(1, )](X)
+
+
 def test_side_effectful_scan(device):
     if device != "cuda":
         pytest.xfail()

python/test/unit/language/test_decorator.py

@@ -23,7 +23,7 @@ def kernel():
         pass
 
     try:
-        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constants={}))
+        triton.compile(triton.compiler.ASTSource(fn=kernel, signature={}, constexprs={}))
     except Exception as e:
         pytest.fail(f"triton compile failed with error: {e}")
 

python/test/unit/language/test_tuple.py

@@ -0,0 +1,100 @@
+import pytest
+import triton
+import triton.language as tl
+import torch
+
+
+@triton.jit
+def _tuple_increment(values):
+    for i in tl.static_range(len(values)):
+        values[i] = values[i] + 1
+    return values
+
+
+@triton.jit
+def _tuple_index_func(Ptrs, values):
+    for i in tl.static_range(len(values)):
+        tl.store(Ptrs[i], values[i])
+
+
+@triton.jit
+def _tuple_index(_0, Ptrs, _1: tl.constexpr, values, _2, _3: tl.constexpr, _4):
+    values = _tuple_increment(values)
+    _tuple_index_func(Ptrs, values)
+
+
+@pytest.mark.parametrize("size", [0, 1, 2, 3, 4])
+def test_index(size, device="xpu"):
+    vals = tuple([i + 1 for i in range(size)])
+    rets = tuple([torch.zeros((1, ), dtype=torch.float32, device=device) for _ in vals])
+    _tuple_index[(1, )](0, rets, 0, vals, 0, 0, 0)
+    assert vals == tuple([x.item() - 1 for x in rets])
+
+
+# ----
+
+
+@triton.jit
+def _tuple_assign(XPtrs, YPtrs, values):
+    # assign from tuple
+    X0, X1 = XPtrs
+    x0, x1 = values
+    tl.store(X0, x0)
+    tl.store(X1, x1)
+    # assign to tuple
+    Y0, Y1, Y2 = YPtrs
+    Y = Y0, Y1, Y2
+    y = x0, 10, x1
+    tl.store(Y[0], y[0])
+    tl.store(Y[1], y[1])
+    tl.store(Y[2], y[2])
+
+
+def test_assign(device="xpu"):
+    vals = (2., 3.)
+    x = tuple([torch.zeros((1, ), dtype=torch.float32, device=device) for _ in range(2)])
+    y = tuple([torch.zeros((1, ), dtype=torch.float32, device=device) for _ in range(3)])
+    _tuple_assign[(1, )](x, y, vals)
+    assert x[0] == vals[0]
+    assert x[1] == vals[1]
+    assert y[0] == vals[0]
+    assert y[1] == 10
+    assert y[2] == vals[1]
+
+
+# -------
+
+
+@triton.jit
+def _tuple_fn0(Ptr, cst2: tl.constexpr, tuple1):
+    tl.static_assert(tuple1[1] is None)
+    tl.store(Ptr + 5, cst2)
+    tl.store(Ptr + 6, tuple1[0])
+    tl.store(Ptr + 7, tl.load(tuple1[2][0]))
+    tl.store(Ptr + 8, tuple1[2][1][0])
+    tl.store(Ptr + 9, tl.load(tuple1[2][1][2]))
+
+
+# test serialization/deserialization of tuple arguments in
+# the frontend.
+@triton.jit
+def _tuple_serialize(Ptr, N1, tuple1, cst1: tl.constexpr, val1, tuple2):
+    tl.static_assert(N1 is None)
+    tl.static_assert(tuple1[1][1] is None)
+    tl.store(Ptr + 0, tl.load(tuple1[0]))
+    tl.store(Ptr + 1, tuple1[1][0])
+    tl.store(Ptr + 2, tl.load(tuple1[1][2]))
+    tl.store(Ptr + 3, cst1 + val1)
+    tl.store(Ptr + 4, tl.load(tuple2[0]))
+    _tuple_fn0(Ptr, 15, (-1, None, tuple1))
+
+
+def test_serialize(device="xpu"):
+    x0 = torch.tensor([8], dtype=torch.int32, device=device)
+    x1 = torch.tensor([12], dtype=torch.int32, device=device)
+    y0 = torch.tensor([10], dtype=torch.int32, device=device)
+    z = torch.empty((10, ), dtype=torch.int32, device=device)
+    # we want to check that JIT specialization propagates to tuples:
+    _tuple_serialize[(1, )](z, None, (x0, (1, None, x1)), 20, 1, (y0, ))
+    ref = torch.tensor([8, 1, 12, 21, 10, 15, -1, 8, 1, 12], device=device)
+    assert torch.equal(z, ref)