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# 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(
torch.allclose(
resulting_tensor[:3],
torch.tensor([-0.0005966668832115829, -0.0003657640190795064, -0.00013439502799883485]),
)
)
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(
torch.allclose(
resulting_tensor[:3],
torch.tensor([-0.0005966668832115829, -0.0003657640190795064, -0.00013439502799883485]),
)
)
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