
'''simple docstring'''







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 			lowerCAmelCase__       (  unittest.TestCase   ,						lowerCamelCase_					):






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					int													=	load_tool('''text-to-speech'''		)
											self.tool.setup()






					def      _snake_case   (       self		):


											"""simple docstring"""





											torch.manual_seed(0		)
											lowercase_     :					Tuple													=	self.tool('''hey'''		)
											lowercase_     :					str													=	result.to_raw()
											self.assertTrue(
											    torch.allclose(
											        resulting_tensor[:3]    ,							torch.tensor([-0.0_005_966_668_832_115_829, -0.0_003_657_640_190_795_064, -0.00_013_439_502_799_883_485]		)    ,							)		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											torch.manual_seed(0		)
											lowercase_     :					str													=	self.tool('''hey'''		)
											lowercase_     :					Dict													=	result.to_raw()
											self.assertTrue(
											    torch.allclose(
											        resulting_tensor[:3]    ,							torch.tensor([-0.0_005_966_668_832_115_829, -0.0_003_657_640_190_795_064, -0.00_013_439_502_799_883_485]		)    ,							)		)





'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase			:  List[Any]   							=	{
    "configuration_x_clip": [
        "XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "XCLIPConfig",
        "XCLIPTextConfig",
        "XCLIPVisionConfig",
    ],
    "processing_x_clip": ["XCLIPProcessor"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase			:  int   							=	[
							    "XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "XCLIPModel",
							    "XCLIPPreTrainedModel",
							    "XCLIPTextModel",
							    "XCLIPVisionModel",
							]

if TYPE_CHECKING:
							from .configuration_x_clip import (
							    XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    XCLIPConfig,
							    XCLIPTextConfig,
							    XCLIPVisionConfig,
							)
							from .processing_x_clip import XCLIPProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_x_clip import (
														    XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    XCLIPModel,
														    XCLIPPreTrainedModel,
														    XCLIPTextModel,
														    XCLIPVisionModel,
														)

else:
							import sys

							_lowercase			:  List[str]   							=	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



