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AI-MXNet-Gluon-ModelZoo-1.32
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/ AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BasicBlockV1

NAME

    AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BasicBlockV1 - BasicBlock V1 from `"Deep Residual Learning for Image Recognition"

DESCRIPTION

    BasicBlock V1 from `"Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385>`_ paper.
    This is used for ResNet V1 for 18, 34 layers.

    Parameters
    ----------
    channels : Int
        Number of output channels.
    stride : Int
        Stride size.
    downsample : Bool, default 0
        Whether to downsample the input.
    in_channels : Int, default 0
        Number of input channels. Default is 0, to infer from the graph.

NAME

    AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BottleneckV1 - Bottleneck V1 from "Deep Residual Learning for Image Recognition"

DESCRIPTION

    Bottleneck V1 from "Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385> paper.
    This is used for ResNet V1 for 50, 101, 152 layers.

    Parameters
    ----------
    channels : int
        Number of output channels.
    stride : int
        Stride size.
    downsample : bool, default False
        Whether to downsample the input.
    in_channels : int, default 0
        Number of input channels. Default is 0, to infer from the graph.

NAME

    AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BasicBlockV2 - BasicBlock V2 from "Identity Mappings in Deep Residual Networks"

DESCRIPTION

    Bottleneck V2 from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.
    This is used for ResNet V2 for 18, 34 layers.

    Parameters
    ----------
    channels : Int
        Number of output channels.
    stride : Int
        Stride size.
    downsample : Bool, default 0
        Whether to downsample the input.
    in_channels : Int, default 0
        Number of input channels. Default is 0, to infer from the graph.

NAME

    AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BottleneckV2 - Bottleneck V2 from "Identity Mappings in Deep Residual Networks"

DESCRIPTION

    Bottleneck V2 from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.
    This is used for ResNet V2 for 50, 101, 152 layers.

    Parameters
    ----------
    channels : int
        Number of output channels.
    stride : int
        Stride size.
    downsample : bool, default False
        Whether to downsample the input.
    in_channels : int, default 0
        Number of input channels. Default is 0, to infer from the graph.

NAME

    AI::MXNet::Gluon::ModelZoo::Vision::ResNet::V1 - ResNet V1 model from "Deep Residual Learning for Image Recognition"

DESCRIPTION

    ResNet V1 model from from "Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385> paper.

    Parameters
    ----------
    block : AI::MXNet::Gluon::HybridBlock
        Class for the residual block. Options are AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BasicBlockV1,
        AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BottleneckV1.
    layers : array ref of Int
        Numbers of layers in each block
    channels : array ref of Int
        Numbers of channels in each block. Length should be one larger than layers list.
    classes : int, default 1000
        Number of classification classes.
    thumbnail : bool, default 0
        Enable thumbnail.

NAME

    AI::MXNet::Gluon::ModelZoo::Vision::ResNet::V2 - ResNet V2 model from "Identity Mappings in Deep Residual Networks"

DESCRIPTION

    ResNet V2 model from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.

    Parameters
    ----------
    block : AI::MXNet::Gluon::HybridBlock
        Class for the residual block. Options are AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BasicBlockV2,
        AI::MXNet::Gluon::ModelZoo::Vision::ResNet::BottleneckV2.
    layers : array ref of Int
        Numbers of layers in each block
    channels : array ref of Int
        Numbers of channels in each block. Length should be one larger than layers list.
    classes : int, default 1000
        Number of classification classes.
    thumbnail : bool, default 0
        Enable thumbnail.

get_resnet

    ResNet V1 model from "Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385> paper.
    ResNet V2 model from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.

    Parameters
    ----------
    $version : Int
        Version of ResNet. Options are 1, 2.
    $num_layers : Int
        Numbers of layers. Options are 18, 34, 50, 101, 152.
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet18_v1

    ResNet-18 V1 model from "Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet34_v1

    ResNet-34 V1 model from "Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet50_v1

    ResNet-50 V1 model from "Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet101_v1

    ResNet-101 V1 model from "Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet152_v1

    ResNet-152 V1 model from "Deep Residual Learning for Image Recognition"
    <http://arxiv.org/abs/1512.03385> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet18_v2

    ResNet-18 V2 model from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet34_v2

    ResNet-34 V2 model from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet50_v2

    ResNet-50 V2 model from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet101_v2

    ResNet-101 V2 model from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.

resnet152_v2

    ResNet-152 V2 model from "Identity Mappings in Deep Residual Networks"
    <https://arxiv.org/abs/1603.05027> paper.

    Parameters
    ----------
    :$pretrained : Bool, default 0
        Whether to load the pretrained weights for model.
    :$ctx : AI::MXNet::Context, default CPU
        The context in which to load the pretrained weights.
    :$root : Str, default '~/.mxnet/models'
        Location for keeping the model parameters.