9a2769db80
The patch extends the yaml code generation to support the following new OpDSL constructs: - captures - constants - iteration index accesses - predefined types These changes have been introduced by revision https://reviews.llvm.org/D101364. Differential Revision: https://reviews.llvm.org/D102075
38 lines
1.0 KiB
Python
38 lines
1.0 KiB
Python
# RUN: %PYTHON -m mlir.dialects.linalg.opdsl.dump_oplib --file %s | FileCheck %s
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from mlir.dialects.linalg.opdsl.lang import *
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# CHECK: ---
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# CHECK-LABEL: matmul
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# CHECK: args:
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# CHECK: name: A
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# CHECK: usage: input
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# CHECK: shape: affine_map<()[s0, s1, s2] -> (s0, s2)>
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# CHECK: element_type_var: T
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# CHECK: name: B
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# CHECK: usage: input
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# CHECK: shape: affine_map<()[s0, s1, s2] -> (s2, s1)>
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# CHECK: element_type_var: T
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# CHECK: name: C
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# CHECK: usage: output
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# CHECK: shape: affine_map<()[s0, s1, s2] -> (s0, s1)>
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# CHECK: element_type_var: U
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@linalg_structured_op
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def matmul(
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A=TensorDef(T, S.M, S.K),
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B=TensorDef(T, S.K, S.N),
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C=TensorDef(U, S.M, S.N, output=True)):
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C[D.m, D.n] += cast(U, A[D.m, D.k]) * cast(U, B[D.k, D.n])
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# CHECK: ---
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# CHECK-LABEL: fill
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# CHECK: captures:
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# CHECK: - !<LinalgCaptureDef>
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# CHECK: name: value
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# CHECK: type_var: T
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@linalg_structured_op
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def fill(O=TensorDef(T, S.M, S.K, output=True), value=CaptureDef(T)):
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O[D.m, D.n] = value
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