82 lines
3.3 KiB
MLIR
82 lines
3.3 KiB
MLIR
// RUN: mlir-hlo-opt %s -verify-diagnostics -split-input-file | mlir-hlo-opt | FileCheck %s
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// CHECK-LABEL: func @minimum_broadcast_shapes
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func @minimum_broadcast_shapes(%lhs: tensor<?xindex>, %rhs: tensor<?xindex>)
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-> (tensor<?xindex>, tensor<?xindex>) {
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%0, %1 = chlo.minimum_broadcast_shapes %lhs, %rhs :
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tensor<?xindex>, tensor<?xindex> -> tensor<?xindex>, tensor<?xindex>
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return %0, %1 : tensor<?xindex>, tensor<?xindex>
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}
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// -----
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func @minimum_broadcast_shapes_mismatch_operand_and_result_count(%lhs: tensor<?xindex>, %rhs: tensor<?xindex>) {
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// expected-error @+1{{number of operand shapes (2) does not match number of result shapes (1)}}
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%0 = chlo.minimum_broadcast_shapes %lhs, %rhs :
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tensor<?xindex>, tensor<?xindex> -> tensor<?xindex>
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return
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}
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// -----
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func @minimum_broadcast_shapes_one_operand(%arg: tensor<?xindex>) {
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// expected-error @+1{{number of operand shapes (1) should be >= 2}}
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%0 = chlo.minimum_broadcast_shapes %arg : tensor<?xindex> -> tensor<?xindex>
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return
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}
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// -----
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func @rank_specialization_cluster(%arg0 : tensor<*xf32>, %arg1 : tensor<*xf32>,
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%arg2 : tensor<*xf32>) -> tensor<*xf32> {
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%0 = "chlo.rank_specialization_cluster"(%arg0, %arg1, %arg2) ({
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^bb0(%arg0_ : tensor<*xf32>, %arg1_ : tensor<*xf32>, %arg2_ : tensor<*xf32>):
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%1 = chlo.broadcast_multiply %arg0_, %arg1_
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: (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
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%2 = chlo.broadcast_add %1, %arg2_
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: (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
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"chlo.rank_specialization_cluster_yield"(%2) : (tensor<*xf32>) -> ()
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}) : (tensor<*xf32>, tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
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return %0 : tensor<*xf32>
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}
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// -----
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func @rank_specialization_cluster(%arg0 : tensor<*xf32>,
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%arg1 : tensor<*xf32>) -> tensor<*xf32> {
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// expected-error @+1{{source has 2 operands, but target successor needs 1}}
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%0 = "chlo.rank_specialization_cluster"(%arg0, %arg1) ({
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^bb0(%arg0_ : tensor<*xf32>, %arg1_ : tensor<*xf32>):
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"chlo.rank_specialization_cluster_yield"(%arg0_, %arg1_)
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: (tensor<*xf32>, tensor<*xf32>) -> ()
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}) : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
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return %0 : tensor<*xf32>
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}
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// -----
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func @rank_specialization_cluster(%arg0 : tensor<*xf32>) -> tensor<*xf32> {
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// expected-error @+1{{block argument types must match operand types}}
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%0 = "chlo.rank_specialization_cluster"(%arg0) ({
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^bb0(%arg0_ : tensor<*xf32>, %arg1_ : tensor<*xf32>):
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"chlo.rank_specialization_cluster_yield"(%arg0_) : (tensor<*xf32>) -> ()
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}) : (tensor<*xf32>) -> tensor<*xf32>
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return %0 : tensor<*xf32>
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}
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// -----
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func @rank_specialization_cluster(%arg0 : tensor<*xf32>, %arg1 : tensor<*xf32>,
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%arg2 : tensor<*xf32>) -> tensor<*xf32> {
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// expected-error @+1{{nested ops must not depend on implicit operands}}
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%0 = "chlo.rank_specialization_cluster"(%arg0, %arg1, %arg2) ({
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^bb0(%arg0_ : tensor<*xf32>, %arg1_ : tensor<*xf32>, %arg2_ : tensor<*xf32>):
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%1 = chlo.broadcast_multiply %arg0_, %arg1_
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: (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
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%2 = chlo.broadcast_add %1, %arg2
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: (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
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"chlo.rank_specialization_cluster_yield"(%2) : (tensor<*xf32>) -> ()
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}) : (tensor<*xf32>, tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
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return %0 : tensor<*xf32>
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}
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