python_code stringlengths 0 456k |
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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 BinaryElementwiseHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVect... |
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.embedding_handler import (
EmbeddingFunctionHandler,
EmbeddingModuleHandler,
)
from colossalai.auto_parallel.tensor_shard.sharding_strategy ... |
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 BMMFunctionHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVector
fro... |
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.default_reshape_handler import DefaultReshapeHandler
from colossalai.auto_parallel.tensor_shard.node_handler.getitem_handler import GetItemHandler
f... |
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, ConvModuleHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, Operat... |
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.layer_norm_handler import LayerNormModuleHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataTyp... |
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 BMMFunctionHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVector
fro... |
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.batch_norm_handler import BatchNormModuleHandler
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataTyp... |
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from transformers.activations import ACT2FN
from transformers.models.gpt2.modeling_gpt2 import BaseModelOutputWithPastAndCrossAttentions, GPT2PreTrainedModel
from transformers.pytorch_utils import Conv1D
class GPT2MLP(nn.Module):
def _... |
import torch
import torch.nn as nn
import transformers
from torch.fx import GraphModule
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, GraphAnalys... |
import copy
import random
from functools import partial
from typing import Dict
import numpy as np
import pytest
import torch
import torch.multiprocessing as mp
import transformers
from torch.fx import GraphModule
from colossalai.auto_parallel.tensor_shard.initialize import (
ModuleWrapper,
build_strategy_con... |
import torch
import torch.nn.functional as F
from colossalai.auto_parallel.passes.runtime_preparation_pass import node_args_converting_pass
from colossalai.device.device_mesh import DeviceMesh
from colossalai.fx.graph_module import ColoGraphModule
from colossalai.fx.tracer import ColoTracer
from colossalai.tensor.shar... |
import torch
import torch.nn.functional as F
from colossalai.auto_parallel.passes.runtime_preparation_pass import size_value_converting_pass
from colossalai.device.device_mesh import DeviceMesh
from colossalai.fx.graph_module import ColoGraphModule
from colossalai.fx.tracer import ColoTracer
from colossalai.tensor.sha... |
import pytest
from functools import partial
import numpy as np
import random
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.utils import free_port
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.tensor import ColoParameter, ProcessGroup, ShardSpec, Compute... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from checks_1d.check_layer_1d import *
from colossalai.core import global_context as gpc
from colossalai.initialize import launch
from colossalai.logging import disable_existing... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import torch
DEPTH = 4
BATCH_SIZE = 8
SEQ_LENGTH = 8
IMG_SIZE = 16
HIDDEN_SIZE = 8
NUM_CLASSES = 8
VOCAB_SIZE = 16
def check_equal(A, B):
assert torch.allclose(A, B, rtol=1e-3, atol=1e-1) == True
|
import torch
import torch.distributed as dist
from torch.nn import Parameter
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.global_variables import tensor_parallel_env as env
from colossalai.nn import (
Classifier1D,
Embedding1D,
... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.core import global_context as gpc
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from colossalai.utils import fr... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import torch
DEPTH = 2
BATCH_SIZE = 8
SEQ_LENGTH = 8
HIDDEN_SIZE = 8
NUM_CLASSES = 8
VOCAB_SIZE = 16
IMG_SIZE = 16
def check_equal(A, B):
assert torch.allclose(A, B, rtol=1e-3, atol=1e-2)
|
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import torch
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.nn.layer.parallel_2d._operation import Matmul_AB_2D, Matmul_ABT_2D, Matmul_ATB_2D
from colossalai.utils import get_current_device
fro... |
import torch
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.nn import (Classifier2D, CrossEntropyLoss2D, Embedding2D, LayerNorm2D, Linear2D, PatchEmbedding2D,
VanillaClassifier, VanillaPatchEmbedding, VocabParallelCl... |
import colossalai
import colossalai.nn as col_nn
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import pytest
from colossalai.core import global_context as gpc
from colossalai.context import ParallelMode
from colossalai.testing import rerun_if_address_is_in_use
from functools import p... |
import torch
from colossalai.context import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.nn import TransformerSelfAttentionRing
from colossalai.utils import get_current_device
def check_selfattention():
WORLD_SIZE = gpc.get_world_size(ParallelMode.SEQUENCE)
SUB_SEQ_LENGTH = ... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.core import global_context as gpc
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from colossalai.utils import free_port
from colossalai.testing import rerun_if_a... |
import torch
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.nn import (Classifier2p5D, CrossEntropyLoss2p5D, Embedding2p5D, LayerNorm2p5D, Linear2p5D,
PatchEmbedding2p5D, VanillaClassifier, VanillaPatchEmbedding, Voc... |
import torch
from colossalai.context import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.nn.layer.parallel_2p5d._operation import Matmul_AB_2p5D, Matmul_ABT_2p5D, \
Matmul_ATB_2p5D
from colossalai.utils import get_current_device
from colossalai.utils import print_rank_0
from .comm... |
import torch
TESSERACT_DIM = 2
TESSERACT_DEP = 2
BATCH_SIZE = 8
SEQ_LENGTH = 8
HIDDEN_SIZE = 8
NUM_CLASSES = 8
VOCAB_SIZE = 16
IMG_SIZE = 16
def check_equal(A, B):
assert torch.allclose(A, B, rtol=1e-5, atol=1e-2) |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.core import global_context as gpc
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from colossalai.utils import fre... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import torch
DEPTH = 2
BATCH_SIZE = 8
SEQ_LENGTH = 8
HIDDEN_SIZE = 8
NUM_CLASSES = 8
NUM_BLOCKS = 2
IMG_SIZE = 16
VOCAB_SIZE = 16
def check_equal(A, B):
eq = torch.allclose(A, B, rtol=1e-3, atol=1e-2)
assert eq, f"\nA = {A}\nB = {B}"
return eq |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import time
import torch
from colossalai.constants import INPUT_GROUP_3D, OUTPUT_GROUP_3D, WEIGHT_GROUP_3D
from colossalai.core import global_context
from colossalai.logging import get_dist_logger
from colossalai.nn import (
Classifier3D,
CrossEntropyLoss3D,
... |
import pytest
import torch
from colossalai.gemini.stateful_tensor import TensorState, StatefulTensor
@pytest.mark.dist
def test_gemini_manager():
# reset the manager, in case that there exists memory information left
manager = StatefulTensor.GST_MGR
manager.reset()
# occupation 8
st1 = StatefulT... |
import copy
import torch
from colossalai.gemini.paramhooks import BaseParamHookMgr
from tests.components_to_test.registry import non_distributed_component_funcs
def allclose(tensor_a: torch.Tensor, tensor_b: torch.Tensor, loose=False) -> bool:
if loose:
return torch.allclose(tensor_a, tensor_b, atol=1e-... |
from copy import deepcopy
import numpy as np
import torch
from colossalai.gemini.memory_tracer.runtime_mem_tracer import RuntimeMemTracer
from colossalai.utils.model.colo_init_context import ColoInitContext
from tests.components_to_test import run_fwd_bwd
from tests.components_to_test.registry import non_distributed_... |
from functools import partial
from typing import Callable
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.testing import assert_close
import colossalai
from colossalai.amp import convert_to_apex_amp
... |
from functools import partial
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import colossalai
from colossalai.gemini.chunk import init_chunk_manager, search_chunk_configuration
from colossalai.tensor import ComputePattern, ComputeSpec, ProcessGroup, ShardSpec
from colo... |
from functools import partial
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import colossalai
from colossalai.gemini import TensorState
from colossalai.gemini.chunk import Chunk
from colossalai.tensor import ColoParameter
from colossalai.tensor import ProcessGroup as C... |
from functools import partial
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.testing import assert_close
import colossalai
from colossalai.amp import convert_to_apex_amp
from colossalai.gemini.chunk... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.testing import assert_close
import colossalai
from colossalai.amp import convert_to_apex_amp
from colossalai.gemini.chunk import ChunkManager, search_chun... |
from functools import partial
from time import time
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.testing import assert_close
import colossalai
from colossalai.amp import convert_to_apex_amp
from c... |
import os
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.nn.parallel import GeminiDDP
from colossalai.nn.parallel.utils import get_static_torch_model
from colossalai.tensor import ColoParameter
from colossalai.testing import parameterize, ... |
from functools import partial
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from torch.testing import assert_close
import colossalai
from colossalai.gemini.chunk import ChunkManager, search_chunk_configuration
from colossalai.gemini.gemini_mgr import GeminiManager
from... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.gemini.chunk import ChunkManager
from colossalai.tensor import ColoTensor, ColoTensorSpec, ProcessGroup
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.gemini.chunk import ChunkManager, search_chunk_configuration
from colossalai.gemini.gemini_mgr import GeminiManager
from colossalai.gemini.memory_tracer.runtime_mem_tracer import RuntimeMemTra... |
from functools import partial
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.gemini.gemini_mgr import GeminiManager
from colossalai.nn.optimizer import HybridA... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
train_data = dict(
dataset=dict(
type='CIFAR10Dataset',
root='/path/to/data',
download=True,
transform_pipeline=[
dict(type='RandomResizedCrop', size=224),
dict(type='RandomHorizontalFlip'),
dict(typ... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from pathlib import Path
import pytest
from colossalai.context.config import Config
@pytest.mark.cpu
def test_load_config():
filename = Path(__file__).parent.joinpath('sample_config.py')
config = Config.from_file(filename)
assert config.train_data, 'cann... |
import torch
from functools import partial
import pytest
import torch.distributed as dist
import torch.multiprocessing as mp
from torch.distributed import ReduceOp
from colossalai.core import global_context as gpc
from colossalai.initialize import launch
from colossalai.utils import free_port
from colossalai.testing i... |
from functools import partial
import pytest
import torch.multiprocessing as mp
from colossalai.device import AlphaBetaProfiler
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.utils ... |
from functools import partial
import pytest
import torch.multiprocessing as mp
from colossalai.device import AlphaBetaProfiler
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.utils ... |
from functools import partial
import pytest
import torch.multiprocessing as mp
from colossalai.device import AlphaBetaProfiler
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.utils ... |
from colossalai.device.device_mesh import DeviceMesh
import torch
def test_device_mesh():
physical_mesh_id = torch.arange(0, 16).reshape(2, 8)
mesh_shape = (4, 4)
# [[0, 1, 2, 3],
# [4, 5, 6, 7],
# [8, 9, 10,11],
# [12,13,14,15]]
device_mesh = DeviceMesh(physical_mesh_id, mesh_shape)
... |
import torch
import pytest
import os
import torch.multiprocessing as mp
import torch.distributed.rpc as rpc
from torch import nn
from torch._C._distributed_rpc import _is_current_rpc_agent_set
from colossalai import launch
from colossalai.logging import disable_existing_loggers
from colossalai.pipeline.pipeline_proces... |
import torch
import torch.multiprocessing as mp
from colossalai.pipeline.pipelinable import PipelinableContext
from colossalai.testing import rerun_on_exception
NUM_CHUNKS = 1
PIPELINE_SIZE = 2
class MLP(torch.nn.Module):
def __init__(self, dim: int = 256):
super().__init__()
intermediate_dim ... |
import torch
from torch import nn
from torch import autograd
from colossalai.pipeline.rpc._pipeline_schedule import FillDrainPipelineEngine, OneFOneBPipelineEngine
from colossalai.testing import assert_close
from rpc_test_utils import rpc_run, parse_args, RpcTestModel
feat_num = 100
h = 100
def partition(pp_rank: i... |
import argparse
import os
import warnings
import torch
import torch.distributed as dist
import torch.distributed.rpc as rpc
import torch.multiprocessing as mp
from colossalai import launch
from colossalai.logging import disable_existing_loggers
from colossalai.pipeline.pipeline_process_group import ppg
from torch impo... |
import os
import torch.distributed.rpc as rpc
import torch.multiprocessing as mp
import pytest
from colossalai.pipeline.pipeline_process_group import ppg
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from rpc_test_utils import pg_parse_args, rpc_is_initialized
def ... |
import torch
from torch import nn
from colossalai.pipeline.rpc._pipeline_schedule import FillDrainPipelineEngine, OneFOneBPipelineEngine
from rpc_test_utils import rpc_run, parse_args, RpcTestModel
# global variable for model created
feat_num = 100
h = 100
def partition(pp_rank: int, chunk: int, stage_num: int):
... |
import torch
from torch import nn
import torch.autograd as autograd
from colossalai.pipeline.rpc import ChimeraPipelineEngine
from colossalai.testing import assert_close
from rpc_test_utils import rpc_run, parse_args, RpcTestModel
# global variable for model created
feat_num = 100
h = 100
def partition(pp_rank: int... |
import os
from typing import Callable, List, Optional, Type, Union
import time
import pytest
import torch
import torch.nn as nn
from titans.dataloader.cifar10 import build_cifar
from torchvision.models import resnet50
from torchvision.models.resnet import BasicBlock, Bottleneck, conv1x1
from tqdm import tqdm
from rpc... |
import torch
from torch import nn
from torch import autograd
from torch.optim import SGD, Adam, RMSprop, Optimizer
from colossalai.pipeline.rpc._pipeline_schedule import FillDrainPipelineEngine, OneFOneBPipelineEngine
from colossalai.testing import assert_close
from rpc_test_utils import rpc_run, parse_args, RpcTestMo... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
import colossalai
from colossalai.amp import convert_to_apex_amp
from colossalai.gemini.chunk import search_chunk_configuration
from colossalai.nn.optimizer.gemini_o... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import torch.nn.functional as F
import colossalai
from colossalai.device.device_mesh import DeviceMesh
from colossalai.nn._ops._utils import gather_forward_split_backward
from colossalai.tensor import ColoParameter, ColoTensor... |
from colossalai.tensor import ColoParameter, ColoTensor, ColoTensorSpec, ProcessGroup
import torch
import pytest
from common_utils import tensor_equal
import colossalai
from colossalai.utils import free_port
@pytest.mark.skip
def test_multiinheritance():
colossalai.launch(config={}, rank=0, world_size=1, host='lo... |
from functools import partial
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from torch.distributed import ReduceOp
from colossalai.core import global_context as gpc
from colossalai.device.device_mesh import DeviceMesh
from colossalai.initialize import launch
from colos... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.tensor import (
ColoParameter,
ColoTensorSpec,
ComputePattern,
ComputeSpec,
ProcessGroup,
ReplicaSpec,
ShardSpec,
)
from colossalai.testing import parameterize, rer... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.core import global_context as gpc
from colossalai.device.device_mesh import DeviceMesh
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from colossalai.tensor.sha... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.device.device_mesh import DeviceMesh
from colossalai.initialize import launch
from colossalai.logging import disable_existing_loggers
from colossalai.tensor.shape_consistency import CollectiveCommPattern, Shape... |
import torch
import pytest
from functools import partial
import torch.multiprocessing as mp
import torch.distributed as dist
import colossalai
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.tensor im... |
import torch
from colossalai.device.device_mesh import DeviceMesh
from colossalai.tensor.sharding_spec import ShardingSpec, _DimSpec
def test_sharding_spec():
physical_mesh_id = torch.arange(0, 16).reshape(2, 8)
mesh_shape = (4, 4)
# [[0, 1, 2, 3],
# [4, 5, 6, 7],
# [8, 9, 10,11],
# [12,13... |
from colossalai.tensor.shape_consistency import ShapeConsistencyManager, CollectiveCommPattern
import torch
from colossalai.tensor.sharding_spec import _DimSpec, ShardingSpec
from colossalai.device.device_mesh import DeviceMesh
physical_mesh_id = torch.arange(0, 16).reshape(2, 8)
mesh_shape = (4, 4)
# [[0, 1, 2, 3],
#... |
from ._utils import *
|
import os
import random
import numpy as np
import torch
import torch.distributed as dist
from torch.testing import assert_close
from colossalai.context import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.tensor import ComputePattern, ComputeSpec, ShardSpec
def set_seed(seed):
r... |
import torch
import pytest
from colossalai.tensor import ColoTensor
from numpy import allclose
import colossalai
from colossalai.utils import free_port
from colossalai.tensor import ColoTensorSpec
from colossalai.core import global_context as gpc
import torch.multiprocessing as mp
from colossalai.testing import rerun_... |
import math
import torch
import torch.distributed as dist
import pytest
import colossalai
import torch.multiprocessing as mp
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.utils import free_port
from colossalai.tensor import DistSpecManager, ProcessGroup, ShardSpec, ReplicaSpec
from functools... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
import colossalai
from colossalai.nn.parallel.data_parallel import ColoDDP
from colossalai.tensor import ColoTensor, ColoTensorSpec, ComputePattern, ComputeSpec, Pro... |
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.nn.optimizer import ColossalaiOptimizer
from colossalai.tensor import ColoTensor, ProcessGroup
from colossalai.tensor.colo_parameter import ColoParameter
from colossalai.testing import rerun_i... |
from copy import deepcopy
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.nn.parallel.layers import check_colo_module, init_colo_module
from colossalai.tensor import (
ColoTensor,
ColoTensorSpec,
ComputePattern,
ComputeSpec,... |
import copy
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.amp import convert_to_apex_amp, convert_to_naive_amp
from colossalai.testing import assert_close_loose, rerun_if_address_is_in_use
from colossalai.utils import free_port
from tests... |
import copy
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
import colossalai
from colossalai.amp import convert_to_apex_amp, convert_to_torch_amp
from colossalai.testing import assert_close_loose, rerun_if_address_is_in_use
from colossalai.utils import free_port
from tests... |
import os
from functools import partial
from pathlib import Path
import colossalai
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.amp import AMP_TYPE
from colossalai.trainer import Trainer, hooks
from colossalai.context import ParallelMode
from colossalai.testing import rerun_if_address... |
import os
from functools import partial
from pathlib import Path
import colossalai
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.amp import AMP_TYPE
from colossalai.trainer import Trainer, hooks
from colossalai.context import ParallelMode
from colossalai.testing import rerun_if_address... |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
from colossalai.core import global_context as gpc
from colossalai.logging import disable_existing_loggers
from colossalai.initialize import launch
from colossalai.utils import fr... |
import colossalai
import torch
from colossalai.fx.passes.utils import get_leaf, get_top, assign_bfs_level_to_nodes
from colossalai.fx import ColoTracer
from torch.fx import GraphModule
from colossalai.fx.passes.meta_info_prop import MetaInfoProp, TensorMetadata
class MLP(torch.nn.Module):
def __init__(self, dim:... |
import torch
import torch.nn as nn
from colossalai.fx.proxy import ColoProxy
from colossalai.fx.tracer.tracer import ColoTracer
from torch.fx import GraphModule
import pytest
class Conv1D(nn.Module):
def __init__(self, nf, nx):
super().__init__()
self.nf = nf
w = torch.empty(nx, nf)
... |
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.fx import ColoTracer
from colossalai.fx.passes.shard_1d_pass import transformer_mlp_pass
from colossalai.tensor import ProcessGroup
from ... |
import torch
from colossalai.fx._compatibility import is_compatible_with_meta
from colossalai.fx.passes.meta_info_prop import MetaInfoProp, TensorMetadata
from torch.fx import symbolic_trace
if is_compatible_with_meta():
from colossalai.fx.profiler import MetaTensor
BATCH_SIZE = 2
DIM_IN = 4
DIM_OUT = 16
def me... |
import colossalai
import colossalai.nn as col_nn
import pytest
import torch
import torch.nn as nn
from colossalai.fx._compatibility import is_compatible_with_meta
from colossalai.fx.passes.adding_split_node_pass import (split_with_split_nodes_pass, uniform_split_pass)
from colossalai.fx.passes.meta_info_prop import Met... |
import torch
import torch.nn as nn
import colossalai
import colossalai.nn as col_nn
from torch.fx import symbolic_trace
from colossalai.fx.passes.adding_split_node_pass import split_with_split_nodes_pass, balanced_split_pass, \
uniform_split_pass, balanced_split_p... |
import copy
import colossalai
import pytest
import torch
import torch.fx
import torch.multiprocessing as mp
import torchvision.models as tm
from colossalai.core import global_context as gpc
from colossalai.fx import ColoGraphModule, ColoTracer
from colossalai.fx._compatibility import is_compatible_with_meta
from colos... |
import pytest
import torch
import torchvision.models as tm
from colossalai.fx import ColoTracer
from colossalai.fx._compatibility import is_compatible_with_meta
from colossalai.fx.graph_module import ColoGraphModule
from colossalai.fx.passes.algorithms import linearize, solver_rotor
from colossalai.fx.passes.algorithms... |
import copy
import re
from typing import Callable
import pytest
import torch
import torch.multiprocessing as mp
import torchvision.models as tm
from torch.fx import GraphModule
import colossalai
from colossalai.core import global_context as gpc
from colossalai.fx import ColoTracer
from colossalai.fx._compatibility im... |
import torch
from torch.nn import functional as F
from colossalai.fx.tracer.meta_patch import patched_function
def test_conv():
# test F.conv_1d
data_1d = torch.rand(3, 16, 10)
weight_1d = torch.rand(3, 16, 3)
out_1d = F.conv1d(data_1d, weight_1d)
patched_out_1d = patched_function.torch_nn_functio... |
import torch
import torch.nn as nn
from torch.fx import GraphModule
from torch.utils.checkpoint import checkpoint
from colossalai.fx import ColoTracer
class MLP(torch.nn.Module):
def __init__(self):
super().__init__()
self.linear1 = torch.nn.Linear(4, 4)
self.linear2 = torch.nn.Linear(4,... |
import torch
from colossalai.fx import ColoGraphModule, ColoTracer
class LinearModel(torch.nn.Module):
def __init__(self, in_features, out_features):
super().__init__()
self.linear = torch.nn.Linear(in_features, out_features)
def forward(self, x):
x = self.linear(x)
x = x * ... |
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