venv/lib/python3.10/site-packages/bitsandbytes/optim/lamb.py

# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from bitsandbytes.optim.optimizer import Optimizer2State


class LAMB(Optimizer2State):
    def __init__(
        self,
        params,
        lr=1e-3,
        bias_correction=True,
        betas=(0.9, 0.999),
        eps=1e-8,
        weight_decay=0,
        amsgrad=False,
        adam_w_mode=True,
        optim_bits=32,
        args=None,
        min_8bit_size=4096,
        percentile_clipping=100,
        block_wise=False,
        max_unorm=1.0,
    ):
        super(LAMB, self).__init__(
            "lamb",
            params,
            lr,
            betas,
            eps,
            weight_decay,
            optim_bits,
            args,
            min_8bit_size,
            percentile_clipping,
            block_wise,
            max_unorm=1.0,
        )


class LAMB8bit(Optimizer2State):
    def __init__(
        self,
        params,
        lr=1e-3,
        bias_correction=True,
        betas=(0.9, 0.999),
        eps=1e-8,
        weight_decay=0,
        amsgrad=False,
        adam_w_mode=True,
        args=None,
        min_8bit_size=4096,
        percentile_clipping=100,
        block_wise=False,
        max_unorm=1.0,
    ):
        super(LAMB8bit, self).__init__(
            "lamb",
            params,
            lr,
            betas,
            eps,
            weight_decay,
            8,
            args,
            min_8bit_size,
            percentile_clipping,
            block_wise,
            max_unorm=1.0,
        )


class LAMB32bit(Optimizer2State):
    def __init__(
        self,
        params,
        lr=1e-3,
        bias_correction=True,
        betas=(0.9, 0.999),
        eps=1e-8,
        weight_decay=0,
        amsgrad=False,
        adam_w_mode=True,
        args=None,
        min_8bit_size=4096,
        percentile_clipping=100,
        block_wise=False,
        max_unorm=1.0,
    ):
        super(LAMB32bit, self).__init__(
            "lamb",
            params,
            lr,
            betas,
            eps,
            weight_decay,
            32,
            args,
            min_8bit_size,
            percentile_clipping,
            block_wise,
            max_unorm=1.0,
        )