File size: 1,950 Bytes
76f9669 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | # Copyright (c) 2021 - present / Neuralmagic, Inc. 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 enum import Enum
from compressed_tensors.utils import delete_offload_parameter
from torch.nn import Module
__all__ = ["QuantizationMetadata", "KVCacheScaleType"]
class KVCacheScaleType(Enum):
KEY = "k_scale"
VALUE = "v_scale"
class QuantizationMetadata:
"""
Container class for metadata related to quantization
"""
@staticmethod
def all_qparam_names():
"""
All quantization parameter names that might be registered
onto a module during lifecycle (excluding serialized parameters)
"""
return [KVCacheScaleType.KEY.value, KVCacheScaleType.VALUE.value] + [
f"{base_name}_{suffix}"
for base_name in ("input", "weight", "output")
for suffix in (
"global_scale",
"scale",
"zero_point",
"g_idx",
)
]
@classmethod
def clear_all_qparams(cls, module: Module):
"""
Remove all parameters related to quantization that might have
been registered onto a module previously in lifecycle (excluding
serialized parameters)
:param module: Module to clear
"""
for key in cls.all_qparam_names():
if hasattr(module, key):
delete_offload_parameter(module, key)
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