derek.holloway
7502bf64a4
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187 lines
7.8 KiB
MLIR
187 lines
7.8 KiB
MLIR
// RUN: mlir-opt %s -linalg-morph-ops=named-to-generic -split-input-file | \
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// RUN: FileCheck %s --check-prefix=ALL,NAMED_TO_GENERIC
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// RUN: mlir-opt %s -linalg-morph-ops=named-to-generic -split-input-file | \
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// RUN: mlir-opt -linalg-morph-ops=generic-to-named -split-input-file | \
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// RUN: FileCheck %s --check-prefix=ALL,ROUND_TRIP
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func.func @unary_ops(%A : tensor<16x8xf32>, %B : tensor<16x8xf32>) -> tensor<16x8xf32> {
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%exp = linalg.exp ins(%A : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%log = linalg.log ins(%exp : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%abs = linalg.abs ins(%log : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%ceil = linalg.ceil ins(%abs : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%floor = linalg.floor ins(%ceil : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%negf = linalg.negf ins(%floor : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%recip = linalg.reciprocal ins(%negf : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%round = linalg.round ins(%recip : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%sqrt = linalg.sqrt ins(%round : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%rsqrt = linalg.rsqrt ins(%sqrt : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%square = linalg.square ins(%rsqrt : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%tanh = linalg.tanh ins(%square : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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%erf = linalg.erf ins(%tanh : tensor<16x8xf32>) outs(%B : tensor<16x8xf32>) -> tensor<16x8xf32>
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return %erf : tensor<16x8xf32>
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}
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// ALL-LABEL: unary_ops
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// NAMED_TO_GENERIC-COUNT-13: linalg.generic
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// NAMED_TO_GENERIC-NOT: linalg.exp
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// NAMED_TO_GENERIC-NOT: linalg.log
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// NAMED_TO_GENERIC-NOT: linalg.abs
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// NAMED_TO_GENERIC-NOT: linalg.ceil
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// NAMED_TO_GENERIC-NOT: linalg.floor
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// NAMED_TO_GENERIC-NOT: linalg.negf
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// NAMED_TO_GENERIC-NOT: linalg.reciprocal
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// NAMED_TO_GENERIC-NOT: linalg.round
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// NAMED_TO_GENERIC-NOT: linalg.sqrt
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// NAMED_TO_GENERIC-NOT: linalg.rsqrt
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// NAMED_TO_GENERIC-NOT: linalg.square
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// NAMED_TO_GENERIC-NOT: linalg.tanh
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// NAMED_TO_GENERIC-NOT: linalg.erf
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// ROUND_TRIP: linalg.exp
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// ROUND_TRIP: linalg.log
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// ROUND_TRIP: linalg.abs
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// ROUND_TRIP: linalg.ceil
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// ROUND_TRIP: linalg.floor
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// ROUND_TRIP: linalg.negf
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// ROUND_TRIP: linalg.reciprocal
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// ROUND_TRIP: linalg.round
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// ROUND_TRIP: linalg.sqrt
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// ROUND_TRIP: linalg.rsqrt
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// ROUND_TRIP: linalg.square
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// ROUND_TRIP: linalg.tanh
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// ROUND_TRIP: linalg.erf
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// ROUND_TRIP-NOT: linalg.generic
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// -----
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func.func @binary_ops_int(%A: tensor<?x?xi32>, %B: tensor<?x?xi32>,
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%Out: tensor<?x?xi32>) -> tensor<?x?xi32> {
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%0 = linalg.add ins(%A, %B : tensor<?x?xi32>, tensor<?x?xi32>)
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outs(%Out : tensor<?x?xi32>) -> tensor<?x?xi32>
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%1 = linalg.sub ins(%0, %B : tensor<?x?xi32>, tensor<?x?xi32>)
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outs(%Out : tensor<?x?xi32>) -> tensor<?x?xi32>
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%2 = linalg.mul ins(%1, %B : tensor<?x?xi32>, tensor<?x?xi32>)
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outs(%Out : tensor<?x?xi32>) -> tensor<?x?xi32>
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%3 = linalg.div ins(%2, %B : tensor<?x?xi32>, tensor<?x?xi32>)
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outs(%Out : tensor<?x?xi32>) -> tensor<?x?xi32>
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%4 = linalg.div_unsigned ins(%3, %B : tensor<?x?xi32>, tensor<?x?xi32>)
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outs(%Out : tensor<?x?xi32>) -> tensor<?x?xi32>
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%5 = linalg.max ins(%4, %B : tensor<?x?xi32>, tensor<?x?xi32>)
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outs(%Out : tensor<?x?xi32>) -> tensor<?x?xi32>
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%6 = linalg.min ins(%5, %B : tensor<?x?xi32>, tensor<?x?xi32>)
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outs(%Out : tensor<?x?xi32>) -> tensor<?x?xi32>
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return %6 : tensor<?x?xi32>
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}
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// ALL-LABEL: binary_ops_int
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// NAMED_TO_GENERIC-COUNT-7: linalg.generic
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// NAMED_TO_GENERIC-NOT: linalg.add
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// NAMED_TO_GENERIC-NOT: linalg.sub
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// NAMED_TO_GENERIC-NOT: linalg.mul
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// NAMED_TO_GENERIC-NOT: linalg.div
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// NAMED_TO_GENERIC-NOT: linalg.div_unsigned
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// NAMED_TO_GENERIC-NOT: linalg.max
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// NAMED_TO_GENERIC-NOT: linalg.min
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// ROUND_TRIP: linalg.add
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// ROUND_TRIP: linalg.sub
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// ROUND_TRIP: linalg.mul
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// ROUND_TRIP: linalg.div
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// ROUND_TRIP: linalg.div_unsigned
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// ROUND_TRIP: linalg.max
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// ROUND_TRIP: linalg.min
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// ROUND_TRIP-NOT: linalg.generic
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// -----
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func.func @binary_ops_float(%A: tensor<?x?xf32>, %B: tensor<?x?xf32>,
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%Out: tensor<?x?xf32>) -> tensor<?x?xf32> {
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%0 = linalg.add ins(%A, %B : tensor<?x?xf32>, tensor<?x?xf32>)
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outs(%Out : tensor<?x?xf32>) -> tensor<?x?xf32>
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%1 = linalg.sub ins(%0, %B : tensor<?x?xf32>, tensor<?x?xf32>)
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outs(%Out : tensor<?x?xf32>) -> tensor<?x?xf32>
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%2 = linalg.mul ins(%1, %B : tensor<?x?xf32>, tensor<?x?xf32>)
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outs(%Out : tensor<?x?xf32>) -> tensor<?x?xf32>
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%3 = linalg.div ins(%2, %B : tensor<?x?xf32>, tensor<?x?xf32>)
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outs(%Out : tensor<?x?xf32>) -> tensor<?x?xf32>
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%4 = linalg.max ins(%3, %B : tensor<?x?xf32>, tensor<?x?xf32>)
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outs(%Out : tensor<?x?xf32>) -> tensor<?x?xf32>
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%5 = linalg.min ins(%4, %B : tensor<?x?xf32>, tensor<?x?xf32>)
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outs(%Out : tensor<?x?xf32>) -> tensor<?x?xf32>
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%6 = linalg.powf ins(%5, %B : tensor<?x?xf32>, tensor<?x?xf32>)
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outs(%Out : tensor<?x?xf32>) -> tensor<?x?xf32>
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return %6 : tensor<?x?xf32>
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}
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// ALL-LABEL: binary_ops_float
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// NAMED_TO_GENERIC-COUNT-7: linalg.generic
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// NAMED_TO_GENERIC-NOT: linalg.add
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// NAMED_TO_GENERIC-NOT: linalg.sub
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// NAMED_TO_GENERIC-NOT: linalg.mul
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// NAMED_TO_GENERIC-NOT: linalg.div
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// NAMED_TO_GENERIC-NOT: linalg.max
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// NAMED_TO_GENERIC-NOT: linalg.min
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// NAMED_TO_GENERIC-NOT: linalg.powf
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// ROUND_TRIP: linalg.add
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// ROUND_TRIP: linalg.sub
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// ROUND_TRIP: linalg.mul
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// ROUND_TRIP: linalg.div
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// ROUND_TRIP: linalg.max
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// ROUND_TRIP: linalg.min
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// ROUND_TRIP: linalg.powf
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// ROUND_TRIP-NOT: linalg.generic
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// -----
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func.func @binary_ops_complex(%A: tensor<?x?xcomplex<f32>>, %B: tensor<?x?xcomplex<f32>>,
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%Out: tensor<?x?xcomplex<f32>>) -> tensor<?x?xcomplex<f32>> {
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%0 = linalg.add ins(%A, %B : tensor<?x?xcomplex<f32>>, tensor<?x?xcomplex<f32>>)
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outs(%Out : tensor<?x?xcomplex<f32>>) -> tensor<?x?xcomplex<f32>>
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%1 = linalg.sub ins(%0, %B : tensor<?x?xcomplex<f32>>, tensor<?x?xcomplex<f32>>)
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outs(%Out : tensor<?x?xcomplex<f32>>) -> tensor<?x?xcomplex<f32>>
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%2 = linalg.mul ins(%1, %B : tensor<?x?xcomplex<f32>>, tensor<?x?xcomplex<f32>>)
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outs(%Out : tensor<?x?xcomplex<f32>>) -> tensor<?x?xcomplex<f32>>
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%3 = linalg.div ins(%2, %B : tensor<?x?xcomplex<f32>>, tensor<?x?xcomplex<f32>>)
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outs(%Out : tensor<?x?xcomplex<f32>>) -> tensor<?x?xcomplex<f32>>
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return %3 : tensor<?x?xcomplex<f32>>
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}
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// ALL-LABEL: binary_ops_complex
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// NAMED_TO_GENERIC-COUNT-4: linalg.generic
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// NAMED_TO_GENERIC-NOT: linalg.add
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// NAMED_TO_GENERIC-NOT: linalg.sub
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// NAMED_TO_GENERIC-NOT: linalg.mul
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// NAMED_TO_GENERIC-NOT: linalg.div
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// ROUND_TRIP: linalg.add
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// ROUND_TRIP: linalg.sub
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// ROUND_TRIP: linalg.mul
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// ROUND_TRIP: linalg.div
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// ROUND_TRIP-NOT: linalg.generic
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// -----
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func.func @binary_ops_bool(%A: tensor<?x?xi1>, %B: tensor<?x?xi1>,
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%Out: tensor<?x?xi1>) -> tensor<?x?xi1> {
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%0 = linalg.add ins(%A, %B : tensor<?x?xi1>, tensor<?x?xi1>)
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outs(%Out : tensor<?x?xi1>) -> tensor<?x?xi1>
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%1 = linalg.mul ins(%0, %B : tensor<?x?xi1>, tensor<?x?xi1>)
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outs(%Out : tensor<?x?xi1>) -> tensor<?x?xi1>
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return %1 : tensor<?x?xi1>
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}
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// ALL-LABEL: binary_ops_bool
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// NAMED_TO_GENERIC-COUNT-2: linalg.generic
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// NAMED_TO_GENERIC-NOT: linalg.add
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// NAMED_TO_GENERIC-NOT: linalg.mul
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// ROUND_TRIP: linalg.add
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// ROUND_TRIP: linalg.mul
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// ROUND_TRIP-NOT: linalg.generic
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