| // RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s |
| |
| // CHECK: {tf_saved_model.index_path = ["input2"]} |
| // CHECK-SAME: {tf_saved_model.index_path = ["input1"]} |
| // CHECK-SAME: {tf_saved_model.index_path = ["start_logits"]} |
| // CHECK-SAME: {tf_saved_model.index_path = ["end_logits"]} |
| // CHECK-SAME: tf.entry_function = {inputs = "serving_default_input2:0,serving_default_input1:0", outputs = "StatefulPartitionedCall:1,StatefulPartitionedCall:0"} |
| // CHECK-SAME: tf_saved_model.exported_names = ["serving_default"] |
| module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 554 : i32}, tf_saved_model.semantics} { |
| func @main(%arg0: tensor<?x384xf32> {tf_saved_model.index_path = ["input2"]}, %arg1: tensor<?x384xf32> {tf_saved_model.index_path = ["input1"]}) -> (tensor<?x5xf32> {tf_saved_model.index_path = ["start_logits"]}, tensor<?x5xf32> {tf_saved_model.index_path = ["end_logits"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_input2:0,serving_default_input1:0", outputs = "StatefulPartitionedCall:1,StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} { |
| %cst = arith.constant dense<0.000000e+00> : tensor<5xf32> |
| %cst_0 = arith.constant dense<1.0> : tensor<5x384xf32> |
| %cst_1 = arith.constant dense<1.0> : tensor<5x384xf32> |
| %0 = "tfl.fully_connected"(%arg0, %cst_0, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<?x384xf32>, tensor<5x384xf32>, tensor<5xf32>) -> tensor<?x5xf32> |
| %1 = "tfl.fully_connected"(%arg0, %cst_1, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<?x384xf32>, tensor<5x384xf32>, tensor<5xf32>) -> tensor<?x5xf32> |
| func.return %1, %0 : tensor<?x5xf32>, tensor<?x5xf32> |
| } |
| } |
