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-rw-r--r--Makefile19
-rw-r--r--bitsandbytes/__init__.py11
-rw-r--r--bitsandbytes/cextension.py13
-rw-r--r--bitsandbytes/functional.py52
-rw-r--r--bitsandbytes/optim/__init__.py20
-rw-r--r--bitsandbytes/optim/rmsprop.py2
-rw-r--r--csrc/common.cpp39
-rw-r--r--csrc/common.h23
-rw-r--r--csrc/cpu_ops.cpp57
-rw-r--r--csrc/cpu_ops.h9
-rw-r--r--csrc/ops.cu451
-rw-r--r--csrc/ops.cuh10
-rw-r--r--csrc/pythonInterface.c118
-rw-r--r--setup.py22
14 files changed, 459 insertions, 387 deletions
diff --git a/Makefile b/Makefile
index f21fde3..b58e233 100644
--- a/Makefile
+++ b/Makefile
@@ -10,10 +10,10 @@ NVCC := $(CUDA_HOME)/bin/nvcc
###########################################
CSRC := $(ROOT_DIR)/csrc
-BUILD_DIR:= $(ROOT_DIR)/cuda_build
+BUILD_DIR:= $(ROOT_DIR)/build
FILES_CUDA := $(CSRC)/ops.cu $(CSRC)/kernels.cu
-FILES_CPP := $(CSRC)/pythonInterface.c
+FILES_CPP := $(CSRC)/common.cpp $(CSRC)/cpu_ops.cpp $(CSRC)/pythonInterface.c
INCLUDE := -I $(CUDA_HOME)/include -I $(ROOT_DIR)/csrc -I $(CONDA_PREFIX)/include -I $(ROOT_DIR)/dependencies/cub -I $(ROOT_DIR)/include
LIB := -L $(CUDA_HOME)/lib64 -lcudart -lcuda -lcublas -lcurand -lcusparse -L $(CONDA_PREFIX)/lib
@@ -46,27 +46,30 @@ CC_CUDA11x += -gencode arch=compute_86,code=sm_86
all: $(ROOT_DIR)/dependencies/cub $(BUILD_DIR) env
$(NVCC) $(COMPUTE_CAPABILITY) -Xcompiler '-fPIC' --use_fast_math -Xptxas=-v -dc $(FILES_CUDA) $(INCLUDE) $(LIB) --output-directory $(BUILD_DIR)
$(NVCC) $(COMPUTE_CAPABILITY) -Xcompiler '-fPIC' -dlink $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o -o $(BUILD_DIR)/link.o
- $(GPP) -std=c++14 -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
+ $(GPP) -std=c++14 -DBUILD_CUDA -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
cuda92: $(ROOT_DIR)/dependencies/cub $(BUILD_DIR) env
$(NVCC) $(COMPUTE_CAPABILITY) $(CC_CUDA92) -Xcompiler '-fPIC' --use_fast_math -Xptxas=-v -dc $(FILES_CUDA) $(INCLUDE) $(LIB) --output-directory $(BUILD_DIR)
$(NVCC) $(COMPUTE_CAPABILITY) $(CC_CUDA92) -Xcompiler '-fPIC' -dlink $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o -o $(BUILD_DIR)/link.o
- $(GPP) -std=c++14 -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
+ $(GPP) -std=c++14 -DBUILD_CUDA -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
cuda10x: $(ROOT_DIR)/dependencies/cub $(BUILD_DIR) env
$(NVCC) $(COMPUTE_CAPABILITY) $(CC_CUDA10x) -Xcompiler '-fPIC' --use_fast_math -Xptxas=-v -dc $(FILES_CUDA) $(INCLUDE) $(LIB) --output-directory $(BUILD_DIR)
$(NVCC) $(COMPUTE_CAPABILITY) $(CC_CUDA10x) -Xcompiler '-fPIC' -dlink $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o -o $(BUILD_DIR)/link.o
- $(GPP) -std=c++14 -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
+ $(GPP) -std=c++14 -DBUILD_CUDA -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
cuda110: $(BUILD_DIR) env
$(NVCC) $(COMPUTE_CAPABILITY) $(CC_CUDA110) -Xcompiler '-fPIC' --use_fast_math -Xptxas=-v -dc $(FILES_CUDA) $(INCLUDE) $(LIB) --output-directory $(BUILD_DIR)
$(NVCC) $(COMPUTE_CAPABILITY) $(CC_CUDA110) -Xcompiler '-fPIC' -dlink $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o -o $(BUILD_DIR)/link.o
- $(GPP) -std=c++14 -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
+ $(GPP) -std=c++14 -DBUILD_CUDA -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
cuda11x: $(BUILD_DIR) env
$(NVCC) $(COMPUTE_CAPABILITY) $(CC_CUDA11x) -Xcompiler '-fPIC' --use_fast_math -Xptxas=-v -dc $(FILES_CUDA) $(INCLUDE) $(LIB) --output-directory $(BUILD_DIR)
$(NVCC) $(COMPUTE_CAPABILITY) $(CC_CUDA11x) -Xcompiler '-fPIC' -dlink $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o -o $(BUILD_DIR)/link.o
- $(GPP) -std=c++14 -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
+ $(GPP) -std=c++14 -DBUILD_CUDA -shared -fPIC $(INCLUDE) $(BUILD_DIR)/ops.o $(BUILD_DIR)/kernels.o $(BUILD_DIR)/link.o $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so $(LIB)
+
+cpuonly: $(BUILD_DIR) env
+ $(GPP) -std=c++14 -shared -fPIC -I $(ROOT_DIR)/csrc -I $(ROOT_DIR)/include $(FILES_CPP) -o ./bitsandbytes/libbitsandbytes.so
env:
@echo "ENVIRONMENT"
@@ -80,7 +83,7 @@ env:
@echo "============================"
$(BUILD_DIR):
- mkdir -p cuda_build
+ mkdir -p build
mkdir -p dependencies
$(ROOT_DIR)/dependencies/cub:
diff --git a/bitsandbytes/__init__.py b/bitsandbytes/__init__.py
index 6e29322..22fb841 100644
--- a/bitsandbytes/__init__.py
+++ b/bitsandbytes/__init__.py
@@ -2,9 +2,14 @@
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
-from .optim import adam
+
from .nn import modules
-__pdoc__ = {'libBitsNBytes' : False,
+from cextension import COMPILED_WITH_CUDA
+
+if COMPILED_WITH_CUDA:
+ from .optim import adam
+
+__pdoc__ = {'libBitsNBytes': False,
'optim.optimizer.Optimizer8bit': False,
'optim.optimizer.MockArgs': False
- }
+ }
diff --git a/bitsandbytes/cextension.py b/bitsandbytes/cextension.py
new file mode 100644
index 0000000..63d627e
--- /dev/null
+++ b/bitsandbytes/cextension.py
@@ -0,0 +1,13 @@
+import ctypes as ct
+import os
+from warnings import warn
+
+lib = ct.cdll.LoadLibrary(os.path.dirname(__file__) + '/libbitsandbytes.so')
+
+try:
+ lib.cadam32bit_g32
+ COMPILED_WITH_CUDA = True
+except AttributeError:
+ warn("The installed version of bitsandbytes was compiled without GPU support. "
+ "8-bit optimizers and GPU quantization are unavailable.")
+ COMPILED_WITH_CUDA = False
diff --git a/bitsandbytes/functional.py b/bitsandbytes/functional.py
index fbd7564..68b1d78 100644
--- a/bitsandbytes/functional.py
+++ b/bitsandbytes/functional.py
@@ -3,38 +3,38 @@
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import ctypes as ct
-import os
import random
from typing import Tuple
import torch
from torch import Tensor
-lib = ct.cdll.LoadLibrary(os.path.dirname(__file__) + '/libbitsandbytes.so')
+from cextension import lib, COMPILED_WITH_CUDA
+
name2qmap = {}
-''' C FUNCTIONS FOR OPTIMIZERS '''
-
-str2optimizer32bit = {}
-str2optimizer32bit['adam'] = (lib.cadam32bit_g32, lib.cadam32bit_g16)
-str2optimizer32bit['momentum'] = (lib.cmomentum32bit_g32, lib.cmomentum32bit_g16)
-str2optimizer32bit['rmsprop'] = (lib.crmsprop32bit_g32, lib.crmsprop32bit_g16)
-str2optimizer32bit['adagrad'] = (lib.cadagrad32bit_g32, lib.cadagrad32bit_g16)
-str2optimizer32bit['lars'] = (lib.cmomentum32bit_g32, lib.cmomentum32bit_g16)
-str2optimizer32bit['lamb'] = (lib.cadam32bit_g32, lib.cadam32bit_g16)
-
-str2optimizer8bit = {}
-str2optimizer8bit['adam'] = (lib.cadam_static_8bit_g32, lib.cadam_static_8bit_g16)
-str2optimizer8bit['momentum'] = (lib.cmomentum_static_8bit_g32, lib.cmomentum_static_8bit_g16)
-str2optimizer8bit['rmsprop'] = (lib.crmsprop_static_8bit_g32, lib.crmsprop_static_8bit_g16)
-str2optimizer8bit['lamb'] = (lib.cadam_static_8bit_g32, lib.cadam_static_8bit_g16)
-str2optimizer8bit['lars'] = (lib.cmomentum_static_8bit_g32, lib.cmomentum_static_8bit_g16)
-
-str2optimizer8bit_blockwise = {}
-str2optimizer8bit_blockwise['adam'] = (lib.cadam_8bit_blockwise_fp32, lib.cadam_8bit_blockwise_fp16)
-str2optimizer8bit_blockwise['momentum'] = (lib.cmomentum_8bit_blockwise_fp32, lib.cmomentum_8bit_blockwise_fp16)
-str2optimizer8bit_blockwise['rmsprop'] = (lib.crmsprop_8bit_blockwise_fp32, lib.crmsprop_8bit_blockwise_fp16)
-str2optimizer8bit_blockwise['adagrad'] = (lib.cadagrad_8bit_blockwise_fp32, lib.cadagrad_8bit_blockwise_fp16)
+if COMPILED_WITH_CUDA:
+ ''' C FUNCTIONS FOR OPTIMIZERS '''
+ str2optimizer32bit = {}
+ str2optimizer32bit['adam'] = (lib.cadam32bit_g32, lib.cadam32bit_g16)
+ str2optimizer32bit['momentum'] = (lib.cmomentum32bit_g32, lib.cmomentum32bit_g16)
+ str2optimizer32bit['rmsprop'] = (lib.crmsprop32bit_g32, lib.crmsprop32bit_g16)
+ str2optimizer32bit['adagrad'] = (lib.cadagrad32bit_g32, lib.cadagrad32bit_g16)
+ str2optimizer32bit['lars'] = (lib.cmomentum32bit_g32, lib.cmomentum32bit_g16)
+ str2optimizer32bit['lamb'] = (lib.cadam32bit_g32, lib.cadam32bit_g16)
+
+ str2optimizer8bit = {}
+ str2optimizer8bit['adam'] = (lib.cadam_static_8bit_g32, lib.cadam_static_8bit_g16)
+ str2optimizer8bit['momentum'] = (lib.cmomentum_static_8bit_g32, lib.cmomentum_static_8bit_g16)
+ str2optimizer8bit['rmsprop'] = (lib.crmsprop_static_8bit_g32, lib.crmsprop_static_8bit_g16)
+ str2optimizer8bit['lamb'] = (lib.cadam_static_8bit_g32, lib.cadam_static_8bit_g16)
+ str2optimizer8bit['lars'] = (lib.cmomentum_static_8bit_g32, lib.cmomentum_static_8bit_g16)
+
+ str2optimizer8bit_blockwise = {}
+ str2optimizer8bit_blockwise['adam'] = (lib.cadam_8bit_blockwise_fp32, lib.cadam_8bit_blockwise_fp16)
+ str2optimizer8bit_blockwise['momentum'] = (lib.cmomentum_8bit_blockwise_fp32, lib.cmomentum_8bit_blockwise_fp16)
+ str2optimizer8bit_blockwise['rmsprop'] = (lib.crmsprop_8bit_blockwise_fp32, lib.crmsprop_8bit_blockwise_fp16)
+ str2optimizer8bit_blockwise['adagrad'] = (lib.cadagrad_8bit_blockwise_fp32, lib.cadagrad_8bit_blockwise_fp16)
optimal_normal = [-0.9939730167388916, -0.8727636337280273, -0.8097418546676636, -0.7660024166107178, -0.7318882346153259, -0.6793879270553589, -0.657649040222168, -0.6385974884033203, -0.6211113333702087, -0.5901028513908386, -0.5762918591499329, -0.5630806684494019, -0.5509274005889893, -0.5394591689109802, -0.5283197164535522, -0.517780065536499, -0.5074946284294128, -0.4980469048023224, -0.48867011070251465, -0.48003149032592773, -0.47125306725502014, -0.4629971981048584, -0.4547359049320221, -0.446626216173172, -0.43902668356895447, -0.43158355355262756, -0.4244747757911682, -0.4173796474933624, -0.41038978099823, -0.4055633544921875, -0.4035947024822235, -0.39701032638549805, -0.39057496190071106, -0.38439232110977173, -0.3782760500907898, -0.3721940815448761, -0.3661896586418152, -0.3604033589363098, -0.354605108499527, -0.34892538189888, -0.34320303797721863, -0.3376772701740265, -0.3323028087615967, -0.3269782066345215, -0.32166096568107605, -0.316457599401474, -0.3112771809101105, -0.3061025142669678, -0.30106794834136963, -0.2961243987083435, -0.2912728488445282, -0.28644347190856934, -0.28165507316589355, -0.2769731283187866, -0.2722635865211487, -0.26779335737228394, -0.26314786076545715, -0.2586647868156433, -0.2541804611682892, -0.2496625930070877, -0.24527113139629364, -0.24097171425819397, -0.23659978806972504, -0.23218469321727753, -0.22799566388130188, -0.22380566596984863, -0.21965542435646057, -0.2154538631439209, -0.2113603949546814, -0.20735277235507965, -0.20334717631340027, -0.19932441413402557, -0.19530178606510162, -0.19136647880077362, -0.18736697733402252, -0.18337111175060272, -0.17951400578022003, -0.1757056713104248, -0.17182783782482147, -0.1680615097284317, -0.16431649029254913, -0.16053077578544617, -0.15685945749282837, -0.15298527479171753, -0.1493264138698578, -0.14566898345947266, -0.14188314974308014, -0.13819937407970428, -0.1344561129808426, -0.1306886374950409, -0.1271020770072937, -0.12346585839986801, -0.11981867253780365, -0.11614970862865448, -0.11256207525730133, -0.10889036953449249, -0.10525048524141312, -0.1016591489315033, -0.09824034571647644, -0.09469068050384521, -0.0911419615149498, -0.08773849159479141, -0.08416644483804703, -0.08071305602788925, -0.07720902562141418, -0.07371306419372559, -0.07019119709730148, -0.06673648208379745, -0.06329209357500076, -0.059800852090120316, -0.0564190037548542, -0.05296570807695389, -0.049522045999765396, -0.04609023034572601, -0.04262964054942131, -0.039246633648872375, -0.03577171266078949, -0.03236335143446922, -0.028855687007308006, -0.02542758360505104, -0.022069433704018593, -0.018754752352833748, -0.015386369079351425, -0.01194947212934494, -0.008439815603196621, -0.004995611496269703, -0.0016682245768606663, 0.0, 0.0015510577941313386, 0.005062474869191647, 0.008417150937020779, 0.011741090565919876, 0.015184164978563786, 0.018582714721560478, 0.02204744517803192, 0.025471193715929985, 0.02889077737927437, 0.0323684960603714, 0.03579240292310715, 0.039281025528907776, 0.0427563451230526, 0.04619763046503067, 0.04968220740556717, 0.05326594039797783, 0.05679265409708023, 0.060245808213949203, 0.06372645497322083, 0.06721872836351395, 0.0706876739859581, 0.0742349922657013, 0.07774098962545395, 0.08123527467250824, 0.08468879014253616, 0.08810535818338394, 0.09155989438295364, 0.09498448669910431, 0.0985206812620163, 0.10206405073404312, 0.10563778132200241, 0.10921968519687653, 0.11284469068050385, 0.11653254181146622, 0.12008969485759735, 0.12368203699588776, 0.1272617131471634, 0.13089501857757568, 0.134552001953125, 0.1382799744606018, 0.14194637537002563, 0.14563234150409698, 0.14930322766304016, 0.15303383767604828, 0.1567956507205963, 0.16050070524215698, 0.16431072354316711, 0.16813558340072632, 0.17204202711582184, 0.1758781224489212, 0.17973239719867706, 0.1836014688014984, 0.18753431737422943, 0.19138391315937042, 0.19535475969314575, 0.19931404292583466, 0.20333819091320038, 0.20738255977630615, 0.21152682602405548, 0.21568812429904938, 0.21978361904621124, 0.22393859922885895, 0.22814159095287323, 0.23241068422794342, 0.23675410449504852, 0.24123944342136383, 0.24569889903068542, 0.2500703036785126, 0.25904011726379395, 0.26349544525146484, 0.2682226300239563, 0.272907555103302, 0.2774306833744049, 0.28220856189727783, 0.2869136929512024, 0.2916390895843506, 0.29649388790130615, 0.30142995715141296, 0.3065022826194763, 0.3114383816719055, 0.31648796796798706, 0.3216581642627716, 0.32700115442276, 0.3322487473487854, 0.33778008818626404, 0.3431521952152252, 0.3487405776977539, 0.3543166518211365, 0.3601346015930176, 0.36605337262153625, 0.37217751145362854, 0.378179669380188, 0.3843980133533478, 0.3906566798686981, 0.39714935421943665, 0.40357843041419983, 0.4104187488555908, 0.4171563684940338, 0.42418959736824036, 0.43136918544769287, 0.4389212429523468, 0.44673123955726624, 0.45457619428634644, 0.4627031683921814, 0.47130417823791504, 0.4798591434955597, 0.48897242546081543, 0.4979848861694336, 0.5, 0.5076631307601929, 0.5177803635597229, 0.5282770991325378, 0.5392990112304688, 0.5506287813186646, 0.5632893443107605, 0.5764452815055847, 0.5903191566467285, 0.6051878333091736, 0.6209936141967773, 0.6382884979248047, 0.6573970913887024, 0.6795773506164551, 0.7037051916122437, 0.7327037453651428, 0.7677436470985413, 0.8111193776130676, 0.875165581703186, 1.0]
@@ -138,7 +138,7 @@ def estimate_quantiles(A: Tensor, out: Tensor=None, offset: float=1/512) -> Tens
elif A.dtype == torch.float16:
lib.cestimate_quantiles_fp16(get_ptr(A), get_ptr(out), ct.c_float(offset), ct.c_int(A.numel()))
else:
- raise NotImplementError(f'Not supported data type {A.dtype}')
+ raise NotImplementedError(f'Not supported data type {A.dtype}')
return out
def quantize_blockwise(A: Tensor, code: Tensor=None, absmax: Tensor=None, rand=None, out: Tensor=None) -> Tensor:
@@ -384,7 +384,7 @@ def optimizer_update_32bit(optimizer_name:str, g: Tensor, p: Tensor, state1: Ten
param_norm = torch.norm(p.data.float())
if optimizer_name not in str2optimizer32bit:
- raise NotImplementError(f'Optimizer not implemented: {optimizer_name}. Choices: {",".join(str2optimizer32bit.keys())}')
+ raise NotImplementedError(f'Optimizer not implemented: {optimizer_name}. Choices: {",".join(str2optimizer32bit.keys())}')
if g.dtype == torch.float32 and state1.dtype == torch.float32:
str2optimizer32bit[optimizer_name][0](get_ptr(g), get_ptr(p), get_ptr(state1), get_ptr(state2), get_ptr(unorm_vec), ct.c_float(max_unorm),
diff --git a/bitsandbytes/optim/__init__.py b/bitsandbytes/optim/__init__.py
index 5e73414..e833ecc 100644
--- a/bitsandbytes/optim/__init__.py
+++ b/bitsandbytes/optim/__init__.py
@@ -2,11 +2,15 @@
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
-from .adam import Adam, Adam8bit, Adam32bit
-from .adamw import AdamW, AdamW8bit, AdamW32bit
-from .sgd import SGD, SGD8bit, SGD32bit
-from .lars import LARS, LARS8bit, LARS32bit, PytorchLARS
-from .lamb import LAMB, LAMB8bit, LAMB32bit
-from .rmsprop import RMSprop, RMSprop8bit, RMSprop32bit
-from .adagrad import Adagrad, Adagrad8bit, Adagrad32bit
-from .optimizer import GlobalOptimManager
+
+from bitsandbytes.cextension import COMPILED_WITH_CUDA
+
+if COMPILED_WITH_CUDA:
+ from .adam import Adam, Adam8bit, Adam32bit
+ from .adamw import AdamW, AdamW8bit, AdamW32bit
+ from .sgd import SGD, SGD8bit, SGD32bit
+ from .lars import LARS, LARS8bit, LARS32bit, PytorchLARS
+ from .lamb import LAMB, LAMB8bit, LAMB32bit
+ from .rmsprop import RMSprop, RMSprop8bit, RMSprop32bit
+ from .adagrad import Adagrad, Adagrad8bit, Adagrad32bit
+ from .optimizer import GlobalOptimManager
diff --git a/bitsandbytes/optim/rmsprop.py b/bitsandbytes/optim/rmsprop.py
index 7909d5d..0f1ffaa 100644
--- a/bitsandbytes/optim/rmsprop.py
+++ b/bitsandbytes/optim/rmsprop.py
@@ -31,6 +31,6 @@ class RMSprop32bit(Optimizer1State):
if alpha == 0:
raise NotImplementedError(f'RMSprop with alpha==0.0 is not supported!')
if centered:
- raise NotImplementError(f'Centered RMSprop is not supported!')
+ raise NotImplementedError(f'Centered RMSprop is not supported!')
super(RMSprop32bit, self).__init__('rmsprop', params, lr, (alpha, momentum), eps,
weight_decay, 32, args, min_8bit_size, percentile_clipping, block_wise)
diff --git a/csrc/common.cpp b/csrc/common.cpp
new file mode 100644
index 0000000..972602b
--- /dev/null
+++ b/csrc/common.cpp
@@ -0,0 +1,39 @@
+#include <common.h>
+#include <float.h>
+
+void *quantize_block(void *arguments) {
+ // 1. find absmax in block
+ // 2. divide input value by absmax to normalize into [-1.0, 1.0]
+ // 3. do binary search to find the closest value
+ // 4. check minimal distance
+ // 5. store index
+
+ struct quantize_block_args *args = (quantize_block_args *) arguments;
+
+ // 1. find absmax in block
+ float absmax_block = -FLT_MAX;
+ for (int i = args->block_idx; i < args->block_end; i++)
+ absmax_block = fmax(absmax_block, fabs(args->A[i]));
+
+ args->absmax[args->block_idx / BLOCK_SIZE] = absmax_block;
+
+ for (int i = args->block_idx; i < args->block_end; i++) {
+ // 2. divide input value by absmax to normalize into [-1.0, 1.0]
+ // 3. do binary search to find the closest value
+ float normed_value = args->A[i] / absmax_block;
+ int idx = args->bin_searcher->scalar(normed_value);
+
+ // 4. check minimal distance
+ // The binary search returns always the value to the left, which might not be the closest value
+ if (idx < 255) {
+ float dist_left = fabs(normed_value - (args->code[idx]));
+ float dist_right = fabs(normed_value - (args->code[idx + 1]));
+ if (dist_right < dist_left) { idx += 1; }
+ }
+
+ // 5. store index
+ args->out[i] = (unsigned char) idx;
+ }
+
+ return NULL;
+}
diff --git a/csrc/common.h b/csrc/common.h
new file mode 100644
index 0000000..35f2463
--- /dev/null
+++ b/csrc/common.h
@@ -0,0 +1,23 @@
+#include <BinSearch.h>
+
+#ifndef common
+#define common
+
+using namespace BinSearch;
+
+struct quantize_block_args {
+ BinAlgo<Scalar, float, Direct2> *bin_searcher;
+ float *code;
+ float *A;
+ float *absmax;
+ unsigned char *out;
+ int block_end;
+ int block_idx;
+ int threadidx;
+};
+
+#define BLOCK_SIZE 4096
+
+void *quantize_block(void *arguments);
+
+#endif \ No newline at end of file
diff --git a/csrc/cpu_ops.cpp b/csrc/cpu_ops.cpp
new file mode 100644
index 0000000..11a2615
--- /dev/null
+++ b/csrc/cpu_ops.cpp
@@ -0,0 +1,57 @@
+#include <BinSearch.h>
+#include <pthread.h>
+#include <common.h>
+
+using namespace BinSearch;
+
+void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, int n) {
+ for (int block_idx = 0; block_idx < n; block_idx += BLOCK_SIZE) {
+ int valid_items = n - block_idx >= BLOCK_SIZE ? BLOCK_SIZE : n - block_idx;
+ int block_end = block_idx + valid_items;
+ for (int i = block_idx; i < block_end; i++)
+ out[i] = code[A[i]] * absmax[block_idx / BLOCK_SIZE];
+ }
+}
+
+void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, int n) {
+
+ // the default code is has range [-0.993, 1.0] which can cause an error in the binary search algorithm used below
+ code[0] = -1.0f;
+
+ int num_blocks = n / BLOCK_SIZE;
+ num_blocks += n % BLOCK_SIZE == 0 ? 0 : 1;
+
+ pthread_t *threads = (pthread_t *) malloc(sizeof(pthread_t) * num_blocks);
+ struct quantize_block_args **args = (quantize_block_args **) malloc(num_blocks * sizeof(quantize_block_args *));
+
+ for (int i = 0; i < num_blocks; i++)
+ args[i] = (quantize_block_args *) malloc(sizeof(quantize_block_args));
+
+ const uint32 elements_code = 256;
+ BinAlgo<Scalar, float, Direct2> bin_searcher(code, elements_code);
+
+ for (int block_idx = 0; block_idx < n; block_idx += BLOCK_SIZE) {
+ int valid_items = n - block_idx >= BLOCK_SIZE ? BLOCK_SIZE : n - block_idx;
+ int block_end = block_idx + valid_items;
+
+ struct quantize_block_args *arg = args[block_idx / BLOCK_SIZE];
+ arg->bin_searcher = &bin_searcher;
+ arg->code = code;
+ arg->A = A;
+ arg->absmax = absmax;
+ arg->out = out;
+ arg->block_end = block_end;
+ arg->block_idx = block_idx;
+ arg->threadidx = block_idx / BLOCK_SIZE;
+
+ pthread_create(&threads[block_idx / BLOCK_SIZE], NULL, &quantize_block, (void *) arg);
+ }
+
+ for (int i = 0; i < num_blocks; i++)
+ int err = pthread_join(threads[i], NULL);
+
+ free(threads);
+ for (int i = 0; i < num_blocks; i++)
+ free(args[i]);
+ free(args);
+} \ No newline at end of file
diff --git a/csrc/cpu_ops.h b/csrc/cpu_ops.h
new file mode 100644
index 0000000..57145a9
--- /dev/null
+++ b/csrc/cpu_ops.h
@@ -0,0 +1,9 @@
+#ifndef BITSANDBYTES_CPU_OPS_H
+#define BITSANDBYTES_CPU_OPS_H
+
+
+void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, int n);
+
+void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, int n);
+
+#endif
diff --git a/csrc/ops.cu b/csrc/ops.cu
index 9691241..464ea2e 100644
--- a/csrc/ops.cu
+++ b/csrc/ops.cu
@@ -8,251 +8,141 @@
#include <cub/device/device_scan.cuh>
#include <limits>
#include <BinSearch.h>
+#include <common.h>
using namespace BinSearch;
using std::cout;
using std::endl;
-#define BLOCK_SIZE 4096
-
-struct quantize_block_args
-{
- BinAlgo<Scalar, float, Direct2> *bin_searcher;
- float *code;
- float *A;
- float *absmax;
- unsigned char *out;
- int block_end;
- int block_idx;
- int threadidx;
-};
-
-void *quantize_block(void *arguments)
-{
- // 1. find absmax in block
- // 2. divide input value by absmax to normalize into [-1.0, 1.0]
- // 3. do binary search to find the closest value
- // 4. check minimal distance
- // 5. store index
-
- struct quantize_block_args *args = (quantize_block_args*)arguments;
-
- // 1. find absmax in block
- float absmax_block = -FLT_MAX;
- for (int i = args->block_idx; i < args->block_end; i++)
- absmax_block = fmax(absmax_block, fabs(args->A[i]));
-
- args->absmax[args->block_idx/BLOCK_SIZE] = absmax_block;
-
- for (int i = args->block_idx; i < args->block_end; i++)
- {
- // 2. divide input value by absmax to normalize into [-1.0, 1.0]
- // 3. do binary search to find the closest value
- float normed_value = args->A[i]/absmax_block;
- int idx = args->bin_searcher->scalar(normed_value);
-
- // 4. check minimal distance
- // The binary search returns always the value to the left, which might not be the closest value
- if(idx < 255)
- {
- float dist_left = fabs(normed_value-(args->code[idx]));
- float dist_right = fabs(normed_value-(args->code[idx+1]));
- if(dist_right < dist_left){ idx+=1; }
- }
-
- // 5. store index
- args->out[i] = (unsigned char)idx;
- }
-
- return NULL;
+void histogramScatterAdd2D(float *histogram, int *index1, int *index2, float *src, int maxidx1, int n) {
+ int threads = 512;
+ int blocks = n / threads;
+ blocks = n % threads == 0 ? blocks : blocks + 1;
+ kHistogramScatterAdd2D<<<blocks, 512>>>(histogram, index1, index2, src, maxidx1, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
-void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, int n)
-{
-
- // the default code is has range [-0.993, 1.0] which can cause an error in the binary search algorithm used below
- code[0] = -1.0f;
-
- int num_blocks = n/BLOCK_SIZE;
- num_blocks += n % BLOCK_SIZE == 0 ? 0 : 1;
-
- pthread_t *threads = (pthread_t*)malloc(sizeof(pthread_t)*num_blocks);
- struct quantize_block_args **args = (quantize_block_args**)malloc(num_blocks*sizeof(quantize_block_args*));
-
- for(int i = 0; i < num_blocks; i++)
- args[i] = (quantize_block_args*)malloc(sizeof(quantize_block_args));
-
- const uint32 elements_code = 256;
- BinAlgo<Scalar, float, Direct2> bin_searcher(code, elements_code);
-
- for(int block_idx = 0; block_idx < n; block_idx+=BLOCK_SIZE)
- {
- int valid_items = n-block_idx >= BLOCK_SIZE ? BLOCK_SIZE : n - block_idx;
- int block_end = block_idx + valid_items;
-
- struct quantize_block_args *arg = args[block_idx/BLOCK_SIZE];
- arg->bin_searcher = &bin_searcher;
- arg->code = code;
- arg->A = A;
- arg->absmax = absmax;
- arg->out = out;
- arg->block_end = block_end;
- arg->block_idx = block_idx;
- arg->threadidx = block_idx/BLOCK_SIZE;
-
- pthread_create(&threads[block_idx/BLOCK_SIZE], NULL, &quantize_block, (void *)arg);
- }
-
- for(int i = 0; i < num_blocks; i++)
- int err = pthread_join(threads[i], NULL);
-
- free(threads);
- for(int i = 0; i < num_blocks; i++)
- free(args[i]);
- free(args);
-}
-
-
-void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, int n)
-{
- for(int block_idx = 0; block_idx < n; block_idx+=BLOCK_SIZE)
- {
- int valid_items = n-block_idx >= BLOCK_SIZE ? BLOCK_SIZE : n - block_idx;
- int block_end = block_idx + valid_items;
- for (int i = block_idx; i < block_end; i++)
- out[i] = code[A[i]]*absmax[block_idx/BLOCK_SIZE];
- }
+template<typename T>
+void estimateQuantiles(T *A, float *code, float offset, int n) {
+ int blocks = n / 4096;
+ blocks = n % 4096 == 0 ? blocks : blocks + 1;
+ CUDA_CHECK_RETURN(cudaMemset(code, 0, 256 * sizeof(float)));
+ kEstimateQuantiles < T ><<<blocks, 512>>>(A, code, offset, std::numeric_limits<T>::max(), n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
-void histogramScatterAdd2D(float* histogram, int *index1, int *index2, float *src, int maxidx1, int n)
-{
- int threads = 512;
- int blocks = n/threads;
- blocks = n % threads == 0 ? blocks : blocks + 1;
- kHistogramScatterAdd2D<<<blocks, 512>>>(histogram, index1, index2, src, maxidx1, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
+void quantize(float *code, float *A, unsigned char *out, int n) {
+ int blocks = n / 1024;
+ blocks = n % 1024 == 0 ? blocks : blocks + 1;
+ kQuantize<<<blocks, 1024>>>(code, A, out, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
-template <typename T> void estimateQuantiles(T *A, float *code, float offset, int n)
-{
- int blocks = n/4096;
- blocks = n % 4096 == 0 ? blocks : blocks + 1;
- CUDA_CHECK_RETURN(cudaMemset(code, 0, 256*sizeof(float)));
- kEstimateQuantiles<T><<<blocks, 512>>>(A, code, offset, std::numeric_limits<T>::max(), n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
+void dequantize(float *code, unsigned char *A, float *out, int n) {
+ int blocks = n / 1024;
+ blocks = n % 1024 == 0 ? blocks : blocks + 1;
+ kDequantize<<<blocks, 1024>>>(code, A, out, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
-void quantize(float *code, float *A, unsigned char *out, int n)
-{
- int blocks = n/1024;
- blocks = n % 1024 == 0 ? blocks : blocks + 1;
- kQuantize<<<blocks, 1024>>>(code, A, out, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
+template<typename T, int STOCHASTIC>
+void quantizeBlockwise(float *code, T *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n) {
+ int blocks = n / 4096;
+ blocks = n % 4096 == 0 ? blocks : blocks + 1;
+ kQuantizeBlockwise < T, 4096, 4, STOCHASTIC ><<<blocks, 1024>>>(code, A, absmax, out, rand, rand_offset, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
-void dequantize(float *code, unsigned char *A, float *out, int n)
-{
- int blocks = n/1024;
- blocks = n % 1024 == 0 ? blocks : blocks + 1;
- kDequantize<<<blocks, 1024>>>(code, A, out, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
+template<typename T>
+void dequantizeBlockwise(float *code, unsigned char *A, float *absmax, T *out, int blocksize, const int n) {
+ int blocks = n / blocksize;
+ blocks = n % blocksize == 0 ? blocks : blocks + 1;
+ if (blocksize == 4096)
+ kDequantizeBlockwise < T, 4096, 1024, 4 ><<<blocks, 4096 / 4>>>(code, A, absmax, out, n);
+ else if (blocksize == 2048)
+ kDequantizeBlockwise < T, 2048, 512, 4 ><<<blocks, 2048 / 4>>>(code, A, absmax, out, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
-template <typename T, int STOCHASTIC> void quantizeBlockwise(float * code, T *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n)
-{
- int blocks = n/4096;
- blocks = n % 4096 == 0 ? blocks : blocks + 1;
- kQuantizeBlockwise<T, 4096, 4, STOCHASTIC><<<blocks, 1024>>>(code, A, absmax, out, rand, rand_offset, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
-}
-
-template<typename T> void dequantizeBlockwise(float *code, unsigned char *A, float *absmax, T *out, int blocksize, const int n)
-{
- int blocks = n/blocksize;
- blocks = n % blocksize == 0 ? blocks : blocks + 1;
- if(blocksize == 4096)
- kDequantizeBlockwise<T, 4096, 1024, 4><<<blocks, 4096/4>>>(code, A, absmax, out, n);
- else if(blocksize == 2048)
- kDequantizeBlockwise<T, 2048, 512, 4><<<blocks, 2048/4>>>(code, A, absmax, out, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
-}
-
-template<typename T, int OPTIMIZER> void optimizer32bit(T* g, T* p,
- float* state1, float* state2, float *unorm, float max_unorm, float param_norm,
- const float beta1, const float beta2, const float eps, const float weight_decay,
- const int step, const float lr, const float gnorm_scale, bool skip_zeros, const int n)
-{
- int blocks = n/4096;
- blocks = n % 4096 == 0 ? blocks : blocks + 1;
- switch(OPTIMIZER)
- {
- case ADAM:
- if(max_unorm > 0.0f)
- {
- CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1*sizeof(float)));
- kPreconditionOptimizer32bit2State<T, OPTIMIZER, 4096, 8><<<blocks, 512>>>(g, p, state1, state2, unorm, beta1, beta2, eps, weight_decay, step, lr, gnorm_scale, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- }
- kOptimizer32bit2State<T, OPTIMIZER><<<blocks, 1024>>>(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, weight_decay, step, lr, gnorm_scale, skip_zeros, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- break;
- case MOMENTUM:
- case RMSPROP:
- case ADAGRAD:
-
- if(max_unorm > 0.0f)
- {
- CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1*sizeof(float)));
- kPreconditionOptimizer32bit1State<T, OPTIMIZER, 4096, 8><<<blocks, 512>>>(g, p, state1, unorm, beta1, eps, weight_decay, step, lr, gnorm_scale, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- }
-
- kOptimizer32bit1State<T, OPTIMIZER><<<blocks, 1024>>>(g, p, state1, unorm, max_unorm, param_norm, beta1, eps, weight_decay, step, lr, gnorm_scale, skip_zeros, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- break;
- }
+template<typename T, int OPTIMIZER>
+void optimizer32bit(T *g, T *p,
+ float *state1, float *state2, float *unorm, float max_unorm, float param_norm,
+ const float beta1, const float beta2, const float eps, const float weight_decay,
+ const int step, const float lr, const float gnorm_scale, bool skip_zeros, const int n) {
+ int blocks = n / 4096;
+ blocks = n % 4096 == 0 ? blocks : blocks + 1;
+ switch (OPTIMIZER) {
+ case ADAM:
+ if (max_unorm > 0.0f) {
+ CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1 * sizeof(float)));
+ kPreconditionOptimizer32bit2State < T, OPTIMIZER, 4096,
+ 8 ><<<blocks, 512>>>(g, p, state1, state2, unorm, beta1, beta2, eps, weight_decay, step, lr, gnorm_scale, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ }
+ kOptimizer32bit2State < T,
+ OPTIMIZER ><<<blocks, 1024>>>(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, weight_decay, step, lr, gnorm_scale, skip_zeros, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ break;
+ case MOMENTUM:
+ case RMSPROP:
+ case ADAGRAD:
+
+ if (max_unorm > 0.0f) {
+ CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1 * sizeof(float)));
+ kPreconditionOptimizer32bit1State < T, OPTIMIZER, 4096,
+ 8 ><<<blocks, 512>>>(g, p, state1, unorm, beta1, eps, weight_decay, step, lr, gnorm_scale, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ }
+
+ kOptimizer32bit1State < T,
+ OPTIMIZER ><<<blocks, 1024>>>(g, p, state1, unorm, max_unorm, param_norm, beta1, eps, weight_decay, step, lr, gnorm_scale, skip_zeros, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ break;
+ }
}
-template<typename T, int OPTIMIZER> void optimizerStatic8bit(T* p, T* g,
- unsigned char* state1, unsigned char* state2,
- float *unorm, float max_unorm, float param_norm,
- float beta1, float beta2,
- float eps, int step, float lr,
- float* quantiles1, float* quantiles2,
- float* max1, float* max2, float* new_max1, float* new_max2,
- float weight_decay,
- const float gnorm_scale, int n)
-{
- int blocks = n/4096;
- blocks = n % 4096 == 0 ? blocks : blocks + 1;
-
- if(max_unorm > 0.0f){ CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1*sizeof(float))); }
-
- switch(OPTIMIZER)
- {
- case ADAM:
- CUDA_CHECK_RETURN(cudaMemset(new_max1, 0, 1*sizeof(float)));
- CUDA_CHECK_RETURN(cudaMemset(new_max2, 0, 1*sizeof(float)));
- kPreconditionOptimizerStatic8bit2State<T, OPTIMIZER><<<blocks, 256>>>(p, g, state1, state2, unorm, beta1, beta2, eps, step, quantiles1, quantiles2, max1, max2, new_max1, new_max2, gnorm_scale, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- kOptimizerStatic8bit2State<T, OPTIMIZER><<<blocks, 1024>>>(p, g, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, step, lr,
- quantiles1, quantiles2, max1, max2, new_max1, new_max2, weight_decay, gnorm_scale, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- break;
- case MOMENTUM:
- case RMSPROP:
- case ADAGRAD:
- CUDA_CHECK_RETURN(cudaMemset(new_max1, 0, 1*sizeof(float)));
- kPreconditionOptimizerStatic8bit1State<T, OPTIMIZER><<<blocks, 256>>>(p, g, state1, unorm, beta1, eps, step, quantiles1, max1, new_max1, weight_decay, gnorm_scale, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- kOptimizerStatic8bit1State<T, OPTIMIZER><<<blocks, 1024>>>(p, g, state1, unorm, max_unorm, param_norm, beta1, eps, step, lr,
- quantiles1, max1, new_max1, weight_decay, gnorm_scale, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- break;
- default:
- break;
- }
+template<typename T, int OPTIMIZER>
+void optimizerStatic8bit(T *p, T *g,
+ unsigned char *state1, unsigned char *state2,
+ float *unorm, float max_unorm, float param_norm,
+ float beta1, float beta2,
+ float eps, int step, float lr,
+ float *quantiles1, float *quantiles2,
+ float *max1, float *max2, float *new_max1, float *new_max2,
+ float weight_decay,
+ const float gnorm_scale, int n) {
+ int blocks = n / 4096;
+ blocks = n % 4096 == 0 ? blocks : blocks + 1;
+
+ if (max_unorm > 0.0f) { CUDA_CHECK_RETURN(cudaMemset(unorm, 0, 1 * sizeof(float))); }
+
+ switch (OPTIMIZER) {
+ case ADAM:
+ CUDA_CHECK_RETURN(cudaMemset(new_max1, 0, 1 * sizeof(float)));
+ CUDA_CHECK_RETURN(cudaMemset(new_max2, 0, 1 * sizeof(float)));
+ kPreconditionOptimizerStatic8bit2State < T,
+ OPTIMIZER ><<<blocks, 256>>>(p, g, state1, state2, unorm, beta1, beta2, eps, step, quantiles1, quantiles2, max1, max2, new_max1, new_max2, gnorm_scale, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ kOptimizerStatic8bit2State < T,
+ OPTIMIZER ><<<blocks, 1024>>>(p, g, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, step, lr,
+ quantiles1, quantiles2, max1, max2, new_max1, new_max2, weight_decay, gnorm_scale, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ break;
+ case MOMENTUM:
+ case RMSPROP:
+ case ADAGRAD:
+ CUDA_CHECK_RETURN(cudaMemset(new_max1, 0, 1 * sizeof(float)));
+ kPreconditionOptimizerStatic8bit1State < T,
+ OPTIMIZER ><<<blocks, 256>>>(p, g, state1, unorm, beta1, eps, step, quantiles1, max1, new_max1, weight_decay, gnorm_scale, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ kOptimizerStatic8bit1State < T, OPTIMIZER ><<<blocks, 1024>>>(p, g, state1, unorm, max_unorm, param_norm, beta1, eps, step, lr,
+ quantiles1, max1, new_max1, weight_decay, gnorm_scale, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ break;
+ default:
+ break;
+ }
}
#define BLOCKSIZE_2STATE 2048
@@ -260,42 +150,43 @@ template<typename T, int OPTIMIZER> void optimizerStatic8bit(T* p, T* g,
#define BLOCKSIZE_1STATE 2048
#define NUM_1STATE 8
-template<typename T, int OPTIMIZER> void optimizerStatic8bitBlockwise(T* p, T* g,
- unsigned char* state1, unsigned char* state2, float beta1, float beta2, float eps, int step, float lr,
- float* quantiles1, float* quantiles2, float* absmax1, float* absmax2, float weight_decay, const float gnorm_scale, bool skip_zeros, int n)
-{
-
- int blocks = 0;
- switch(OPTIMIZER)
- {
- case ADAM:
- blocks = n/BLOCKSIZE_2STATE;
- blocks = n % BLOCKSIZE_2STATE == 0 ? blocks : blocks + 1;
- kOptimizerStatic8bit2StateBlockwise<T, OPTIMIZER, BLOCKSIZE_2STATE, NUM_2STATE><<<blocks, BLOCKSIZE_2STATE/NUM_2STATE>>>(p, g, state1, state2, beta1, beta2, eps, step, lr,
- quantiles1, quantiles2, absmax1, absmax2, weight_decay, gnorm_scale, skip_zeros, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- break;
- case MOMENTUM:
- case RMSPROP:
- case ADAGRAD:
- blocks = n/BLOCKSIZE_1STATE;
- blocks = n % BLOCKSIZE_1STATE == 0 ? blocks : blocks + 1;
- kOptimizerStatic8bit1StateBlockwise<T, OPTIMIZER, BLOCKSIZE_1STATE, NUM_1STATE><<<blocks, BLOCKSIZE_1STATE/NUM_1STATE>>>(p, g, state1, beta1, beta2, eps, step, lr,
- quantiles1, absmax1, weight_decay, gnorm_scale, skip_zeros, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
- break;
- }
+template<typename T, int OPTIMIZER>
+void optimizerStatic8bitBlockwise(T *p, T *g,
+ unsigned char *state1, unsigned char *state2, float beta1, float beta2, float eps, int step, float lr,
+ float *quantiles1, float *quantiles2, float *absmax1, float *absmax2, float weight_decay,
+ const float gnorm_scale, bool skip_zeros, int n) {
+
+ int blocks = 0;
+ switch (OPTIMIZER) {
+ case ADAM:
+ blocks = n / BLOCKSIZE_2STATE;
+ blocks = n % BLOCKSIZE_2STATE == 0 ? blocks : blocks + 1;
+ kOptimizerStatic8bit2StateBlockwise < T, OPTIMIZER, BLOCKSIZE_2STATE, NUM_2STATE ><<<blocks, BLOCKSIZE_2STATE /
+ NUM_2STATE>>>(p, g, state1, state2, beta1, beta2, eps, step, lr,
+ quantiles1, quantiles2, absmax1, absmax2, weight_decay, gnorm_scale, skip_zeros, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ break;
+ case MOMENTUM:
+ case RMSPROP:
+ case ADAGRAD:
+ blocks = n / BLOCKSIZE_1STATE;
+ blocks = n % BLOCKSIZE_1STATE == 0 ? blocks : blocks + 1;
+ kOptimizerStatic8bit1StateBlockwise < T, OPTIMIZER, BLOCKSIZE_1STATE, NUM_1STATE ><<<blocks, BLOCKSIZE_1STATE /
+ NUM_1STATE>>>(p, g, state1, beta1, beta2, eps, step, lr,
+ quantiles1, absmax1, weight_decay, gnorm_scale, skip_zeros, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
+ break;
+ }
}
-
-template<typename T> void percentileClipping(T * g, float *gnorm_vec, int step, const int n)
-{
- int blocks = n/2048;
- blocks = n % 2048 == 0 ? blocks : blocks + 1;
- CUDA_CHECK_RETURN(cudaMemset(&gnorm_vec[step % 100], 0, 1*sizeof(float)));
- kPercentileClipping<T, 2048, 4><<<blocks, 512>>>(g, gnorm_vec, step, n);
- CUDA_CHECK_RETURN(cudaPeekAtLastError());
+template<typename T>
+void percentileClipping(T *g, float *gnorm_vec, int step, const int n) {
+ int blocks = n / 2048;
+ blocks = n % 2048 == 0 ? blocks : blocks + 1;
+ CUDA_CHECK_RETURN(cudaMemset(&gnorm_vec[step % 100], 0, 1 * sizeof(float)));
+ kPercentileClipping < T, 2048, 4 ><<<blocks, 512>>>(g, gnorm_vec, step, n);
+ CUDA_CHECK_RETURN(cudaPeekAtLastError());
}
@@ -304,13 +195,23 @@ template<typename T> void percentileClipping(T * g, float *gnorm_vec, int step,
//==============================================================
template void estimateQuantiles(half *A, float *code, float offset, int n);
+
template void estimateQuantiles(float *A, float *code, float offset, int n);
-template void quantizeBlockwise<half, 0>(float * code, half *A, float *absmax, unsigned char *out, float* rand, int rand_offset, const int n);
-template void quantizeBlockwise<float, 0>(float * code, float *A, float *absmax, unsigned char *out, float* rand, int rand_offset, const int n);
-template void quantizeBlockwise<half, 1>(float * code, half *A, float *absmax, unsigned char *out, float* rand, int rand_offset, const int n);
-template void quantizeBlockwise<float, 1>(float * code, float *A, float *absmax, unsigned char *out, float* rand, int rand_offset, const int n);
+template void
+quantizeBlockwise<half, 0>(float *code, half *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n);
+
+template void
+quantizeBlockwise<float, 0>(float *code, float *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n);
+
+template void
+quantizeBlockwise<half, 1>(float *code, half *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n);
+
+template void
+quantizeBlockwise<float, 1>(float *code, float *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n);
+
template void dequantizeBlockwise<half>(float *code, unsigned char *A, float *absmax, half *out, int blocksize, const int n);
+
template void dequantizeBlockwise<float>(float *code, unsigned char *A, float *absmax, float *out, int blocksize, const int n);
#define MAKE_optimizer32bit(name, gtype) \
@@ -320,12 +221,19 @@ template void optimizer32bit<gtype, name>(gtype* g, gtype* p, \
const int step, const float lr, const float gnorm_scale, const bool skip_zeros, const int n);
MAKE_optimizer32bit(ADAM, half)
+
MAKE_optimizer32bit(ADAM, float)
+
MAKE_optimizer32bit(MOMENTUM, half)
+
MAKE_optimizer32bit(MOMENTUM, float)
+
MAKE_optimizer32bit(RMSPROP, half)
+
MAKE_optimizer32bit(RMSPROP, float)
+
MAKE_optimizer32bit(ADAGRAD, half)
+
MAKE_optimizer32bit(ADAGRAD, float)
#define MAKE_optimizerStatic8bit(name, gtype) \
@@ -338,11 +246,17 @@ template void optimizerStatic8bit<gtype, name>(gtype* p, gtype* g, unsigned char
float weight_decay, \
const float gnorm_scale, int n); \
+
MAKE_optimizerStatic8bit(ADAM, half)
+
MAKE_optimizerStatic8bit(ADAM, float)
+
MAKE_optimizerStatic8bit(MOMENTUM, half)
+
MAKE_optimizerStatic8bit(MOMENTUM, float)
+
MAKE_optimizerStatic8bit(RMSPROP, half)
+
MAKE_optimizerStatic8bit(RMSPROP, float)
#define MAKE_optimizerStatic8bitBlockwise(gtype, optim_name) \
@@ -350,14 +264,23 @@ template void optimizerStatic8bitBlockwise<gtype, optim_name>(gtype* p, gtype* g
unsigned char* state1, unsigned char* state2, float beta1, float beta2, float eps, int step, float lr, \
float* quantiles1, float* quantiles2, float* absmax1, float* absmax2, float weight_decay, const float gnorm_scale, bool skip_zeros, int n); \
+
MAKE_optimizerStatic8bitBlockwise(half, ADAM);
+
MAKE_optimizerStatic8bitBlockwise(float, ADAM);
+
MAKE_optimizerStatic8bitBlockwise(half, MOMENTUM);
+
MAKE_optimizerStatic8bitBlockwise(float, MOMENTUM);
+
MAKE_optimizerStatic8bitBlockwise(half, RMSPROP);
+
MAKE_optimizerStatic8bitBlockwise(float, RMSPROP);
+
MAKE_optimizerStatic8bitBlockwise(half, ADAGRAD);
+
MAKE_optimizerStatic8bitBlockwise(float, ADAGRAD);
-template void percentileClipping(float * g, float *gnorm_vec, int step, const int n);
-template void percentileClipping(half * g, float *gnorm_vec, int step, const int n);
+template void percentileClipping(float *g, float *gnorm_vec, int step, const int n);
+
+template void percentileClipping(half *g, float *gnorm_vec, int step, const int n);
diff --git a/csrc/ops.cuh b/csrc/ops.cuh
index 1bc13fb..8fb4cec 100644
--- a/csrc/ops.cuh
+++ b/csrc/ops.cuh
@@ -68,16 +68,6 @@ template<typename T, int OPTIMIZER> void optimizerStatic8bitBlockwise(T* p, T* g
template<typename T> void percentileClipping(T * g, float *gnorm_vec, int step, const int n);
-void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, int n);
-void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, int n);
-
void histogramScatterAdd2D(float* histogram, int *index1, int *index2, float *src, int maxidx1, int n);
#endif
-
-
-
-
-
-
-
diff --git a/csrc/pythonInterface.c b/csrc/pythonInterface.c
index e0b0d59..229b7ed 100644
--- a/csrc/pythonInterface.c
+++ b/csrc/pythonInterface.c
@@ -3,7 +3,10 @@
// This source code is licensed under the MIT license found in the
// LICENSE file in the root directory of this source tree.
+#if BUILD_CUDA
#include <ops.cuh>
+#endif
+#include <cpu_ops.h>
// We cannot call templated code from C, so we wrap the template in a C compatible call here if necessary.
// We use macro functions to expand all the different optimizers. Looks ugly, and is ugly, but its better than to
@@ -12,6 +15,7 @@
// UNMANGLED CALLS
//===================================================================================
+#if BUILD_CUDA
void estimateQuantiles_fp32(float *A, float *code, float offset, int n){ estimateQuantiles<float>(A, code, offset, n); }
void estimateQuantiles_fp16(half *A, float *code, float offset, int n){ estimateQuantiles<half>(A, code, offset, n); }
@@ -34,15 +38,15 @@ MAKE_FUNC32(adagrad, ADAGRAD, half, 16)
#define MAKE_FUNC8(fname, oname, gtype, gbits) \
void fname##_static_8bit_g##gbits(gtype* p, gtype* g, unsigned char* state1, unsigned char* state2, \
- float *unorm, float max_unorm, float param_norm, \
+ float *unorm, float max_unorm, float param_norm, \
float beta1, float beta2, \
float eps, int step, float lr, \
float* quantiles1, float* quantiles2, \
float* max1, float* max2, float* new_max1, float* new_max2, \
float weight_decay, float gnorm_scale, int n) \
{ \
- optimizerStatic8bit<gtype, oname>(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, step, lr, \
- quantiles1, quantiles2, max1, max2, new_max1, new_max2, weight_decay, gnorm_scale, n); \
+ optimizerStatic8bit<gtype, oname>(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, step, lr, \
+ quantiles1, quantiles2, max1, max2, new_max1, new_max2, weight_decay, gnorm_scale, n); \
} \
MAKE_FUNC8(adam, ADAM, float, 32)
@@ -78,39 +82,41 @@ void quantizeBlockwise_stochastic_fp32(float * code, float *A, float *absmax, un
void dequantizeBlockwise_fp16(float *code, unsigned char *A, float *absmax, half *out, int blocksize, const int n){ dequantizeBlockwise<half>(code, A, absmax, out, blocksize, n); } \
void dequantizeBlockwise_fp32(float *code, unsigned char *A, float *absmax, float *out, int blocksize, const int n){ dequantizeBlockwise<float>(code, A, absmax, out, blocksize, n); }
+#endif
extern "C"
{
- void cestimate_quantiles_fp32(float *A, float *code, float offset, int n){ estimateQuantiles_fp32(A, code, offset, n); }
- void cestimate_quantiles_fp16(half *A, float *code, float offset, int n){ estimateQuantiles_fp16(A, code, offset, n); }
- void cquantize(float *code, float *A, unsigned char *out, int n){ quantize(code, A, out, n); }
- void cdequantize(float *code, unsigned char *A, float *out, int n){ dequantize(code, A, out, n); }
- void cquantize_blockwise_fp16(float * code, half *A, float *absmax, unsigned char *out, const int n){ quantizeBlockwise_fp16(code, A, absmax, out, n); }
- void cquantize_blockwise_fp32(float * code, float *A, float *absmax, unsigned char *out, const int n){ quantizeBlockwise_fp32(code, A, absmax, out, n); }
- void cquantize_blockwise_stochastic_fp16(float * code, half *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n){ quantizeBlockwise_stochastic_fp16(code, A, absmax, out, rand, rand_offset, n); }
- void cquantize_blockwise_stochastic_fp32(float * code, float *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n){ quantizeBlockwise_stochastic_fp32(code, A, absmax, out, rand, rand_offset, n); }
-
- void cdequantize_blockwise_fp16(float *code, unsigned char *A, float *absmax, half *out, int blocksize, const int n){ dequantizeBlockwise_fp16(code, A, absmax, out, blocksize, n); }
- void cdequantize_blockwise_fp32(float *code, unsigned char *A, float *absmax, float *out, int blocksize, const int n){ dequantizeBlockwise_fp32(code, A, absmax, out, blocksize, n); }
-
- #define MAKE_CFUNC32(name, gtype, gbits) \
- void c##name##32bit_g##gbits(gtype *g, gtype *p, \
- float* state1, float* state2, float *unorm, float max_unorm, float param_norm, \
- const float beta1, const float beta2, const float eps, const float weight_decay, \
- const int step, const float lr, const float gnorm_scale, bool skip_zeros, const int n) \
- { name##32bit_g##gbits(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, weight_decay, step, lr, gnorm_scale, skip_zeros, n); } \
-
- MAKE_CFUNC32(adam, float, 32)
- MAKE_CFUNC32(adam, half, 16)
- MAKE_CFUNC32(momentum, float, 32)
- MAKE_CFUNC32(momentum, half, 16)
- MAKE_CFUNC32(rmsprop, float, 32)
- MAKE_CFUNC32(rmsprop, half, 16)
- MAKE_CFUNC32(adagrad, float, 32)
- MAKE_CFUNC32(adagrad, half, 16)
-
- #define MAKE_CFUNC8(name, gtype, gbits) \
- void c##name##_static_8bit_g##gbits(gtype* p, gtype* g, unsigned char* state1, unsigned char* state2, \
+#if BUILD_CUDA
+void cestimate_quantiles_fp32(float *A, float *code, float offset, int n){ estimateQuantiles_fp32(A, code, offset, n); }
+void cestimate_quantiles_fp16(half *A, float *code, float offset, int n){ estimateQuantiles_fp16(A, code, offset, n); }
+void cquantize(float *code, float *A, unsigned char *out, int n){ quantize(code, A, out, n); }
+void cdequantize(float *code, unsigned char *A, float *out, int n){ dequantize(code, A, out, n); }
+void cquantize_blockwise_fp16(float * code, half *A, float *absmax, unsigned char *out, const int n){ quantizeBlockwise_fp16(code, A, absmax, out, n); }
+void cquantize_blockwise_fp32(float * code, float *A, float *absmax, unsigned char *out, const int n){ quantizeBlockwise_fp32(code, A, absmax, out, n); }
+void cquantize_blockwise_stochastic_fp16(float * code, half *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n){ quantizeBlockwise_stochastic_fp16(code, A, absmax, out, rand, rand_offset, n); }
+void cquantize_blockwise_stochastic_fp32(float * code, float *A, float *absmax, unsigned char *out, float *rand, int rand_offset, const int n){ quantizeBlockwise_stochastic_fp32(code, A, absmax, out, rand, rand_offset, n); }
+
+void cdequantize_blockwise_fp16(float *code, unsigned char *A, float *absmax, half *out, int blocksize, const int n){ dequantizeBlockwise_fp16(code, A, absmax, out, blocksize, n); }
+void cdequantize_blockwise_fp32(float *code, unsigned char *A, float *absmax, float *out, int blocksize, const int n){ dequantizeBlockwise_fp32(code, A, absmax, out, blocksize, n); }
+
+#define MAKE_CFUNC32(name, gtype, gbits) \
+ void c##name##32bit_g##gbits(gtype *g, gtype *p, \
+ float* state1, float* state2, float *unorm, float max_unorm, float param_norm, \
+ const float beta1, const float beta2, const float eps, const float weight_decay, \
+ const int step, const float lr, const float gnorm_scale, bool skip_zeros, const int n) \
+ { name##32bit_g##gbits(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, weight_decay, step, lr, gnorm_scale, skip_zeros, n); } \
+
+MAKE_CFUNC32(adam, float, 32)
+MAKE_CFUNC32(adam, half, 16)
+MAKE_CFUNC32(momentum, float, 32)
+MAKE_CFUNC32(momentum, half, 16)
+MAKE_CFUNC32(rmsprop, float, 32)
+MAKE_CFUNC32(rmsprop, half, 16)
+MAKE_CFUNC32(adagrad, float, 32)
+MAKE_CFUNC32(adagrad, half, 16)
+
+#define MAKE_CFUNC8(name, gtype, gbits) \
+ void c##name##_static_8bit_g##gbits(gtype* p, gtype* g, unsigned char* state1, unsigned char* state2, \
float *unorm, float max_unorm, float param_norm, \
float beta1, float beta2, \
float eps, int step, float lr, \
@@ -118,40 +124,40 @@ extern "C"
float* max1, float* max2, float* new_max1, float* new_max2, \
float weight_decay, float gnorm_scale, int n) \
{ \
- name##_static_8bit_g##gbits(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, step, lr, \
- quantiles1, quantiles2, max1, max2, new_max1, new_max2, weight_decay, gnorm_scale, n); \
+ name##_static_8bit_g##gbits(g, p, state1, state2, unorm, max_unorm, param_norm, beta1, beta2, eps, step, lr, \
+ quantiles1, quantiles2, max1, max2, new_max1, new_max2, weight_decay, gnorm_scale, n); \
} \
- MAKE_CFUNC8(adam, float, 32)
- MAKE_CFUNC8(adam, half, 16)
- MAKE_CFUNC8(momentum, float, 32)
- MAKE_CFUNC8(momentum, half, 16)
- MAKE_CFUNC8(rmsprop, float, 32)
- MAKE_CFUNC8(rmsprop, half, 16)
+MAKE_CFUNC8(adam, float, 32)
+MAKE_CFUNC8(adam, half, 16)
+MAKE_CFUNC8(momentum, float, 32)
+MAKE_CFUNC8(momentum, half, 16)
+MAKE_CFUNC8(rmsprop, float, 32)
+MAKE_CFUNC8(rmsprop, half, 16)
- #define MAKE_CBLOCKWISE8(fname, optim_name, gtype, gbits) \
+#define MAKE_CBLOCKWISE8(fname, optim_name, gtype, gbits) \
void c##fname##_8bit_blockwise_fp##gbits(gtype* p, gtype* g, \
unsigned char* state1, unsigned char* state2, float beta1, float beta2, float eps, int step, float lr, \
float* quantiles1, float* quantiles2, float* absmax1, float* absmax2, float weight_decay, const float gnorm_scale, bool skip_zeros, int n) \
{ fname##_8bit_blockwise_fp##gbits(p, g, state1, state2, beta1, beta2, eps, step, lr, quantiles1, quantiles2, absmax1, absmax2, weight_decay, gnorm_scale, skip_zeros, n); } \
- MAKE_CBLOCKWISE8(adam, ADAM, half, 16)
- MAKE_CBLOCKWISE8(adam, ADAM, float, 32)
- MAKE_CBLOCKWISE8(momentum, MOMENTUM, half, 16)
- MAKE_CBLOCKWISE8(momentum, MOMENTUM, float, 32)
- MAKE_CBLOCKWISE8(rmsprop, RMSPROP, half, 16)
- MAKE_CBLOCKWISE8(rmsprop, RMSPROP, float, 32)
- MAKE_CBLOCKWISE8(adagrad, ADAGRAD, half, 16)
- MAKE_CBLOCKWISE8(adagrad, ADAGRAD, float, 32)
+MAKE_CBLOCKWISE8(adam, ADAM, half, 16)
+MAKE_CBLOCKWISE8(adam, ADAM, float, 32)
+MAKE_CBLOCKWISE8(momentum, MOMENTUM, half, 16)
+MAKE_CBLOCKWISE8(momentum, MOMENTUM, float, 32)
+MAKE_CBLOCKWISE8(rmsprop, RMSPROP, half, 16)
+MAKE_CBLOCKWISE8(rmsprop, RMSPROP, float, 32)
+MAKE_CBLOCKWISE8(adagrad, ADAGRAD, half, 16)
+MAKE_CBLOCKWISE8(adagrad, ADAGRAD, float, 32)
- void cpercentile_clipping_g32(float * g, float *gnorm_vec, int step, const int n){ percentileClipping_g32(g, gnorm_vec, step, n); }
- void cpercentile_clipping_g16(half * g, float *gnorm_vec, int step, const int n){ percentileClipping_g16(g, gnorm_vec, step, n); }
+void cpercentile_clipping_g32(float * g, float *gnorm_vec, int step, const int n){ percentileClipping_g32(g, gnorm_vec, step, n); }
+void cpercentile_clipping_g16(half * g, float *gnorm_vec, int step, const int n){ percentileClipping_g16(g, gnorm_vec, step, n); }
+void chistogram_scatter_add_2d(float* histogram, int *index1, int *index2, float *src, int maxidx1, int n){ histogramScatterAdd2D(histogram, index1, index2, src, maxidx1, n); }
+#endif
- void cquantize_blockwise_cpu_fp32(float *code, float *A, float *absmax, unsigned char *out, const int n){ quantize_cpu(code, A, absmax, out, n); }
- void cdequantize_blockwise_cpu_fp32(float *code, unsigned char *A, float *absmax, float *out, const int n){ dequantize_cpu(code, A, absmax, out, n); }
-
- void chistogram_scatter_add_2d(float* histogram, int *index1, int *index2, float *src, int maxidx1, int n){ histogramScatterAdd2D(histogram, index1, index2, src, maxidx1, n); }
+void cquantize_blockwise_cpu_fp32(float *code, float *A, float *absmax, unsigned char *out, const int n){ quantize_cpu(code, A, absmax, out, n); }
+void cdequantize_blockwise_cpu_fp32(float *code, unsigned char *A, float *absmax, float *out, const int n){ dequantize_cpu(code, A, absmax, out, n); }
}
diff --git a/setup.py b/setup.py
index 59cd78e..2402c02 100644
--- a/setup.py
+++ b/setup.py
@@ -6,27 +6,27 @@ import os
from setuptools import setup, find_packages
-
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
+version = os.getenv("CUDA_VERSION", "cpu")
+
setup(
- name = f"bitsandbytes-cuda{os.environ['CUDA_VERSION']}",
- version = "0.26.0",
- author = "Tim Dettmers",
- author_email = "dettmers@cs.washington.edu",
- description = ("8-bit optimizers and quantization routines."),
- license = "MIT",
- keywords = "gpu optimizers optimization 8-bit quantization compression",
- url = "http://packages.python.org/bitsandbytes",
+ name="bitsandbytes",
+ version=f"0.26.0+{version}",
+ author="Tim Dettmers",
+ author_email="dettmers@cs.washington.edu",
+ description="8-bit optimizers and quantization routines.",
+ license="MIT",
+ keywords="gpu optimizers optimization 8-bit quantization compression",
+ url="http://packages.python.org/bitsandbytes",
packages=find_packages(),
package_data={'': ['libbitsandbytes.so']},
long_description=read('README.md'),
- long_description_content_type = 'text/markdown',
+ long_description_content_type='text/markdown',
classifiers=[
"Development Status :: 4 - Beta",
'Topic :: Scientific/Engineering :: Artificial Intelligence'
],
)
-