`elasticai.creator.torch2ir.default_handlers`#

Module Contents#

Functions#

`conv1d`
`maxpool1d`
`linear`
`batchnorm1d`
`flatten`
`relu`
`sigmoid`
`conv2d`
`batchnorm2d`
`maxpool2d`
`adaptiveavgpool2d`
`add`

Data#

API#

elasticai.creator.torch2ir.default_handlers.handlers#: []

elasticai.creator.torch2ir.default_handlers.conv1d(module: torch.nn.Conv1d) → dict[source]#

elasticai.creator.torch2ir.default_handlers.maxpool1d(module: torch.nn.MaxPool1d) → dict[source]#

elasticai.creator.torch2ir.default_handlers.linear(module: torch.nn.Linear) → dict[source]#

elasticai.creator.torch2ir.default_handlers.batchnorm1d(module: torch.nn.BatchNorm1d) → dict[source]#

elasticai.creator.torch2ir.default_handlers.flatten(module: torch.nn.Flatten) → dict[source]#

elasticai.creator.torch2ir.default_handlers.relu(module: torch.nn.ReLU) → dict[source]#

elasticai.creator.torch2ir.default_handlers.sigmoid(module: torch.nn.Sigmoid) → dict[source]#

elasticai.creator.torch2ir.default_handlers.conv2d(module: torch.nn.Conv2d) → dict[source]#

elasticai.creator.torch2ir.default_handlers.batchnorm2d(module: torch.nn.BatchNorm2d) → dict[source]#

elasticai.creator.torch2ir.default_handlers.maxpool2d(module: torch.nn.MaxPool2d) → dict[source]#

elasticai.creator.torch2ir.default_handlers.adaptiveavgpool2d(module: torch.nn.AdaptiveAvgPool2d) → dict[source]#

elasticai.creator.torch2ir.default_handlers.add(module) → dict[source]#