d50571ab07
Index attributes had no default value, which means the attribute values had to be set on the operation. This revision adds a default parameter to `IndexAttrDef`. After the change, every index attribute has to define a default value. For example, we may define the following strides attribute: ``` ``` When using the operation the default stride is used if the strides attribute is not set. The mechanism is implemented using `DefaultValuedAttr`. Additionally, the revision uses the naming index attribute instead of attribute more consistently, which is a preparation for follow up revisions that will introduce function attributes. Depends On D119125 Reviewed By: stellaraccident Differential Revision: https://reviews.llvm.org/D119126
64 lines
1.8 KiB
Python
64 lines
1.8 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: type_var: T
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# CHECK: shape_map: affine_map<()[s0, s1, s2] -> (s0, s1)>
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# CHECK: name: B
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# CHECK: usage: Input
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# CHECK: type_var: T
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# CHECK: shape_map: affine_map<()[s0, s1, s2] -> (s1, s2)>
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# CHECK: name: C
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# CHECK: usage: Output
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# CHECK: type_var: U
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# CHECK: shape_map: affine_map<()[s0, s1, s2] -> (s0, s2)>
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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] += TypeFn.cast(U, A[D.m, D.k]) * TypeFn.cast(U, B[D.k, D.n])
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# CHECK: ---
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# CHECK-LABEL: fill
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# CHECK: args:
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# CHECK: name: value
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# CHECK: usage: Input
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# CHECK-NOT: shape_map:
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# CHECK: type_var: T
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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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# CHECK: ---
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# CHECK-LABEL: strided_copy
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# CHECK: args:
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# CHECK: name: I
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# CHECK: usage: Input
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# CHECK: type_var: T
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# CHECK: shape_map: affine_map<()[s0, s1, s2, s3, s4, s5] -> (s0, s1)>
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# CHECK: name: O
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# CHECK: usage: Output
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# CHECK: type_var: T
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# CHECK: shape_map: affine_map<()[s0, s1, s2, s3, s4, s5] -> (s2, s3)>
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# CHECK: name: strides
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# CHECK: usage: IndexAttr
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# CHECK: index_attr_map: affine_map<()[s0, s1, s2, s3, s4, s5] -> (s4, s5)>
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# CHECK: default_vals:
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# CHECK: - 1
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# CHECK: - 2
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@linalg_structured_op
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def strided_copy(
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I=TensorDef(T, S.IH, S.IW),
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O=TensorDef(T, S.OH, S.OW, output=True),
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strides=IndexAttrDef(S.SH, S.SW, default=[1, 2])):
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O[D.oh, D.ow] = I[D.oh * S.SH, D.ow * S.SW]
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