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# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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 Optional, Union
from ...layers import MoeConfig
from ..modeling_utils import PretrainedConfig
class DbrxConfig(PretrainedConfig):
def __init__(self,
*,
bias: bool = False,
clip_qkv: Optional[float] = None,
rotary_base: float = 500000.0,
rotary_scaling: Optional[dict] = None,
moe: Optional[Union[MoeConfig, dict]] = None,
**kwargs):
self.bias = bias
self.clip_qkv = clip_qkv
self.rotary_base = rotary_base
self.rotary_scaling = rotary_scaling
if moe is None:
# Legacy MOE config fields
moe = MoeConfig(
num_experts=kwargs.pop('moe_num_experts', 0),
top_k=kwargs.pop('moe_top_k', 0),
normalization_mode=kwargs.pop(
'moe_normalization_mode',
MoeConfig.ExpertScaleNormalizationMode.RENORMALIZE))
elif isinstance(moe, dict):
moe = MoeConfig.from_dict(moe)
assert isinstance(moe, MoeConfig)
self.moe = moe.validate()
super().__init__(**kwargs)
def to_dict(self):
output = super().to_dict()
# Serialize the fields added in DbrxConfig
output['bias'] = self.bias
output['clip_qkv'] = self.clip_qkv
output['rotary_base'] = self.rotary_base
output['rotary_scaling'] = self.rotary_scaling
output['moe'] = self.moe.to_dict()
return output
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