Fix contraction matching bug, add tests

Signed-off-by: Max Dawkins <[email protected]>

Author: Max191

tuner/tuner/dispatch_parser.py

@@ -117,17 +117,20 @@ def get_shapes(self, template: list[str]) -> ProblemSize:
             assert False, f"contraction op not found"
         cdims = matcher.contraction_dimensions
         assert cdims, "no contraction dimensions"
+        assert len(cdims.batch) <= 1, f"must have at most 1 batch dimension"
         assert len(cdims.m) == 1, f"must have a single m dimension"
         assert len(cdims.n) == 1, f"must have a single n dimension"
         assert len(cdims.k) == 1, f"must have a single k dimension"
         lhs_type = ir.RankedTensorType(contraction_op.operands[0].type)
         rhs_type = ir.RankedTensorType(contraction_op.operands[1].type)
         res_type = ir.RankedTensorType(contraction_op.operands[2].type)
         matmul_size = MatmulSize(
-            lhs_type.shape[0],
-            rhs_type.shape[0],
-            lhs_type.shape[1],
+            lhs_type.shape[matcher.lhs_dims.index(cdims.m[0])],
+            rhs_type.shape[matcher.rhs_dims.index(cdims.n[0])],
+            lhs_type.shape[matcher.lhs_dims.index(cdims.k[0])],
         )
+        if len(cdims.batch) == 1:
+            matmul_size.B = lhs_type.shape[matcher.lhs_dims.index(cdims.batch[0])]
         return ProblemSize(
             matmul_size,
             lhs_type=ShapedType(lhs_type.shape, lhs_type.element_type),

tuner/tuner/dispatch_parser_test.py

@@ -41,38 +41,82 @@ def test_parse_tensor_type(tuner_ctx: common.TunerContext) -> None:
     )
 
 
+CONTRACTION_TEMPLATE = r"""
+builtin.module{{
+    func.func @test(%arg0: {lhs_type}, %arg1: {rhs_type}) -> {res_type} {{
+        %cst = arith.constant 0.000000e+00 : f32
+        %0 = tensor.empty() : {res_type}
+        %1 = linalg.fill ins(%cst : f32) outs(%0 : {res_type}) -> {res_type}
+        %2 = linalg.generic {{
+            indexing_maps = [
+                {lhs_map},
+                {rhs_map},
+                {res_map}],
+            iterator_types = {iterator_types}}}
+            {{root_op}}
+            ins(%arg0, %arg1 : {lhs_type}, {rhs_type})
+            outs(%1 : {res_type}) {{
+        ^bb0(%in: f16, %in_0: f16, %out: f32):
+            %3 = arith.extf %in : f16 to f32
+            %4 = arith.extf %in_0 : f16 to f32
+            %5 = arith.mulf %3, %4 : f32
+            %6 = arith.addf %out, %5 : f32
+            linalg.yield %6 : f32
+        }} -> {res_type}
+        return %2 : {res_type}
+    }}
+}}"""
+
+
 def test_get_contraction_operation(tuner_ctx: common.TunerContext) -> None:
     context = tuner_ctx.mlir_ctx
-    module_str = """
-        builtin.module{
-            func.func @test(%arg0: tensor<4x4xf16>, %arg1: tensor<4x4xf16>) -> tensor<4x4xf32> {
-                %cst = arith.constant 0.000000e+00 : f32
-                %0 = tensor.empty() : tensor<4x4xf32>
-                %1 = linalg.fill ins(%cst : f32) outs(%0 : tensor<4x4xf32>) -> tensor<4x4xf32>
-                %2 = linalg.generic {
-                    indexing_maps = [
-                        affine_map<(d0, d1, d2) -> (d0, d2)>,
-                        affine_map<(d0, d1, d2) -> (d1, d2)>,
-                        affine_map<(d0, d1, d2) -> (d0, d1)>],
-                    iterator_types = ["parallel", "parallel", "reduction"]}
-                    {root_op}
-                    ins(%arg0, %arg1 : tensor<4x4xf16>, tensor<4x4xf16>)
-                    outs(%1 : tensor<4x4xf32>) {
-                ^bb0(%in: f16, %in_0: f16, %out: f32):
-                    %3 = arith.extf %in : f16 to f32
-                    %4 = arith.extf %in_0 : f16 to f32
-                    %5 = arith.mulf %3, %4 : f32
-                    %6 = arith.addf %out, %5 : f32
-                    linalg.yield %6 : f32
-                } -> tensor<4x4xf32>
-                return %2 : tensor<4x4xf32>
-            }
-        }"""
-    module = ir.Module.parse(module_str, context)
+
+    with ir.Location.unknown():
+        transpose_b_str = CONTRACTION_TEMPLATE.format(
+            lhs_type=ir.RankedTensorType.get([16, 64], ir.F16Type.get()),
+            rhs_type=ir.RankedTensorType.get([32, 64], ir.F16Type.get()),
+            res_type=ir.RankedTensorType.get([16, 32], ir.F32Type.get()),
+            lhs_map="affine_map<(d0, d1, d2) -> (d0, d2)>",
+            rhs_map="affine_map<(d0, d1, d2) -> (d1, d2)>",
+            res_map="affine_map<(d0, d1, d2) -> (d0, d1)>",
+            iterator_types='["parallel", "parallel", "reduction"]',
+        )
+    module = ir.Module.parse(transpose_b_str, context)
     parser = dispatch_parser.ContractionOpInterfaceParser()
     mmt_op = parser.get_contraction_operation(module)
     assert mmt_op is not None
     assert isinstance(mmt_op.opview, linalg.GenericOp)
+    shapes: common.ProblemSize = parser.get_shapes(transpose_b_str.splitlines())
+    assert shapes.matmul_size.B == 1
+    assert shapes.matmul_size.M == 16
+    assert shapes.matmul_size.N == 32
+    assert shapes.matmul_size.K == 64
+    assert shapes.lhs_type.shape == [16, 64]
+    assert isinstance(shapes.lhs_type.element_type, ir.F16Type)
+    assert shapes.rhs_type.shape == [32, 64]
+    assert isinstance(shapes.rhs_type.element_type, ir.F16Type)
+    assert shapes.res_type.shape == [16, 32]
+    assert isinstance(shapes.res_type.element_type, ir.F32Type)
+
+    with ir.Location.unknown():
+        bmm_transposed_inputs_str = CONTRACTION_TEMPLATE.format(
+            lhs_type=ir.RankedTensorType.get([5, 8, 128], ir.F16Type.get()),
+            rhs_type=ir.RankedTensorType.get([128, 40, 5], ir.F16Type.get()),
+            res_type=ir.RankedTensorType.get([5, 40, 8], ir.F32Type.get()),
+            lhs_map="affine_map<(d0, d1, d2, d3) -> (d0, d1, d3)>",
+            rhs_map="affine_map<(d0, d1, d2, d3) -> (d3, d2, d0)>",
+            res_map="affine_map<(d0, d1, d2, d3) -> (d0, d2, d1)>",
+            iterator_types='["parallel", "parallel", "parallel", "reduction"]',
+        )
+    module = ir.Module.parse(bmm_transposed_inputs_str, context)
+    mmt_op = parser.get_contraction_operation(module)
+    shapes: common.ProblemSize = parser.get_shapes(
+        bmm_transposed_inputs_str.splitlines()
+    )
+    assert shapes.matmul_size.B == 5
+    assert shapes.matmul_size.M == 8
+    assert shapes.matmul_size.N == 40
+    assert shapes.matmul_size.K == 128
 
 
 def test_get_conv_operation(tuner_ctx: common.TunerContext) -> None:

tuner/tuner/op_matchers.py

@@ -125,6 +125,9 @@ class ContractionOpInterfaceMatcher(GenericOpMatcher):
     def __init__(self):
         super().__init__()
         self.contraction_dimensions: Optional[ContractionDimensions] = None
+        self.lhs_dims: Optional[list[int]] = None
+        self.rhs_dims: Optional[list[int]] = None
+        self.res_dims: Optional[list[int]] = None
 
     def match_operands(self, operands: ir.OpOperandList) -> bool:
         if len(operands) != 3:
@@ -169,4 +172,7 @@ def match_indexing_maps(self, maps: list[ir.AffineMap]) -> bool:
             n=n_dims,
             k=k_dims,
         )
+        self.lhs_dims = lhs_dims
+        self.rhs_dims = rhs_dims
+        self.res_dims = res_dims
         return True