test/e2e/xla/fragment_000.mlir

// Copyright 2019 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

// RUN: iree-run-mlir --target_backends=interpreter-bytecode %s --input_values="f32=0\n5x1xf32=[1][-2][-3][4][-5]\nf32=1\n5x5xf32=[3.46499 -7.64389 -5.72249 5.98053 17.6892][2.9707 -6.20734 -4.25962 4.76055 13.8784][2.47641 -4.77079 -2.79675 3.54056 10.0675][1.98212 -3.33424 -1.33388 2.32058 6.25666][1.48783 -1.8977 0.12899 1.1006 2.4458]\n5xf32=0 0 0 0 0" | FileCheck %s --implicit-check-not="[" --implicit-check-not="]" --dump-input=fail

// CHECK-LABEL: EXEC @main_entry_dispatch_3
func @main_entry_dispatch_3(
    %0: tensor<f32>,
    %1: tensor<5x1xf32>,
    %2: tensor<f32>,
    %3: tensor<5x5xf32>,
    %4: tensor<5xf32>) -> tensor<5x5xf32> {
  %5 = "xla_hlo.broadcast_in_dim"(%1) {broadcast_dimensions = dense<[0, 1]> : tensor<2xi64>, name = "broadcast.44"} : (tensor<5x1xf32>) -> tensor<5x1x5xf32>
  %6 = "xla_hlo.broadcast_in_dim"(%2) {name = "broadcast.9"} : (tensor<f32>) -> tensor<5x1x5xf32>
  %7 = mulf %5, %6 : tensor<5x1x5xf32>
  %8 = "xla_hlo.broadcast_in_dim"(%0) {name = "broadcast.47"} : (tensor<f32>) -> tensor<5x1x5xf32>
  %9 = cmpf "ogt", %7, %8 : tensor<5x1x5xf32>
  %10 = "xla_hlo.broadcast_in_dim"(%0) {name = "broadcast.11"} : (tensor<f32>) -> tensor<5x1x5xf32>
  %11 = "xla_hlo.broadcast_in_dim"(%0) {name = "broadcast.67"} : (tensor<f32>) -> tensor<5x5xf32>
  %12 = "xla_hlo.broadcast_in_dim"(%4) {broadcast_dimensions = dense<1> : tensor<1xi64>, name = "broadcast.64"} : (tensor<5xf32>) -> tensor<5x5xf32>
  %13 = addf %3, %12 : tensor<5x5xf32>
  %14 = xla_hlo.max %11, %13 {name = "maximum.68"} : tensor<5x5xf32>
  %15 = "xla_hlo.reshape"(%14) {name = "reshape.70"} : (tensor<5x5xf32>) -> tensor<5x1x5xf32>
  %16 = "xla_hlo.select"(%9, %10, %15) {name = "select.71"} : (tensor<5x1x5xi1>, tensor<5x1x5xf32>, tensor<5x1x5xf32>) -> tensor<5x1x5xf32>
  %17 = "xla_hlo.copy"(%16) {name = "copy.4"} : (tensor<5x1x5xf32>) -> tensor<5x1x5xf32>
  %18 = "xla_hlo.reshape"(%17) {name = "reshape.72"} : (tensor<5x1x5xf32>) -> tensor<5x5xf32>
  return %18 : tensor<5x5xf32>
}

// On separate lines to avoid "[[" which FileCheck interprets as substitutions
// CHECK: 5x5xf32=
// CHECK-SAME: [0 0 0 0 0]
// CHECK-SAME: [2.97{{[0-9]+}} 0 0 4.76{{[0-9]+}} 13.87{{[0-9]+}}]
// CHECK-SAME: [2.47{{[0-9]+}} 0 0 3.54{{[0-9]+}} 10.06{{[0-9]+}}]
// CHECK-SAME: [0 0 0 0 0]
// CHECK-SAME: [1.48{{[0-9]+}} 0 0.12{{[0-9]+}} 1.10{{[0-9]+}} 2.44{{[0-9]+}}]