# Copyright 2023 The KerasNLP 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
#
#     https://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 pytest

from keras_nlp.src.models.roberta.roberta_tokenizer import RobertaTokenizer
from keras_nlp.src.tests.test_case import TestCase


class RobertaTokenizerTest(TestCase):
    def setUp(self):
        self.vocab = ["<s>", "<pad>", "</s>", "air", "Ġair", "plane", "Ġat"]
        self.vocab += ["port", "<mask>"]
        self.vocab = dict([(token, i) for i, token in enumerate(self.vocab)])
        self.merges = ["Ġ a", "Ġ t", "Ġ i", "Ġ b", "a i", "p l", "n e"]
        self.merges += ["Ġa t", "p o", "r t", "Ġt h", "ai r", "pl a", "po rt"]
        self.merges += ["Ġai r", "Ġa i", "pla ne"]
        self.init_kwargs = {"vocabulary": self.vocab, "merges": self.merges}
        self.input_data = [
            "<s> airplane at airport</s><pad>",
            " airplane airport",
        ]

    def test_tokenizer_basics(self):
        self.run_preprocessing_layer_test(
            cls=RobertaTokenizer,
            init_kwargs=self.init_kwargs,
            input_data=self.input_data,
            # TODO: </s> should not get tokenized as <s>
            expected_output=[[0, 4, 5, 6, 4, 7, 0, 1], [4, 5, 4, 7]],
            expected_detokenize_output=[
                "<s> airplane at airport<s><pad>",
                " airplane airport",
            ],
        )

    def test_errors_missing_special_tokens(self):
        with self.assertRaises(ValueError):
            RobertaTokenizer(vocabulary=["a", "b", "c"], merges=[])

    @pytest.mark.large
    def test_smallest_preset(self):
        self.run_preset_test(
            cls=RobertaTokenizer,
            preset="roberta_base_en",
            input_data=["The quick brown fox."],
            expected_output=[[133, 2119, 6219, 23602, 4]],
        )

    @pytest.mark.extra_large
    def test_all_presets(self):
        for preset in RobertaTokenizer.presets:
            self.run_preset_test(
                cls=RobertaTokenizer,
                preset=preset,
                input_data=self.input_data,
            )

