# Inference code generated from the JSON schema spec in @huggingface/tasks.
#
# See:
#   - script: https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-codegen.ts
#   - specs:  https://github.com/huggingface/huggingface.js/tree/main/packages/tasks/src/tasks.
from typing import Any, Literal, Optional

from .base import BaseInferenceType, dataclass_with_extra


VideoClassificationOutputTransform = Literal["sigmoid", "softmax", "none"]


@dataclass_with_extra
class VideoClassificationParameters(BaseInferenceType):
    """Additional inference parameters for Video Classification"""

    frame_sampling_rate: int | None = None
    """The sampling rate used to select frames from the video."""
    function_to_apply: Optional["VideoClassificationOutputTransform"] = None
    """The function to apply to the model outputs in order to retrieve the scores."""
    num_frames: int | None = None
    """The number of sampled frames to consider for classification."""
    top_k: int | None = None
    """When specified, limits the output to the top K most probable classes."""


@dataclass_with_extra
class VideoClassificationInput(BaseInferenceType):
    """Inputs for Video Classification inference"""

    inputs: Any
    """The input video data"""
    parameters: VideoClassificationParameters | None = None
    """Additional inference parameters for Video Classification"""


@dataclass_with_extra
class VideoClassificationOutputElement(BaseInferenceType):
    """Outputs of inference for the Video Classification task"""

    label: str
    """The predicted class label."""
    score: float
    """The corresponding probability."""