1# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-graph-as-function | tf-mlir-translate -mlir-tf-graph-to-hlo-text -tf-input-shapes='' -tf-input-data-types=DT_FLOAT -tf-xla-emit-return-tuple | FileCheck %s 2 3node { 4 name: "arg" 5 op: "_Arg" 6 attr { 7 key: "T" 8 value { 9 type: DT_FLOAT 10 } 11 } 12 attr { 13 key: "index" 14 value { 15 i: 0 16 } 17 } 18} 19node { 20 name: "retval" 21 op: "_Retval" 22 input: "arg" 23 attr { 24 key: "T" 25 value { 26 type: DT_FLOAT 27 } 28 } 29 attr { 30 key: "index" 31 value { 32 i: 0 33 } 34 } 35} 36versions { 37 producer: 511 38} 39 40# Verify that conversion from Graph to MLIR and empty shape representation 41# function is successful. 42 43# CHECK-LABEL: HloModule main 44# CHECK: ENTRY %main.{{[0-9]+}} ([[ARG0:.*]]: f32[]) -> (f32[]) { 45# CHECK-NEXT: %[[ARG0]] = f32[] parameter(0) 46# CHECK-NEXT: ROOT %tuple.{{[0-9]+}} = (f32[]) tuple(f32[] %[[ARG0]]) 47# CHECK-NEXT: } 48