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