View Source Nx.Constants (Nx v0.4.0)
Common constants used in computations.
Link to this section Summary
Functions
Returns the imaginary constant.
Returns infinity in f32.
Returns infinity.
Returns a scalar tensor with the maximum value for the given type.
Returns a scalar tensor with the maximum finite value for the given type.
Returns a scalar tensor with the minimum value for the given type.
Returns a scalar tensor with the minimum finite value for the given type.
Returns infinity in f32.
Returns NaN (Not a Number).
Returns infinity in f32.
Returns negative infinity.
Returns a scalar tensor with the maximum finite value for the given type.
Link to this section Functions
Returns the imaginary constant.
Accepts the same options as Nx.tensor/2
examples
Examples
iex> Nx.Constants.i()
#Nx.Tensor<
c64
0.0+1.0i
>
iex> Nx.Constants.i(type: {:c, 128})
#Nx.Tensor<
c128
0.0+1.0i
>
error-cases
Error cases
iex> Nx.Constants.i(type: {:f, 32})
** (ArgumentError) invalid type for complex number. Expected {:c, 64} or {:c, 128}, got: {:f, 32}Returns infinity in f32.
Returns infinity.
options
Options
:backend- a backend to allocate the tensor on.
examples
Examples
iex> Nx.Constants.infinity({:bf, 16})
#Nx.Tensor<
bf16
Inf
>
iex> Nx.Constants.infinity({:f, 16})
#Nx.Tensor<
f16
Inf
>
iex> Nx.Constants.infinity({:f, 32})
#Nx.Tensor<
f32
Inf
>
iex> Nx.Constants.infinity({:f, 64})
#Nx.Tensor<
f64
Inf
>Returns a scalar tensor with the maximum value for the given type.
It is infinity for floating point tensors.
options
Options
:backend- a backend to allocate the tensor on.
examples
Examples
iex> Nx.Constants.max({:u, 8})
#Nx.Tensor<
u8
255
>
iex> Nx.Constants.max({:f, 32})
#Nx.Tensor<
f32
Inf
>Returns a scalar tensor with the maximum finite value for the given type.
options
Options
:backend- a backend to allocate the tensor on.
examples
Examples
iex> Nx.Constants.max_finite({:u, 8})
#Nx.Tensor<
u8
255
>
iex> Nx.Constants.max_finite({:s, 16})
#Nx.Tensor<
s16
32677
>
iex> Nx.Constants.max_finite({:f, 32})
#Nx.Tensor<
f32
3.4028234663852886e38
>Returns a scalar tensor with the minimum value for the given type.
It is negative infinity for floating point tensors.
options
Options
:backend- a backend to allocate the tensor on.
examples
Examples
iex> Nx.Constants.min({:u, 8})
#Nx.Tensor<
u8
0
>
iex> Nx.Constants.min({:f, 32})
#Nx.Tensor<
f32
-Inf
>Returns a scalar tensor with the minimum finite value for the given type.
options
Options
:backend- a backend to allocate the tensor on.
examples
Examples
iex> Nx.Constants.min_finite({:u, 8})
#Nx.Tensor<
u8
0
>
iex> Nx.Constants.min_finite({:s, 16})
#Nx.Tensor<
s16
-32678
>
iex> Nx.Constants.min_finite({:f, 32})
#Nx.Tensor<
f32
-3.4028234663852886e38
>Returns infinity in f32.
Returns NaN (Not a Number).
options
Options
:backend- a backend to allocate the tensor on.
examples
Examples
iex> Nx.Constants.nan({:bf, 16})
#Nx.Tensor<
bf16
NaN
>
iex> Nx.Constants.nan({:f, 16})
#Nx.Tensor<
f16
NaN
>
iex> Nx.Constants.nan({:f, 32})
#Nx.Tensor<
f32
NaN
>
iex> Nx.Constants.nan({:f, 64})
#Nx.Tensor<
f64
NaN
>Returns infinity in f32.
Returns negative infinity.
options
Options
:backend- a backend to allocate the tensor on.
examples
Examples
iex> Nx.Constants.neg_infinity({:bf, 16})
#Nx.Tensor<
bf16
-Inf
>
iex> Nx.Constants.neg_infinity({:f, 16})
#Nx.Tensor<
f16
-Inf
>
iex> Nx.Constants.neg_infinity({:f, 32})
#Nx.Tensor<
f32
-Inf
>
iex> Nx.Constants.neg_infinity({:f, 64})
#Nx.Tensor<
f64
-Inf
>Returns a scalar tensor with the maximum finite value for the given type.
options
Options
:backend- a backend to allocate the tensor on.
examples
Examples
iex> Nx.Constants.smallest_positive_normal({:f, 64})
#Nx.Tensor<
f64
2.2250738585072014e-308
>
iex> Nx.Constants.smallest_positive_normal({:f, 32})
#Nx.Tensor<
f32
1.1754943508222875e-38
>
iex> Nx.Constants.smallest_positive_normal({:f, 16})
#Nx.Tensor<
f16
6.103515625e-5
>
iex> Nx.Constants.smallest_positive_normal(:bf16)
#Nx.Tensor<
bf16
1.1754943508222875e-38
>
iex> Nx.Constants.smallest_positive_normal({:s, 32})
** (ArgumentError) only floating types are supported, got: {:s, 32}