tensor-safe-0.1.0.0: Create valid deep neural network architectures

Safe HaskellNone
LanguageHaskell2010

TensorSafe.Layers

Description

This module exposes all Layers declared at TensorSafe.Layers.

Synopsis

Documentation

data Conv2D :: Nat -> Nat -> Nat -> Nat -> Nat -> Nat -> Type Source #

A 2D Convolutional layer

Instances
Show (Conv2D a b c d e f) Source # 
Instance details

Defined in TensorSafe.Layers.Conv2D

Methods

showsPrec :: Int -> Conv2D a b c d e f -> ShowS #

show :: Conv2D a b c d e f -> String #

showList :: [Conv2D a b c d e f] -> ShowS #

(KnownNat channels, KnownNat filters, KnownNat kernelRows, KnownNat kernelColumns, KnownNat strideRows, KnownNat strideColumns) => Layer (Conv2D channels filters kernelRows kernelColumns strideRows strideColumns) Source # 
Instance details

Defined in TensorSafe.Layers.Conv2D

Methods

layer :: Conv2D channels filters kernelRows kernelColumns strideRows strideColumns Source #

compile :: Conv2D channels filters kernelRows kernelColumns strideRows strideColumns -> InputShape -> CNetwork Source #

data Dense :: Nat -> Nat -> Type Source #

A classic Dense, or FullyConnected, layer with input and output parameters.

Instances
Show (Dense a b) Source # 
Instance details

Defined in TensorSafe.Layers.Dense

Methods

showsPrec :: Int -> Dense a b -> ShowS #

show :: Dense a b -> String #

showList :: [Dense a b] -> ShowS #

(KnownNat input, KnownNat output) => Layer (Dense input output) Source # 
Instance details

Defined in TensorSafe.Layers.Dense

Methods

layer :: Dense input output Source #

compile :: Dense input output -> InputShape -> CNetwork Source #

data Dropout :: Nat -> Nat -> Type Source #

A Dropout layer with rate and seed arguments

Instances
Show (Dropout a b) Source # 
Instance details

Defined in TensorSafe.Layers.Dropout

Methods

showsPrec :: Int -> Dropout a b -> ShowS #

show :: Dropout a b -> String #

showList :: [Dropout a b] -> ShowS #

(KnownNat rate, KnownNat seed) => Layer (Dropout rate seed) Source # 
Instance details

Defined in TensorSafe.Layers.Dropout

Methods

layer :: Dropout rate seed Source #

compile :: Dropout rate seed -> InputShape -> CNetwork Source #

data Flatten Source #

Flattens the dimensions of the shapes to a list of values with shape D1

Instances
Show Flatten Source # 
Instance details

Defined in TensorSafe.Layers.Flatten

Layer Flatten Source # 
Instance details

Defined in TensorSafe.Layers.Flatten

data LSTM :: Nat -> Bool -> Type Source #

A LSTM layer with a number of units and a option to return the original sequences.

Instances
Show (LSTM a b) Source # 
Instance details

Defined in TensorSafe.Layers.LSTM

Methods

showsPrec :: Int -> LSTM a b -> ShowS #

show :: LSTM a b -> String #

showList :: [LSTM a b] -> ShowS #

KnownNat units => Layer (LSTM units b) Source # 
Instance details

Defined in TensorSafe.Layers.LSTM

Methods

layer :: LSTM units b Source #

compile :: LSTM units b -> InputShape -> CNetwork Source #

data MaxPooling :: Nat -> Nat -> Nat -> Nat -> Type Source #

A 2D MaxPooling pooling that works for D2 and D3 shapes

Instances
Show (MaxPooling a b c d) Source # 
Instance details

Defined in TensorSafe.Layers.MaxPooling

Methods

showsPrec :: Int -> MaxPooling a b c d -> ShowS #

show :: MaxPooling a b c d -> String #

showList :: [MaxPooling a b c d] -> ShowS #

(KnownNat kernelRows, KnownNat kernelColumns, KnownNat strideRows, KnownNat strideColumns) => Layer (MaxPooling kernelRows kernelColumns strideRows strideColumns) Source # 
Instance details

Defined in TensorSafe.Layers.MaxPooling

Methods

layer :: MaxPooling kernelRows kernelColumns strideRows strideColumns Source #

compile :: MaxPooling kernelRows kernelColumns strideRows strideColumns -> InputShape -> CNetwork Source #

data Relu Source #

A ReLu activation function

Instances
Show Relu Source # 
Instance details

Defined in TensorSafe.Layers.Relu

Methods

showsPrec :: Int -> Relu -> ShowS #

show :: Relu -> String #

showList :: [Relu] -> ShowS #

Layer Relu Source # 
Instance details

Defined in TensorSafe.Layers.Relu

data Sigmoid Source #

A Sigmoid activation function

Instances
Show Sigmoid Source # 
Instance details

Defined in TensorSafe.Layers.Sigmoid

Layer Sigmoid Source # 
Instance details

Defined in TensorSafe.Layers.Sigmoid