# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# 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 unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
    import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin


@require_torch
class TextToSpeechToolTester(unittest.TestCase, ToolTesterMixin):
    def setUp(self):
        self.tool = load_tool("text_to_speech")
        self.tool.setup()

    def test_exact_match_arg(self):
        # SpeechT5 isn't deterministic
        torch.manual_seed(0)
        result = self.tool("hey")
        resulting_tensor = result.to_raw()
        self.assertTrue(len(resulting_tensor.detach().shape) == 1)
        self.assertTrue(resulting_tensor.detach().shape[0] > 1000)

    def test_exact_match_kwarg(self):
        # SpeechT5 isn't deterministic
        torch.manual_seed(0)
        result = self.tool("hey")
        resulting_tensor = result.to_raw()
        self.assertTrue(len(resulting_tensor.detach().shape) == 1)
        self.assertTrue(resulting_tensor.detach().shape[0] > 1000)