Extend lowering from hlo to lhlo to also support buffer allocation with escaping result buffers. This is now a flag to the pass (defaults to the current preallocation behavior).
PiperOrigin-RevId: 316660810 Change-Id: I89e46b494d09acf2dbe14b300ee5b9df431ab09c
This commit is contained in:
Stephan Herhut
TensorFlower Gardener
parent
a5ebf37c1d
commit
fb7fe20ec7
@ -1,12 +1,13 @@
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// RUN: xla-opt -hlo-legalize-to-lhlo -buffer-placement -split-input-file %s -o - | FileCheck %s
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// RUN: xla-opt -hlo-legalize-to-lhlo -buffer-placement -split-input-file %s -o - | FileCheck --check-prefixes=PRE,BOTH %s
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// RUN: xla-opt -hlo-legalize-to-lhlo=results-escape-function=true -buffer-placement -split-input-file %s -o - | FileCheck --check-prefixes=ESC,BOTH %s
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// CHECK-LABEL: func @attrs
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// BOTH-LABEL: func @attrs
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func @attrs_copy(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
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%tensor_operand = tensor_load %operand : memref<2x2xf32>
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%tensor_result = "xla_hlo.exponential"(%tensor_operand)
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{some_attr_1 = "exp.1", some_attr_2 = dense<1> : tensor<1xi64>}
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: (tensor<2x2xf32>) -> tensor<2x2xf32>
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// CHECK: "xla_lhlo.exponential"(%{{.*}}, %{{.*}}) {some_attr_1 = "exp.1", some_attr_2 = dense<1> : tensor<1xi64>}
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// BOTH: "xla_lhlo.exponential"(%{{.*}}, %{{.*}}) {some_attr_1 = "exp.1", some_attr_2 = dense<1> : tensor<1xi64>}
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tensor_store %tensor_result, %result : memref<2x2xf32>
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return
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}
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@ -16,13 +17,16 @@ func @attrs_copy(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
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func @return_func(%arg0: tensor<4xf32>) -> tensor<4xf32> {
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return %arg0 : tensor<4xf32>
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}
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// CHECK: (%[[ARG0:.*]]: [[TYPE:.*]], %[[RESULT:.*]]: [[TYPE]])
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// CHECK-NEXT: "xla_lhlo.copy"(%[[ARG0]], %[[RESULT]]) : ([[TYPE]], [[TYPE]]) -> ()
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// CHECK-NEXT: return
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// PRE: (%[[ARG0:.*]]: [[TYPE:.*]], %[[RESULT:.*]]: [[TYPE]])
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// PRE-NEXT: "xla_lhlo.copy"(%[[ARG0]], %[[RESULT]]) : ([[TYPE]], [[TYPE]]) -> ()
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// PRE-NEXT: return
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// ESC: (%[[ARG0:.*]]: [[TYPE:.*]]) -> [[TYPE]]
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// ESC-NOT: "xla_lhlo.copy"
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// ESC-NEXT: return %[[ARG0]]
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// -----
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// CHECK-LABEL: func @func_op_long
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// BOTH-LABEL: func @func_op_long
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func @func_op_long(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>) -> tensor<4xf32> {
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%1 = xla_hlo.maximum %arg0, %arg1 : tensor<4xf32>
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%2 = xla_hlo.add %arg0, %1 : tensor<4xf32>
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@ -31,89 +35,91 @@ func @func_op_long(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>) -> tensor<4xf32>
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%5 = xla_hlo.multiply %2, %4 : tensor<4xf32>
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return %5 : tensor<4xf32>
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}
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// CHECK: (%[[NEW_ARG0:.*]]: memref<4xf32>, %[[NEW_ARG1:.*]]: memref<4xf32>, %[[RESULT:.*]]: memref<4xf32>)
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// CHECK-NEXT: %[[MAX_RESULT:.*]] = alloc() : memref<4xf32>
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// CHECK-NEXT: "xla_lhlo.maximum"(%[[NEW_ARG0]], %[[NEW_ARG1]], %[[MAX_RESULT]])
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// CHECK-NEXT: %[[ADD_RESULT:.*]] = alloc() : memref<4xf32>
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// CHECK-NEXT: "xla_lhlo.add"(%[[NEW_ARG0]], %[[MAX_RESULT]], %[[ADD_RESULT]])
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// CHECK-NEXT: dealloc %[[MAX_RESULT]] : memref<4xf32>
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// CHECK-NEXT: %[[MIN_RESULT:.*]] = alloc() : memref<4xf32>
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// CHECK-NEXT: "xla_lhlo.minimum"(%[[NEW_ARG0]], %[[NEW_ARG1]], %[[MIN_RESULT]])
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// CHECK-NEXT: %[[SUB_RESULT:.*]] = alloc() : memref<4xf32>
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// CHECK-NEXT: "xla_lhlo.subtract"(%[[NEW_ARG1]], %[[MIN_RESULT]], %[[SUB_RESULT]])
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// CHECK-NEXT: dealloc %[[MIN_RESULT]] : memref<4xf32>
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// CHECK-NEXT: %[[MUL_RESULT:.*]] = alloc() : memref<4xf32>
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// CHECK-NEXT: "xla_lhlo.multiply"(%[[ADD_RESULT]], %[[SUB_RESULT]], %[[MUL_RESULT]])
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// CHECK-NEXT: dealloc %[[SUB_RESULT]] : memref<4xf32>
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// CHECK-NEXT: dealloc %[[ADD_RESULT]] : memref<4xf32>
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// CHECK-NEXT: "xla_lhlo.copy"(%[[MUL_RESULT]], %[[RESULT]]) : (memref<4xf32>, memref<4xf32>) -> ()
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// CHECK-NEXT: dealloc %[[MUL_RESULT]] : memref<4xf32>
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// CHECK-NEXT: return
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// PRE: (%[[NEW_ARG0:.*]]: memref<4xf32>, %[[NEW_ARG1:.*]]: memref<4xf32>, %[[RESULT:.*]]: memref<4xf32>)
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// ESC: (%[[NEW_ARG0:.*]]: memref<4xf32>, %[[NEW_ARG1:.*]]: memref<4xf32>) -> memref<4xf32>
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// BOTH-NEXT: %[[MAX_RESULT:.*]] = alloc() : memref<4xf32>
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// BOTH-NEXT: "xla_lhlo.maximum"(%[[NEW_ARG0]], %[[NEW_ARG1]], %[[MAX_RESULT]])
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// BOTH-NEXT: %[[ADD_RESULT:.*]] = alloc() : memref<4xf32>
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// BOTH-NEXT: "xla_lhlo.add"(%[[NEW_ARG0]], %[[MAX_RESULT]], %[[ADD_RESULT]])
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// BOTH-NEXT: dealloc %[[MAX_RESULT]] : memref<4xf32>
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// BOTH-NEXT: %[[MIN_RESULT:.*]] = alloc() : memref<4xf32>
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// BOTH-NEXT: "xla_lhlo.minimum"(%[[NEW_ARG0]], %[[NEW_ARG1]], %[[MIN_RESULT]])
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// BOTH-NEXT: %[[SUB_RESULT:.*]] = alloc() : memref<4xf32>
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// BOTH-NEXT: "xla_lhlo.subtract"(%[[NEW_ARG1]], %[[MIN_RESULT]], %[[SUB_RESULT]])
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// BOTH-NEXT: dealloc %[[MIN_RESULT]] : memref<4xf32>
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// BOTH-NEXT: %[[MUL_RESULT:.*]] = alloc() : memref<4xf32>
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// BOTH-NEXT: "xla_lhlo.multiply"(%[[ADD_RESULT]], %[[SUB_RESULT]], %[[MUL_RESULT]])
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// BOTH-NEXT: dealloc %[[SUB_RESULT]] : memref<4xf32>
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// BOTH-NEXT: dealloc %[[ADD_RESULT]] : memref<4xf32>
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// PRE-NEXT: "xla_lhlo.copy"(%[[MUL_RESULT]], %[[RESULT]]) : (memref<4xf32>, memref<4xf32>) -> ()
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// PRE-NEXT: dealloc %[[MUL_RESULT]] : memref<4xf32>
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// PRE-NEXT: return
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// ESC-NEXT: return %[[MUL_RESULT]] : memref<4xf32>
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// -----
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// CHECK-LABEL: func @fusion
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// BOTH-LABEL: func @fusion
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func @fusion(%multiplier: memref<2x2xf32>, %summand_1: memref<2x2xf32>,
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%summand_2: memref<2x2xf32>, %result: memref<2x2xf32>) {
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// CHECK: (%{{.*}}: {{.*}}, {{.*}}: {{.*}}, {{.*}}: {{.*}}, %[[RESULT:.*]]: {{.*}})
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// CHECK-NEXT: %[[ADD_RESULT:.*]] = alloc() : memref<2x2xf32>
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// BOTH: (%{{.*}}: {{.*}}, {{.*}}: {{.*}}, {{.*}}: {{.*}}, %[[RESULT:.*]]: {{.*}})
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// BOTH-NEXT: %[[ADD_RESULT:.*]] = alloc() : memref<2x2xf32>
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%tensor_summand_1 = tensor_load %summand_1 : memref<2x2xf32>
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%tensor_summand_2 = tensor_load %summand_2 : memref<2x2xf32>
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%sum = "xla_hlo.add"(%tensor_summand_1, %tensor_summand_2)
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: (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
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// CHECK-NEXT: "xla_lhlo.add"(%{{.*}}, %{{.*}}, %[[ADD_RESULT]])
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// CHECK-NEXT: %[[MUL_RESULT:.*]] = alloc() : memref<2x2xf32>
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// BOTH-NEXT: "xla_lhlo.add"(%{{.*}}, %{{.*}}, %[[ADD_RESULT]])
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// BOTH-NEXT: %[[MUL_RESULT:.*]] = alloc() : memref<2x2xf32>
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%tensor_multiplier = tensor_load %multiplier : memref<2x2xf32>
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%tensor_result = "xla_hlo.multiply"(%sum, %tensor_multiplier)
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: (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
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// CHECK-NEXT: "xla_lhlo.multiply"(%[[ADD_RESULT]], %{{.*}}, %[[MUL_RESULT]])
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// CHECK-NEXT: dealloc %[[ADD_RESULT]] : memref<2x2xf32>
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// CHECK-NEXT: "xla_lhlo.copy"(%[[MUL_RESULT]], %[[RESULT]])
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// BOTH-NEXT: "xla_lhlo.multiply"(%[[ADD_RESULT]], %{{.*}}, %[[MUL_RESULT]])
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// BOTH-NEXT: dealloc %[[ADD_RESULT]] : memref<2x2xf32>
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// BOTH-NEXT: "xla_lhlo.copy"(%[[MUL_RESULT]], %[[RESULT]])
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tensor_store %tensor_result, %result : memref<2x2xf32>
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// CHECK-NEXT: dealloc %[[MUL_RESULT]] : memref<2x2xf32>
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// CHECK-NEXT: "xla_lhlo.terminator"() : () -> ()
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"xla_lhlo.terminator"() : () -> ()
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// BOTH-NEXT: dealloc %[[MUL_RESULT]] : memref<2x2xf32>
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// BOTH-NEXT: return
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return
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}
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// -----
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// CHECK-LABEL: func @copy
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// BOTH-LABEL: func @copy
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func @copy(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
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%tensor_operand = tensor_load %operand : memref<2x2xf32>
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%tensor_result = "xla_hlo.copy"(%tensor_operand)
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: (tensor<2x2xf32>) -> tensor<2x2xf32>
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// CHECK: "xla_lhlo.copy"(%{{.*}}, %{{.*}})
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// BOTH: "xla_lhlo.copy"(%{{.*}}, %{{.*}})
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tensor_store %tensor_result, %result : memref<2x2xf32>
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return
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}
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// -----
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// CHECK-LABEL: func @exp
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// BOTH-LABEL: func @exp
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func @exp(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
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%tensor_operand = tensor_load %operand : memref<2x2xf32>
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%tensor_result = "xla_hlo.exponential"(%tensor_operand)
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: (tensor<2x2xf32>) -> tensor<2x2xf32>
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// CHECK: "xla_lhlo.exponential"(%{{.*}}, %{{.*}})
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// BOTH: "xla_lhlo.exponential"(%{{.*}}, %{{.*}})
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tensor_store %tensor_result, %result : memref<2x2xf32>
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return
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}
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// -----
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// CHECK-LABEL: func @log
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// BOTH-LABEL: func @log
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func @log(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
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%tensor_operand = tensor_load %operand : memref<2x2xf32>
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%tensor_result = "xla_hlo.log"(%tensor_operand)
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: (tensor<2x2xf32>) -> tensor<2x2xf32>
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// CHECK: "xla_lhlo.log"(%{{.*}}, %{{.*}})
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// BOTH: "xla_lhlo.log"(%{{.*}}, %{{.*}})
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tensor_store %tensor_result, %result : memref<2x2xf32>
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return
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}
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// -----
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// CHECK-LABEL: func @select
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// BOTH-LABEL: func @select
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func @select(%pred: memref<2x2xi1>, %lhs: memref<2x2xf32>,
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%rhs: memref<2x2xf32>, %result: memref<2x2xf32>) {
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%tensor_pred = tensor_load %pred : memref<2x2xi1>
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@ -121,34 +127,34 @@ func @select(%pred: memref<2x2xi1>, %lhs: memref<2x2xf32>,
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%tensor_rhs = tensor_load %rhs : memref<2x2xf32>
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%tensor_result = "xla_hlo.select"(%tensor_pred, %tensor_lhs, %tensor_rhs)
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: (tensor<2x2xi1>, tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
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// CHECK: "xla_lhlo.select"(%{{.*}}, %{{.*}}, %{{.*}}, %{{.*}})
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// BOTH: "xla_lhlo.select"(%{{.*}}, %{{.*}}, %{{.*}}, %{{.*}})
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tensor_store %tensor_result, %result : memref<2x2xf32>
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return
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}
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// -----
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// CHECK-LABEL: func @compare
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// BOTH-LABEL: func @compare
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func @compare(%lhs: memref<2x2xf32>, %rhs: memref<2x2xf32>, %result: memref<2x2xi1>) {
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%tensor_lhs = tensor_load %lhs : memref<2x2xf32>
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%tensor_rhs = tensor_load %rhs : memref<2x2xf32>
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%tensor_result = "xla_hlo.compare"(%tensor_lhs, %tensor_rhs)
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{comparison_direction = "EQ"}
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: (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xi1>
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// CHECK: "xla_lhlo.compare"(%{{.*}}, %{{.*}}, %{{.*}}) {comparison_direction = "EQ"}
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// BOTH: "xla_lhlo.compare"(%{{.*}}, %{{.*}}, %{{.*}}) {comparison_direction = "EQ"}
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tensor_store %tensor_result, %result : memref<2x2xi1>
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return
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}
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// -----
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// CHECK-LABEL: func @broadcast
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// BOTH-LABEL: func @broadcast
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func @broadcast(%operand: memref<5xf32>, %result: memref<10x5xf32>) {
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%tensor_operand = tensor_load %operand : memref<5xf32>
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%tensor_result = "xla_hlo.broadcast_in_dim"(%tensor_operand)
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{broadcast_dimensions = dense<1> : tensor<1xi64>}
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: (tensor<5xf32>) -> tensor<10x5xf32>
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// CHECK: "xla_lhlo.broadcast_in_dim"(%{{.*}}, %{{.*}}) {broadcast_dimensions = dense<1> : tensor<1xi64>}
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// BOTH: "xla_lhlo.broadcast_in_dim"(%{{.*}}, %{{.*}}) {broadcast_dimensions = dense<1> : tensor<1xi64>}
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tensor_store %tensor_result, %result : memref<10x5xf32>
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return
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}
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@ -157,55 +163,55 @@ func @broadcast(%operand: memref<5xf32>, %result: memref<10x5xf32>) {
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func @external_func() -> tensor<3xi64>
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// CHECK: #[[MAP:.*]] = affine_map<(d0, d1)[s0, s1] -> (d0 * s0 + d1 * s1)>
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// BOTH: #[[MAP:.*]] = affine_map<(d0, d1)[s0, s1] -> (d0 * s0 + d1 * s1)>
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// CHECK-LABEL: func @dyn_broadcast
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// BOTH-LABEL: func @dyn_broadcast
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func @dyn_broadcast(%operand: memref<?x?xf32>) {
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// CHECK-SAME: (%[[OPERAND:.*]]: memref<?x?xf32>)
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// BOTH-SAME: (%[[OPERAND:.*]]: memref<?x?xf32>)
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%tensor_operand = tensor_load %operand : memref<?x?xf32>
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%shape = call @external_func() : () -> tensor<3xi64>
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%tensor_result = "xla_hlo.dynamic_broadcast_in_dim"(%tensor_operand, %shape) {
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broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>
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} : (tensor<?x?xf32>, tensor<3xi64>) -> tensor<?x?x?xf32>
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// CHECK: %[[SHAPE:.*]] = call @external_func()
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// CHECK: %[[C0:.*]] = constant 0 : index
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// CHECK: %[[EL0:.*]] = extract_element %[[SHAPE]][%[[C0]]] : tensor<3xi64>
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// CHECK: %[[IC0:.*]] = index_cast %[[EL0]] : i64 to index
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// CHECK: %[[C1:.*]] = constant 1 : index
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// CHECK: %[[EL1:.*]] = extract_element %[[SHAPE]][%[[C1]]] : tensor<3xi64>
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// CHECK: %[[IC1:.*]] = index_cast %[[EL1]] : i64 to index
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// CHECK: %[[C2:.*]] = constant 2 : index
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// CHECK: %[[EL2:.*]] = extract_element %[[SHAPE]][%[[C2]]] : tensor<3xi64>
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// CHECK: %[[IC2:.*]] = index_cast %[[EL2]] : i64 to index
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// CHECK: %[[RESULT:.*]] = alloc(%[[IC0]], %[[IC1]], %[[IC2]])
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// BOTH: %[[SHAPE:.*]] = call @external_func()
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// BOTH: %[[C0:.*]] = constant 0 : index
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// BOTH: %[[EL0:.*]] = extract_element %[[SHAPE]][%[[C0]]] : tensor<3xi64>
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// BOTH: %[[IC0:.*]] = index_cast %[[EL0]] : i64 to index
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// BOTH: %[[C1:.*]] = constant 1 : index
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// BOTH: %[[EL1:.*]] = extract_element %[[SHAPE]][%[[C1]]] : tensor<3xi64>
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// BOTH: %[[IC1:.*]] = index_cast %[[EL1]] : i64 to index
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// BOTH: %[[C2:.*]] = constant 2 : index
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// BOTH: %[[EL2:.*]] = extract_element %[[SHAPE]][%[[C2]]] : tensor<3xi64>
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// BOTH: %[[IC2:.*]] = index_cast %[[EL2]] : i64 to index
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// BOTH: %[[RESULT:.*]] = alloc(%[[IC0]], %[[IC1]], %[[IC2]])
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// CHECK: %[[C0_:.*]] = constant 0 : index
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// CHECK: %[[C1_:.*]] = constant 1 : index
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// BOTH: %[[C0_:.*]] = constant 0 : index
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// BOTH: %[[C1_:.*]] = constant 1 : index
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// CHECK: %[[C1__:.*]] = constant 1 : index
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// CHECK: %[[EL1_:.*]] = extract_element %[[SHAPE]]{{\[}}%[[C1__]]] : tensor<3xi64>
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// CHECK: %[[C0___:.*]] = constant 0 : index
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// CHECK: %[[OPERAND_DIM_0:.*]] = dim %[[OPERAND]], %[[C0___]] : memref<?x?xf32>
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// CHECK: %[[RESULT_DIM_1:.*]] = index_cast %[[EL1_]] : i64 to index
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// CHECK: %[[EXPAND_0:.*]] = cmpi "slt", %[[OPERAND_DIM_0]], %[[RESULT_DIM_1]]
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// CHECK: %[[STRIDE_0:.*]] = select %[[EXPAND_0]], %[[C0_]], %[[C1_]] : index
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// BOTH: %[[C1__:.*]] = constant 1 : index
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// BOTH: %[[EL1_:.*]] = extract_element %[[SHAPE]]{{\[}}%[[C1__]]] : tensor<3xi64>
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// BOTH: %[[C0___:.*]] = constant 0 : index
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// BOTH: %[[OPERAND_DIM_0:.*]] = dim %[[OPERAND]], %[[C0___]] : memref<?x?xf32>
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// BOTH: %[[RESULT_DIM_1:.*]] = index_cast %[[EL1_]] : i64 to index
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// BOTH: %[[EXPAND_0:.*]] = cmpi "slt", %[[OPERAND_DIM_0]], %[[RESULT_DIM_1]]
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// BOTH: %[[STRIDE_0:.*]] = select %[[EXPAND_0]], %[[C0_]], %[[C1_]] : index
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// CHECK: %[[C2_:.*]] = constant 2 : index
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// CHECK: %[[EL2_:.*]] = extract_element %[[SHAPE]]{{\[}}%[[C2_]]] : tensor<3xi64>
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// CHECK: %[[C1___:.*]] = constant 1 : index
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// CHECK: %[[OPERAND_DIM_1:.*]] = dim %[[OPERAND]], %[[C1___]] : memref<?x?xf32>
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// CHECK: %[[RESULT_DIM_2:.*]] = index_cast %[[EL2_]] : i64 to index
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// CHECK: %[[EXPAND_1:.*]] = cmpi "slt", %[[OPERAND_DIM_1]], %[[RESULT_DIM_2]]
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||||
// CHECK: %[[STRIDE_1:.*]] = select %[[EXPAND_1]], %[[C0_]], %[[C1_]] : index
|
||||
// BOTH: %[[C2_:.*]] = constant 2 : index
|
||||
// BOTH: %[[EL2_:.*]] = extract_element %[[SHAPE]]{{\[}}%[[C2_]]] : tensor<3xi64>
|
||||
// BOTH: %[[C1___:.*]] = constant 1 : index
|
||||
// BOTH: %[[OPERAND_DIM_1:.*]] = dim %[[OPERAND]], %[[C1___]] : memref<?x?xf32>
|
||||
// BOTH: %[[RESULT_DIM_2:.*]] = index_cast %[[EL2_]] : i64 to index
|
||||
// BOTH: %[[EXPAND_1:.*]] = cmpi "slt", %[[OPERAND_DIM_1]], %[[RESULT_DIM_2]]
|
||||
// BOTH: %[[STRIDE_1:.*]] = select %[[EXPAND_1]], %[[C0_]], %[[C1_]] : index
|
||||
|
||||
// CHECK: %[[TRANSFORMED_MEMREF:.*]] = xla_lhlo.dynamic_memref_cast
|
||||
// CHECK-SAME: %[[OPERAND]](%[[RESULT_DIM_1]], %[[RESULT_DIM_2]])
|
||||
// CHECK-SAME: {{\[}}%[[STRIDE_0]], %[[STRIDE_1]]]
|
||||
// CHECK-SAME: : memref<?x?xf32> -> memref<?x?xf32, #map0>
|
||||
// BOTH: %[[TRANSFORMED_MEMREF:.*]] = xla_lhlo.dynamic_memref_cast
|
||||
// BOTH-SAME: %[[OPERAND]](%[[RESULT_DIM_1]], %[[RESULT_DIM_2]])
|
||||
// BOTH-SAME: {{\[}}%[[STRIDE_0]], %[[STRIDE_1]]]
|
||||
// BOTH-SAME: : memref<?x?xf32> -> memref<?x?xf32, #map0>
|
||||
|
||||
// CHECK: "xla_lhlo.broadcast_in_dim"(%[[TRANSFORMED_MEMREF]], %[[RESULT]]) {
|
||||
// CHECK-SAME: broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>
|
||||
// CHECK-SAME: } : (memref<?x?xf32, #[[MAP]]>, memref<?x?x?xf32>) -> ()
|
||||
// BOTH: "xla_lhlo.broadcast_in_dim"(%[[TRANSFORMED_MEMREF]], %[[RESULT]]) {
|
||||
// BOTH-SAME: broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>
|
||||
// BOTH-SAME: } : (memref<?x?xf32, #[[MAP]]>, memref<?x?x?xf32>) -> ()
|
||||
|
||||
// Do not store the value back to avoid the tensor-store being rewritten to
|
||||
// a copy into the pre-allocated argument.
|
||||
@ -214,7 +220,7 @@ func @dyn_broadcast(%operand: memref<?x?xf32>) {
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @complex
|
||||
// BOTH-LABEL: func @complex
|
||||
func @complex(%real: memref<2x2xf32>,
|
||||
%imag: memref<2x2xf32>,
|
||||
%result: memref<2x2xcomplex<f32>>) {
|
||||
@ -222,164 +228,164 @@ func @complex(%real: memref<2x2xf32>,
|
||||
%tensor_imag = tensor_load %imag : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.complex"(%tensor_real, %tensor_imag)
|
||||
: (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xcomplex<f32>>
|
||||
// CHECK: "xla_lhlo.complex"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.complex"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xcomplex<f32>>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @real
|
||||
// BOTH-LABEL: func @real
|
||||
func @real(%operand: memref<2x2xcomplex<f32>>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xcomplex<f32>>
|
||||
%tensor_result = "xla_hlo.real"(%tensor_operand)
|
||||
: (tensor<2x2xcomplex<f32>>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.real"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.real"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @imag
|
||||
// BOTH-LABEL: func @imag
|
||||
func @imag(%operand: memref<2x2xcomplex<f32>>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xcomplex<f32>>
|
||||
%tensor_result = "xla_hlo.imag"(%tensor_operand)
|
||||
: (tensor<2x2xcomplex<f32>>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.imag"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.imag"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @iota
|
||||
// BOTH-LABEL: func @iota
|
||||
func @iota(%result: memref<10xi32>) {
|
||||
%tensor_result = "xla_hlo.iota"()
|
||||
{iota_dimension = 0 : i64} : () -> tensor<10xi32>
|
||||
// CHECK: "xla_lhlo.iota"(%{{.*}}) {iota_dimension = 0 : i64}
|
||||
// BOTH: "xla_lhlo.iota"(%{{.*}}) {iota_dimension = 0 : i64}
|
||||
tensor_store %tensor_result, %result : memref<10xi32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @abs
|
||||
// BOTH-LABEL: func @abs
|
||||
func @abs(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.abs"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.abs"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.abs"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @ceil
|
||||
// BOTH-LABEL: func @ceil
|
||||
func @ceil(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.ceil"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.ceil"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.ceil"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @convert
|
||||
// BOTH-LABEL: func @convert
|
||||
func @convert(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.convert"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.copy"(%{{.*}}, %{{.*}})
|
||||
// CHECK-NOT: tensor_store
|
||||
// BOTH: "xla_lhlo.copy"(%{{.*}}, %{{.*}})
|
||||
// BOTH-NOT: tensor_store
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @cos
|
||||
// BOTH-LABEL: func @cos
|
||||
func @cos(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.cosine"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.cosine"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.cosine"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @neg
|
||||
// BOTH-LABEL: func @neg
|
||||
func @neg(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.negate"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.negate"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.negate"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @rsqrt
|
||||
// BOTH-LABEL: func @rsqrt
|
||||
func @rsqrt(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.rsqrt"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.rsqrt"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.rsqrt"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @sign
|
||||
// BOTH-LABEL: func @sign
|
||||
func @sign(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.sign"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.sign"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.sign"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @sqrt
|
||||
// BOTH-LABEL: func @sqrt
|
||||
func @sqrt(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.sqrt"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.sqrt"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.sqrt"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @tanh
|
||||
// BOTH-LABEL: func @tanh
|
||||
func @tanh(%operand: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_operand = tensor_load %operand : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.tanh"(%tensor_operand)
|
||||
: (tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.tanh"(%{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.tanh"(%{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @remainder
|
||||
// BOTH-LABEL: func @remainder
|
||||
func @remainder(%lhs: memref<2x2xf32>, %rhs: memref<2x2xf32>, %result: memref<2x2xf32>) {
|
||||
%tensor_lhs = tensor_load %lhs : memref<2x2xf32>
|
||||
%tensor_rhs = tensor_load %rhs : memref<2x2xf32>
|
||||
%tensor_result = "xla_hlo.remainder"(%tensor_lhs, %tensor_rhs)
|
||||
: (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
|
||||
// CHECK: "xla_lhlo.remainder"(%{{.*}}, %{{.*}}, %{{.*}})
|
||||
// BOTH: "xla_lhlo.remainder"(%{{.*}}, %{{.*}}, %{{.*}})
|
||||
tensor_store %tensor_result, %result : memref<2x2xf32>
|
||||
return
|
||||
}
|
||||
@ -387,76 +393,79 @@ func @remainder(%lhs: memref<2x2xf32>, %rhs: memref<2x2xf32>, %result: memref<2x
|
||||
// -----
|
||||
|
||||
// Dynamic shape binary element-wise operation.
|
||||
// CHECK-LABEL: func @add_dyn
|
||||
// BOTH-LABEL: func @add_dyn
|
||||
func @add_dyn(%lhs: tensor<?x?xf32>, %rhs: tensor<?x?xf32>) {
|
||||
%result = "xla_hlo.add"(%lhs, %rhs)
|
||||
: (tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>
|
||||
// CHECK: %[[C0:.*]] = constant 0 : index
|
||||
// CHECK: %[[DIM0:.*]] = dim %arg0, %[[C0]] : memref<?x?xf32>
|
||||
// CHECK: %[[IC0:.*]] = index_cast %[[DIM0]] : index to i64
|
||||
// CHECK: %[[C1:.*]] = constant 1 : index
|
||||
// CHECK: %[[DIM1:.*]] = dim %arg0, %[[C1]] : memref<?x?xf32>
|
||||
// CHECK: %[[IC1:.*]] = index_cast %[[DIM1]] : index to i64
|
||||
// CHECK: %[[SHAPE:.*]] = tensor_from_elements(%[[IC0]], %[[IC1]]) : tensor<2xi64>
|
||||
// CHECK: %[[C0_:.*]] = constant 0 : index
|
||||
// CHECK: %[[EE0:.*]] = extract_element %[[SHAPE]][%[[C0_]]] : tensor<2xi64>
|
||||
// CHECK: %[[ICS0:.*]] = index_cast %[[EE0]] : i64 to index
|
||||
// CHECK: %[[C1_:.*]] = constant 1 : index
|
||||
// CHECK: %[[EE1:.*]] = extract_element %[[SHAPE]][%[[C1_]]] : tensor<2xi64>
|
||||
// CHECK: %[[ICS1:.*]] = index_cast %[[EE1]] : i64 to index
|
||||
// CHECK: %[[RESULT:.*]] = alloc(%[[ICS0]], %[[ICS1]])
|
||||
// CHECK: "xla_lhlo.add"(%arg0, %arg1, %[[RESULT]]) : (memref<?x?xf32>, memref<?x?xf32>, memref<?x?xf32>) -> ()
|
||||
// BOTH: %[[C0:.*]] = constant 0 : index
|
||||
// BOTH: %[[DIM0:.*]] = dim %arg0, %[[C0]] : memref<?x?xf32>
|
||||
// BOTH: %[[IC0:.*]] = index_cast %[[DIM0]] : index to i64
|
||||
// BOTH: %[[C1:.*]] = constant 1 : index
|
||||
// BOTH: %[[DIM1:.*]] = dim %arg0, %[[C1]] : memref<?x?xf32>
|
||||
// BOTH: %[[IC1:.*]] = index_cast %[[DIM1]] : index to i64
|
||||
// BOTH: %[[SHAPE:.*]] = tensor_from_elements(%[[IC0]], %[[IC1]]) : tensor<2xi64>
|
||||
// BOTH: %[[C0_:.*]] = constant 0 : index
|
||||
// BOTH: %[[EE0:.*]] = extract_element %[[SHAPE]][%[[C0_]]] : tensor<2xi64>
|
||||
// BOTH: %[[ICS0:.*]] = index_cast %[[EE0]] : i64 to index
|
||||
// BOTH: %[[C1_:.*]] = constant 1 : index
|
||||
// BOTH: %[[EE1:.*]] = extract_element %[[SHAPE]][%[[C1_]]] : tensor<2xi64>
|
||||
// BOTH: %[[ICS1:.*]] = index_cast %[[EE1]] : i64 to index
|
||||
// BOTH: %[[RESULT:.*]] = alloc(%[[ICS0]], %[[ICS1]])
|
||||
// BOTH: "xla_lhlo.add"(%arg0, %arg1, %[[RESULT]]) : (memref<?x?xf32>, memref<?x?xf32>, memref<?x?xf32>) -> ()
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// Dynamic shape unary element-wise operation.
|
||||
// CHECK-LABEL: func @tanh_dyn
|
||||
// BOTH-LABEL: func @tanh_dyn
|
||||
func @tanh_dyn(%arg0: tensor<?x?xf32>) {
|
||||
%result = "xla_hlo.tanh"(%arg0)
|
||||
: (tensor<?x?xf32>) -> tensor<?x?xf32>
|
||||
// CHECK: %[[C0:.*]] = constant 0 : index
|
||||
// CHECK: %[[DIM0:.*]] = dim %arg0, %[[C0]] : memref<?x?xf32>
|
||||
// CHECK: %[[IC0:.*]] = index_cast %[[DIM0]] : index to i64
|
||||
// CHECK: %[[C1:.*]] = constant 1 : index
|
||||
// CHECK: %[[DIM1:.*]] = dim %arg0, %[[C1]] : memref<?x?xf32>
|
||||
// CHECK: %[[IC1:.*]] = index_cast %[[DIM1]] : index to i64
|
||||
// CHECK: %[[SHAPE:.*]] = tensor_from_elements(%[[IC0]], %[[IC1]]) : tensor<2xi64>
|
||||
// CHECK: %[[C0_:.*]] = constant 0 : index
|
||||
// CHECK: %[[EE0:.*]] = extract_element %[[SHAPE]][%[[C0_]]] : tensor<2xi64>
|
||||
// CHECK: %[[ICS0:.*]] = index_cast %[[EE0]] : i64 to index
|
||||
// CHECK: %[[C1_:.*]] = constant 1 : index
|
||||
// CHECK: %[[EE1:.*]] = extract_element %[[SHAPE]][%[[C1_]]] : tensor<2xi64>
|
||||
// CHECK: %[[ICS1:.*]] = index_cast %[[EE1]] : i64 to index
|
||||
// CHECK: %[[RESULT:.*]] = alloc(%[[ICS0]], %[[ICS1]])
|
||||
// CHECK: "xla_lhlo.tanh"(%arg0, %[[RESULT]]) : (memref<?x?xf32>, memref<?x?xf32>) -> ()
|
||||
// BOTH: %[[C0:.*]] = constant 0 : index
|
||||
// BOTH: %[[DIM0:.*]] = dim %arg0, %[[C0]] : memref<?x?xf32>
|
||||
// BOTH: %[[IC0:.*]] = index_cast %[[DIM0]] : index to i64
|
||||
// BOTH: %[[C1:.*]] = constant 1 : index
|
||||
// BOTH: %[[DIM1:.*]] = dim %arg0, %[[C1]] : memref<?x?xf32>
|
||||
// BOTH: %[[IC1:.*]] = index_cast %[[DIM1]] : index to i64
|
||||
// BOTH: %[[SHAPE:.*]] = tensor_from_elements(%[[IC0]], %[[IC1]]) : tensor<2xi64>
|
||||
// BOTH: %[[C0_:.*]] = constant 0 : index
|
||||
// BOTH: %[[EE0:.*]] = extract_element %[[SHAPE]][%[[C0_]]] : tensor<2xi64>
|
||||
// BOTH: %[[ICS0:.*]] = index_cast %[[EE0]] : i64 to index
|
||||
// BOTH: %[[C1_:.*]] = constant 1 : index
|
||||
// BOTH: %[[EE1:.*]] = extract_element %[[SHAPE]][%[[C1_]]] : tensor<2xi64>
|
||||
// BOTH: %[[ICS1:.*]] = index_cast %[[EE1]] : i64 to index
|
||||
// BOTH: %[[RESULT:.*]] = alloc(%[[ICS0]], %[[ICS1]])
|
||||
// BOTH: "xla_lhlo.tanh"(%arg0, %[[RESULT]]) : (memref<?x?xf32>, memref<?x?xf32>) -> ()
|
||||
return
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @dot
|
||||
// BOTH-LABEL: func @dot
|
||||
func @dot(%arg0: tensor<1024x1024xf32>) -> tensor<1024x1024xf32> {
|
||||
// CHECK-SAME: (%[[ARG0:.*]]: [[TYPE:.*]],
|
||||
// CHECK-SAME: %[[RESULT:.*]]: [[TYPE]])
|
||||
// CHECK: "xla_lhlo.dot"(%[[ARG0]], %[[ARG0]], %{{.*}}) : ([[TYPE]], [[TYPE]], [[TYPE]]) -> ()
|
||||
// PRE-SAME: (%[[ARG0:.*]]: [[TYPE:.*]], %[[RESULT:.*]]: [[TYPE]])
|
||||
// ESC-SAME: (%[[ARG0:.*]]: [[TYPE:.*]]) -> [[TYPE]]
|
||||
// BOTH-NEXT: %[[ALLOC:.*]] = alloc
|
||||
// BOTH: "xla_lhlo.dot"(%[[ARG0]], %[[ARG0]], %[[ALLOC]]) : ([[TYPE]], [[TYPE]], [[TYPE]]) -> ()
|
||||
%dot = "xla_hlo.dot"(%arg0, %arg0)
|
||||
: (tensor<1024x1024xf32>, tensor<1024x1024xf32>) -> tensor<1024x1024xf32>
|
||||
// PRE: "xla_lhlo.copy"(%[[ALLOC]], %[[RESULT]])
|
||||
// ESC: return %[[ALLOC]]
|
||||
return %dot : tensor<1024x1024xf32>
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
// CHECK-LABEL: func @conv
|
||||
// BOTH-LABEL: func @conv
|
||||
func @conv(%input: tensor<3x5x5x3xf32>, %filter : tensor<2x2x3x4xf32>) -> tensor<3x5x5x4xf32> {
|
||||
%c0 = constant 0 : index
|
||||
// CHECK: %[[OUT:.*]] = alloc() : memref<3x5x5x4xf32>
|
||||
// CHECK: "xla_lhlo.convolution"(%{{.+}}, %{{.+}}, %[[OUT]])
|
||||
// CHECK-SAME: padding = dense<[
|
||||
// CHECK-SAME: [0, 1], [0, 1]]> : tensor<2x2xi64>
|
||||
// CHECK-SAME: rhs_dilation = dense<[1, 2]>
|
||||
// CHECK-SAME: window_strides = dense<[2, 1]>
|
||||
// BOTH: %[[OUT:.*]] = alloc() : memref<3x5x5x4xf32>
|
||||
// BOTH: "xla_lhlo.convolution"(%{{.+}}, %{{.+}}, %[[OUT]])
|
||||
// BOTH-SAME: padding = dense<[
|
||||
// BOTH-SAME: [0, 1], [0, 1]]> : tensor<2x2xi64>
|
||||
// BOTH-SAME: rhs_dilation = dense<[1, 2]>
|
||||
// BOTH-SAME: window_strides = dense<[2, 1]>
|
||||
%out = "xla_hlo.convolution"(%filter, %input) {
|
||||
batch_group_count = 1 : i64,
|
||||
dimension_numbers = {
|
||||
|
||||
@ -368,6 +368,15 @@ class HloToLhloTensorStoreOpConverter
|
||||
|
||||
struct HloLegalizeToLhlo
|
||||
: public PassWrapper<HloLegalizeToLhlo, OperationPass<ModuleOp>> {
|
||||
public:
|
||||
HloLegalizeToLhlo() = default;
|
||||
HloLegalizeToLhlo(const HloLegalizeToLhlo& o) {
|
||||
this->results_escape_function = o.results_escape_function.getValue();
|
||||
}
|
||||
explicit HloLegalizeToLhlo(bool results_escape_function) {
|
||||
this->results_escape_function.setValue(results_escape_function);
|
||||
}
|
||||
|
||||
void runOnOperation() override {
|
||||
OwningRewritePatternList patterns;
|
||||
auto& context = getContext();
|
||||
@ -398,10 +407,28 @@ struct HloLegalizeToLhlo
|
||||
OwningRewritePatternList patterns;
|
||||
populateHLOToLHLOConversionPattern(func.getContext(), &bufferAssignment,
|
||||
&converter, &patterns);
|
||||
if (results_escape_function) {
|
||||
populateWithBufferAssignmentOpConversionPatterns<
|
||||
mlir::ReturnOp, mlir::ReturnOp, xla_lhlo::CopyOp,
|
||||
/*allowMemrefFunctionResults=*/true>(&context, &bufferAssignment,
|
||||
&converter, &patterns);
|
||||
} else {
|
||||
populateWithBufferAssignmentOpConversionPatterns<
|
||||
mlir::ReturnOp, mlir::ReturnOp, xla_lhlo::CopyOp,
|
||||
/*allowMemrefFunctionResults=*/false>(&context, &bufferAssignment,
|
||||
&converter, &patterns);
|
||||
}
|
||||
return WalkResult(
|
||||
applyPartialConversion(func, target, patterns, &converter));
|
||||
});
|
||||
}
|
||||
|
||||
private:
|
||||
Option<bool> results_escape_function{
|
||||
*this, "results-escape-function",
|
||||
llvm::cl::desc(
|
||||
"Allocate the results of functions within the functions body"),
|
||||
llvm::cl::init(false)};
|
||||
};
|
||||
} // namespace
|
||||
|
||||
@ -446,14 +473,11 @@ void populateHLOToLHLOConversionPattern(
|
||||
HloToLhloTensorStoreOpConverter
|
||||
>(context, bufferAssignment, converter);
|
||||
// clang-format on
|
||||
populateWithBufferAssignmentOpConversionPatterns<
|
||||
mlir::ReturnOp, mlir::ReturnOp, xla_lhlo::CopyOp,
|
||||
/*allowMemrefFunctionResults=*/false>(context, bufferAssignment,
|
||||
converter, patterns);
|
||||
}
|
||||
|
||||
std::unique_ptr<OperationPass<ModuleOp>> createLegalizeToLhloPass() {
|
||||
return absl::make_unique<HloLegalizeToLhlo>();
|
||||
std::unique_ptr<OperationPass<ModuleOp>> createLegalizeToLhloPass(
|
||||
bool results_escape_function) {
|
||||
return absl::make_unique<HloLegalizeToLhlo>(results_escape_function);
|
||||
}
|
||||
|
||||
static PassRegistration<HloLegalizeToLhlo> legalize_pass(
|
||||
|
||||
@ -59,9 +59,13 @@ std::unique_ptr<OperationPass<FuncOp>> createLegalizeControlFlowPass();
|
||||
/// Lowers from HLO dialect to Standard dialect.
|
||||
std::unique_ptr<OperationPass<FuncOp>> createLegalizeToStdPass();
|
||||
|
||||
// Lowers from HLO dialect to LHLO dialect allocating/deallocating temporary
|
||||
// buffers if necessary.
|
||||
std::unique_ptr<OperationPass<ModuleOp>> createLegalizeToLhloPass();
|
||||
/// Lowers from HLO dialect to LHLO dialect allocating/deallocating temporary
|
||||
/// buffers if necessary. If `results_escape_functions` is set to true,
|
||||
/// allocated buffers for function results will be returned and escape the
|
||||
/// function. Otherwise, the signature is rewritten with extra arguments for the
|
||||
/// buffers that are to be used for results.
|
||||
std::unique_ptr<OperationPass<ModuleOp>> createLegalizeToLhloPass(
|
||||
bool results_escape_functions = false);
|
||||
|
||||
// Lowers from HLO dialect to Linalg dialect.
|
||||
std::unique_ptr<OperationPass<FuncOp>> createLegalizeHloToLinalgPass();
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user