ColossalAI/colossalai/auto_parallel/tensor_shard/constants.py

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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', 'ELEMENTWISE_METHOD_OP', 'RESHAPE_METHOD_OP', 'INFINITY_COST'
]
ELEMENTWISE_MODULE_OP = [torch.nn.Dropout, torch.nn.ReLU]
ELEMENTWISE_FUNC_OP = [
torch.abs,
torch.cos,
torch.exp,
operator.neg,
torch.multiply,
torch.nn.functional.relu,
torch.nn.functional.dropout,
# softmax should not be here
torch.nn.functional.softmax
]
ELEMENTWISE_METHOD_OP = [
torch.Tensor.to,
torch.Tensor.type,
# TODO: contiguous maybe need some extra processes.
torch.Tensor.contiguous
]
RESHAPE_FUNC_OP = [torch.flatten, torch.reshape]
RESHAPE_METHOD_OP = [
torch.Tensor.view,
torch.Tensor.unsqueeze,
torch.Tensor.split,
torch.Tensor.permute,
torch.Tensor.transpose,
]
BCAST_FUNC_OP = [
torch.add, torch.sub, torch.mul, torch.div, torch.floor_divide, torch.true_divide, operator.add, operator.sub,
operator.mul, operator.floordiv, operator.truediv, torch.matmul, operator.pow, torch.pow
]
CONV_MODULE_OP = [
torch.nn.Conv1d, torch.nn.Conv2d, torch.nn.Conv3d, torch.nn.ConvTranspose1d, torch.nn.ConvTranspose2d,
torch.nn.ConvTranspose3d
]
CONV_FUNC_OP = [
torch.conv1d, torch.conv2d, torch.conv3d, torch.conv_transpose1d, torch.conv_transpose2d, torch.conv_transpose3d
]
EMBEDDING_MODULE_OP = [torch.nn.modules.sparse.Embedding]
LINEAR_MODULE_OP = [torch.nn.Linear]
LINEAR_FUNC_OP = [torch.nn.functional.linear, torch.matmul, torch.bmm]
BATCHNORM_MODULE_OP = [torch.nn.BatchNorm1d, torch.nn.BatchNorm2d, torch.nn.BatchNorm3d, torch.nn.SyncBatchNorm]
LAYERNORM_MODULE_OP = [torch.nn.LayerNorm]
POOL_MODULE_OP = [torch.nn.MaxPool1d, torch.nn.MaxPool2d, torch.nn.MaxPool3d, torch.nn.AdaptiveAvgPool2d]
NON_PARAM_FUNC_OP = [
torch.flatten,
torch.reshape,
torch.abs,
torch.cos,
torch.exp,
operator.neg,
torch.multiply,
torch.nn.functional.relu,
torch.nn.functional.dropout,
torch.flatten,
torch.where,
operator.pow,
torch.pow,
torch.tanh,
torch.add,
torch.sub,
torch.mul,
torch.div,
torch.floor_divide,
torch.true_divide,
operator.add,
operator.sub,
operator.mul,
operator.floordiv,
operator.truediv,
# softmax should not be here
torch.nn.functional.softmax
]
INFINITY_COST = 1e13