| torch.nn.modules.container.Sequential.b5ab24e63b447fae(1) | Automatically created pytorch flow. |
| torch.nn.modules.container.Sequential.b5ab24e63b447fae(1)_children | [{"oml-python:serialized_object": "component_reference", "value": {"key": "0", "step_name": "0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "1", "step_name": "1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "2", "step_name": "2"}}] |
| torch.nn.modules.container.Sequential.bea83715a3ce7bb8(1)_children | [{"oml-python:serialized_object": "component_reference", "value": {"key": "0", "step_name": "0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "1", "step_name": "1"}}] |
| openml.extensions.pytorch.layers.functional.Functional.692319b2f8895654(1)_args | [] |
| openml.extensions.pytorch.layers.functional.Functional.692319b2f8895654(1)_function | {"oml-python:serialized_object": "methoddescriptor", "value": "torch._C._TensorBase.reshape"} |
| openml.extensions.pytorch.layers.functional.Functional.692319b2f8895654(1)_kwargs | {"shape": [-1, 1, 28, 28]} |
| torch.nn.modules.batchnorm.BatchNorm2d.5b43f4567252307e(1)_affine | true |
| torch.nn.modules.batchnorm.BatchNorm2d.5b43f4567252307e(1)_eps | 1e-05 |
| torch.nn.modules.batchnorm.BatchNorm2d.5b43f4567252307e(1)_momentum | 0.1 |
| torch.nn.modules.batchnorm.BatchNorm2d.5b43f4567252307e(1)_num_features | 1 |
| torch.nn.modules.batchnorm.BatchNorm2d.5b43f4567252307e(1)_track_running_stats | true |
| torch.nn.modules.container.Sequential.8c3a3adae048736d(1)_children | [{"oml-python:serialized_object": "component_reference", "value": {"key": "0", "step_name": "0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "1", "step_name": "1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "2", "step_name": "2"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "3", "step_name": "3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "4", "step_name": "4"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "5", "step_name": "5"}}] |
| torch.nn.modules.conv.Conv2d.68c2708bb5ca5271(1)_dilation | [1, 1] |
| torch.nn.modules.conv.Conv2d.68c2708bb5ca5271(1)_groups | 1 |
| torch.nn.modules.conv.Conv2d.68c2708bb5ca5271(1)_in_channels | 1 |
| torch.nn.modules.conv.Conv2d.68c2708bb5ca5271(1)_kernel_size | [5, 5] |
| torch.nn.modules.conv.Conv2d.68c2708bb5ca5271(1)_out_channels | 32 |
| torch.nn.modules.conv.Conv2d.68c2708bb5ca5271(1)_padding | [0, 0] |
| torch.nn.modules.conv.Conv2d.68c2708bb5ca5271(1)_padding_mode | "zeros" |
| torch.nn.modules.conv.Conv2d.68c2708bb5ca5271(1)_stride | [1, 1] |
| torch.nn.modules.activation.LeakyReLU.33129a7dc8151b58(1)_inplace | false |
| torch.nn.modules.activation.LeakyReLU.33129a7dc8151b58(1)_negative_slope | 0.01 |
| torch.nn.modules.pooling.MaxPool2d.a82ab0cb4dc62f81(1)_ceil_mode | false |
| torch.nn.modules.pooling.MaxPool2d.a82ab0cb4dc62f81(1)_dilation | 1 |
| torch.nn.modules.pooling.MaxPool2d.a82ab0cb4dc62f81(1)_kernel_size | 2 |
| torch.nn.modules.pooling.MaxPool2d.a82ab0cb4dc62f81(1)_padding | 0 |
| torch.nn.modules.pooling.MaxPool2d.a82ab0cb4dc62f81(1)_return_indices | false |
| torch.nn.modules.pooling.MaxPool2d.a82ab0cb4dc62f81(1)_stride | 2 |
| torch.nn.modules.conv.Conv2d.c9a20b6cbd88b470(1)_dilation | [1, 1] |
| torch.nn.modules.conv.Conv2d.c9a20b6cbd88b470(1)_groups | 1 |
| torch.nn.modules.conv.Conv2d.c9a20b6cbd88b470(1)_in_channels | 32 |
| torch.nn.modules.conv.Conv2d.c9a20b6cbd88b470(1)_kernel_size | [5, 5] |
| torch.nn.modules.conv.Conv2d.c9a20b6cbd88b470(1)_out_channels | 64 |
| torch.nn.modules.conv.Conv2d.c9a20b6cbd88b470(1)_padding | [0, 0] |
| torch.nn.modules.conv.Conv2d.c9a20b6cbd88b470(1)_padding_mode | "zeros" |
| torch.nn.modules.conv.Conv2d.c9a20b6cbd88b470(1)_stride | [1, 1] |
| torch.nn.modules.activation.LeakyReLU.aaff3d78de23baa9(1)_inplace | false |
| torch.nn.modules.activation.LeakyReLU.aaff3d78de23baa9(1)_negative_slope | 0.01 |
| torch.nn.modules.pooling.MaxPool2d.f09c527ba30d54ac(1)_ceil_mode | false |
| torch.nn.modules.pooling.MaxPool2d.f09c527ba30d54ac(1)_dilation | 1 |
| torch.nn.modules.pooling.MaxPool2d.f09c527ba30d54ac(1)_kernel_size | 2 |
| torch.nn.modules.pooling.MaxPool2d.f09c527ba30d54ac(1)_padding | 0 |
| torch.nn.modules.pooling.MaxPool2d.f09c527ba30d54ac(1)_return_indices | false |
| torch.nn.modules.pooling.MaxPool2d.f09c527ba30d54ac(1)_stride | 2 |
| torch.nn.modules.container.Sequential.188f7c65ed526385(1)_children | [{"oml-python:serialized_object": "component_reference", "value": {"key": "0", "step_name": "0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "1", "step_name": "1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "2", "step_name": "2"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "3", "step_name": "3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "4", "step_name": "4"}}] |
| openml.extensions.pytorch.layers.functional.Functional.64a05b68d7ce34c7(1)_args | [] |
| openml.extensions.pytorch.layers.functional.Functional.64a05b68d7ce34c7(1)_function | {"oml-python:serialized_object": "methoddescriptor", "value": "torch._C._TensorBase.reshape"} |
| openml.extensions.pytorch.layers.functional.Functional.64a05b68d7ce34c7(1)_kwargs | {"shape": [-1, 1024]} |
| torch.nn.modules.linear.Linear.763c71e8857b490b(1)_in_features | 1024 |
| torch.nn.modules.linear.Linear.763c71e8857b490b(1)_out_features | 256 |
| torch.nn.modules.activation.LeakyReLU.a147269bee07b60(1)_inplace | false |
| torch.nn.modules.activation.LeakyReLU.a147269bee07b60(1)_negative_slope | 0.01 |
| torch.nn.modules.dropout.Dropout.21f7bcdd2fb8559f(1)_inplace | false |
| torch.nn.modules.dropout.Dropout.21f7bcdd2fb8559f(1)_p | 0.5 |
| torch.nn.modules.linear.Linear.18e72296e9b53012(1)_in_features | 256 |
| torch.nn.modules.linear.Linear.18e72296e9b53012(1)_out_features | 10 |