Safe Haskell | Safe-Inferred |
---|---|
Language | Haskell2010 |
Synopsis
- sOnes :: forall gradient layout device dataType shape m. MonadThrow m => TensorSpec gradient layout device dataType shape -> m (Tensor gradient layout device dataType shape)
- ones :: forall gradient layout device dataType shape m. MonadThrow m => (SingI gradient, SingI layout, SingI device, SingI dataType, SingI shape) => m (Tensor gradient layout device dataType shape)
- sZeros :: forall gradient layout device dataType shape m. MonadThrow m => TensorSpec gradient layout device dataType shape -> m (Tensor gradient layout device dataType shape)
- zeros :: forall gradient layout device dataType shape m. MonadThrow m => (SingI gradient, SingI layout, SingI device, SingI dataType, SingI shape) => m (Tensor gradient layout device dataType shape)
- sFull :: forall gradient layout device dataType shape input m. (MonadThrow m, Scalar input) => TensorSpec gradient layout device dataType shape -> input -> m (Tensor gradient layout device dataType shape)
- full :: forall gradient layout device dataType shape input m. (MonadThrow m, SingI gradient, SingI layout, SingI device, SingI dataType, SingI shape, Scalar input) => input -> m (Tensor gradient layout device dataType shape)
- sRandn :: forall gradient layout device dataType shape generatorDevice m. (SGetGeneratorDevice generatorDevice, MonadThrow m) => TensorSpec gradient layout device dataType shape -> Generator generatorDevice -> m (Tensor gradient layout (device <+> generatorDevice) dataType shape, Generator (device <+> generatorDevice))
- randn :: forall gradient layout device dataType shape generatorDevice m. (SGetGeneratorDevice generatorDevice, MonadThrow m) => (SingI gradient, SingI layout, SingI device, SingI dataType, SingI shape) => Generator generatorDevice -> m (Tensor gradient layout (device <+> generatorDevice) dataType shape, Generator (device <+> generatorDevice))
- sArangeNaturals :: forall m gradient layout device dataType size shape. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") size]) => SGradient gradient -> SLayout layout -> SDevice device -> SDataType dataType -> SSize size -> m (Tensor gradient layout device dataType shape)
- arangeNaturals :: forall size gradient layout device dataType shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") size], SingI gradient, SingI layout, SingI device, SingI dataType, SingI size) => m (Tensor gradient layout device dataType shape)
- sEye :: forall gradient layout device dataType rows cols shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") rows, 'Dim ('Name "*") cols]) => SGradient gradient -> SLayout layout -> SDevice device -> SDataType dataType -> SSize rows -> SSize cols -> m (Tensor gradient layout device dataType shape)
- eye :: forall rows cols gradient layout device dataType shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") rows, 'Dim ('Name "*") cols], SingI gradient, SingI layout, SingI device, SingI dataType, SingI rows, SingI cols) => m (Tensor gradient layout device dataType shape)
- sEyeSquare :: forall gradient layout device dataType size shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") size, 'Dim ('Name "*") size]) => SGradient gradient -> SLayout layout -> SDevice device -> SDataType dataType -> SSize size -> m (Tensor gradient layout device dataType shape)
- eyeSquare :: forall size gradient layout device dataType shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") size, 'Dim ('Name "*") size], SingI gradient, SingI layout, SingI device, SingI dataType, SingI size) => m (Tensor gradient layout device dataType shape)
Documentation
sOnes :: forall gradient layout device dataType shape m. MonadThrow m => TensorSpec gradient layout device dataType shape -> m (Tensor gradient layout device dataType shape) Source #
Create a gradually typed tensor of ones.
>>>
shape = SShape $ SName @"batch" :&: SSize @32 :|: SUncheckedName "feature" :&: SUncheckedSize 8 :|: SNil
>>>
:type sOnes $ TensorSpec (SGradient SWithoutGradient) (SLayout SDense) (SDevice SCPU) (SDataType SInt64) shape
sOnes $ TensorSpec (SGradient SWithoutGradient) (SLayout SDense) (SDevice SCPU) (SDataType SInt64) shape :: MonadThrow m => m (Tensor ('Gradient 'WithoutGradient) ('Layout 'Dense) ('Device 'CPU) ('DataType 'Int64) ('Shape '[ 'Dim ('Name "batch") ('Size 32), 'Dim 'UncheckedName 'UncheckedSize]))
ones :: forall gradient layout device dataType shape m. MonadThrow m => (SingI gradient, SingI layout, SingI device, SingI dataType, SingI shape) => m (Tensor gradient layout device dataType shape) Source #
Create a typed tensor of ones.
>>>
ones :: IO (CPUParameter ('DataType 'Float) ('Shape '[]))
Tensor Float [] 1.0000>>>
ones :: IO (CPUTensor ('DataType 'Int64) ('Shape '[ 'Dim ('Name "*") ('Size 1)]))
Tensor Int64 [1] [ 1]
sZeros :: forall gradient layout device dataType shape m. MonadThrow m => TensorSpec gradient layout device dataType shape -> m (Tensor gradient layout device dataType shape) Source #
Create a gradually typed tensor of zeros.
>>>
shape = SShape $ SName @"batch" :&: SSize @32 :|: SUncheckedName "feature" :&: SUncheckedSize 8 :|: SNil
>>>
:type sZeros $ TensorSpec (SGradient SWithoutGradient) (SLayout SDense) (SDevice SCPU) (SDataType SInt64) shape
sZeros $ TensorSpec (SGradient SWithoutGradient) (SLayout SDense) (SDevice SCPU) (SDataType SInt64) shape :: MonadThrow m => m (Tensor ('Gradient 'WithoutGradient) ('Layout 'Dense) ('Device 'CPU) ('DataType 'Int64) ('Shape '[ 'Dim ('Name "batch") ('Size 32), 'Dim 'UncheckedName 'UncheckedSize]))
zeros :: forall gradient layout device dataType shape m. MonadThrow m => (SingI gradient, SingI layout, SingI device, SingI dataType, SingI shape) => m (Tensor gradient layout device dataType shape) Source #
Create a typed tensor of zeros.
>>>
zeros :: IO (CPUParameter ('DataType 'Float) ('Shape '[]))
Tensor Float [] 0.0000>>>
zeros :: IO (CPUTensor ('DataType 'Int64) ('Shape '[ 'Dim ('Name "*") ('Size 1)]))
Tensor Int64 [1] [ 0]
sFull :: forall gradient layout device dataType shape input m. (MonadThrow m, Scalar input) => TensorSpec gradient layout device dataType shape -> input -> m (Tensor gradient layout device dataType shape) Source #
Create a gradually typed tensor filled with a given scalar value.
>>>
shape = SShape $ SName @"batch" :&: SSize @32 :|: SUncheckedName "feature" :&: SUncheckedSize 8 :|: SNil
>>>
input = -1
>>>
:type sFull (TensorSpec (SGradient SWithoutGradient) (SLayout SDense) (SDevice SCPU) (SDataType SInt64) shape) input
sFull (TensorSpec (SGradient SWithoutGradient) (SLayout SDense) (SDevice SCPU) (SDataType SInt64) shape) input :: MonadThrow m => m (Tensor ('Gradient 'WithoutGradient) ('Layout 'Dense) ('Device 'CPU) ('DataType 'Int64) ('Shape '[ 'Dim ('Name "batch") ('Size 32), 'Dim 'UncheckedName 'UncheckedSize]))
full :: forall gradient layout device dataType shape input m. (MonadThrow m, SingI gradient, SingI layout, SingI device, SingI dataType, SingI shape, Scalar input) => input -> m (Tensor gradient layout device dataType shape) Source #
Create a typed tensor filled with a given scalar value.
>>>
full (-1) :: IO (CPUParameter ('DataType 'Float) ('Shape '[]))
Tensor Float [] -1.0000>>>
full (-1) :: IO (CPUTensor ('DataType 'Int64) ('Shape '[ 'Dim ('Name "*") ('Size 1)]))
Tensor Int64 [1] [-1]
sRandn :: forall gradient layout device dataType shape generatorDevice m. (SGetGeneratorDevice generatorDevice, MonadThrow m) => TensorSpec gradient layout device dataType shape -> Generator generatorDevice -> m (Tensor gradient layout (device <+> generatorDevice) dataType shape, Generator (device <+> generatorDevice)) Source #
Create a gradually typed random tensor.
randn :: forall gradient layout device dataType shape generatorDevice m. (SGetGeneratorDevice generatorDevice, MonadThrow m) => (SingI gradient, SingI layout, SingI device, SingI dataType, SingI shape) => Generator generatorDevice -> m (Tensor gradient layout (device <+> generatorDevice) dataType shape, Generator (device <+> generatorDevice)) Source #
Create typed random tensor.
sArangeNaturals :: forall m gradient layout device dataType size shape. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") size]) => SGradient gradient -> SLayout layout -> SDevice device -> SDataType dataType -> SSize size -> m (Tensor gradient layout device dataType shape) Source #
Create a gradually typed one-dimensional tensor of the numbers 0
to size -1
.
arangeNaturals :: forall size gradient layout device dataType shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") size], SingI gradient, SingI layout, SingI device, SingI dataType, SingI size) => m (Tensor gradient layout device dataType shape) Source #
Create a typed one-dimensional tensor of the numbers 0
to size -1
.
sEye :: forall gradient layout device dataType rows cols shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") rows, 'Dim ('Name "*") cols]) => SGradient gradient -> SLayout layout -> SDevice device -> SDataType dataType -> SSize rows -> SSize cols -> m (Tensor gradient layout device dataType shape) Source #
Create a gradually typed rectangular tensor with ones on the diagonal and zeros elsewhere.
eye :: forall rows cols gradient layout device dataType shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") rows, 'Dim ('Name "*") cols], SingI gradient, SingI layout, SingI device, SingI dataType, SingI rows, SingI cols) => m (Tensor gradient layout device dataType shape) Source #
Create a typed rectangular tensor with ones on the diagonal and zeros elsewhere.
sEyeSquare :: forall gradient layout device dataType size shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") size, 'Dim ('Name "*") size]) => SGradient gradient -> SLayout layout -> SDevice device -> SDataType dataType -> SSize size -> m (Tensor gradient layout device dataType shape) Source #
Create a gradually typed square tensor with ones on the diagonal and zeros elsewhere.
eyeSquare :: forall size gradient layout device dataType shape m. (MonadThrow m, shape ~ 'Shape '['Dim ('Name "*") size, 'Dim ('Name "*") size], SingI gradient, SingI layout, SingI device, SingI dataType, SingI size) => m (Tensor gradient layout device dataType shape) Source #
Create a typed square tensor with ones on the diagonal and zeros elsewhere.