Safe Haskell	Safe-Inferred
Language	Haskell2010

Torch.TensorFactories

Synopsis

type FactoryType = ForeignPtr IntArray -> ForeignPtr TensorOptions -> IO (ForeignPtr Tensor)
type FactoryTypeWithDimnames = ForeignPtr IntArray -> ForeignPtr DimnameList -> ForeignPtr TensorOptions -> IO (ForeignPtr Tensor)
mkFactory :: FactoryType -> [Int] -> TensorOptions -> IO Tensor
mkFactoryUnsafe :: FactoryType -> [Int] -> TensorOptions -> Tensor
mkFactoryWithDimnames :: FactoryTypeWithDimnames -> [(Int, Dimname)] -> TensorOptions -> IO Tensor
mkFactoryUnsafeWithDimnames :: FactoryTypeWithDimnames -> [(Int, Dimname)] -> TensorOptions -> Tensor
mkDefaultFactory :: ([Int] -> TensorOptions -> a) -> [Int] -> a
mkDefaultFactoryWithDimnames :: ([(Int, Dimname)] -> TensorOptions -> a) -> [(Int, Dimname)] -> a
ones :: [Int] -> TensorOptions -> Tensor
onesLike :: Tensor -> Tensor
zeros :: [Int] -> TensorOptions -> Tensor
zerosLike :: Tensor -> Tensor
randIO :: [Int] -> TensorOptions -> IO Tensor
randnIO :: [Int] -> TensorOptions -> IO Tensor
randintIO :: Int -> Int -> [Int] -> TensorOptions -> IO Tensor
randnLikeIO :: Tensor -> IO Tensor
randLikeIO :: Tensor -> TensorOptions -> IO Tensor
fullLike :: Tensor -> Float -> TensorOptions -> IO Tensor
onesWithDimnames :: [(Int, Dimname)] -> TensorOptions -> Tensor
zerosWithDimnames :: [(Int, Dimname)] -> TensorOptions -> Tensor
randWithDimnames :: [(Int, Dimname)] -> TensorOptions -> IO Tensor
randnWithDimnames :: [(Int, Dimname)] -> TensorOptions -> IO Tensor
linspace :: (Scalar a, Scalar b) => a -> b -> Int -> TensorOptions -> Tensor
logspace :: (Scalar a, Scalar b) => a -> b -> Int -> Double -> TensorOptions -> Tensor
eyeSquare :: Int -> TensorOptions -> Tensor
eye :: Int -> Int -> TensorOptions -> Tensor
full :: Scalar a => [Int] -> a -> TensorOptions -> Tensor
sparseCooTensor :: Tensor -> Tensor -> [Int] -> TensorOptions -> Tensor
ones' :: [Int] -> Tensor
zeros' :: [Int] -> Tensor
randIO' :: [Int] -> IO Tensor
randnIO' :: [Int] -> IO Tensor
randintIO' :: Int -> Int -> [Int] -> IO Tensor
randLikeIO' :: Tensor -> IO Tensor
bernoulliIO' :: Tensor -> IO Tensor
bernoulliIO :: Tensor -> Double -> IO Tensor
poissonIO :: Tensor -> IO Tensor
multinomialIO' :: Tensor -> Int -> IO Tensor
multinomialIO :: Tensor -> Int -> Bool -> IO Tensor
normalIO' :: Tensor -> IO Tensor
normalIO :: Tensor -> Tensor -> IO Tensor
normalScalarIO :: Tensor -> Double -> IO Tensor
normalScalarIO' :: Double -> Tensor -> IO Tensor
normalWithSizeIO :: Double -> Double -> Int -> IO Tensor
rreluIO''' :: Tensor -> IO Tensor
rreluIO'' :: Scalar a => Tensor -> a -> IO Tensor
rreluIO' :: Scalar a => Tensor -> a -> a -> IO Tensor
rreluIO :: Scalar a => Tensor -> a -> a -> Bool -> IO Tensor
rreluWithNoiseIO''' :: Tensor -> Tensor -> IO Tensor
rreluWithNoiseIO'' :: Scalar a => Tensor -> Tensor -> a -> IO Tensor
rreluWithNoiseIO' :: Scalar a => Tensor -> Tensor -> a -> a -> IO Tensor
rreluWithNoiseIO :: Scalar a => Tensor -> Tensor -> a -> a -> Bool -> IO Tensor
onesWithDimnames' :: [(Int, Dimname)] -> Tensor
zerosWithDimnames' :: [(Int, Dimname)] -> Tensor
randWithDimnames' :: [(Int, Dimname)] -> IO Tensor
randnWithDimnames' :: [(Int, Dimname)] -> IO Tensor
linspace' :: (Scalar a, Scalar b) => a -> b -> Int -> Tensor
logspace' :: (Scalar a, Scalar b) => a -> b -> Int -> Double -> Tensor
eyeSquare' :: Int -> Tensor
eye' :: Int -> Int -> Tensor
full' :: Scalar a => [Int] -> a -> Tensor
sparseCooTensor' :: Tensor -> Tensor -> [Int] -> Tensor
arange :: Int -> Int -> Int -> TensorOptions -> Tensor
arange' :: Int -> Int -> Int -> Tensor

Documentation

type FactoryType = ForeignPtr IntArray -> ForeignPtr TensorOptions -> IO (ForeignPtr Tensor) Source #

type FactoryTypeWithDimnames = ForeignPtr IntArray -> ForeignPtr DimnameList -> ForeignPtr TensorOptions -> IO (ForeignPtr Tensor) Source #

mkFactory Source #

Arguments

:: FactoryType	aten_impl
-> [Int]	shape
-> TensorOptions	opts
-> IO Tensor	output

mkFactoryUnsafe :: FactoryType -> [Int] -> TensorOptions -> Tensor Source #

mkFactoryWithDimnames :: FactoryTypeWithDimnames -> [(Int, Dimname)] -> TensorOptions -> IO Tensor Source #

mkFactoryUnsafeWithDimnames :: FactoryTypeWithDimnames -> [(Int, Dimname)] -> TensorOptions -> Tensor Source #

mkDefaultFactory :: ([Int] -> TensorOptions -> a) -> [Int] -> a Source #

mkDefaultFactoryWithDimnames :: ([(Int, Dimname)] -> TensorOptions -> a) -> [(Int, Dimname)] -> a Source #

ones Source #

Arguments

:: [Int]	sequence of integers defining the shape of the output tensor.
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> Tensor	output

Returns a tensor filled with the scalar value 1, with the shape defined by the variable argument size.

onesLike Source #

Arguments

:: Tensor	input
-> Tensor	output

Returns a tensor filled with the scalar value 1, with the same size as input tensor

zeros Source #

Arguments

:: [Int]	sequence of integers defining the shape of the output tensor.
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> Tensor	output

Returns a tensor filled with the scalar value 0, with the shape defined by the variable argument size.

zerosLike Source #

Arguments

:: Tensor	input
-> Tensor	output

Returns a tensor filled with the scalar value 0, with the same size as input tensor

randIO Source #

Arguments

:: [Int]	sequence of integers defining the shape of the output tensor.
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> IO Tensor	output

Returns a tensor filled with random numbers from a uniform distribution on the interval [0,1)

randnIO Source #

Arguments

:: [Int]	sequence of integers defining the shape of the output tensor.
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> IO Tensor	output

Returns a tensor filled with random numbers from a standard normal distribution.

randintIO Source #

Arguments

:: Int	lowest integer to be drawn from the distribution. Default: 0.
-> Int	one above the highest integer to be drawn from the distribution.
-> [Int]	the shape of the output tensor.
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> IO Tensor	output

Returns a tensor filled with random integers generated uniformly between low (inclusive) and high (exclusive).

randnLikeIO Source #

Arguments

:: Tensor	input
-> IO Tensor	output

Returns a tensor with the same size as input that is filled with random numbers from standard normal distribution.

randLikeIO Source #

Arguments

:: Tensor	input
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> IO Tensor	output

Returns a tensor with the same size as input that is filled with random numbers from a uniform distribution on the interval [0,1).

fullLike Source #

Arguments

:: Tensor	input
-> Float	_fill_value
-> TensorOptions	opt
-> IO Tensor	output

onesWithDimnames :: [(Int, Dimname)] -> TensorOptions -> Tensor Source #

zerosWithDimnames :: [(Int, Dimname)] -> TensorOptions -> Tensor Source #

randWithDimnames :: [(Int, Dimname)] -> TensorOptions -> IO Tensor Source #

randnWithDimnames :: [(Int, Dimname)] -> TensorOptions -> IO Tensor Source #

linspace Source #

Arguments

:: (Scalar a, Scalar b)
=> a	start
-> b	end
-> Int	steps
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> Tensor	output

Returns a one-dimensional tensor of steps equally spaced points between start and end.

logspace :: (Scalar a, Scalar b) => a -> b -> Int -> Double -> TensorOptions -> Tensor Source #

eyeSquare Source #

Arguments

:: Int	dim
-> TensorOptions	opts
-> Tensor	output

eye Source #

Arguments

:: Int	the number of rows
-> Int	the number of columns
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> Tensor	output

Returns a 2-D tensor with ones on the diagonal and zeros elsewhere.

full Source #

Arguments

:: Scalar a
=> [Int]	the shape of the output tensor.
-> a	the number to fill the output tensor with
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> Tensor	output

Returns a tensor of given size filled with fill_value.

sparseCooTensor Source #

Arguments

:: Tensor	The indices are the coordinates of the non-zero values in the matrix
-> Tensor	Initial values for the tensor.
-> [Int]	the shape of the output tensor.
-> TensorOptions
-> Tensor	output

Constructs a sparse tensors in COO(rdinate) format with non-zero elements at the given indices with the given values.

ones' :: [Int] -> Tensor Source #

zeros' :: [Int] -> Tensor Source #

randIO' :: [Int] -> IO Tensor Source #

randnIO' :: [Int] -> IO Tensor Source #

randintIO' :: Int -> Int -> [Int] -> IO Tensor Source #

randLikeIO' :: Tensor -> IO Tensor Source #

bernoulliIO' Source #

Arguments

:: Tensor	t
-> IO Tensor	output

bernoulliIO Source #

Arguments

:: Tensor	t
-> Double	p
-> IO Tensor	output

poissonIO Source #

Arguments

:: Tensor	t
-> IO Tensor	output

multinomialIO' Source #

Arguments

:: Tensor	t
-> Int	num_samples
-> IO Tensor	output

multinomialIO Source #

Arguments

:: Tensor	t
-> Int	num_samples
-> Bool	replacement
-> IO Tensor	output

normalIO' Source #

Arguments

:: Tensor	_mean
-> IO Tensor	output

normalIO Source #

Arguments

:: Tensor	_mean
-> Tensor	_std
-> IO Tensor	output

normalScalarIO Source #

Arguments

:: Tensor	_mean
-> Double	_std
-> IO Tensor	output

normalScalarIO' Source #

Arguments

:: Double	_mean
-> Tensor	_std
-> IO Tensor	output

normalWithSizeIO Source #

Arguments

:: Double	_mean
-> Double	_std
-> Int	_size
-> IO Tensor	output

rreluIO''' Source #

Arguments

:: Tensor	t
-> IO Tensor	output

rreluIO'' Source #

Arguments

:: Scalar a
=> Tensor	t
-> a	upper
-> IO Tensor	output

rreluIO' Source #

Arguments

:: Scalar a
=> Tensor	t
-> a	lower
-> a	upper
-> IO Tensor	output

rreluIO Source #

Arguments

:: Scalar a
=> Tensor	t
-> a	lower
-> a	upper
-> Bool	training
-> IO Tensor	output

rreluWithNoiseIO''' Source #

Arguments

:: Tensor	t
-> Tensor	noise
-> IO Tensor	output

rreluWithNoiseIO'' Source #

Arguments

:: Scalar a
=> Tensor	t
-> Tensor	noise
-> a	upper
-> IO Tensor	output

rreluWithNoiseIO' Source #

Arguments

:: Scalar a
=> Tensor	t
-> Tensor	noise
-> a	lower
-> a	upper
-> IO Tensor	output

rreluWithNoiseIO Source #

Arguments

:: Scalar a
=> Tensor	t
-> Tensor	noise
-> a	lower
-> a	upper
-> Bool	training
-> IO Tensor	output

onesWithDimnames' :: [(Int, Dimname)] -> Tensor Source #

zerosWithDimnames' :: [(Int, Dimname)] -> Tensor Source #

randWithDimnames' :: [(Int, Dimname)] -> IO Tensor Source #

randnWithDimnames' :: [(Int, Dimname)] -> IO Tensor Source #

linspace' :: (Scalar a, Scalar b) => a -> b -> Int -> Tensor Source #

logspace' :: (Scalar a, Scalar b) => a -> b -> Int -> Double -> Tensor Source #

eyeSquare' :: Int -> Tensor Source #

eye' :: Int -> Int -> Tensor Source #

full' :: Scalar a => [Int] -> a -> Tensor Source #

sparseCooTensor' :: Tensor -> Tensor -> [Int] -> Tensor Source #

arange Source #

Arguments

:: Int	start
-> Int	end
-> Int	step
-> TensorOptions	configures the data type, device, layout and other properties of the resulting tensor.
-> Tensor	output

Returns a 1-D tensor with values from the interval [start, end) taken with common difference step beginning from start.

arange' Source #

Arguments

:: Int	start
-> Int	end
-> Int	step
-> Tensor	output

Returns a 1-D tensor with values from the interval [start, end) taken with common difference step beginning from start.