content: from copy import copy
  
  import pytest
  import torch
  from transformers import AutoTokenizer
  
  from lorax_server.models.seq2seq_lm import Seq2SeqLM, Seq2SeqLMBatch
  from lorax_server.pb import generate_pb2
  from lorax_server.utils.tokenizer import TokenizerManager
  
  
  @pytest.fixture(scope="session")
  def mt0_small_tokenizer():
      tokenizer = AutoTokenizer.from_pretrained(
          "bigscience/mt0-small", padding_side="left"
      )
      tokenizer.bos_token_id = 0
      return tokenizer
  
  
  @pytest.fixture(scope="session")
  def default_seq2seq_lm():
      return Seq2SeqLM("bigscience/mt0-small")
  
  
  @pytest.fixture
  def default_pb_request(default_pb_parameters, default_pb_stop_parameters):
      return generate_pb2.Request(
          id=0,
          inputs="Test",
          prefill_logprobs=True,
          truncate=100,
          parameters=default_pb_parameters,
          stopping_parameters=default_pb_stop_parameters,
      )
  
  
  @pytest.fixture
  def default_pb_batch(default_pb_request):
      return generate_pb2.Batch(id=0, requests=[default_pb_request], size=1)
  
  
  @pytest.fixture
  def default_seq2seq_lm_batch(default_pb_batch, mt0_small_tokenizer):
      return Seq2SeqLMBatch.from_pb(
          default_pb_batch, mt0_small_tokenizer, TokenizerManager(), None, None, torch.float32, torch.device("cpu")
      )
  
  
  @pytest.fixture
  def default_multi_requests_seq2seq_lm_batch(default_pb_request, mt0_small_tokenizer):
      req_0 = copy(default_pb_request)
      req_0.id = 1
      req_1 = default_pb_request
      req_1.id = 2
      req_1.stopping_parameters.max_new_tokens = 5
  
      batch_pb = generate_pb2.Batch(id=0, requests=[req_0, req_1], size=2)
      return Seq2SeqLMBatch.from_pb(
          batch_pb, mt0_small_tokenizer, TokenizerManager(), None, None, torch.float32, torch.device("cpu")
      )
  
  
  def test_batch_from_pb(default_pb_batch, default_seq2seq_lm_batch):
      batch = default_seq2seq_lm_batch
      sequence_length = len(default_seq2seq_lm_batch.input_ids[0])
  
      assert batch.batch_id == default_pb_batch.id
      assert batch.requests == default_pb_batch.requests
  
      assert batch.input_ids.shape == (default_pb_batch.size, sequence_length)
      assert batch.input_ids[0][-2] == 4268
      assert batch.input_ids[0][-1] == 1
      assert torch.all(batch.input_ids[0][:-2] == 0)
  
      assert torch.all(batch.attention_mask[0][-2:] == 1)
      assert torch.all(batch.attention_mask[0][:-2] == 0)
  
      assert len(batch.decoder_input_ids) == default_pb_batch.size
      assert batch.decoder_attention_mask is None
      assert batch.encoder_last_hidden_state is None
  
      assert batch.past_key_values is None
  
      assert batch.input_lengths == [2]
      assert batch.decoder_input_lengths == [1]
  
      assert len(batch) == default_pb_batch.size
      assert len(batch.next_token_choosers) == len(batch.stopping_criterias) == len(batch)
  
      assert batch.max_input_length == batch.input_lengths[0]
      assert batch.max_decoder_input_length == batch.decoder_input_lengths[0]
  
  
  def test_batch_concatenate_no_prefill(default_seq2seq_lm_batch):
      with pytest.raises(ValueError):
          Seq2SeqLMBatch.concatenate([default_seq2seq_lm_batch, default_seq2seq_lm_batch])
  
  
  def test_seq2seq_lm_batch_type(default_seq2seq_lm):
      assert default_seq2seq_lm.batch_type == Seq2SeqLMBatch
  
  
  def test_seq2seq_lm_generate_token(default_seq2seq_lm, default_seq2seq_lm_batch):
      sequence_length = len(default_seq2seq_lm_batch.input_ids[0])
      generations, next_batch = default_seq2seq_lm.generate_token(
          default_seq2seq_lm_batch
      )
  
      assert len(generations) == len(next_batch)
      assert isinstance(next_batch, Seq2SeqLMBatch)
  
      assert next_batch.input_ids is None
      assert torch.equal(
          next_batch.attention_mask, default_seq2seq_lm_batch.attention_mask
      )
      assert next_batch.input_lengths == default_seq2seq_lm_batch.input_lengths
      assert next_batch.max_input_length == default_seq2seq_lm_batch.max_input_length
      assert (
          next_batch.next_token_choosers == default_seq2seq_lm_batch.next_token_choosers
      )
      assert next_batch.stopping_criterias == default_seq2seq_lm_batch.stopping_criterias
  
      assert len(next_batch.decoder_input_ids) == len(next_batch)
      assert next_batch.all_decoder_input_ids[0][0] == 0
      assert next_batch.all_decoder_input_ids[0][1] == 259
      assert next_batch.decoder_attention_mask is None
      assert next_batch.encoder_last_hidden_state.shape == (1, sequence_length, 512)
  
      assert next_batch.decoder_input_lengths == [2]
      assert next_batch.max_decoder_input_length == 2
  
      assert next_batch.past_key_values is not None
      assert all(
          [p[0].shape == (len(next_batch), 6, 1, 64) for p in next_batch.past_key_values]
      )
      assert all(
          [p[1].shape == (len(next_batch), 6, 1, 64) for p in next_batch.past_key_values]
      )
      assert all(
          [
              p[2].shape == (len(next_batch), 6, sequence_length, 64)
              for p in next_batch.past_key_values
          ]
      )
      assert all(
          [
              p[3].shape == (len(next_batch), 6, sequence_length, 64)
              for p in next_batch.past_key_values
          ]
      )
      assert all([generation.generated_text is None for generation in generations])
      assert all([len(generation.prefill_tokens) == 1 for generation in generations])
      assert all([generation.next_tokens.token_ids[0] == 259 for generation in generations])
      assert all([generation.next_tokens.texts[0] == " " for generation in generations])
      assert generations[0].request_id == 0
  
  
  def test_seq2seq_lm_generate_token_completion(
      default_seq2seq_lm, default_seq2seq_lm_batch
  ):
      next_batch = default_seq2seq_lm_batch
      for _ in range(6):
          generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
          assert len(generations) == len(next_batch)
  
      generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
      assert next_batch is None
  
      assert len(generations) == 1
      assert generations[0].generated_text.text == "a few weeks"
      assert generations[0].request_id == default_seq2seq_lm_batch.requests[0].id
      assert generations[0].generated_text.generated_tokens == 7
  
  
  def test_seq2seq_lm_generate_token_completion_multi(
      default_seq2seq_lm, default_multi_requests_seq2seq_lm_batch
  ):
      next_batch = default_multi_requests_seq2seq_lm_batch
  
      for i in range(4):
          generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
          assert len(generations) == len(next_batch)
  
      generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
      assert next_batch is not None
  
      assert len(generations) == 2
      assert generations[1].generated_text.text == "a few "
      assert (
          generations[1].request_id
          == default_multi_requests_seq2seq_lm_batch.requests[1].id
      )
      assert generations[1].generated_text.generated_tokens == 5
  
      next_batch = next_batch.filter([next_batch.requests[0].id])
  
      generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
      assert len(generations) == len(next_batch)
  
      generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
      assert next_batch is None
  
      assert len(generations) == 1
      assert generations[0].generated_text.text == "a few weeks"
      assert (
          generations[0].request_id
          == default_multi_requests_seq2seq_lm_batch.requests[0].id
      )
      assert generations[0].generated_text.generated_tokens == 7
  
  
  def test_batch_concatenate(
      default_seq2seq_lm,
      default_seq2seq_lm_batch,
      default_multi_requests_seq2seq_lm_batch,
  ):
      next_batch_0 = default_seq2seq_lm_batch
      _, next_batch_0 = default_seq2seq_lm.generate_token(next_batch_0)
      _, next_batch_0 = default_seq2seq_lm.generate_token(next_batch_0)
  
      next_batch_1 = default_multi_requests_seq2seq_lm_batch
      _, next_batch_1 = default_seq2seq_lm.generate_token(next_batch_1)
  
      # Copy hidden state because it is removed from the concatenated branches
      next_batch_0_encoder_last_hidden_state = next_batch_0.encoder_last_hidden_state
      next_batch_1_encoder_last_hidden_state = next_batch_1.encoder_last_hidden_state
  
      # Clone past_key_values before concatenating to compare after,
      # because they are removed from the concatenated batches
      next_batch_0_past_key_values = [
          [t.clone() for t in layer] for layer in next_batch_0.past_key_values
      ]
      next_batch_1_past_key_values = [
          [t.clone() for t in layer] for layer in next_batch_1.past_key_values
      ]
  
      next_batch = Seq2SeqLMBatch.concatenate([next_batch_0, next_batch_1])
  
      assert next_batch.batch_id == 0
  
      assert torch.equal(
          next_batch.decoder_input_ids[0], next_batch_0.decoder_input_ids[0]
      )
      assert next_batch.all_decoder_input_ids[1][0] == 0
      assert next_batch.all_decoder_input_ids[2][0] == 0
      assert torch.equal(
          next_batch.decoder_input_ids[1:, -2:], next_batch_1.decoder_input_ids
      )
  
      assert torch.all(next_batch.decoder_attention_mask[0, :3] == 1)
      assert torch.all(next_batch.decoder_attention_mask[0, 3:] == 0)
      assert torch.all(next_batch.decoder_attention_mask[1:, 0] == 0)
      assert torch.all(next_batch.decoder_attention_mask[1:, 1:3] == 1)
  
      assert torch.equal(
          next_batch.encoder_last_hidden_state[0],
          next_batch_0_encoder_last_hidden_state[0, -2:],
      )
      assert torch.equal(
          next_batch.encoder_last_hidden_state[1:],
          next_batch_1_encoder_last_hidden_state[:, -2:],
      )
  
      assert next_batch.input_lengths == [2, 2, 2]
      assert next_batch.decoder_input_lengths == [3, 2, 2]
      assert next_batch.max_input_length == 2
      assert next_batch.max_decoder_input_length == 3
  
      assert next_batch.requests[0] == next_batch_0.requests[0]
      assert next_batch.requests[1:] == next_batch_1.requests
  
      assert next_batch.next_token_choosers[0] == next_batch_0.next_token_choosers[0]
      assert next_batch.next_token_choosers[1:] == next_batch_1.next_token_choosers
  
      assert next_batch.stopping_criterias[0] == next_batch_0.stopping_criterias[0]
      assert next_batch.stopping_criterias[1:] == next_batch_1.stopping_criterias
  
      assert next_batch.past_key_values is not None
      assert all(
          [p[0].shape == (len(next_batch), 6, 2, 64) for p in next_batch.past_key_values]
      )
      assert all(
          [p[1].shape == (len(next_batch), 6, 2, 64) for p in next_batch.past_key_values]
      )
      assert all(
          [p[2].shape == (len(next_batch), 6, 2, 64) for p in next_batch.past_key_values]
      )
      assert all(
          [p[3].shape == (len(next_batch), 6, 2, 64) for p in next_batch.past_key_values]
      )
  
      for i, past in enumerate(next_batch.past_key_values):
          assert torch.equal(next_batch_0_past_key_values[i][0][0, :, -2:, :], past[0][0])
          assert torch.equal(
              next_batch_1_past_key_values[i][0][:, :, -1:, :], past[0][1:, :, -1:, :]
          )
  
          assert torch.equal(next_batch_0_past_key_values[i][1][0, :, -2:, :], past[1][0])
          assert torch.equal(
              next_batch_1_past_key_values[i][1][:, :, -1:, :], past[1][1:, :, -1:, :]
          )
  
          assert torch.equal(next_batch_0_past_key_values[i][2][0, :, -2:, :], past[2][0])
          assert torch.equal(
              next_batch_1_past_key_values[i][2][:, :, -2:, :], past[2][1:]
          )
  
          assert torch.equal(next_batch_0_past_key_values[i][3][0, :, -2:, :], past[3][0])
          assert torch.equal(
              next_batch_1_past_key_values[i][3][:, :, -2:, :], past[3][1:]
          )
  
      for _ in range(3):
          generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
          assert len(generations) == len(next_batch)
  
      generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
      assert next_batch is not None
  
      assert len(generations) == 3
      assert generations[2].generated_text.text == "a few "
      assert (
          generations[2].request_id
          == default_multi_requests_seq2seq_lm_batch.requests[1].id
      )
      assert generations[2].generated_text.generated_tokens == 5
  
      next_batch = next_batch.filter(
          [next_batch.requests[0].id, next_batch.requests[1].id]
      )
  
      generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
      assert next_batch is not None
  
      assert len(generations) == 2
      assert generations[0].generated_text.text == "a few weeks"
      assert generations[0].request_id == default_seq2seq_lm_batch.requests[0].id
      assert generations[0].generated_text.generated_tokens == 7
  
      next_batch = next_batch.filter([next_batch.requests[1].id])
  
      generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
      assert next_batch is None
  
      assert len(generations) == 1
      assert generations[0].generated_text.text == "a few weeks"
      assert (
          generations[0].request_id
          == default_multi_requests_seq2seq_lm_batch.requests[0].id
      )
      assert generations[0].generated_text.generated_tokens == 7
  