diff --git a/src/Grenade/Core/Layer.hs b/src/Grenade/Core/Layer.hs
index db62808c..9911dae6 100644
--- a/src/Grenade/Core/Layer.hs
+++ b/src/Grenade/Core/Layer.hs
@@ -48,6 +48,7 @@ import           Data.Kind (Type)
 
 import           Grenade.Core.Shape
 import           Grenade.Core.LearningParameters
+import           Control.DeepSeq (NFData)
 
 -- | Class for updating a layer. All layers implement this, as it
 --   describes how to create and update the layer.
@@ -73,7 +74,7 @@ class UpdateLayer x where
 --   need to implement it for all shapes, only ones which are
 --   appropriate.
 --
-class UpdateLayer x => Layer x (i :: Shape) (o :: Shape) where
+class (UpdateLayer x, NFData x) => Layer x (i :: Shape) (o :: Shape) where
   -- | The Wengert tape for this layer. Includes all that is required
   --   to generate the back propagated gradients efficiently. As a
   --   default, `S i` is fine.
diff --git a/src/Grenade/Core/Network.hs b/src/Grenade/Core/Network.hs
index f7b1f002..6690355c 100644
--- a/src/Grenade/Core/Network.hs
+++ b/src/Grenade/Core/Network.hs
@@ -44,6 +44,7 @@ import           Data.Kind (Type)
 import           Grenade.Core.Layer
 import           Grenade.Core.LearningParameters
 import           Grenade.Core.Shape
+import           Control.DeepSeq
 
 -- | Type of a network.
 --
@@ -68,6 +69,12 @@ instance Show (Network '[] '[i]) where
 instance (Show x, Show (Network xs rs)) => Show (Network (x ': xs) (i ': rs)) where
   show (x :~> xs) = show x ++ "\n~>\n" ++ show xs
 
+instance NFData (Network '[] '[i]) where
+  rnf NNil = ()
+
+instance NFData (Network xs rs) => NFData (Network (x ': xs) (i ': rs)) where
+  rnf (x :~> xs) = x `deepseq` xs `deepseq` ()
+
 -- | Gradient of a network.
 --
 --   Parameterised on the layers of the network.
@@ -191,7 +198,7 @@ instance CreatableNetwork sublayers subshapes => UpdateLayer (Network sublayers
 -- | Ultimate composition.
 --
 --   This allows a complete network to be treated as a layer in a larger network.
-instance (CreatableNetwork sublayers subshapes, i ~ (Head subshapes), o ~ (Last subshapes)) => Layer (Network sublayers subshapes) i o where
+instance (CreatableNetwork sublayers subshapes, i ~ (Head subshapes), o ~ (Last subshapes), NFData (Network sublayers subshapes)) => Layer (Network sublayers subshapes) i o where
   type Tape (Network sublayers subshapes) i o = Tapes sublayers subshapes
   runForwards  = runNetwork
   runBackwards = runGradient
diff --git a/src/Grenade/Layers/Concat.hs b/src/Grenade/Layers/Concat.hs
index ca3eba69..74de3e3d 100644
--- a/src/Grenade/Layers/Concat.hs
+++ b/src/Grenade/Layers/Concat.hs
@@ -35,6 +35,7 @@ import           Data.Kind (Type)
 import           Grenade.Core
 
 import           Numeric.LinearAlgebra.Static ( row, (===), splitRows, unrow, (#), split, R )
+import           Control.DeepSeq
 
 -- | A Concatentating Layer.
 --
@@ -52,6 +53,9 @@ import           Numeric.LinearAlgebra.Static ( row, (===), splitRows, unrow, (#
 data Concat :: Shape -> Type -> Shape -> Type -> Type where
   Concat :: x -> y -> Concat m x n y
 
+instance (NFData x, NFData y) => NFData (Concat m x n y) where
+  rnf (Concat x y) = rnf x `deepseq` rnf y `deepseq` ()
+
 instance (Show x, Show y) => Show (Concat m x n y) where
   show (Concat x y) = "Concat\n" ++ show x ++ "\n" ++ show y
 
diff --git a/src/Grenade/Layers/Convolution.hs b/src/Grenade/Layers/Convolution.hs
index aa0048b0..3d96ddbe 100644
--- a/src/Grenade/Layers/Convolution.hs
+++ b/src/Grenade/Layers/Convolution.hs
@@ -46,6 +46,7 @@ import           Numeric.LinearAlgebra.Static hiding ((|||), build, toRows)
 import           Grenade.Core
 import           Grenade.Layers.Internal.Convolution
 import           Grenade.Layers.Internal.Update
+import           Control.DeepSeq
 
 -- | A convolution layer for a neural network.
 --   This uses the im2col convolution trick popularised by Caffe, which essentially turns the
@@ -113,6 +114,9 @@ instance Show (Convolution c f k k' s s') where
             px = (fmap . fmap . fmap) render ms
         in unlines $ foldl1 (zipWith (\a' b' -> a' ++ "   |   " ++ b')) $ px
 
+instance NFData (Convolution c f k k' s s') where
+  rnf (Convolution a b) = rnf a `deepseq` rnf b `deepseq` ()
+
 randomConvolution :: ( MonadRandom m
                      , KnownNat channels
                      , KnownNat filters
diff --git a/src/Grenade/Layers/Crop.hs b/src/Grenade/Layers/Crop.hs
index 0634bca6..bcf9b693 100644
--- a/src/Grenade/Layers/Crop.hs
+++ b/src/Grenade/Layers/Crop.hs
@@ -37,6 +37,7 @@ import           Grenade.Layers.Internal.Pad
 
 import           Numeric.LinearAlgebra (konst, subMatrix, diagBlock)
 import           Numeric.LinearAlgebra.Static (extract, create)
+import           Control.DeepSeq
 
 -- | A cropping layer for a neural network.
 data Crop :: Nat
@@ -45,6 +46,9 @@ data Crop :: Nat
           -> Nat -> Type where
   Crop :: Crop cropLeft cropTop cropRight cropBottom
 
+instance NFData (Crop cropLeft cropTop cropRight cropBottom) where
+  rnf Crop = ()
+
 instance Show (Crop cropLeft cropTop cropRight cropBottom) where
   show Crop = "Crop"
 
diff --git a/src/Grenade/Layers/Deconvolution.hs b/src/Grenade/Layers/Deconvolution.hs
index f46d12b2..f4ab8827 100644
--- a/src/Grenade/Layers/Deconvolution.hs
+++ b/src/Grenade/Layers/Deconvolution.hs
@@ -50,6 +50,7 @@ import           Numeric.LinearAlgebra.Static hiding ((|||), build, toRows)
 import           Grenade.Core
 import           Grenade.Layers.Internal.Convolution
 import           Grenade.Layers.Internal.Update
+import           Control.DeepSeq
 
 -- | A Deconvolution layer for a neural network.
 --   This uses the im2col Convolution trick popularised by Caffe.
@@ -94,6 +95,9 @@ data Deconvolution' :: Nat -- Number of channels, for the first layer this could
                => !(L kernelFlattened channels) -- The kernel filter gradient
                -> Deconvolution' channels filters kernelRows kernelColumns strideRows strideColumns
 
+instance NFData (Deconvolution c f k k' s s') where
+  rnf (Deconvolution a b) = rnf a `deepseq` rnf b `deepseq` ()
+
 instance Show (Deconvolution c f k k' s s') where
   show (Deconvolution a _) = renderConv a
     where
diff --git a/src/Grenade/Layers/Dropout.hs b/src/Grenade/Layers/Dropout.hs
index 530947d1..6354b6a4 100644
--- a/src/Grenade/Layers/Dropout.hs
+++ b/src/Grenade/Layers/Dropout.hs
@@ -11,6 +11,7 @@ import           Control.Monad.Random hiding (fromList)
 
 import           GHC.TypeLits
 import           Grenade.Core
+import           Control.DeepSeq
 
 -- Dropout layer help to reduce overfitting.
 -- Idea here is that the vector is a shape of 1s and 0s, which we multiply the input by.
@@ -20,7 +21,10 @@ import           Grenade.Core
 data Dropout = Dropout {
     dropoutRate :: Double
   , dropoutSeed :: Int
-  } deriving Show
+  } deriving (Show)
+
+instance NFData Dropout where
+  rnf (Dropout r s) = rnf r `deepseq` rnf s `deepseq` ()
 
 instance UpdateLayer Dropout where
   type Gradient Dropout = ()
diff --git a/src/Grenade/Layers/Elu.hs b/src/Grenade/Layers/Elu.hs
index a1090860..7524c768 100644
--- a/src/Grenade/Layers/Elu.hs
+++ b/src/Grenade/Layers/Elu.hs
@@ -19,6 +19,7 @@ import           GHC.TypeLits
 import           Grenade.Core
 
 import qualified Numeric.LinearAlgebra.Static as LAS
+import           Control.DeepSeq
 
 -- | An exponential linear unit.
 --   A layer which can act between any shape of the same dimension, acting as a
@@ -26,6 +27,9 @@ import qualified Numeric.LinearAlgebra.Static as LAS
 data Elu = Elu
   deriving Show
 
+instance NFData Elu where
+  rnf Elu = ()
+
 instance UpdateLayer Elu where
   type Gradient Elu = ()
   runUpdate _ _ _ = Elu
diff --git a/src/Grenade/Layers/FullyConnected.hs b/src/Grenade/Layers/FullyConnected.hs
index 70416586..a97c4ae4 100644
--- a/src/Grenade/Layers/FullyConnected.hs
+++ b/src/Grenade/Layers/FullyConnected.hs
@@ -21,6 +21,7 @@ import           Numeric.LinearAlgebra.Static
 import           Grenade.Core
 
 import           Grenade.Layers.Internal.Update
+import           Control.DeepSeq
 
 -- | A basic fully connected (or inner product) neural network layer.
 data FullyConnected i o = FullyConnected
@@ -31,6 +32,12 @@ data FullyConnected' i o = FullyConnected'
                          !(R o)   -- Bias
                          !(L o i) -- Activations
 
+instance NFData (FullyConnected' i o) where
+  rnf (FullyConnected' a b) = a `deepseq` b `deepseq` ()
+
+instance NFData (FullyConnected i o) where
+  rnf (FullyConnected a b) = a `deepseq` b `deepseq` ()
+
 instance Show (FullyConnected i o) where
   show FullyConnected {} = "FullyConnected"
 
diff --git a/src/Grenade/Layers/Logit.hs b/src/Grenade/Layers/Logit.hs
index cc584825..fb7343d2 100644
--- a/src/Grenade/Layers/Logit.hs
+++ b/src/Grenade/Layers/Logit.hs
@@ -19,6 +19,7 @@ import           Data.Serialize
 import           Data.Singletons
 
 import           Grenade.Core
+import           Control.DeepSeq
 
 -- | A Logit layer.
 --
@@ -28,6 +29,9 @@ import           Grenade.Core
 data Logit = Logit
   deriving Show
 
+instance NFData Logit where
+  rnf Logit = ()
+
 instance UpdateLayer Logit where
   type Gradient Logit = ()
   runUpdate _ _ _ = Logit
diff --git a/src/Grenade/Layers/Merge.hs b/src/Grenade/Layers/Merge.hs
index f5333f21..34b7b594 100644
--- a/src/Grenade/Layers/Merge.hs
+++ b/src/Grenade/Layers/Merge.hs
@@ -29,6 +29,7 @@ import           Data.Kind (Type)
 #endif
 
 import           Grenade.Core
+import           Control.DeepSeq 
 
 -- | A Merging layer.
 --
@@ -37,6 +38,9 @@ import           Grenade.Core
 data Merge :: Type -> Type -> Type where
   Merge :: x -> y -> Merge x y
 
+instance (NFData x, NFData y) => NFData (Merge x y) where
+  rnf (Merge x y) = rnf x `deepseq` rnf y `deepseq` ()
+
 instance (Show x, Show y) => Show (Merge x y) where
   show (Merge x y) = "Merge\n" ++ show x ++ "\n" ++ show y
 
diff --git a/src/Grenade/Layers/Pad.hs b/src/Grenade/Layers/Pad.hs
index 652a778c..ae1cc999 100644
--- a/src/Grenade/Layers/Pad.hs
+++ b/src/Grenade/Layers/Pad.hs
@@ -37,6 +37,7 @@ import           Grenade.Layers.Internal.Pad
 
 import           Numeric.LinearAlgebra (konst, subMatrix, diagBlock)
 import           Numeric.LinearAlgebra.Static (extract, create)
+import           Control.DeepSeq
 
 -- | A padding layer for a neural network.
 --
@@ -47,6 +48,9 @@ data Pad  :: Nat
           -> Nat -> Type where
   Pad  :: Pad padLeft padTop padRight padBottom
 
+instance NFData (Pad padLeft padTop padRight padBottom) where
+  rnf Pad = ()
+
 instance Show (Pad padLeft padTop padRight padBottom) where
   show Pad = "Pad"
 
diff --git a/src/Grenade/Layers/Pooling.hs b/src/Grenade/Layers/Pooling.hs
index ecfb9ee1..53fbe57e 100644
--- a/src/Grenade/Layers/Pooling.hs
+++ b/src/Grenade/Layers/Pooling.hs
@@ -37,6 +37,7 @@ import           Grenade.Core
 import           Grenade.Layers.Internal.Pooling
 
 import           Numeric.LinearAlgebra.Static as LAS hiding ((|||), build, toRows)
+import           Control.DeepSeq
 
 -- | A pooling layer for a neural network.
 --
@@ -49,6 +50,9 @@ import           Numeric.LinearAlgebra.Static as LAS hiding ((|||), build, toRow
 data Pooling :: Nat -> Nat -> Nat -> Nat -> Type where
   Pooling :: Pooling kernelRows kernelColumns strideRows strideColumns
 
+instance NFData (Pooling k k' s s') where
+  rnf Pooling = ()
+
 instance Show (Pooling k k' s s') where
   show Pooling = "Pooling"
 
diff --git a/src/Grenade/Layers/Relu.hs b/src/Grenade/Layers/Relu.hs
index 3db4670f..6e413a93 100644
--- a/src/Grenade/Layers/Relu.hs
+++ b/src/Grenade/Layers/Relu.hs
@@ -19,6 +19,7 @@ import           GHC.TypeLits
 import           Grenade.Core
 
 import qualified Numeric.LinearAlgebra.Static as LAS
+import           Control.DeepSeq
 
 -- | A rectifying linear unit.
 --   A layer which can act between any shape of the same dimension, acting as a
@@ -26,6 +27,9 @@ import qualified Numeric.LinearAlgebra.Static as LAS
 data Relu = Relu
   deriving Show
 
+instance NFData Relu where
+  rnf Relu = ()
+
 instance UpdateLayer Relu where
   type Gradient Relu = ()
   runUpdate _ _ _ = Relu
diff --git a/src/Grenade/Layers/Reshape.hs b/src/Grenade/Layers/Reshape.hs
index 8a657bc3..25700a8c 100644
--- a/src/Grenade/Layers/Reshape.hs
+++ b/src/Grenade/Layers/Reshape.hs
@@ -24,6 +24,7 @@ import           Numeric.LinearAlgebra.Static
 import           Numeric.LinearAlgebra.Data as LA ( flatten )
 
 import           Grenade.Core
+import           Control.DeepSeq
 
 -- | Reshape Layer
 --
@@ -36,6 +37,9 @@ import           Grenade.Core
 data Reshape = Reshape
   deriving Show
 
+instance NFData Reshape where
+  rnf Reshape = ()
+
 instance UpdateLayer Reshape where
   type Gradient Reshape = ()
   runUpdate _ _ _ = Reshape
diff --git a/src/Grenade/Layers/Sinusoid.hs b/src/Grenade/Layers/Sinusoid.hs
index cc68dd01..91adcdd5 100644
--- a/src/Grenade/Layers/Sinusoid.hs
+++ b/src/Grenade/Layers/Sinusoid.hs
@@ -18,12 +18,16 @@ import           Data.Serialize
 import           Data.Singletons
 
 import           Grenade.Core
+import           Control.DeepSeq
 
 -- | A Sinusoid layer.
 --   A layer which can act between any shape of the same dimension, performing a sin function.
 data Sinusoid = Sinusoid
   deriving Show
 
+instance NFData Sinusoid where
+  rnf Sinusoid = ()
+
 instance UpdateLayer Sinusoid where
   type Gradient Sinusoid  = ()
   runUpdate _ _ _ = Sinusoid
diff --git a/src/Grenade/Layers/Softmax.hs b/src/Grenade/Layers/Softmax.hs
index 27ca4b68..e850509c 100644
--- a/src/Grenade/Layers/Softmax.hs
+++ b/src/Grenade/Layers/Softmax.hs
@@ -22,6 +22,7 @@ import           GHC.TypeLits
 import           Grenade.Core
 
 import           Numeric.LinearAlgebra.Static as LAS
+import           Control.DeepSeq
 
 -- | A Softmax layer
 --
@@ -33,6 +34,9 @@ import           Numeric.LinearAlgebra.Static as LAS
 data Softmax = Softmax
   deriving Show
 
+instance NFData Softmax where
+  rnf Softmax = ()
+
 instance UpdateLayer Softmax where
   type Gradient Softmax = ()
   runUpdate _ _ _ = Softmax
diff --git a/src/Grenade/Layers/Tanh.hs b/src/Grenade/Layers/Tanh.hs
index fafbe3d3..44482702 100644
--- a/src/Grenade/Layers/Tanh.hs
+++ b/src/Grenade/Layers/Tanh.hs
@@ -18,12 +18,16 @@ import           Data.Serialize
 import           Data.Singletons
 
 import           Grenade.Core
+import           Control.DeepSeq
 
 -- | A Tanh layer.
 --   A layer which can act between any shape of the same dimension, performing a tanh function.
 data Tanh = Tanh
   deriving Show
 
+instance NFData Tanh where
+  rnf Tanh = ()
+
 instance UpdateLayer Tanh where
   type Gradient Tanh = ()
   runUpdate _ _ _ = Tanh
diff --git a/src/Grenade/Layers/Trivial.hs b/src/Grenade/Layers/Trivial.hs
index 0d756ca7..61bbe9f1 100644
--- a/src/Grenade/Layers/Trivial.hs
+++ b/src/Grenade/Layers/Trivial.hs
@@ -17,6 +17,7 @@ module Grenade.Layers.Trivial (
 import           Data.Serialize
 
 import           Grenade.Core
+import           Control.DeepSeq
 
 -- | A Trivial layer.
 --
@@ -25,6 +26,9 @@ import           Grenade.Core
 data Trivial = Trivial
   deriving Show
 
+instance NFData Trivial where
+  rnf Trivial = ()
+
 instance Serialize Trivial where
   put _ = return ()
   get = return Trivial
diff --git a/src/Grenade/Recurrent/Core/Layer.hs b/src/Grenade/Recurrent/Core/Layer.hs
index 91243712..a7660018 100644
--- a/src/Grenade/Recurrent/Core/Layer.hs
+++ b/src/Grenade/Recurrent/Core/Layer.hs
@@ -14,6 +14,7 @@ import           Data.Kind (Type)
 #endif
 
 import           Grenade.Core
+import           Control.DeepSeq (NFData)
 
 -- | Class for a recurrent layer.
 --   It's quite similar to a normal layer but for the input and output
@@ -22,7 +23,7 @@ class UpdateLayer x => RecurrentUpdateLayer x where
   -- | Shape of data that is passed between each subsequent run of the layer
   type RecurrentShape x   :: Type
 
-class (RecurrentUpdateLayer x, Num (RecurrentShape x)) => RecurrentLayer x (i :: Shape) (o :: Shape) where
+class (RecurrentUpdateLayer x, Num (RecurrentShape x), NFData x) => RecurrentLayer x (i :: Shape) (o :: Shape) where
   -- | Wengert Tape
   type RecTape x i o :: Type
   -- | Used in training and scoring. Take the input from the previous
diff --git a/src/Grenade/Recurrent/Core/Network.hs b/src/Grenade/Recurrent/Core/Network.hs
index 62df741e..414c969d 100644
--- a/src/Grenade/Recurrent/Core/Network.hs
+++ b/src/Grenade/Recurrent/Core/Network.hs
@@ -39,6 +39,7 @@ import           Data.Kind (Type)
 
 import           Grenade.Core
 import           Grenade.Recurrent.Core.Layer
+import           Control.DeepSeq
 
 -- | Witness type to say indicate we're building up with a normal feed
 --   forward layer.
@@ -198,6 +199,12 @@ applyRecurrentUpdate rate (layer :~@> rest) (gradient ://> grest)
 applyRecurrentUpdate _ RNil RGNil
   = RNil
 
+instance NFData (RecurrentNetwork '[] '[i]) where
+  rnf RNil = ()
+
+instance NFData (RecurrentNetwork xs rs) => NFData (RecurrentNetwork (x ': xs) (i ': rs)) where
+  rnf (layer :~~> rest) = rnf layer `deepseq` rnf rest `deepseq` ()
+  rnf (layer :~@> rest) = rnf layer `deepseq` rnf rest `deepseq` ()
 
 instance Show (RecurrentNetwork '[] '[i]) where
   show RNil = "NNil"
@@ -325,6 +332,7 @@ instance CreatableRecurrent sublayers subshapes => RecurrentUpdateLayer (Recurre
 instance ( CreatableRecurrent sublayers subshapes
          , i ~ (Head subshapes), o ~ (Last subshapes)
          , Num (RecurrentShape (RecurrentNetwork sublayers subshapes))
+         , NFData (RecurrentNetwork sublayers subshapes)
          ) => RecurrentLayer (RecurrentNetwork sublayers subshapes) i o where
   type RecTape (RecurrentNetwork sublayers subshapes) i o = RecurrentTape sublayers subshapes
   runRecurrentForwards = runRecurrent
diff --git a/src/Grenade/Recurrent/Layers/BasicRecurrent.hs b/src/Grenade/Recurrent/Layers/BasicRecurrent.hs
index 53b0133a..009022c9 100644
--- a/src/Grenade/Recurrent/Layers/BasicRecurrent.hs
+++ b/src/Grenade/Recurrent/Layers/BasicRecurrent.hs
@@ -28,6 +28,7 @@ import           GHC.TypeLits
 
 import           Grenade.Core
 import           Grenade.Recurrent.Core
+import           Control.DeepSeq
 
 data BasicRecurrent :: Nat -- Input layer size
                     -> Nat -- Output layer size
@@ -42,6 +43,9 @@ data BasicRecurrent :: Nat -- Input layer size
                  -> !(L output matrixCols) -- Momentum
                  -> BasicRecurrent input output
 
+instance NFData (BasicRecurrent input output) where
+  rnf (BasicRecurrent b bm a aM) = rnf b `deepseq` rnf bm `deepseq` rnf a `deepseq` rnf aM `deepseq` ()
+
 data BasicRecurrent' :: Nat -- Input layer size
                      -> Nat -- Output layer size
                      -> Type where
diff --git a/src/Grenade/Recurrent/Layers/ConcatRecurrent.hs b/src/Grenade/Recurrent/Layers/ConcatRecurrent.hs
index 65aa197e..9477347e 100644
--- a/src/Grenade/Recurrent/Layers/ConcatRecurrent.hs
+++ b/src/Grenade/Recurrent/Layers/ConcatRecurrent.hs
@@ -36,6 +36,7 @@ import           Grenade.Core
 import           Grenade.Recurrent.Core
 
 import           Numeric.LinearAlgebra.Static ( (#), split, R )
+import           Control.DeepSeq
 
 -- | A Concatentating Layer.
 --
@@ -55,6 +56,15 @@ data ConcatRecurrent :: Shape -> Type -> Shape -> Type -> Type where
   ConcatRecRight :: x -> y -> ConcatRecurrent m (FeedForward x) n (Recurrent y)
   ConcatRecBoth  :: x -> y -> ConcatRecurrent m (Recurrent x) n   (Recurrent y)
 
+instance (NFData x, NFData y) => NFData (ConcatRecurrent m (Recurrent x) n (Recurrent y)) where
+  rnf (ConcatRecBoth  x y) = rnf x `deepseq` rnf y `deepseq` ()
+
+instance (NFData x, NFData y) => NFData (ConcatRecurrent m (Recurrent x) n (FeedForward y)) where
+  rnf (ConcatRecLeft  x y) = rnf x `deepseq` rnf y `deepseq` ()
+
+instance (NFData x, NFData y) => NFData (ConcatRecurrent m (FeedForward x) n (Recurrent y)) where
+  rnf (ConcatRecRight x y) = rnf x `deepseq` rnf y `deepseq` ()
+
 instance (Show x, Show y) => Show (ConcatRecurrent m (p x) n (q y)) where
   show (ConcatRecLeft x y)  = "ConcatRecLeft\n" ++ show x ++ "\n" ++ show y
   show (ConcatRecRight x y) = "ConcatRecRight\n" ++ show x ++ "\n" ++ show y
diff --git a/src/Grenade/Recurrent/Layers/LSTM.hs b/src/Grenade/Recurrent/Layers/LSTM.hs
index 24371489..0c07d48e 100644
--- a/src/Grenade/Recurrent/Layers/LSTM.hs
+++ b/src/Grenade/Recurrent/Layers/LSTM.hs
@@ -33,6 +33,7 @@ import           Numeric.LinearAlgebra.Static
 import           Grenade.Core
 import           Grenade.Recurrent.Core
 import           Grenade.Layers.Internal.Update
+import           Control.DeepSeq
 
 
 -- | Long Short Term Memory Recurrent unit
@@ -64,6 +65,16 @@ data LSTMWeights :: Nat -> Nat -> Type where
                  , lstmBc :: !(R output)        -- Bias Cell         (b_c)
                  } -> LSTMWeights input output
 
+instance NFData (LSTMWeights input output) where
+  rnf (LSTMWeights wf uf bf wi ui bi wo uo bo wc bc) =
+    rnf wf `deepseq` rnf uf `deepseq` rnf bf `deepseq`
+    rnf wi `deepseq` rnf ui `deepseq` rnf bi `deepseq`
+    rnf wo `deepseq` rnf uo `deepseq` rnf bo `deepseq`
+    rnf wc `deepseq` rnf bc `deepseq` ()
+
+instance NFData (LSTM input output) where
+  rnf (LSTM w m) = rnf w `deepseq` rnf m `deepseq` ()
+
 instance Show (LSTM i o) where
   show LSTM {} = "LSTM"