# What does this PR do?

Fix #24650

This is to address the feature request #24650.

Although we have default values of bos/eos been corrected in #24773, the existing config on the Hub still have the incorrect value `1` and `2`, which prevents CLIP model to use new added tokens when a user add them.

Although we can open mass PRs on the Hub, I want to decouple (slightly) this with the ability to support such feature.
With this PR, if a user want to use new added tokens, they has to specify/update the `eos_token_id`.

**We don't need to wait all Hub repo. to be updated to merge this PR.**


Make CLIP model could use new added tokens with meaningful pooling. # What does this PR do?

Fix #24650

This is to address the feature request #24650.

Although we have default values of bos/eos been corrected in #24773, the existing config on the Hub still have the incorrect value `1` and `2`, which prevents CLIP model to use new added tokens when a user add them.

Although we can open mass PRs on the Hub, I want to decouple (slightly) this with the ability to support such feature.
With this PR, if a user want to use new added tokens, they has to specify/update the `eos_token_id`.

**We don't need to wait all Hub repo. to be updated to merge this PR.**


# Copyright 2023 The HuggingFace Team. 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 ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_import_structure = {
    "configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_gpt_bigcode"] = [
        "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST",
        "GPTBigCodeForSequenceClassification",
        "GPTBigCodeForTokenClassification",
        "GPTBigCodeForCausalLM",
        "GPTBigCodeModel",
        "GPTBigCodePreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_gpt_bigcode import (
            GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
            GPTBigCodeForCausalLM,
            GPTBigCodeForSequenceClassification,
            GPTBigCodeForTokenClassification,
            GPTBigCodeModel,
            GPTBigCodePreTrainedModel,
        )


else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

# Copyright 2023 The HuggingFace Team. 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 ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_import_structure = {
    "configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_gpt_bigcode"] = [
        "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST",
        "GPTBigCodeForSequenceClassification",
        "GPTBigCodeForTokenClassification",
        "GPTBigCodeForCausalLM",
        "GPTBigCodeModel",
        "GPTBigCodePreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_gpt_bigcode import (
            GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
            GPTBigCodeForCausalLM,
            GPTBigCodeForSequenceClassification,
            GPTBigCodeForTokenClassification,
            GPTBigCodeModel,
            GPTBigCodePreTrainedModel,
        )


else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
