From bfa0e33294f2b1dc25e65a33be2397f989824298 Mon Sep 17 00:00:00 2001 From: Titus von Koeller Date: Mon, 1 Aug 2022 03:31:48 -0700 Subject: ran black and isort for coherent code formatting --- bitsandbytes/optim/lamb.py | 117 +++++++++++++++++++++++++++++++++++++-------- 1 file changed, 97 insertions(+), 20 deletions(-) (limited to 'bitsandbytes/optim/lamb.py') diff --git a/bitsandbytes/optim/lamb.py b/bitsandbytes/optim/lamb.py index 58cc13d..8f365f7 100644 --- a/bitsandbytes/optim/lamb.py +++ b/bitsandbytes/optim/lamb.py @@ -1,28 +1,105 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the +# 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) + 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) +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, + ) -- cgit v1.2.3