code: # coding=utf-8
  # Copyright 2018 The Google AI Language Team Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  
  import random
  import unittest
  
  from transformers import TransfoXLConfig, is_tf_available
  
  from .test_configuration_common import ConfigTester
  from .test_modeling_tf_common import TFModelTesterMixin, ids_tensor
  from .utils import CACHE_DIR, require_tf, slow
  
  
  if is_tf_available():
      import tensorflow as tf
      from transformers import (
          TFTransfoXLModel,
          TFTransfoXLLMHeadModel,
          TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP,
      )
  
  
  @require_tf
  class TFTransfoXLModelTest(TFModelTesterMixin, unittest.TestCase):
  
      all_model_classes = (TFTransfoXLModel, TFTransfoXLLMHeadModel) if is_tf_available() else ()
      all_generative_model_classes = () if is_tf_available() else ()
      # TODO: add this test when TFTransfoXLLMHead has a linear output layer implemented
      test_pruning = False
      test_torchscript = False
      test_resize_embeddings = False
  
      class TFTransfoXLModelTester(object):
          def __init__(
              self,
              parent,
              batch_size=13,
              seq_length=7,
              mem_len=30,
              clamp_len=15,
              is_training=True,
              use_labels=True,
              vocab_size=99,
              cutoffs=[10, 50, 80],
              hidden_size=32,
              d_embed=32,
              num_attention_heads=4,
              d_head=8,
              d_inner=128,
              div_val=2,
              num_hidden_layers=5,
              scope=None,
              seed=1,
              eos_token_id=0,
          ):
              self.parent = parent
              self.batch_size = batch_size
              self.seq_length = seq_length
              self.mem_len = mem_len
              self.key_length = seq_length + mem_len
              self.clamp_len = clamp_len
              self.is_training = is_training
              self.use_labels = use_labels
              self.vocab_size = vocab_size
              self.cutoffs = cutoffs
              self.hidden_size = hidden_size
              self.d_embed = d_embed
              self.num_attention_heads = num_attention_heads
              self.d_head = d_head
              self.d_inner = d_inner
              self.div_val = div_val
              self.num_hidden_layers = num_hidden_layers
              self.scope = scope
              self.seed = seed
              self.eos_token_id = eos_token_id
  
          def prepare_config_and_inputs(self):
              input_ids_1 = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
              input_ids_2 = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
  
              lm_labels = None
              if self.use_labels:
                  lm_labels = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
  
              config = TransfoXLConfig(
                  vocab_size=self.vocab_size,
                  mem_len=self.mem_len,
                  clamp_len=self.clamp_len,
                  cutoffs=self.cutoffs,
                  d_model=self.hidden_size,
                  d_embed=self.d_embed,
                  n_head=self.num_attention_heads,
                  d_head=self.d_head,
                  d_inner=self.d_inner,
                  div_val=self.div_val,
                  n_layer=self.num_hidden_layers,
                  eos_token_id=self.eos_token_id,
              )
  
              return (config, input_ids_1, input_ids_2, lm_labels)
  
          def set_seed(self):
              random.seed(self.seed)
              tf.random.set_seed(self.seed)
  
          def create_and_check_transfo_xl_model(self, config, input_ids_1, input_ids_2, lm_labels):
              model = TFTransfoXLModel(config)
  
              hidden_states_1, mems_1 = model(input_ids_1)
  
              inputs = {"input_ids": input_ids_2, "mems": mems_1}
  
              hidden_states_2, mems_2 = model(inputs)
  
              result = {
                  "hidden_states_1": hidden_states_1.numpy(),
                  "mems_1": [mem.numpy() for mem in mems_1],
                  "hidden_states_2": hidden_states_2.numpy(),
                  "mems_2": [mem.numpy() for mem in mems_2],
              }
  
              self.parent.assertListEqual(
                  list(result["hidden_states_1"].shape), [self.batch_size, self.seq_length, self.hidden_size]
              )
              self.parent.assertListEqual(
                  list(result["hidden_states_2"].shape), [self.batch_size, self.seq_length, self.hidden_size]
              )
              self.parent.assertListEqual(
                  list(list(mem.shape) for mem in result["mems_1"]),
                  [[self.mem_len, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
              )
              self.parent.assertListEqual(
                  list(list(mem.shape) for mem in result["mems_2"]),
                  [[self.mem_len, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
              )
  
          def create_and_check_transfo_xl_lm_head(self, config, input_ids_1, input_ids_2, lm_labels):
              model = TFTransfoXLLMHeadModel(config)
  
              lm_logits_1, mems_1 = model(input_ids_1)
  
              inputs = {"input_ids": input_ids_1, "labels": lm_labels}
              _, mems_1 = model(inputs)
  
              lm_logits_2, mems_2 = model([input_ids_2, mems_1])
  
              inputs = {"input_ids": input_ids_1, "mems": mems_1, "labels": lm_labels}
  
              _, mems_2 = model(inputs)
  
              result = {
                  "mems_1": [mem.numpy() for mem in mems_1],
                  "lm_logits_1": lm_logits_1.numpy(),
                  "mems_2": [mem.numpy() for mem in mems_2],
                  "lm_logits_2": lm_logits_2.numpy(),
              }
  
              self.parent.assertListEqual(
                  list(result["lm_logits_1"].shape), [self.batch_size, self.seq_length, self.vocab_size]
              )
              self.parent.assertListEqual(
                  list(list(mem.shape) for mem in result["mems_1"]),
                  [[self.mem_len, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
              )
  
              self.parent.assertListEqual(
                  list(result["lm_logits_2"].shape), [self.batch_size, self.seq_length, self.vocab_size]
              )
              self.parent.assertListEqual(
                  list(list(mem.shape) for mem in result["mems_2"]),
                  [[self.mem_len, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
              )
  
          def prepare_config_and_inputs_for_common(self):
              config_and_inputs = self.prepare_config_and_inputs()
              (config, input_ids_1, input_ids_2, lm_labels) = config_and_inputs
              inputs_dict = {"input_ids": input_ids_1}
              return config, inputs_dict
  
      def setUp(self):
          self.model_tester = TFTransfoXLModelTest.TFTransfoXLModelTester(self)
          self.config_tester = ConfigTester(self, config_class=TransfoXLConfig, d_embed=37)
  
      def test_config(self):
          self.config_tester.run_common_tests()
  
      def test_transfo_xl_model(self):
          self.model_tester.set_seed()
          config_and_inputs = self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_transfo_xl_model(*config_and_inputs)
  
      def test_transfo_xl_lm_head(self):
          self.model_tester.set_seed()
          config_and_inputs = self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_transfo_xl_lm_head(*config_and_inputs)
  
      @slow
      def test_model_from_pretrained(self):
          for model_name in list(TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
              model = TFTransfoXLModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
              self.assertIsNotNone(model)
  
  
  class TFTransfoXLModelLanguageGenerationTest(unittest.TestCase):
      @slow
      def test_lm_generate_transfo_xl_wt103(self):
          model = TFTransfoXLLMHeadModel.from_pretrained("transfo-xl-wt103")
          input_ids = tf.convert_to_tensor(
              [
                  [
                      33,
                      1297,
                      2,
                      1,
                      1009,
                      4,
                      1109,
                      11739,
                      4762,
                      358,
                      5,
                      25,
                      245,
                      22,
                      1706,
                      17,
                      20098,
                      5,
                      3215,
                      21,
                      37,
                      1110,
                      3,
                      13,
                      1041,
                      4,
                      24,
                      603,
                      490,
                      2,
                      71477,
                      20098,
                      104447,
                      2,
                      20961,
                      1,
                      2604,
                      4,
                      1,
                      329,
                      3,
                      6224,
                      831,
                      16002,
                      2,
                      8,
                      603,
                      78967,
                      29546,
                      23,
                      803,
                      20,
                      25,
                      416,
                      5,
                      8,
                      232,
                      4,
                      277,
                      6,
                      1855,
                      4601,
                      3,
                      29546,
                      54,
                      8,
                      3609,
                      5,
                      57211,
                      49,
                      4,
                      1,
                      277,
                      18,
                      8,
                      1755,
                      15691,
                      3,
                      341,
                      25,
                      416,
                      693,
                      42573,
                      71,
                      17,
                      401,
                      94,
                      31,
                      17919,
                      2,
                      29546,
                      7873,
                      18,
                      1,
                      435,
                      23,
                      11011,
                      755,
                      5,
                      5167,
                      3,
                      7983,
                      98,
                      84,
                      2,
                      29546,
                      3267,
                      8,
                      3609,
                      4,
                      1,
                      4865,
                      1075,
                      2,
                      6087,
                      71,
                      6,
                      346,
                      8,
                      5854,
                      3,
                      29546,
                      824,
                      1400,
                      1868,
                      2,
                      19,
                      160,
                      2,
                      311,
                      8,
                      5496,
                      2,
                      20920,
                      17,
                      25,
                      15097,
                      3,
                      24,
                      24,
                      0,
                  ]
              ],
              dtype=tf.int32,
          )
          #  In 1991 , the remains of Russian Tsar Nicholas II and his family
          #  ( except for Alexei and Maria ) are discovered .
          #  The voice of Nicholas's young son , Tsarevich Alexei Nikolaevich , narrates the
          #  remainder of the story . 1883 Western Siberia ,
          #  a young Grigori Rasputin is asked by his father and a group of men to perform magic .
          #  Rasputin has a vision and denounces one of the men as a horse thief . Although his
          #  father initially slaps him for making such an accusation , Rasputin watches as the
          #  man is chased outside and beaten . Twenty years later , Rasputin sees a vision of
          #  the Virgin Mary , prompting him to become a priest . Rasputin quickly becomes famous ,
          #  with people , even a bishop , begging for his blessing . <eod> </s> <eos>
  
          expected_output_ids = [
              33,
              1297,
              2,
              1,
              1009,
              4,
              1109,
              11739,
              4762,
              358,
              5,
              25,
              245,
              22,
              1706,
              17,
              20098,
              5,
              3215,
              21,
              37,
              1110,
              3,
              13,
              1041,
              4,
              24,
              603,
              490,
              2,
              71477,
              20098,
              104447,
              2,
              20961,
              1,
              2604,
              4,
              1,
              329,
              3,
              6224,
              831,
              16002,
              2,
              8,
              603,
              78967,
              29546,
              23,
              803,
              20,
              25,
              416,
              5,
              8,
              232,
              4,
              277,
              6,
              1855,
              4601,
              3,
              29546,
              54,
              8,
              3609,
              5,
              57211,
              49,
              4,
              1,
              277,
              18,
              8,
              1755,
              15691,
              3,
              341,
              25,
              416,
              693,
              42573,
              71,
              17,
              401,
              94,
              31,
              17919,
              2,
              29546,
              7873,
              18,
              1,
              435,
              23,
              11011,
              755,
              5,
              5167,
              3,
              7983,
              98,
              84,
              2,
              29546,
              3267,
              8,
              3609,
              4,
              1,
              4865,
              1075,
              2,
              6087,
              71,
              6,
              346,
              8,
              5854,
              3,
              29546,
              824,
              1400,
              1868,
              2,
              19,
              160,
              2,
              311,
              8,
              5496,
              2,
              20920,
              17,
              25,
              15097,
              3,
              24,
              24,
              0,
              33,
              1,
              1857,
              2,
              1,
              1009,
              4,
              1109,
              11739,
              4762,
              358,
              5,
              25,
              245,
              28,
              1110,
              3,
              13,
              1041,
              4,
              24,
              603,
              490,
              2,
              71477,
              20098,
              104447,
              2,
              20961,
              1,
              2604,
              4,
              1,
              329,
              3,
              0,
          ]
          #  In 1991, the remains of Russian Tsar Nicholas II and his family (
          #  except for Alexei and Maria ) are discovered. The voice of young son,
          #  Tsarevich Alexei Nikolaevich, narrates the remainder of the story.
          #  1883 Western Siberia, a young Grigori Rasputin is asked by his father
          #  and a group of men to perform magic. Rasputin has a vision and
          #  denounces one of the men as a horse thief. Although his father initially
          #  slaps him for making such an accusation, Rasputin watches as the man
          #  is chased outside and beaten. Twenty years later, Rasputin sees a vision
          #  of the Virgin Mary, prompting him to become a priest.
          #  Rasputin quickly becomes famous, with people, even a bishop, begging for
          #  his blessing. <unk> <unk> <eos> In the 1990s, the remains of Russian Tsar
          # Nicholas II and his family were discovered. The voice of <unk> young son,
          # Tsarevich Alexei Nikolaevich, narrates the remainder of the story.<eos>
  
          output_ids = model.generate(input_ids, max_length=200, do_sample=False)
          self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
  