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lib/snakebridge_generated/dspy/datasets/data_loader.ex

# Generated by SnakeBridge v0.14.0 - DO NOT EDIT MANUALLY
# Regenerate with: mix compile
# Library: dspy 3.1.2
# Python module: dspy.datasets
# Python class: DataLoader
defmodule Dspy.Datasets.DataLoader do
@moduledoc """
Wrapper for Python class DataLoader.
"""
def __snakebridge_python_name__, do: "dspy.datasets"
def __snakebridge_python_class__, do: "DataLoader"
def __snakebridge_library__, do: "dspy"
@opaque t :: SnakeBridge.Ref.t()
@doc """
Initialize self. See help(type(self)) for accurate signature.
"""
@spec new(keyword()) :: {:ok, SnakeBridge.Ref.t()} | {:error, Snakepit.Error.t()}
def new(opts \\ []) do
SnakeBridge.Runtime.call_class(__MODULE__, :__init__, [], opts)
end
@doc """
Python method `DataLoader._shuffle_and_sample`.
## Parameters
- `split` (String.t())
- `data` (term())
- `size` (term())
- `seed` (integer() default: 0)
## Returns
- `list(Dspy.Primitives.ExampleClass.t())`
"""
@spec _shuffle_and_sample(
SnakeBridge.Ref.t(),
String.t(),
term(),
term(),
list(term()),
keyword()
) :: {:ok, list(Dspy.Primitives.ExampleClass.t())} | {:error, Snakepit.Error.t()}
def _shuffle_and_sample(ref, split, data, size, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(
ref,
:_shuffle_and_sample,
[split, data, size] ++ List.wrap(args),
opts
)
end
@doc """
Python method `DataLoader.from_csv`.
## Parameters
- `file_path` (String.t())
- `fields` (term() default: None)
- `input_keys` ({String.t()} default: ())
## Returns
- `list(Dspy.Primitives.ExampleClass.t())`
"""
@spec from_csv(SnakeBridge.Ref.t(), String.t(), list(term()), keyword()) ::
{:ok, list(Dspy.Primitives.ExampleClass.t())} | {:error, Snakepit.Error.t()}
def from_csv(ref, file_path, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(ref, :from_csv, [file_path] ++ List.wrap(args), opts)
end
@doc """
Python method `DataLoader.from_huggingface`.
## Parameters
- `dataset_name` (String.t())
- `args` (term())
- `input_keys` ({String.t()} keyword-only default: ())
- `fields` (term() keyword-only default: None)
- `kwargs` (term())
## Returns
- `term()`
"""
@spec from_huggingface(SnakeBridge.Ref.t(), String.t(), list(term()), keyword()) ::
{:ok, term()} | {:error, Snakepit.Error.t()}
def from_huggingface(ref, dataset_name, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(
ref,
:from_huggingface,
[dataset_name] ++ List.wrap(args),
opts
)
end
@doc """
Python method `DataLoader.from_json`.
## Parameters
- `file_path` (String.t())
- `fields` (term() default: None)
- `input_keys` ({String.t()} default: ())
## Returns
- `list(Dspy.Primitives.ExampleClass.t())`
"""
@spec from_json(SnakeBridge.Ref.t(), String.t(), list(term()), keyword()) ::
{:ok, list(Dspy.Primitives.ExampleClass.t())} | {:error, Snakepit.Error.t()}
def from_json(ref, file_path, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(ref, :from_json, [file_path] ++ List.wrap(args), opts)
end
@doc """
Python method `DataLoader.from_pandas`.
## Parameters
- `df` (term())
- `fields` (term() default: None)
- `input_keys` ({String.t()} default: ())
## Returns
- `list(Dspy.Primitives.ExampleClass.t())`
"""
@spec from_pandas(SnakeBridge.Ref.t(), term(), list(term()), keyword()) ::
{:ok, list(Dspy.Primitives.ExampleClass.t())} | {:error, Snakepit.Error.t()}
def from_pandas(ref, df, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(ref, :from_pandas, [df] ++ List.wrap(args), opts)
end
@doc """
Python method `DataLoader.from_parquet`.
## Parameters
- `file_path` (String.t())
- `fields` (term() default: None)
- `input_keys` ({String.t()} default: ())
## Returns
- `list(Dspy.Primitives.ExampleClass.t())`
"""
@spec from_parquet(SnakeBridge.Ref.t(), String.t(), list(term()), keyword()) ::
{:ok, list(Dspy.Primitives.ExampleClass.t())} | {:error, Snakepit.Error.t()}
def from_parquet(ref, file_path, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(ref, :from_parquet, [file_path] ++ List.wrap(args), opts)
end
@doc """
Python method `DataLoader.from_rm`.
## Parameters
- `num_samples` (integer())
- `fields` (list(String.t()))
- `input_keys` (list(String.t()))
## Returns
- `list(Dspy.Primitives.ExampleClass.t())`
"""
@spec from_rm(SnakeBridge.Ref.t(), integer(), list(String.t()), list(String.t()), keyword()) ::
{:ok, list(Dspy.Primitives.ExampleClass.t())} | {:error, Snakepit.Error.t()}
def from_rm(ref, num_samples, fields, input_keys, opts \\ []) do
SnakeBridge.Runtime.call_method(ref, :from_rm, [num_samples, fields, input_keys], opts)
end
@doc """
Python method `DataLoader.prepare_by_seed`.
## Parameters
- `train_seeds` (term() default: None)
- `train_size` (integer() default: 16)
- `dev_size` (integer() default: 1000)
- `divide_eval_per_seed` (boolean() default: True)
- `eval_seed` (integer() default: 2023)
- `kwargs` (term())
## Returns
- `term()`
"""
@spec prepare_by_seed(SnakeBridge.Ref.t(), list(term()), keyword()) ::
{:ok, term()} | {:error, Snakepit.Error.t()}
def prepare_by_seed(ref, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(ref, :prepare_by_seed, [] ++ List.wrap(args), opts)
end
@doc """
Python method `DataLoader.reset_seeds`.
## Parameters
- `train_seed` (term() default: None)
- `train_size` (term() default: None)
- `eval_seed` (term() default: None)
- `dev_size` (term() default: None)
- `test_size` (term() default: None)
## Returns
- `nil`
"""
@spec reset_seeds(SnakeBridge.Ref.t(), list(term()), keyword()) ::
{:ok, nil} | {:error, Snakepit.Error.t()}
def reset_seeds(ref, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(ref, :reset_seeds, [] ++ List.wrap(args), opts)
end
@doc """
Python method `DataLoader.sample`.
## Parameters
- `dataset` (list(Dspy.Primitives.ExampleClass.t()))
- `n` (integer())
- `args` (term())
- `kwargs` (term())
## Returns
- `list(Dspy.Primitives.ExampleClass.t())`
"""
@spec sample(
SnakeBridge.Ref.t(),
list(Dspy.Primitives.ExampleClass.t()),
integer(),
list(term()),
keyword()
) :: {:ok, list(Dspy.Primitives.ExampleClass.t())} | {:error, Snakepit.Error.t()}
def sample(ref, dataset, n, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(ref, :sample, [dataset, n] ++ List.wrap(args), opts)
end
@doc """
Python method `DataLoader.train_test_split`.
## Parameters
- `dataset` (list(Dspy.Primitives.ExampleClass.t()))
- `train_size` (term() default: 0.75)
- `test_size` (term() default: None)
- `random_state` (term() default: None)
## Returns
- `term()`
"""
@spec train_test_split(
SnakeBridge.Ref.t(),
list(Dspy.Primitives.ExampleClass.t()),
list(term()),
keyword()
) :: {:ok, term()} | {:error, Snakepit.Error.t()}
def train_test_split(ref, dataset, args, opts \\ []) do
{args, opts} = SnakeBridge.Runtime.normalize_args_opts(args, opts)
SnakeBridge.Runtime.call_method(ref, :train_test_split, [dataset] ++ List.wrap(args), opts)
end
@spec dev(SnakeBridge.Ref.t()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
def dev(ref) do
SnakeBridge.Runtime.get_attr(ref, :dev)
end
@spec test(SnakeBridge.Ref.t()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
def test(ref) do
SnakeBridge.Runtime.get_attr(ref, :test)
end
@spec train(SnakeBridge.Ref.t()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
def train(ref) do
SnakeBridge.Runtime.get_attr(ref, :train)
end
end