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Added normal with extra value.

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This commit is contained in:
Tim Dettmers 2023-04-02 14:09:08 -07:00
parent 2dd5d69056
commit 0d332a641f
2 changed files with 23 additions and 8 deletions
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28
bitsandbytes/functional.py
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@ -9,7 +9,7 @@ import random
import torch
import itertools
import math
import scipy.stats
from scipy.stats import norm
import numpy as np
from functools import reduce # Required in Python 3
@ -181,7 +181,7 @@ def create_custom_map(seed=0, scale=0.01):
#v = [1.6072478919002173, 1.1864907014855421, 0.9099343314196248, 0.6898544638558411, 0.4990924080314459, 0.32505049268156666, 0.16039309503073892] # 0.946 24.207
#v = [1.6118251211466303, 1.188665228776879, 0.9112895004060624, 0.690763326564427, 0.4997008778346997, 0.3254280317127771, 0.16057446047146948] # 0.9465 24.30
#v = [1.6027040905517569, 1.184321770169049, 0.9085808314549837, 0.6889461706317986, 0.4984841229538408, 0.32467299997597887, 0.1602117348657326] # 0.9455 24.293
#v = [1.6072478919002173, 1.1864907014855421, 0.9099343314196248, 0.6898544638558411, 0.4990924080314459, 0.32505049268156666, 0.16039309503073892] # 0.946 24.37 22.88
v = [1.6072478919002173, 1.1864907014855421, 0.9099343314196248, 0.6898544638558411, 0.4990924080314459, 0.32505049268156666, 0.16039309503073892] # 0.946 24.37 22.88
# 7B evo start
#v = [1.62129629, 1.18870191, 0.90848106, 0.69108646, 0.50515268, 0.34927819905, 0.14122701] # 22.06
@ -197,9 +197,7 @@ def create_custom_map(seed=0, scale=0.01):
#v = [1.5993337549066253, 1.1965624035328402, 0.9000864380418481, 0.6925840978034195, 0.5011181210961458, 0.32040328389777434, 0.13570386022711237]
# theoretically optiomal (0.93333)
v = [1.501085946044025, 1.1331700302595604, 0.8761428492468408, 0.6670160135425023, 0.48373855304610314, 0.3155014472579608, 0.15580024666388428] # 0.9333333333333333
#v = [1.501085946044025, 1.1331700302595604, 0.8761428492468408, 0.6670160135425023, 0.48373855304610314, 0.3155014472579608, 0.15580024666388428] # 0.9333333333333333
if seed > 0:
v = np.array(v)
@ -220,6 +218,26 @@ def create_custom_map(seed=0, scale=0.01):
assert values.numel() == 256
return values
def create_normal_map(offset=0.966666, use_extra_value=True):
if use_extra_value:
# one more positive value, this is an asymmetric type
v1 = norm.ppf(torch.linspace(offset, 0.5, 9)[:-1]).tolist()
v2 = [0]*(256-15) ## we have 15 non-zero values in this data type
v3 = (-norm.ppf(torch.linspace(offset, 0.5, 8)[:-1])).tolist()
v = v1 + v2 + v3
else:
v1 = norm.ppf(torch.linspace(offset, 0.5, 8)[:-1]).tolist()
v2 = [0]*(256-14) ## we have 14 non-zero values in this data type
v3 = (-norm.ppf(torch.linspace(offset, 0.5, 8)[:-1])).tolist()
v = v1 + v2 + v3
values = torch.Tensor(v)
values = values.sort().values
values /= values.max()
assert values.numel() == 256
return values
def create_fp8_map(signed=True, exponent_bits=5, precision_bits=2, total_bits=8):
e = exponent_bits
p = precision_bits

3
tests/test_functional.py
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@ -2318,6 +2318,3 @@ def test_bench_fp4_dequant():
# torch.matmul(b, a.t())
#torch.cuda.synchronize()
#print((time.time()-t0)/iters*1e6)