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