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docs/torchvision/torchvision.models/resnet

resnet

torchvision.models.resnet
object resnet

ResNet architecture implementations

Derived from https://github.com/pytorch/vision/blob/v0.14.1/torchvision/models/resnet.py

TODO ResNeXt and wide ResNet variants

Attributes

Source
resnet.scala
Graph
Supertypes
class Object
trait Matchable
class Any
Self type
resnet.type

Members list

Type members

Classlikes

class BasicBlock[D <: BFloat16 | Float32 | Float64](inplanes: Int, planes: Int, stride: Int, downsample: Option[TensorModule[D]], groups: Int, baseWidth: Int, dilation: Int, normLayer: => Int => TensorModule[D])(implicit evidence$3: Default[D]) extends TensorModule[D]

Attributes

Companion
object
Source
resnet.scala
Supertypes
trait TensorModule[D]
trait Tensor[D] => Tensor[D]
class Module
class Object
trait Matchable
class Any
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object BasicBlock extends BlockBuilder

Attributes

Companion
class
Source
resnet.scala
Supertypes
class BlockBuilder
class Object
trait Matchable
class Any
Self type
BasicBlock.type
sealed abstract class BlockBuilder

Attributes

Source
resnet.scala
Supertypes
class Object
trait Matchable
class Any
Known subtypes
object BasicBlock.type
object Bottleneck.type
class Bottleneck[D <: BFloat16 | Float32 | Float64](inplanes: Int, planes: Int, stride: Int, downsample: Option[TensorModule[D]], groups: Int, baseWidth: Int, dilation: Int, normLayer: Int => HasWeight[D] & TensorModule[D])(implicit evidence$4: Default[D]) extends TensorModule[D]

Bottleneck in torchvision places the stride for downsampling at 3x3 convolution(self.conv2) while original implementation places the stride at the first 1x1 convolution(self.conv1) according to "Deep residual learning for image recognition"https://arxiv.org/abs/1512.03385. This variant is also known as ResNet V1.5 and improves accuracy according to https://ngc.nvidia.com/catalog/model-scripts/nvidia:resnet_50_v1_5_for_pytorch.

Bottleneck in torchvision places the stride for downsampling at 3x3 convolution(self.conv2) while original implementation places the stride at the first 1x1 convolution(self.conv1) according to "Deep residual learning for image recognition"https://arxiv.org/abs/1512.03385. This variant is also known as ResNet V1.5 and improves accuracy according to https://ngc.nvidia.com/catalog/model-scripts/nvidia:resnet_50_v1_5_for_pytorch.

Attributes

Companion
object
Source
resnet.scala
Supertypes
trait TensorModule[D]
trait Tensor[D] => Tensor[D]
class Module
class Object
trait Matchable
class Any
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object Bottleneck extends BlockBuilder

Attributes

Companion
class
Source
resnet.scala
Supertypes
class BlockBuilder
class Object
trait Matchable
class Any
Self type
Bottleneck.type
class ResNet[D <: BFloat16 | Float32 | Float64](block: BlockBuilder, layers: Seq[Int], numClasses: Int, zeroInitResidual: Boolean, groups: Int, widthPerGroup: Int, replaceStrideWithDilation: (Boolean, Boolean, Boolean))(using x$8: Default[D])(normLayer: Int => HasWeight[D] & TensorModule[D]) extends Module

Attributes

Source
resnet.scala
Supertypes
class Module
class Object
trait Matchable
class Any
object ResNet101 extends ResNetFactory

ResNet-101 from Deep Residual Learning for Image Recognition

ResNet-101 from Deep Residual Learning for Image Recognition

Attributes

Source
resnet.scala
Supertypes
class Object
trait Matchable
class Any
Self type
ResNet101.type
object ResNet152 extends ResNetFactory

ResNet-152 from Deep Residual Learning for Image Recognition

ResNet-152 from Deep Residual Learning for Image Recognition

Attributes

Source
resnet.scala
Supertypes
class Object
trait Matchable
class Any
Self type
ResNet152.type
object ResNet18 extends ResNetFactory

ResNet-18 from Deep Residual Learning for Image Recognition.

ResNet-18 from Deep Residual Learning for Image Recognition.

Attributes

Source
resnet.scala
Supertypes
class Object
trait Matchable
class Any
Self type
ResNet18.type
object ResNet34 extends ResNetFactory

ResNet-34 from Deep Residual Learning for Image Recognition.

ResNet-34 from Deep Residual Learning for Image Recognition.

Attributes

Source
resnet.scala
Supertypes
class Object
trait Matchable
class Any
Self type
ResNet34.type
object ResNet50 extends ResNetFactory

ResNet-50 from Deep Residual Learning for Image Recognition

ResNet-50 from Deep Residual Learning for Image Recognition

Attributes

Source
resnet.scala
Supertypes
class Object
trait Matchable
class Any
Self type
ResNet50.type
abstract class ResNetFactory

Attributes

Source
resnet.scala
Supertypes
class Object
trait Matchable
class Any
Known subtypes
object ResNet101.type
object ResNet152.type
object ResNet18.type
object ResNet34.type
object ResNet50.type
enum ResNetVariant(val factory: ResNetFactory)

Attributes

Source
resnet.scala
Supertypes
trait Enum
trait Serializable
trait Product
trait Equals
class Object
trait Matchable
class Any
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case class Weights(url: String, transforms: ImageClassification)

Attributes

Source
resnet.scala
Supertypes
trait Serializable
trait Product
trait Equals
class Object
trait Matchable
class Any
Show all

Value members

Concrete methods

def conv1x1[D <: FloatNN : Default](inPlanes: Int, outPlanes: Int, stride: Int): Conv2d[D]

1x1 convolution

1x1 convolution

Attributes

Source
resnet.scala
def conv3x3[D <: BFloat16 | Float32 | Float64 : Default](inPlanes: Int, outPlanes: Int, stride: Int, groups: Int, dilation: Int): Conv2d[D]

3x3 convolution with padding

3x3 convolution with padding

Attributes

Source
resnet.scala
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