Claudio Ortolina
115 lines
3.2 KiB
Elixir
115 lines
3.2 KiB
Elixir
defmodule SqliteVec.Float32 do
|
|
@moduledoc """
|
|
A vector struct for float32 vectors.
|
|
Vectors are stored as binaries in the endianness of the system.
|
|
|
|
> ### Consider endianness {: .warning}
|
|
>
|
|
> `SqliteVec.Float32.Vector` holds data in system endianness.
|
|
> Therefore, the same vector data will be interpreted differently on another system with different endianness.
|
|
> Moreover, you must consider endianness when converting the binary data directly to a list of numbers.
|
|
|
|
iex> v = SqliteVec.Float32.new([-1.0, 2.0])
|
|
...> b = SqliteVec.Float32.to_binary(v)
|
|
...> <<f1::float-32, f2::float-32>> = b
|
|
...> [f1, f2]
|
|
case System.endianness() do
|
|
:big -> [-1.0, 2.0]
|
|
:little -> [4.618539608568165e-41, 8.96831017167883e-44]
|
|
end
|
|
"""
|
|
|
|
@type t :: %__MODULE__{data: binary()}
|
|
|
|
defstruct [:data]
|
|
|
|
@doc """
|
|
Creates a new vector from a vector, list, or tensor
|
|
|
|
The vector must be a `SqliteVec.Float32` vector.
|
|
The list may contain any number but the values will be converted to f32 format.
|
|
The tensor must have a rank of 1 and must be of type :f32.
|
|
|
|
## Examples
|
|
iex> SqliteVec.Float32.new([1.0, 2.0])
|
|
%SqliteVec.Float32{data: <<1.0::float-32-native, 2.0::float-32-native>>}
|
|
|
|
iex> v1 = SqliteVec.Float32.new([1, 2])
|
|
...> SqliteVec.Float32.new(v1)
|
|
%SqliteVec.Float32{data: <<1.0::float-32-native, 2.0::float-32-native>>}
|
|
|
|
iex> SqliteVec.Float32.new(Nx.tensor([1, 2], type: :f32))
|
|
%SqliteVec.Float32{data: <<1.0::float-32-native, 2.0::float-32-native>>}
|
|
"""
|
|
def new(vector_or_list_or_tensor)
|
|
|
|
def new(%SqliteVec.Float32{} = vector) do
|
|
vector
|
|
end
|
|
|
|
def new(list) when is_list(list) do
|
|
if list == [] do
|
|
raise ArgumentError, "list must not be empty"
|
|
end
|
|
|
|
bin = for v <- list, into: <<>>, do: <<v::float-32-native>>
|
|
from_binary(<<bin::binary>>)
|
|
end
|
|
|
|
if Code.ensure_loaded?(Nx) do
|
|
def new(tensor) when is_struct(tensor, Nx.Tensor) do
|
|
if Nx.rank(tensor) != 1 do
|
|
raise ArgumentError, "expected rank to be 1"
|
|
end
|
|
|
|
if Nx.type(tensor) != {:f, 32} do
|
|
raise ArgumentError, "expected type to be :f32"
|
|
end
|
|
|
|
bin = tensor |> Nx.to_binary()
|
|
from_binary(<<bin::binary>>)
|
|
end
|
|
end
|
|
|
|
@doc """
|
|
Creates a new vector from its binary representation
|
|
"""
|
|
def from_binary(binary) when is_binary(binary) do
|
|
%SqliteVec.Float32{data: binary}
|
|
end
|
|
|
|
@doc """
|
|
Converts the vector to its binary representation
|
|
"""
|
|
def to_binary(vector) when is_struct(vector, SqliteVec.Float32) do
|
|
vector.data
|
|
end
|
|
|
|
@doc """
|
|
Converts the vector to a list
|
|
"""
|
|
def to_list(vector) when is_struct(vector, SqliteVec.Float32) do
|
|
<<bin::binary>> = vector.data
|
|
|
|
for <<v::float-32-native <- bin>>, do: v
|
|
end
|
|
|
|
if Code.ensure_loaded?(Nx) do
|
|
@doc """
|
|
Converts the vector to a tensor
|
|
"""
|
|
def to_tensor(vector) when is_struct(vector, SqliteVec.Float32) do
|
|
<<bin::binary>> = vector.data
|
|
Nx.from_binary(bin, :f32)
|
|
end
|
|
end
|
|
end
|
|
|
|
defimpl Inspect, for: SqliteVec.Float32 do
|
|
import Inspect.Algebra
|
|
|
|
def inspect(vector, opts) do
|
|
concat(["vec_f32('", to_doc(SqliteVec.Float32.to_list(vector), opts), "')"])
|
|
end
|
|
end
|