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60 lines
2.2 KiB
Python
60 lines
2.2 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Optional, Union
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from ...layers import MoeConfig
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from ..modeling_utils import PretrainedConfig
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class DbrxConfig(PretrainedConfig):
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def __init__(self,
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*,
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bias: bool = False,
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clip_qkv: Optional[float] = None,
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rotary_base: float = 500000.0,
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rotary_scaling: Optional[dict] = None,
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moe: Optional[Union[MoeConfig, dict]] = None,
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**kwargs):
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self.bias = bias
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self.clip_qkv = clip_qkv
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self.rotary_base = rotary_base
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self.rotary_scaling = rotary_scaling
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if moe is None:
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# Legacy MOE config fields
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moe = MoeConfig(
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num_experts=kwargs.pop('moe_num_experts', 0),
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top_k=kwargs.pop('moe_top_k', 0),
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normalization_mode=kwargs.pop(
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'moe_normalization_mode',
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MoeConfig.ExpertScaleNormalizationMode.RENORMALIZE))
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elif isinstance(moe, dict):
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moe = MoeConfig.from_dict(moe)
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assert isinstance(moe, MoeConfig)
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self.moe = moe.validate()
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super().__init__(**kwargs)
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def to_dict(self):
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output = super().to_dict()
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# Serialize the fields added in DbrxConfig
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output['bias'] = self.bias
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output['clip_qkv'] = self.clip_qkv
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output['rotary_base'] = self.rotary_base
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output['rotary_scaling'] = self.rotary_scaling
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output['moe'] = self.moe.to_dict()
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return output
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