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__init__.py
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# Copyright 2023 Salesforce authors, The EleutherAI, and HuggingFace Teams. All rights reserved.
#
# 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.
from typing import TYPE_CHECKING
from transformers.utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_import_structure = {
"configuration_moduleformer": ["SPARSEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ModuleFormerConfig", "ModuleFormerOnnxConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["modeling_moduleformer"] = [
"SPARSEGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
"ModuleFormerForCausalLM",
"ModuleFormerModel",
"ModuleFormerPreTrainedModel",
"ModuleFormerForSequenceClassification",
]
if TYPE_CHECKING:
from .configuration_moduleformer import SPARSEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ModuleFormerConfig, ModuleFormerOnnxConfig
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .modeling_moduleformer import (
SPARSEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
ModuleFormerForCausalLM,
ModuleFormerModel,
ModuleFormerPreTrainedModel,
ModuleFormerForSequenceClassification,
)
else:
import sys
sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)