python_code stringlengths 0 456k |
|---|
from typing import Dict, List, Tuple
from torch.fx.node import Node
from .trace_indice import TraceIndice
from .utils import (
NodeMgr,
find_chunk_all_input_nodes,
find_chunk_compute_input_and_output_nodes,
find_tensor_shape_node,
flat_list,
get_node_name,
get_node_shape,
is_non_comput... |
from .estimate_memory import EstimateMemory
from .reorder_graph import ReorderGraph
from .trace_indice import TraceIndice
from .utils import NodeMgr, is_non_compute_node
class SelectChunk(object):
def __init__(
self,
trace_indice: TraceIndice,
estimate_memory: EstimateMemory,
reor... |
from typing import Any, Callable, Dict, Iterable, List, Tuple, Union
from torch.fx.node import Node
from colossalai.logging import get_dist_logger
NON_COMPUTE_OP = ["placeholder", "get_attr", "output"]
NON_COMPUTE_NAME = ["getattr", "eq", "_assert_is_none", "_assert", "finfo", "size"]
logger = get_dist_logger()
cl... |
import copy
from typing import Dict, List, Tuple
from torch.fx.node import Node
from .utils import NodeMgr, find_first_tensor_arg, flat_list, get_module_node_name, get_node_name, get_node_shape
class TraceIndice(object):
"""
Trace all indice infomation for every node.
Indice is a logical concept. Equal... |
from typing import Any, Dict, Iterable, List, Tuple
import torch
import colossalai
from colossalai.fx._compatibility import is_compatible_with_meta
from colossalai.fx.codegen.activation_checkpoint_codegen import CODEGEN_AVAILABLE
AUTOCHUNK_AVAILABLE = CODEGEN_AVAILABLE and is_compatible_with_meta()
if AUTOCHUNK_AVA... |
from .cli import cli
__all__ = ['cli']
|
import click
from .benchmark import benchmark
from .check import check
from .launcher import run
class Arguments():
def __init__(self, arg_dict):
for k, v in arg_dict.items():
self.__dict__[k] = v
@click.group()
def cli():
pass
cli.add_command(run)
cli.add_command(check)
cli.add_comm... |
from functools import partial
from typing import Dict, List
import click
import torch.multiprocessing as mp
import colossalai
from colossalai.cli.benchmark.utils import find_all_configs, get_batch_data, profile_model
from colossalai.context import Config
from colossalai.context.random import reset_seeds
from colossal... |
import torch
import colossalai.nn as col_nn
class MLP(torch.nn.Module):
def __init__(self, dim: int, layers: int):
super().__init__()
self.layers = torch.nn.ModuleList()
for _ in range(layers):
self.layers.append(col_nn.Linear(dim, dim))
def forward(self, x):
for... |
import click
from colossalai.context import Config
from .benchmark import run_benchmark
from .utils import *
__all__ = ['benchmark']
@click.command()
@click.option("-g", "--gpus", type=int, default=None, help="Total number of devices to use.")
@click.option("-b", "--batch_size", type=int, default=8, help="Batch si... |
import math
import time
import torch
from colossalai.utils import MultiTimer
from colossalai.context import ParallelMode, Config
from typing import List, Dict, Tuple, Callable
def get_time_stamp() -> int:
"""
Return the time stamp for profiling.
Returns:
time_stamp (int): the time given by time.... |
import os
import sys
from typing import List
import click
import torch
from packaging import version
from colossalai.context import Config
from .hostinfo import HostInfo, HostInfoList
from .multinode_runner import MultiNodeRunner
# Constants that define our syntax
NODE_SEP = ','
def fetch_hostfile(hostfile_path: ... |
from multiprocessing import Pipe, Process
from multiprocessing import connection as mp_connection
import click
import fabric
from .hostinfo import HostInfo, HostInfoList
def run_on_host(hostinfo: HostInfo, workdir: str, recv_conn: mp_connection.Connection,
send_conn: mp_connection.Connection, env: d... |
import click
from colossalai.context import Config
from .run import launch_multi_processes
@click.command(help="Launch distributed training on a single node or multiple nodes",
context_settings=dict(ignore_unknown_options=True))
@click.option("-H",
"-host",
"--host",
... |
import socket
from typing import List
class HostInfo:
"""
A data class to store host connection-related data.
Args:
hostname (str): name or IP address of the host
port (str): the port for ssh connection
"""
def __init__(
self,
hostname: str,
port: str = No... |
import click
from .check_installation import check_installation
__all__ = ['check']
@click.command(help="Check if Colossal-AI is correct based on the given option")
@click.option('-i', '--installation', is_flag=True, help="Check if Colossal-AI is built correctly")
def check(installation):
if installation:
... |
import subprocess
import click
import torch
from torch.utils.cpp_extension import CUDA_HOME
import colossalai
def to_click_output(val):
# installation check output to understandable symbols for readability
VAL_TO_SYMBOL = {True: u'\u2713', False: 'x', None: 'N/A'}
if val in VAL_TO_SYMBOL:
retur... |
from abc import ABC, abstractmethod
from copy import deepcopy
from typing import Any, List
import torch
from torch.fx import Graph, Node
from colossalai.auto_parallel.passes.runtime_apply_pass import (
runtime_apply,
runtime_apply_for_iterable_object,
runtime_comm_spec_apply,
)
from colossalai.fx.codegen.... |
from .ckpt_solver_base import CheckpointSolverBase
from .ckpt_solver_chen import CheckpointSolverChen
from .ckpt_solver_rotor import CheckpointSolverRotor
|
import math
from abc import ABC
from typing import Any, Iterable, List
from torch.utils._pytree import tree_map
class Chain:
def __init__(self,
ftime: List[float],
btime: List[float],
x: List[int],
xbar: List[int],
ftmp: List[i... |
from copy import deepcopy
from typing import Any, Dict, List, Tuple
from torch import Tensor
from torch.fx import Graph, Node
from colossalai.auto_parallel.passes.runtime_apply_pass import runtime_apply, runtime_comm_spec_apply
from colossalai.fx.codegen.activation_checkpoint_codegen import _find_nested_ckpt_regions
... |
import math
from copy import deepcopy
from typing import List, Set, Tuple
from torch.fx import Graph, Node
from colossalai.fx.profiler import calculate_fwd_in, calculate_fwd_tmp
from .ckpt_solver_base import CheckpointSolverBase
__all__ = ['CheckpointSolverChen']
class CheckpointSolverChen(CheckpointSolverBase):
... |
import os
from setuptools import Extension, setup
this_dir = os.path.dirname(os.path.abspath(__file__))
ext_modules = [Extension(
'rotorc',
sources=[os.path.join(this_dir, 'ckpt_solver_rotor.c')],
)]
setup(
name='rotor c extension',
version='0.1',
description='rotor c extension for faster dp comp... |
from typing import Callable, List
import torch
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
MemoryCost,
OperationData,
OperationDataType,
ShardingStrategy,
StrategiesVector,
TrainCycleItem,
)
from colossalai.tensor.sharding_spec import ShardingSpec
from .constants imp... |
__all__ = ['Registry']
class Registry:
def __init__(self, name):
self.name = name
self.store = {}
def register(self, source):
def wrapper(func):
if isinstance(source, (list, tuple)):
# support register a list of items for this func
for ele... |
import operator
import torch
import torch.nn as nn
from ..tensor_shard.constants import *
# list of inplace module
INPLACE_MODULE = [nn.ReLU]
# list of inplace operations
INPLACE_OPS = [torch.flatten]
# list of operations that do not save forward activations
NO_SAVE_ACTIVATION = [torch.add, torch.sub, operator.add... |
from .meta_registry import *
from .metainfo import *
from .registry import meta_register
|
from functools import reduce
from typing import Callable, Dict, List, Tuple, Union
import torch
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
MemoryCost,
OperationData,
OperationDataType,
ShardingStrategy,
StrategiesVector,
TrainCycleItem,
)
from colossalai.fx.profiler.... |
from typing import Callable, Dict, List, Tuple, Union
import torch
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
MemoryCost,
OperationData,
OperationDataType,
ShardingStrategy,
StrategiesVector,
TrainCycleItem,
)
from colossalai.fx.profiler.memory_utils import activatio... |
from typing import List, Tuple
import torch
from colossalai.auto_parallel.tensor_shard.sharding_strategy import MemoryCost, OperationDataType, TrainCycleItem
from colossalai.fx.profiler.memory_utils import activation_size
from colossalai.fx.profiler.opcount import flop_mapping
from ..constants import BCAST_FUNC_OP, ... |
from typing import List, Tuple
import torch
from colossalai.auto_parallel.tensor_shard.sharding_strategy import MemoryCost, OperationDataType, TrainCycleItem
from colossalai.fx.profiler.memory_utils import activation_size
from colossalai.fx.profiler.opcount import flop_mapping
from ..registry import meta_register
_... |
from .activation import *
from .binary_elementwise_ops import *
from .conv import *
from .linear import *
from .norm import *
from .pooling import *
|
from typing import List, Tuple
import torch
from colossalai.auto_parallel.tensor_shard.sharding_strategy import MemoryCost, OperationDataType, TrainCycleItem
from colossalai.fx.profiler.memory_utils import activation_size
from colossalai.fx.profiler.opcount import flop_mapping
from ..registry import meta_register
_... |
from typing import Callable, Dict, List, Tuple, Union
import torch
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
MemoryCost,
OperationData,
OperationDataType,
ShardingStrategy,
StrategiesVector,
TrainCycleItem,
)
from colossalai.fx.profiler.memory_utils import activatio... |
from copy import deepcopy
from typing import Dict, List
import torch
from torch.fx.node import Node
from colossalai.auto_parallel.meta_profiler import MetaInfo
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommAction,
CommType,
OperationData,
OperationDataType,
TrainCycleIt... |
import uuid
from dataclasses import asdict
from typing import List
import torch
import torch.fx
from torch.fx import GraphModule
from torch.fx.node import Node
from colossalai.auto_parallel.meta_profiler import MetaInfo
from colossalai.auto_parallel.passes.constants import OUTPUT_SAVED_MOD, OUTPUT_SAVED_OPS
from colo... |
import torch
OUTPUT_SAVED_OPS = [torch.nn.functional.relu, torch.nn.functional.softmax, torch.flatten]
OUTPUT_SAVED_MOD = [
torch.nn.ReLU,
torch.nn.Softmax,
]
# SHAPE_ARGUMENT_OPS contains node with (input, *shape) style args.
# This list could be extended if any other method has the same
# argument style as... |
from typing import Dict
import torch
from torch.fx import GraphModule
from torch.fx.node import Node
from colossalai.auto_parallel.meta_profiler import MetaInfo
from colossalai.auto_parallel.passes.runtime_apply_pass import runtime_apply, runtime_comm_spec_apply
from colossalai.auto_parallel.tensor_shard.sharding_str... |
import operator
from copy import deepcopy
from typing import Dict, List, Union
import torch
from torch.fx import symbolic_trace
from torch.fx.node import Node
from colossalai.auto_parallel.tensor_shard.constants import RESHAPE_FUNC_OP
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommActio... |
from dataclasses import dataclass
from enum import Enum
__all__ = ['SolverOptions', 'SolverPerference', 'DataloaderOption', 'ShardOption']
class SolverPerference(Enum):
"""
This enum class is to define the solver preference.
"""
STANDARD = 0
DP = 1
TP = 2
class ShardOption(Enum):
"""
... |
from copy import deepcopy
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, List, Tuple, Union
import torch
from torch.fx.node import Node
from colossalai.tensor.comm_spec import CommSpec
from colossalai.tensor.sharding_spec import ShardingSpec
from .constants import (
BCAST_F... |
from typing import Dict, List, Tuple
import torch
import torch.distributed as dist
import torch.nn as nn
from torch.fx import GraphModule
from torch.fx.graph import Graph
from colossalai.auto_parallel.passes.runtime_apply_pass import runtime_apply_pass
from colossalai.auto_parallel.passes.runtime_preparation_pass imp... |
import operator
import torch
__all__ = [
'ELEMENTWISE_MODULE_OP', 'ELEMENTWISE_FUNC_OP', 'RESHAPE_FUNC_OP', 'CONV_MODULE_OP', 'CONV_FUNC_OP',
'LINEAR_MODULE_OP', 'LINEAR_FUNC_OP', 'BATCHNORM_MODULE_OP', 'POOL_MODULE_OP', 'NON_PARAM_FUNC_OP', 'BCAST_FUNC_OP',
'EMBEDDING_MODULE_OP', 'LAYERNORM_MODULE_OP', '... |
import operator
from copy import deepcopy
from functools import reduce
from typing import Dict
import torch
from colossalai.tensor.sharding_spec import ShardingSpec
__all__ = [
'transpose_partition_dim', 'update_partition_dim', 'enumerate_all_possible_1d_sharding',
'enumerate_all_possible_2d_sharding', 'gene... |
import functools
from typing import Any, Callable, Dict, List, Tuple, Type, Union
import torch
from colossalai.logging import get_dist_logger
from colossalai.tensor.sharding_spec import ShardingSpec, ShardingSpecException
__all__ = ['ignore_sharding_exception', 'pytree_map']
def ignore_sharding_exception(func):
... |
from enum import Enum
from typing import Dict, List, Tuple
import torch
class PreviousStatus(Enum):
"""
This class shows the status of previous comparision.
"""
RESET = 0
# ORIGIN means the dimension size of original tensor is larger in the previous comparision.
ORIGIN = 1
# TGT means the... |
from .broadcast import (
BroadcastType,
comm_actions_for_oprands,
get_broadcast_shape,
is_broadcastable,
recover_sharding_spec_for_broadcast_shape,
)
from .factory import generate_resharding_costs, generate_sharding_spec
from .misc import check_sharding_spec_validity, ignore_sharding_exception, pytr... |
import operator
import warnings
from functools import reduce
from typing import Dict, List, Optional, Union
import torch
from colossalai.device.device_mesh import DeviceMesh
from colossalai.tensor.shape_consistency import ShapeConsistencyManager
from colossalai.tensor.sharding_spec import ShardingSpec
from torch.fx.no... |
from enum import Enum, auto
from typing import List
import torch
from torch.fx.node import Node
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommAction,
CommType,
OperationData,
OperationDataType,
)
from colossalai.tensor.comm_spec import CollectiveCommPattern, CommSpec
from c... |
import builtins
import math
import operator
from copy import deepcopy
from typing import Dict, List
import torch
from torch.fx import Graph, Node
from colossalai.auto_parallel.tensor_shard.node_handler import (
GetattrHandler,
OutputHandler,
PlaceholderHandler,
operator_registry,
)
from colossalai.aut... |
import torch
from colossalai.auto_parallel.tensor_shard.constants import INFINITY_COST
class CostGraph:
'''
A graph data structure to simplify the edge cost graph. It has two main functions:
1. To feed the quadratic resharding costs into solver, we need to linearize it. We build edge_cost in
CostGrap... |
import multiprocessing
import time
import warnings
from typing import Dict
import numpy as np
from torch.fx.graph import Graph
from torch.fx.node import Node
from colossalai.auto_parallel.tensor_shard.constants import INFINITY_COST
from .cost_graph import CostGraph
from .graph_analysis import GraphAnalyser
from .str... |
from .cost_graph import CostGraph
from .graph_analysis import GraphAnalyser
from .solver import Solver
from .strategies_constructor import StrategiesConstructor
__all__ = ['GraphAnalyser', 'Solver', 'StrategiesConstructor', 'CostGraph']
|
from dataclasses import dataclass
from typing import List
from torch.fx.graph import Graph
from torch.fx.graph_module import GraphModule
from torch.fx.node import Node
from colossalai.fx.passes.utils import get_node_module
__all__ = ['LiveVariable', 'LiveVariableVector', 'LiveStage', 'GraphAnalyser']
@dataclass
cl... |
from abc import ABC, abstractmethod
from typing import Dict, List, Tuple, Union
import torch
from torch.fx.node import Node
from colossalai.auto_parallel.meta_profiler.metainfo import MetaInfo, meta_register
from colossalai.auto_parallel.tensor_shard.options import ShardOption, SolverPerference
from colossalai.auto_p... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import MetaInfoNodeHandler, NodeHandler
from .registry import operator_registry
from .strategy import StrategyGenerator, UnaryElementwiseGenerator
__all__ = ['UnaryElementwiseHandler']
@op... |
from typing import Dict, List
import torch
from colossalai.auto_parallel.meta_profiler.metainfo import MetaInfo
from ..sharding_strategy import OperationData, OperationDataType, StrategiesVector
from .node_handler import MetaInfoModuleHandler, ModuleHandler
from .registry import operator_registry
from .strategy impo... |
from typing import Dict, List, Union
import torch
from torch.fx.node import Node
from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, ShardingStrategy
from colossalai.tensor.shape_consistency import CollectiveCommPattern, CommSpec, ShapeConsistencyManager
from ..const... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import MetaInfoModuleHandler, ModuleHandler
from .registry import operator_registry
from .strategy import LayerNormGenerator, StrategyGenerator
__all__ = ['LayerNormModuleHandler']
@operat... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .registry import operator_registry
from .strategy import SplitGenerator, StrategyGenerator
__all__ = ['SplitHandler']
@operator_registry.register(torch.Tensor.split... |
from typing import Dict, List
import torch
import torch.nn.functional as F
from ..sharding_strategy import OperationData, OperationDataType, ShardingStrategy, StrategiesVector
from ..utils import transpose_partition_dim
from .node_handler import MetaInfoModuleHandler, MetaInfoNodeHandler, ModuleHandler, NodeHandler
f... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import MetaInfoModuleHandler, ModuleHandler
from .registry import operator_registry
from .strategy import NormalPoolStrategyGenerator, StrategyGenerator
__all__ = ['NormPoolingHandler']
@o... |
import operator
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .registry import operator_registry
from .strategy import StrategyGenerator, TensorStrategyGenerator, TensorTupleStrategyGenerator
__all__ = ['GetItemH... |
class Registry:
# TODO: refactor the registry classes used in colossalai.registry, colossalai.fx and here
def __init__(self, name):
self.name = name
self.store = {}
def register(self, source):
def wrapper(func):
if isinstance(source, (list, tuple)):
# s... |
import copy
import operator
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType, ShardingStrategy, StrategiesVector
from ..utils import recover_sharding_spec_for_broadcast_shape
from .node_handler import NodeHandler
from .registry import operator_registry
from .... |
from typing import Dict, List, Union
import torch
import torch.nn.functional as F
from colossalai.auto_parallel.tensor_shard.utils import update_partition_dim
from colossalai.logging import get_dist_logger
from colossalai.tensor.sharding_spec import ShardingNotDivisibleError
from ..sharding_strategy import Operation... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .registry import operator_registry
from .strategy import PermuteGenerator, StrategyGenerator
__all__ = ['PermuteHandler']
@operator_registry.register(torch.Tensor.p... |
from .addmm_handler import ADDMMFunctionHandler
from .batch_norm_handler import BatchNormModuleHandler
from .binary_elementwise_handler import BinaryElementwiseHandler
from .bmm_handler import AddBMMFunctionHandler, BMMFunctionHandler
from .conv_handler import ConvFunctionHandler, ConvModuleHandler
from .default_reshap... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .registry import operator_registry
from .strategy import StrategyGenerator, ViewGenerator
__all__ = ['ViewHandler']
@operator_registry.register(torch.Tensor.reshape... |
from typing import Dict, List, Union
import torch
import torch.nn.functional as F
from colossalai.auto_parallel.tensor_shard.utils import (
check_sharding_spec_validity,
transpose_partition_dim,
update_partition_dim,
)
from colossalai.logging import get_dist_logger
from colossalai.tensor.sharding_spec imp... |
from typing import Dict, List, Union
import torch
from colossalai.tensor.shape_consistency import CollectiveCommPattern, CommSpec, ShapeConsistencyManager
from ..sharding_strategy import CommAction, CommType, OperationData, OperationDataType, ShardingStrategy
from ..utils import comm_actions_for_oprands, recover_sha... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import MetaInfoNodeHandler, NodeHandler
from .registry import operator_registry
from .strategy import DefaultReshapeGenerator, StrategyGenerator
__all__ = ['DefaultReshapeHandler']
@operat... |
from typing import Dict, List
from torch.fx.node import Node
from colossalai.device.device_mesh import DeviceMesh
from ..sharding_strategy import OperationData, OperationDataType, StrategiesVector
from .node_handler import NodeHandler
from .strategy import PlaceholderGenerator, StrategyGenerator
__all__ = ['Placeho... |
from typing import Dict, List
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .strategy import GetattrGenerator, StrategyGenerator
__all__ = ['GetattrHandler']
class GetattrHandler(NodeHandler):
"""
A GetattrHandler which deals with the sharding st... |
from typing import Dict, List, Union
import torch
from colossalai.tensor.shape_consistency import CollectiveCommPattern, CommSpec, ShapeConsistencyManager
from ..sharding_strategy import CommAction, CommType, OperationData, OperationDataType, ShardingStrategy
from ..utils import comm_actions_for_oprands, recover_sha... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .registry import operator_registry
from .strategy import StrategyGenerator, TransposeGenerator
__all__ = ['TransposeHandler']
@operator_registry.register(torch.Tens... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .registry import operator_registry
from .strategy import SoftmaxGenerator, StrategyGenerator
__all__ = ['SoftmaxHandler']
@operator_registry.register(torch.nn.Softm... |
from typing import Dict, List
import torch
from colossalai.device.device_mesh import DeviceMesh
from ..sharding_strategy import OperationData, OperationDataType, StrategiesVector
from .node_handler import NodeHandler
from .strategy import OutputGenerator, StrategyGenerator
__all__ = ['OutputHandler']
class Output... |
import operator
from abc import ABC, abstractmethod
from copy import deepcopy
from enum import Enum
from functools import reduce
from typing import Dict, List, Union
import torch
from colossalai.auto_parallel.tensor_shard.utils.broadcast import (
BroadcastType,
get_broadcast_dim_info,
get_broadcast_shape,... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .registry import operator_registry
from .strategy import StrategyGenerator
from .strategy.tensor_constructor_generator import TensorConstructorGenerator
__all__ = ['T... |
from typing import Dict, List
import torch
from ..sharding_strategy import OperationData, OperationDataType
from .node_handler import NodeHandler
from .registry import operator_registry
from .strategy import StrategyGenerator, SumGenerator
__all__ = ['SumHandler']
@operator_registry.register(torch.Tensor.sum)
@ope... |
import copy
from typing import List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (MemoryCost, ShardingStrategy, TrainCycleItem)
from .strategy_generator import FollowingStrategyGenerator
__all__ = ['UnaryElementwiseGenerator']
class UnaryElementwiseGenerator(FollowingStrategyGenerator):
... |
import copy
import operator
import warnings
from functools import reduce
from typing import List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommAction,
CommType,
MemoryCost,
ShardingStrategy,
TrainCycleItem,
)
from colossalai.auto_parallel.tensor_shard.utils import ignore... |
import copy
from typing import List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import MemoryCost, ShardingStrategy, TrainCycleItem
from colossalai.auto_parallel.tensor_shard.utils import (
enumerate_all_possible_1d_sharding,
enumerate_all_possible_2d_sharding,
ignore_sharding_exception,
)... |
from typing import Dict, List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
MemoryCost,
OperationData,
ShardingStrategy,
TrainCycleItem,
)
from colossalai.device.device_mesh import DeviceMesh
from .strategy_generator import StrategyGenerator
__all__ = ['PlaceholderGenerator']
... |
import copy
import operator
from functools import reduce
from typing import List
from colossalai.auto_parallel.tensor_shard.node_handler.strategy.strategy_generator import FollowingStrategyGenerator
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommAction,
CommType,
MemoryCost,
... |
from .batch_norm_generator import BatchNormStrategyGenerator
from .binary_elementwise_generator import BinaryElementwiseStrategyGenerator
from .conv_strategy_generator import ConvStrategyGenerator
from .embedding_generator import EmbeddingStrategyGenerator
from .getattr_generator import GetattrGenerator
from .getitem_g... |
import operator
from abc import ABC, abstractmethod
from functools import reduce
from typing import Any, Dict, List, Union
import torch
from torch.fx import Node
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommAction,
CommType,
OperationData,
OperationDataType,
ShardingSt... |
import copy
import operator
from functools import reduce
from typing import List
from colossalai.auto_parallel.tensor_shard.node_handler.strategy.strategy_generator import FollowingStrategyGenerator
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommAction,
CommType,
MemoryCost,
... |
from typing import List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import MemoryCost, ShardingStrategy, TrainCycleItem
from colossalai.auto_parallel.tensor_shard.utils import (
enumerate_all_possible_1d_sharding,
enumerate_all_possible_2d_sharding,
ignore_sharding_exception,
)
from coloss... |
import copy
import operator
from functools import reduce
from typing import List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommType,
MemoryCost,
ShardingStrategy,
TrainCycleItem,
)
from colossalai.auto_parallel.tensor_shard.utils import ignore_sharding_exception
from colossa... |
import copy
from typing import List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommType,
MemoryCost,
ShardingStrategy,
TrainCycleItem,
)
from colossalai.logging import get_dist_logger
from colossalai.tensor.shape_consistency import CollectiveCommPattern
from colossalai.tensor... |
import copy
from typing import List
from colossalai.auto_parallel.tensor_shard.node_handler.strategy.strategy_generator import FollowingStrategyGenerator
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommAction,
CommType,
MemoryCost,
ShardingStrategy,
TrainCycleItem,
)
from ... |
import operator
from ast import arg
from functools import reduce
from typing import List
from colossalai.auto_parallel.tensor_shard.options import SolverPerference
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommType,
MemoryCost,
ShardingStrategy,
TrainCycleItem,
)
from coloss... |
import copy
import operator
from functools import reduce
from typing import List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommType,
MemoryCost,
ShardingStrategy,
TrainCycleItem,
)
from colossalai.auto_parallel.tensor_shard.utils import (
enumerate_all_possible_1d_shardi... |
import copy
import operator
import warnings
from functools import reduce
from typing import List
from colossalai.auto_parallel.tensor_shard.sharding_strategy import (
CommAction,
CommType,
MemoryCost,
ShardingStrategy,
TrainCycleItem,
)
from colossalai.auto_parallel.tensor_shard.utils import ignore... |
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