e9085d0d25
The revision renames the following OpDSL functions: ``` TypeFn.cast -> TypeFn.cast_signed BinaryFn.min -> BinaryFn.min_signed BinaryFn.max -> BinaryFn.max_signed ``` The corresponding enum values on the C++ side are renamed accordingly: ``` #linalg.type_fn<cast> -> #linalg.type_fn<cast_signed> #linalg.binary_fn<min> -> #linalg.binary_fn<min_signed> #linalg.binary_fn<max> -> #linalg.binary_fn<max_signed> ``` Depends On D120110 Reviewed By: aartbik Differential Revision: https://reviews.llvm.org/D120562
115 lines
3.4 KiB
Python
115 lines
3.4 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: assignments:
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# CHECK: -
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# CHECK: arg: C
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# CHECK: value:
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# CHECK: scalar_fn:
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# CHECK: kind: binary
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# CHECK: fn_name: add
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# CHECK: operands:
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# CHECK: scalar_fn:
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# CHECK: kind: binary
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# CHECK: attr_name: mul
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# CHECK: operands:
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# CHECK: scalar_fn:
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# CHECK: kind: type
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# CHECK: attr_name: cast
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# CHECK: type_var: U
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# CHECK: operands:
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# CHECK: scalar_arg: A
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# CHECK: scalar_fn:
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# CHECK: kind: type
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# CHECK: attr_name: cast
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# CHECK: type_var: U
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# CHECK: operands:
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# CHECK: scalar_arg: B
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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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mul=BinaryFnAttrDef(default=BinaryFn.mul),
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cast=TypeFnAttrDef(default=TypeFn.cast_signed)):
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C[D.m, D.n] += mul(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: constants
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# CHECK: assignments:
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# CHECK: -
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# CHECK: arg: O
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# CHECK: scalar_fn:
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# CHECK: kind: binary
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# CHECK: fn_name: sub
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# CHECK: operands:
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# CHECK: scalar_fn:
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# CHECK: kind: binary
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# CHECK: fn_name: add
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# CHECK: operands:
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# CHECK: scalar_fn:
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# CHECK: kind: unary
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# CHECK: fn_name: exp
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# CHECK: operands:
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# CHECK: scalar_fn:
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# CHECK: kind: type
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# CHECK: type_var: T
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# CHECK: operands:
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# CHECK: scalar_const: '3.1415926535897931 : f64'
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# CHECK: scalar_fn:
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# CHECK: kind: type
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# CHECK: fn_name: cast_signed
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# CHECK: type_var: T
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# CHECK: operands:
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# CHECK: scalar_const: '42 : i64'
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# CHECK: scalar_fn:
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# CHECK: kind: type
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# CHECK: fn_name: cast_signed
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# CHECK: type_var: T
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# CHECK: operands:
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# CHECK: scalar_fn:
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# CHECK: kind: unary
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# CHECK: attr_name: exp
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# CHECK: operands:
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# CHECK: scalar_const: '1.{{[0]*}}e+03 : f64'
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@linalg_structured_op
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def constants(
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O=TensorDef(T, S.M, S.K, output=True),
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exp=UnaryFnAttrDef(default=UnaryFn.exp)):
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pi = TypeFn.cast_signed(T, const(3.1415926535897931))
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cst42 = TypeFn.cast_signed(T, const(42))
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cst1000 = TypeFn.cast_signed(T, exp(const(1e+3)))
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O[D.m, D.n] = UnaryFn.exp(pi) + cst42 - cst1000
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# CHECK: ---
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# CHECK-LABEL: indices
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# CHECK: assignments:
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# CHECK: -
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# CHECK: arg: O
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# CHECK: scalar_fn:
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# CHECK: kind: binary
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# CHECK: fn_name: add
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# CHECK: operands:
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# CHECK: scalar_index: 1
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# CHECK: scalar_index: 0
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@linalg_structured_op
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def indices(O=TensorDef(T, S.M, S.K, output=True)):
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O[D.m, D.n] = index(D.n) + index(D.m)
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# CHECK: ---
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# CHECK-LABEL: fill
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# CHECK: assignments:
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# CHECK: -
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# CHECK: arg: O
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# CHECK: scalar_arg: value
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@linalg_structured_op
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def fill(value=ScalarDef(T), O=TensorDef(T, S.M, S.K, output=True)):
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O[D.m, D.n] = value
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