"tf.InitializeTableFromTextFileV2"(%0, %arg0) {delimiter = "\09", device = "", key_index = -2 : i64, offset = 0 : i64, value_index = -1 : i64, vocab_size = 437 : i64} : (tensor<!tf_type.resource>, tensor<!tf_type.string>) -> ()
    // CHECK: "tf.InitializeTableFromTextFileV2"(%0, %arg0)
    func.return
  }
}

// -----

          %c_9 = tf_executor.island wraps "tf.InitializeTableFromTextFileV2"(%o, %arg1) <{delimiter = "\09", key_index = -2 : i64, value_index = -1 : i64, vocab_size = -1 : i64}> {_has_manual_control_dependencies = true, device = ""} : (tensor<!tf_type.resource>, tensor<!tf_type.string>) -> ()

# CHECK-SAME: tf_saved_model.initializer_type = "init_op"
# CHECK-NEXT: [[R0:%.*]] = "tf.HashTableV2"()
# CHECK-SAME: shared_name = "[[hash_table:.*]]"
# CHECK-NEXT: "tf.InitializeTableFromTextFileV2"([[R0]], [[ARG0]])


def write_vocabulary_file(vocabulary):
  """Write temporary vocab file for module construction."""
  tmpdir = tempfile.mkdtemp()
  vocabulary_file = os.path.join(tmpdir, 'tokens.txt')

    %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>
    "tf.InitializeTableFromTextFileV2"(%0, %arg0) {delimiter = "\09", device = "", key_index = -2 : i64, offset = 0 : i64, value_index = -1 : i64, vocab_size = 437 : i64} : (tensor<!tf_type.resource>, tensor<!tf_type.string>) -> ()
    func.return
  }

    %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_shared_name", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>
    "tf.InitializeTableFromTextFileV2"(%0, %arg0) {delimiter = "\09", device = "", key_index = -2 : i64, value_index = -1 : i64, vocab_size = 205 : i64} : (tensor<!tf_type.resource>, tensor<!tf_type.string>) -> ()
    func.return
  }

  let constructor = "TF::CreateRewriteTPUEmbeddingOpsPass()";
}

def InitTextFileToImportPass : Pass<"tf-init-text-file-to-import", "mlir::func::FuncOp"> {
  let summary = "convert InitializeTableFromTextFileV2 ops to LookupTableImportV2Op "
           "to remove the dependency on asset files";

  let constructor = "TF::CreateInitTextFileToImportPass()";
  let options = [

  %handle = "tf.HashTable"() {container = "", device = "", shared_name = "table", key_dtype = !tf_type.string, value_dtype = i32} : () -> tensor<*x!tf_type.stringref>

  // CHECK: "tf.InitializeTableFromTextFileV2"([[handle]]
  // CHECK-SAME: device = ""
  "tf.InitializeTableFromTextFile"(%handle, %arg0) {device = "", key_index=1, value_index=1, delimiter="\t"} : (tensor<*x!tf_type.stringref>, tensor<!tf_type.string>) -> ()

allocate buffer space to receive the device output from all replicas, which is
not required. We can use the output of first replica in such cases.
### `-tf-init-text-file-to-import`

_Convert InitializeTableFromTextFileV2 ops to LookupTableImportV2Op to remove the dependency on asset files_


#### Options
```

    DefaultValuedOptionalAttr<I64Attr, "0">:$offset
  );

  let results = (outs);
}

def TF_InitializeTableFromTextFileV2Op : TF_Op<"InitializeTableFromTextFileV2", []> {
  let summary = "Initializes a table from a text file.";

  let description = [{
It inserts one key-value pair into the table for each line of the file.