| // RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s |
| // This only test the exporter and importer are working without min/max quantization parameters. |
| |
| func @main(tensor<40x37xf32>, tensor<40x37xf32>) -> tensor<40x40xf32> { |
| ^bb0(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>): |
| %cst = arith.constant dense<1.0> : tensor<40xf32> |
| %0:2 = "tfl.fully_connected"(%arg0, %arg1, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<40x37xf32>, tensor<40x37xf32>, tensor<40xf32>) -> (tensor<40x40xf32>, tensor<40x40xf32>) |
| func.return %0 : tensor<40x40xf32> |
| |
| // CHECK-LABEL: func @main(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>) -> tensor<40x40xf32> |
| // CHECK: %[[CONST:[0-9]+]] = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<40xf32>} |
| // CHECK-NEXT: %[[FULL:[0-9]+]]:2 = "tfl.fully_connected"(%arg0, %arg1, %[[CONST]]) {asymmetric_quantize_inputs = false, fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} |
| // CHECK-NEXT: return %[[FULL]]#0 |
| } |
