torch-mlir/test/Dialect/ATen/aten_maxpool2d.mlir

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// RUN: npcomp-opt %s -aten-layer-name -aten-op-report |& FileCheck %s
// CHECK-LABEL: "L0-max_pool2d-0": {
// CHECK-NEXT: "activation_in": 8192,
// CHECK-NEXT: "activation_out": 2048,
// CHECK-NEXT: "ops:>": 16384,
// CHECK-NEXT: "reads": 8192,
// CHECK-NEXT: "writes": 2048
module {
func @graph(%arg0: tensor<1x32x16x16xf32>) -> tensor<1x32x8x8xf32> {
%0 = "aten.constant"() {type = "List[i32]", value = dense<3> : vector<2xi64>} : () -> !aten.list<i32>
%1 = "aten.constant"() {type = "List[i32]", value = dense<2> : vector<2xi64>} : () -> !aten.list<i32>
%2 = "aten.constant"() {type = "List[i32]", value = dense<1> : vector<2xi64>} : () -> !aten.list<i32>
%3 = "aten.constant"() {type = "List[i32]", value = dense<1> : vector<2xi64>} : () -> !aten.list<i32>
%4 = "aten.constant"() {type = "bool", value = 0 : i1} : () -> i1
%5 = "aten.max_pool2d"(%arg0, %0, %1, %2, %3, %4) : (tensor<1x32x16x16xf32>, !aten.list<i32>, !aten.list<i32>, !aten.list<i32>, !aten.list<i32>, i1) -> tensor<1x32x8x8xf32>
"std.return"(%5) : (tensor<1x32x8x8xf32>) -> ()
}
}