Note
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About float 8#
Float 8 types were recently introduced to speed up the training of deep learning models.
Possible values#
First E4M3FN.
import pprint
from onnx_array_api.validation.f8 import CastFloat8
pprint.pprint(CastFloat8.values_e4m3fn)
[(-448.0, 254),
(-416.0, 253),
(-384.0, 252),
(-352.0, 251),
(-320.0, 250),
(-288.0, 249),
(-256.0, 248),
(-240.0, 247),
(-224.0, 246),
(-208.0, 245),
(-192.0, 244),
(-176.0, 243),
(-160.0, 242),
(-144.0, 241),
(-128.0, 240),
(-120.0, 239),
(-112.0, 238),
(-104.0, 237),
(-96.0, 236),
(-88.0, 235),
(-80.0, 234),
(-72.0, 233),
(-64.0, 232),
(-60.0, 231),
(-56.0, 230),
(-52.0, 229),
(-48.0, 228),
(-44.0, 227),
(-40.0, 226),
(-36.0, 225),
(-32.0, 224),
(-30.0, 223),
(-28.0, 222),
(-26.0, 221),
(-24.0, 220),
(-22.0, 219),
(-20.0, 218),
(-18.0, 217),
(-16.0, 216),
(-15.0, 215),
(-14.0, 214),
(-13.0, 213),
(-12.0, 212),
(-11.0, 211),
(-10.0, 210),
(-9.0, 209),
(-8.0, 208),
(-7.5, 207),
(-7.0, 206),
(-6.5, 205),
(-6.0, 204),
(-5.5, 203),
(-5.0, 202),
(-4.5, 201),
(-4.0, 200),
(-3.75, 199),
(-3.5, 198),
(-3.25, 197),
(-3.0, 196),
(-2.75, 195),
(-2.5, 194),
(-2.25, 193),
(-2.0, 192),
(-1.875, 191),
(-1.75, 190),
(-1.625, 189),
(-1.5, 188),
(-1.375, 187),
(-1.25, 186),
(-1.125, 185),
(-1.0, 184),
(-0.9375, 183),
(-0.875, 182),
(-0.8125, 181),
(-0.75, 180),
(-0.6875, 179),
(-0.625, 178),
(-0.5625, 177),
(-0.5, 176),
(-0.46875, 175),
(-0.4375, 174),
(-0.40625, 173),
(-0.375, 172),
(-0.34375, 171),
(-0.3125, 170),
(-0.28125, 169),
(-0.25, 168),
(-0.234375, 167),
(-0.21875, 166),
(-0.203125, 165),
(-0.1875, 164),
(-0.171875, 163),
(-0.15625, 162),
(-0.140625, 161),
(-0.125, 160),
(-0.1171875, 159),
(-0.109375, 158),
(-0.1015625, 157),
(-0.09375, 156),
(-0.0859375, 155),
(-0.078125, 154),
(-0.0703125, 153),
(-0.0625, 152),
(-0.05859375, 151),
(-0.0546875, 150),
(-0.05078125, 149),
(-0.046875, 148),
(-0.04296875, 147),
(-0.0390625, 146),
(-0.03515625, 145),
(-0.03125, 144),
(-0.029296875, 143),
(-0.02734375, 142),
(-0.025390625, 141),
(-0.0234375, 140),
(-0.021484375, 139),
(-0.01953125, 138),
(-0.017578125, 137),
(-0.015625, 136),
(-0.013671875, 135),
(-0.01171875, 134),
(-0.009765625, 133),
(-0.0078125, 132),
(-0.005859375, 131),
(-0.00390625, 130),
(-0.001953125, 129),
(0.0, 0),
(-0.0, 128),
(0.001953125, 1),
(0.00390625, 2),
(0.005859375, 3),
(0.0078125, 4),
(0.009765625, 5),
(0.01171875, 6),
(0.013671875, 7),
(0.015625, 8),
(0.017578125, 9),
(0.01953125, 10),
(0.021484375, 11),
(0.0234375, 12),
(0.025390625, 13),
(0.02734375, 14),
(0.029296875, 15),
(0.03125, 16),
(0.03515625, 17),
(0.0390625, 18),
(0.04296875, 19),
(0.046875, 20),
(0.05078125, 21),
(0.0546875, 22),
(0.05859375, 23),
(0.0625, 24),
(0.0703125, 25),
(0.078125, 26),
(0.0859375, 27),
(0.09375, 28),
(0.1015625, 29),
(0.109375, 30),
(0.1171875, 31),
(0.125, 32),
(0.140625, 33),
(0.15625, 34),
(0.171875, 35),
(0.1875, 36),
(0.203125, 37),
(0.21875, 38),
(0.234375, 39),
(0.25, 40),
(0.28125, 41),
(0.3125, 42),
(0.34375, 43),
(0.375, 44),
(0.40625, 45),
(0.4375, 46),
(0.46875, 47),
(0.5, 48),
(0.5625, 49),
(0.625, 50),
(0.6875, 51),
(0.75, 52),
(0.8125, 53),
(0.875, 54),
(0.9375, 55),
(1.0, 56),
(1.125, 57),
(1.25, 58),
(1.375, 59),
(1.5, 60),
(1.625, 61),
(1.75, 62),
(1.875, 63),
(2.0, 64),
(2.25, 65),
(2.5, 66),
(2.75, 67),
(3.0, 68),
(3.25, 69),
(3.5, 70),
(3.75, 71),
(4.0, 72),
(4.5, 73),
(5.0, 74),
(5.5, 75),
(6.0, 76),
(6.5, 77),
(7.0, 78),
(7.5, 79),
(8.0, 80),
(9.0, 81),
(10.0, 82),
(11.0, 83),
(12.0, 84),
(13.0, 85),
(14.0, 86),
(15.0, 87),
(16.0, 88),
(18.0, 89),
(20.0, 90),
(22.0, 91),
(24.0, 92),
(26.0, 93),
(28.0, 94),
(30.0, 95),
(32.0, 96),
(36.0, 97),
(40.0, 98),
(44.0, 99),
(48.0, 100),
(52.0, 101),
(56.0, 102),
(60.0, 103),
(64.0, 104),
(72.0, 105),
(80.0, 106),
(88.0, 107),
(96.0, 108),
(104.0, 109),
(112.0, 110),
(120.0, 111),
(128.0, 112),
(144.0, 113),
(160.0, 114),
(176.0, 115),
(192.0, 116),
(208.0, 117),
(224.0, 118),
(240.0, 119),
(256.0, 120),
(288.0, 121),
(320.0, 122),
(352.0, 123),
(384.0, 124),
(416.0, 125),
(448.0, 126)]
Then E5M2.
[(-inf, 252),
(-57344.0, 251),
(-49152.0, 250),
(-40960.0, 249),
(-32768.0, 248),
(-28672.0, 247),
(-24576.0, 246),
(-20480.0, 245),
(-16384.0, 244),
(-14336.0, 243),
(-12288.0, 242),
(-10240.0, 241),
(-8192.0, 240),
(-7168.0, 239),
(-6144.0, 238),
(-5120.0, 237),
(-4096.0, 236),
(-3584.0, 235),
(-3072.0, 234),
(-2560.0, 233),
(-2048.0, 232),
(-1792.0, 231),
(-1536.0, 230),
(-1280.0, 229),
(-1024.0, 228),
(-896.0, 227),
(-768.0, 226),
(-640.0, 225),
(-512.0, 224),
(-448.0, 223),
(-384.0, 222),
(-320.0, 221),
(-256.0, 220),
(-224.0, 219),
(-192.0, 218),
(-160.0, 217),
(-128.0, 216),
(-112.0, 215),
(-96.0, 214),
(-80.0, 213),
(-64.0, 212),
(-56.0, 211),
(-48.0, 210),
(-40.0, 209),
(-32.0, 208),
(-28.0, 207),
(-24.0, 206),
(-20.0, 205),
(-16.0, 204),
(-14.0, 203),
(-12.0, 202),
(-10.0, 201),
(-8.0, 200),
(-7.0, 199),
(-6.0, 198),
(-5.0, 197),
(-4.0, 196),
(-3.5, 195),
(-3.0, 194),
(-2.5, 193),
(-2.0, 192),
(-1.75, 191),
(-1.5, 190),
(-1.25, 189),
(-1.0, 188),
(-0.875, 187),
(-0.75, 186),
(-0.625, 185),
(-0.5, 184),
(-0.4375, 183),
(-0.375, 182),
(-0.3125, 181),
(-0.25, 180),
(-0.21875, 179),
(-0.1875, 178),
(-0.15625, 177),
(-0.125, 176),
(-0.109375, 175),
(-0.09375, 174),
(-0.078125, 173),
(-0.0625, 172),
(-0.0546875, 171),
(-0.046875, 170),
(-0.0390625, 169),
(-0.03125, 168),
(-0.02734375, 167),
(-0.0234375, 166),
(-0.01953125, 165),
(-0.015625, 164),
(-0.013671875, 163),
(-0.01171875, 162),
(-0.009765625, 161),
(-0.0078125, 160),
(-0.0068359375, 159),
(-0.005859375, 158),
(-0.0048828125, 157),
(-0.00390625, 156),
(-0.0034179688, 155),
(-0.0029296875, 154),
(-0.0024414062, 153),
(-0.001953125, 152),
(-0.0017089844, 151),
(-0.0014648438, 150),
(-0.0012207031, 149),
(-0.0009765625, 148),
(-0.0008544922, 147),
(-0.0007324219, 146),
(-0.00061035156, 145),
(-0.00048828125, 144),
(-0.0004272461, 143),
(-0.00036621094, 142),
(-0.00030517578, 141),
(-0.00024414062, 140),
(-0.00021362305, 139),
(-0.00018310547, 138),
(-0.00015258789, 137),
(-0.00012207031, 136),
(-0.00010681152, 135),
(-9.1552734e-05, 134),
(-7.6293945e-05, 133),
(-6.1035156e-05, 132),
(-4.5776367e-05, 131),
(-3.0517578e-05, 130),
(-1.5258789e-05, 129),
(0.0, 0),
(0.0, 128),
(1.5258789e-05, 1),
(3.0517578e-05, 2),
(4.5776367e-05, 3),
(6.1035156e-05, 4),
(7.6293945e-05, 5),
(9.1552734e-05, 6),
(0.00010681152, 7),
(0.00012207031, 8),
(0.00015258789, 9),
(0.00018310547, 10),
(0.00021362305, 11),
(0.00024414062, 12),
(0.00030517578, 13),
(0.00036621094, 14),
(0.0004272461, 15),
(0.00048828125, 16),
(0.00061035156, 17),
(0.0007324219, 18),
(0.0008544922, 19),
(0.0009765625, 20),
(0.0012207031, 21),
(0.0014648438, 22),
(0.0017089844, 23),
(0.001953125, 24),
(0.0024414062, 25),
(0.0029296875, 26),
(0.0034179688, 27),
(0.00390625, 28),
(0.0048828125, 29),
(0.005859375, 30),
(0.0068359375, 31),
(0.0078125, 32),
(0.009765625, 33),
(0.01171875, 34),
(0.013671875, 35),
(0.015625, 36),
(0.01953125, 37),
(0.0234375, 38),
(0.02734375, 39),
(0.03125, 40),
(0.0390625, 41),
(0.046875, 42),
(0.0546875, 43),
(0.0625, 44),
(0.078125, 45),
(0.09375, 46),
(0.109375, 47),
(0.125, 48),
(0.15625, 49),
(0.1875, 50),
(0.21875, 51),
(0.25, 52),
(0.3125, 53),
(0.375, 54),
(0.4375, 55),
(0.5, 56),
(0.625, 57),
(0.75, 58),
(0.875, 59),
(1.0, 60),
(1.25, 61),
(1.5, 62),
(1.75, 63),
(2.0, 64),
(2.5, 65),
(3.0, 66),
(3.5, 67),
(4.0, 68),
(5.0, 69),
(6.0, 70),
(7.0, 71),
(8.0, 72),
(10.0, 73),
(12.0, 74),
(14.0, 75),
(16.0, 76),
(20.0, 77),
(24.0, 78),
(28.0, 79),
(32.0, 80),
(40.0, 81),
(48.0, 82),
(56.0, 83),
(64.0, 84),
(80.0, 85),
(96.0, 86),
(112.0, 87),
(128.0, 88),
(160.0, 89),
(192.0, 90),
(224.0, 91),
(256.0, 92),
(320.0, 93),
(384.0, 94),
(448.0, 95),
(512.0, 96),
(640.0, 97),
(768.0, 98),
(896.0, 99),
(1024.0, 100),
(1280.0, 101),
(1536.0, 102),
(1792.0, 103),
(2048.0, 104),
(2560.0, 105),
(3072.0, 106),
(3584.0, 107),
(4096.0, 108),
(5120.0, 109),
(6144.0, 110),
(7168.0, 111),
(8192.0, 112),
(10240.0, 113),
(12288.0, 114),
(14336.0, 115),
(16384.0, 116),
(20480.0, 117),
(24576.0, 118),
(28672.0, 119),
(32768.0, 120),
(40960.0, 121),
(49152.0, 122),
(57344.0, 123),
(inf, 124)]
Total running time of the script: ( 0 minutes 0.050 seconds)