python_code stringlengths 0 456k |
|---|
import numpy as np
import cv2 as cv
# aruco
adict = cv.aruco.Dictionary_get(cv.aruco.DICT_4X4_50)
cv.imshow("marker", cv.aruco.drawMarker(adict, 0, 400))
# random calibration data. your mileage may vary.
imsize = (800, 600)
K = cv.getDefaultNewCameraMatrix(np.diag([800, 800, 1]), imsize, True)
# AR scene
cv.ovis.add... |
import numpy as np
import cv2 as cv
# add some external resources
cv.ovis.addResourceLocation("packs/Sinbad.zip")
# camera intrinsics
imsize = (800, 600)
K = np.diag([800, 800, 1])
K[:2, 2] = (400, 500) # offset pp
# observer scene
owin = cv.ovis.createWindow("VR", imsize)
cv.ovis.createGridMesh("ground", (10, 10), ... |
#!/usr/bin/env python
import os
import cv2 as cv
import numpy as np
from tests_common import NewOpenCVTests, unittest
class cudaarithm_test(NewOpenCVTests):
def setUp(self):
super(cudaarithm_test, self).setUp()
if not cv.cuda.getCudaEnabledDeviceCount():
self.skipTest("No CUDA-capable ... |
#!/usr/bin/env python
import subprocess
import os
import sys
basedir = os.path.dirname(sys.argv[0])
readme = os.path.join(basedir, "README.md")
with open(readme) as f:
inp = f.read()
out = ""
it = iter(inp.splitlines(True))
for line in it:
out += line
if line.startswith("```cmdoutput"):
# Get command.
... |
import os
import re
from datetime import datetime
from setuptools import find_packages, setup
from op_builder.utils import get_cuda_bare_metal_version
try:
import torch
from torch.utils.cpp_extension import CUDA_HOME, BuildExtension, CUDAExtension
print("\n\ntorch.__version__ = {}\n\n".format(torch.__ve... |
import os
from .builder import Builder
from .utils import append_nvcc_threads
class ScaledMaskedSoftmaxBuilder(Builder):
NAME = "scaled_masked_softmax"
PREBUILT_IMPORT_PATH = "colossalai._C.scaled_masked_softmax"
def __init__(self):
super().__init__(name=ScaledMaskedSoftmaxBuilder.NAME, prebuilt... |
import os
from .builder import Builder
from .utils import append_nvcc_threads, get_cuda_cc_flag
class LayerNormBuilder(Builder):
NAME = "layernorm"
PREBUILT_IMPORT_PATH = "colossalai._C.layernorm"
def __init__(self):
super().__init__(name=LayerNormBuilder.NAME, prebuilt_import_path=LayerNormBuil... |
import os
from .builder import Builder
from .utils import get_cuda_cc_flag
class FusedOptimBuilder(Builder):
NAME = "fused_optim"
PREBUILT_IMPORT_PATH = "colossalai._C.fused_optim"
def __init__(self):
super().__init__(name=FusedOptimBuilder.NAME, prebuilt_import_path=FusedOptimBuilder.PREBUILT_I... |
import os
from .builder import Builder
from .utils import append_nvcc_threads, get_cuda_cc_flag
class MultiHeadAttnBuilder(Builder):
NAME = "multihead_attention"
PREBUILT_IMPORT_PATH = "colossalai._C.multihead_attention"
def __init__(self):
super().__init__(name=MultiHeadAttnBuilder.NAME,
... |
from .cpu_adam import CPUAdamBuilder
from .fused_optim import FusedOptimBuilder
from .layernorm import LayerNormBuilder
from .moe import MOEBuilder
from .multi_head_attn import MultiHeadAttnBuilder
from .scaled_masked_softmax import ScaledMaskedSoftmaxBuilder
from .scaled_upper_triangle_masked_softmax import ScaledUppe... |
import importlib
import os
import time
from abc import ABC, abstractmethod
from pathlib import Path
from typing import List
def print_rank_0(message):
"""
Print on only one process to avoid spamming.
"""
try:
import torch.distributed as dist
if not dist.is_initialized():
is... |
import os
from .builder import Builder
from .utils import append_nvcc_threads
class CPUAdamBuilder(Builder):
NAME = "cpu_adam"
PREBUILT_IMPORT_PATH = "colossalai._C.cpu_adam"
def __init__(self):
super().__init__(name=CPUAdamBuilder.NAME, prebuilt_import_path=CPUAdamBuilder.PREBUILT_IMPORT_PATH)
... |
import re
import subprocess
from typing import List
def get_cuda_bare_metal_version(cuda_dir):
raw_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True)
output = raw_output.split()
release_idx = output.index("release") + 1
release = output[release_idx].split(".")
... |
import os
from .builder import Builder
from .utils import append_nvcc_threads, get_cuda_cc_flag
class ScaledUpperTrainglemaskedSoftmaxBuilder(Builder):
NAME = "scaled_upper_triangle_masked_softmax"
PREBUILT_IMPORT_PATH = "colossalai._C.scaled_upper_triangle_masked_softmax"
def __init__(self):
su... |
import os
from .builder import Builder
from .utils import append_nvcc_threads, get_cuda_cc_flag
class MOEBuilder(Builder):
NAME = "moe"
PREBUILT_IMPORT_PATH = "colossalai._C.moe"
def __init__(self):
super().__init__(name=MOEBuilder.NAME, prebuilt_import_path=MOEBuilder.PREBUILT_IMPORT_PATH)
... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
from pathlib import Path
import pytest
import torch
import torch.multiprocessing as mp
from colossalai import launch
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
from colossalai... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
parallel = dict(
pipeline=dict(size=2),
tensor=dict(
size=4,
mode='2d'
)
)
|
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
parallel = dict(
pipeline=dict(size=2),
tensor=dict(
size=8,
mode='3d'
)
)
|
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
parallel = dict(
pipeline=dict(size=2),
tensor=dict(
size=8,
depth=2,
mode='2.5d'
)
)
|
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
import colossalai
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.tes... |
from functools import partial
import colossalai
from colossalai.utils.cuda import get_current_device
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.nn.optimizer import HybridAdam
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.utils import free_por... |
import pytest
import colossalai
from colossalai.utils.cuda import get_current_device
from colossalai.gemini.tensor_utils import (colo_tensor_mem_usage, colo_model_data_tensor_move,
colo_model_data_tensor_move_inline, colo_model_data_move_to_cpu,
... |
from copy import deepcopy
from functools import partial
import colossalai
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.utils import free_port
from colossalai.zero.shard_utils import (BucketTensorShardStrategy, Tens... |
import pytest
import colossalai
import torch
import torch.multiprocessing as mp
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.utils.cuda import get_current_device
from colossalai.utils import free_port
from functools import partial
from tests.test_tensor.common_utils import set_seed
from tes... |
from functools import partial
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from common import CONFIG, check_sharded_model_params
from torch.nn.parallel import DistributedDataParallel as DDP
import colossalai
from colossalai.amp import convert_to_apex_amp
from colossal... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
import colossalai
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from colossalai.core import global_context as gpc
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.uti... |
from functools import partial
import torch
import torch.distributed as dist
from colossalai.logging import get_dist_logger
from colossalai.utils import checkpoint
from colossalai.zero.shard_utils import TensorShardStrategy
from colossalai.zero.sharded_model import ShardedModelV2
LOGGER = get_dist_logger('zero_test')
... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from common import CONFIG
import colossalai
from colossalai.gemini.memory_tracer.utils import colo_model_mem_usage
from colossalai.logging import get_dist_logger
from colossalai... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from common import CONFIG, check_grads_padding, run_fwd_bwd
from torch.nn.parallel import DistributedDataParallel as DDP
import colossalai
from colossalai.testing import paramet... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from copy import deepcopy
from functools import partial
import colossalai
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.utils import free_port
from colossalai.zero.in... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.testing import assert_close
import colossalai
from colossalai.tensor import ProcessGroup
from colossalai.testing import parameterize... |
from functools import partial
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import torch.nn as nn
import colossalai
from colossalai.tensor import ProcessGroup
from colossalai.utils import free_port, get_current_device
from colossalai.utils.model.colo_init_context impor... |
import copy
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.testing import assert_close
import colossalai
from colossalai.testing.random import seed_all
from colossalai.utils impor... |
import copy
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.testing import assert_close
import colossalai
from colossalai.testing.random import seed_all
from colossalai.utils impor... |
import pytest
import torch
from einops import rearrange
from colossalai.kernel.cuda_native.flash_attention import HAS_FLASH_ATTN, HAS_MEM_EFF_ATTN, HAS_TRITON
if HAS_FLASH_ATTN:
from colossalai.kernel.cuda_native.flash_attention import (
MaskedFlashAttention,
flash_attention_q_k_v,
flash_a... |
import torch
from colossalai.utils.model.lazy_init_context import LazyInitContext
from torchvision.models import resnet34
import random
import numpy as np
MANUAL_SEED = 0
random.seed(MANUAL_SEED)
np.random.seed(MANUAL_SEED)
torch.manual_seed(MANUAL_SEED)
def test_lazy_init_with_meta():
ctx = LazyInitContext(to_m... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import copy
import colossalai
from colossalai.zero.sharded_model.sharded_model_v2 import ShardedModelV2
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.logging import disable_existing_l... |
from colossalai.tensor import distspec, ColoTensorSpec, ProcessGroup
from colossalai.tensor.colo_parameter import ColoParameter
import colossalai
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.logging import disable_existing_loggers
from colossalai.utils import free_port, get_current_devi... |
from colossalai.utils import free_port
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.zero.sharded_param import ShardedTensor
from colossalai.gemini.tensor_utils import colo_model_data_tensor_move, colo_model_data_tensor_move_inline
import colossalai
import torch
import torch.multiprocessin... |
import os, shutil
import torch
import pytest
from copy import deepcopy
from functools import partial
import torch.multiprocessing as mp
import torch.distributed as dist
from torch.optim.lr_scheduler import CosineAnnealingLR
from torch.optim.lr_scheduler import MultiplicativeLR
from colossalai.nn.lr_scheduler import C... |
import pytest
import colossalai
from colossalai.utils.cuda import get_current_device
from colossalai.utils.memory import colo_set_process_memory_fraction, colo_device_memory_capacity
from colossalai.utils import free_port
from functools import partial
import torch.multiprocessing as mp
def _run_colo_set_process_mem... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import pytest
import torch
import torch.nn.functional as F
from colossalai.context.parallel_mode import ParallelMode
from colossalai.context.random import add_seed, seed, set_mode, reset_seeds
from colossalai.utils.activation_checkpoint import checkpoint
def forward(x,... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import pprint
from functools import partial
import colossalai.nn as col_nn
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
fro... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import pprint
from functools import partial
import colossalai.nn as col_nn
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
fro... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import pprint
from functools import partial
import colossalai.nn as col_nn
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
fro... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import pprint
from functools import partial
import colossalai.nn as col_nn
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
fro... |
import os
from functools import partial
from tempfile import TemporaryDirectory
from typing import Dict
import colossalai
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.utils ... |
import torch
import torch.nn as nn
from colossalai.utils.checkpoint_io.meta import ParamDistMeta
from colossalai.utils.checkpoint_io.utils import build_checkpoints
from torch.optim import Adam
class DummyModel(nn.Module):
def __init__(self) -> None:
super().__init__()
self.fc = nn.Linear(20, 1)
... |
import os
from functools import partial
from tempfile import TemporaryDirectory
import colossalai
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.utils import free_port
from co... |
from colossalai.utils.checkpoint_io.meta import ParamDistMeta
from colossalai.utils.checkpoint_io.constant import GLOBAL_META_FILE_NAME
from colossalai.utils.checkpoint_io.io import save, merge
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.utils import free_port
from tempfile import Temporar... |
import torch
from colossalai.utils.checkpoint_io.meta import ParamRedistMeta
from colossalai.utils.checkpoint_io.distributed import flatten_zero_param, split_tp_param, unmerge_param
def test_flatten_zero_param_even() -> None:
redist_meta = ParamRedistMeta(4, 1, zero_start_dp_rank=0, zero_offsets=[0, 4, 8, 12])
... |
import torch
from colossalai.utils.checkpoint_io.meta import ParamDistMeta
from colossalai.utils.checkpoint_io.distributed import unflatten_zero_param, gather_tp_param, merge_param
def test_unflatten_zero_param_even() -> None:
dist_metas = [ParamDistMeta(i, 4, 0, 1, zero_numel=16, zero_orig_shape=[4, 4]) for i in... |
from copy import deepcopy
from functools import partial
from tempfile import TemporaryDirectory
from typing import Dict
import colossalai
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.testing import rerun_if_address_is_in_use
from c... |
import copy
import pytest
import colossalai
import torch
import torch.multiprocessing as mp
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.utils.cuda import get_current_device
from colossalai.utils import free_port
from colossalai.utils.model.colo_init_context import ColoInitContext
from fun... |
import pytest
import colossalai
import torch
import torch.multiprocessing as mp
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.utils.cuda import get_current_device
from colossalai.utils import free_port
from functools import partial
from colossalai.nn.parallel.reducer import Reducer
import to... |
import os
import random
from functools import partial
from typing import Callable, Type
import numpy as np
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import colossalai
from colossalai.gemini.chunk import ChunkManager, search_chunk_configuration
from colossalai.gemin... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import os
from pathlib import Path
import pytest
from torchvision import transforms, datasets
from torch.utils.data import DataLoader
@pytest.mark.cpu
def test_cifar10_dataset():
# build transform
transform_pipeline = [transforms.ToTensor()]
transform_pipe... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import os
from functools import partial
from pathlib import Path
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import colossalai
from torchvision import transforms, datasets
from colossalai.context import ParallelMode, C... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import os
from functools import partial
from pathlib import Path
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from torchvision import transforms, datasets
import colossalai
from colossalai.context import ParallelMode, C... |
import torch
from colossalai.auto_parallel.tensor_shard.utils import (
get_broadcast_shape,
is_broadcastable,
recover_sharding_spec_for_broadcast_shape,
)
from colossalai.device.device_mesh import DeviceMesh
from colossalai.tensor.sharding_spec import ShardingSpec
def test_is_broadcastable():
x1 = to... |
import torch
from colossalai.auto_parallel.tensor_shard.options import SolverOptions
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationDataType
from colossalai.auto_parallel.tensor_shard.solver import CostGraph, GraphAnalyser, Solver, StrategiesConstructor
from colossalai.device.device_mesh ... |
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.solver import GraphAnalyser
from colossalai.fx import ColoGraphModule, ColoTracer
class LinearModel(nn.Module):
def __init__(self):
super().__init__()
self.linear1 = nn.Linear(4, 4)
self.relu = nn.ReLU(inplace=... |
import copy
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
from colossalai.auto_parallel.tensor_shard.initialize import initialize_model
from colossalai.device.device_mesh import DeviceMesh
from colossalai.initia... |
import torch
from torch.fx import GraphModule
from torchvision.models import resnet50
from colossalai.auto_parallel.tensor_shard.constants import BATCHNORM_MODULE_OP
from colossalai.auto_parallel.tensor_shard.options import SolverOptions
from colossalai.auto_parallel.tensor_shard.solver import CostGraph, GraphAnalyser... |
import copy
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
from colossalai.auto_parallel.tensor_shard.initialize import initialize_model
from colossalai.device.device_mesh import DeviceMesh
from colossalai.initia... |
import copy
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.initialize import initialize_model
from colossalai.device.device_mesh import DeviceMesh
from colossalai.initialize import launch
from colossalai.logg... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.auto_parallel.tensor_shard.initialize import initialize_model
from colossalai.device.device_mesh import DeviceMesh
from colossalai.initialize import launch
from colossalai.logging import disable_existing_logger... |
from functools import partial
from typing import Optional, Tuple, Union
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from torch.utils.checkpoint import checkpoint
from transformers.pytorch_utils import Conv1D
from colossalai.auto_parallel.tensor_shard.initialize import initializ... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler import LinearModuleHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import ShardingStrategy, StrategiesVector
from colossalai.de... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.meta_profiler import meta_register
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType
from colossalai.device.device_mesh imp... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.device.device_mesh import DeviceMesh
from colossalai.fx import ColoGraphModule, ColoTracer
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.device.device_mesh import DeviceMesh
from colossalai.fx import ColoGraphModule, ColoTracer
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.device.device_mesh import DeviceMesh
from colossalai.fx import ColoGraphModule, ColoTracer
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
... |
import copy
from pprint import pprint
from typing import Dict, List
import torch
from torch.fx import GraphModule
from colossalai.auto_parallel.passes.runtime_apply_pass import runtime_apply_pass
from colossalai.auto_parallel.passes.runtime_preparation_pass import runtime_preparation_pass
from colossalai.auto_paralle... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
MemoryCost,
OperationData,
OperationDataType,
ShardingStrategy,
StrategiesVector,
TrainCycleItem,
)
from colos... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler import LinearModuleHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
MemoryCost,
OperationData,
OperationDat... |
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.getattr_handler import GetattrHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVector
from colossalai.device.device_mesh import DeviceMesh
from colossalai.fx... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler import SplitHandler
from colossalai.auto_parallel.tensor_shard.node_handler.conv_handler import ConvFunctionHandler
from colossalai.auto_parallel.te... |
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler import DefaultReshapeHandler
from colossalai.auto_parallel.tensor_shard.node_handler.conv_handler import ConvFunctionHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, S... |
import pytest
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.matmul_handler import (
MatMulHandler,
MatMulType,
_get_bmm_logical_shape,
get_matmul_type,
)
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
OperationData,
OperationDa... |
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.output_handler import OutputHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVector
from colossalai.device.device_mesh import DeviceMesh
from colossalai.fx i... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
import torch.nn.functional as F
from colossalai.auto_parallel.tensor_shard.node_handler.linear_handler import LinearFunctionHandler
from colossalai.auto_parallel.tensor_shard.node_handler.softmax_handler ... |
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.placeholder_handler import PlaceholderHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVector
from colossalai.device.device_mesh import DeviceMesh
from colos... |
from functools import partial
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler import LinearFunctionHandler
from colossalai.auto_parallel.tensor_shard.options import ShardOption
from colossalai.auto_parallel.tensor_shard.sharding_strategy im... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler import PermuteHandler, TransposeHandler
from colossalai.auto_parallel.tensor_shard.node_handler.conv_handler import ConvFunctionHandler
from colossa... |
from faulthandler import disable
from functools import partial
from xml.dom import WrongDocumentErr
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from typing_extensions import Self
from colossalai.auto_parallel.tensor_shard.node_handler import LinearFunctionHandler
from colossala... |
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.where_handler import \
WhereHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (OperationData, OperationDataType, StrategiesVector)
from colossalai.device.device_mesh import DeviceMesh
from colossala... |
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.tensor_constructor_handler import TensorConstructorHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVector
from colossalai.device.device_mesh import DeviceMe... |
from faulthandler import disable
from functools import partial
from xml.dom import WrongDocumentErr
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
import torch.nn.functional as F
from typing_extensions import Self
from colossalai.auto_parallel.tensor_shard.node_handler import Line... |
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.conv_handler import ConvFunctionHandler
from colossalai.auto_parallel.tensor_shard.node_handler.unary_elementwise_handler import UnaryElementwiseHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import Operati... |
import copy
from typing import Dict, List
import torch
from torch.fx import GraphModule
from colossalai.auto_parallel.passes.runtime_apply_pass import runtime_apply_pass
from colossalai.auto_parallel.passes.runtime_preparation_pass import runtime_preparation_pass
from colossalai.auto_parallel.tensor_shard.options imp... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler import ViewHandler
from colossalai.auto_parallel.tensor_shard.node_handler.conv_handler import ConvFunctionHandler
from colossalai.auto_parallel.ten... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler import LinearFunctionHandler, LinearModuleHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
OperationData,
Opera... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.conv_handler import ConvFunctionHandler
from colossalai.auto_parallel.tensor_shard.node_handler.linear_handler import LinearFunctionHandler
from col... |
import pytest
import torch
import torch.nn as nn
from colossalai.auto_parallel.tensor_shard.node_handler.normal_pooling_handler import NormPoolingHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVector
from colossalai.device.device_mesh import Devi... |
from faulthandler import disable
from functools import partial
from xml.dom import WrongDocumentErr
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn as nn
from typing_extensions import Self
from colossalai.auto_parallel.tensor_shard.node_handler import LinearFunctionHandler, LinearModuleH... |
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