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_types.py
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_types.py
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# coding=utf-8
# Copyright 2023-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING, List, TypedDict
if TYPE_CHECKING:
from PIL import Image
class ClassificationOutput(TypedDict):
"""Dictionary containing the output of a [`~InferenceClient.audio_classification`] and [`~InferenceClient.image_classification`] task.
Args:
label (`str`):
The label predicted by the model.
score (`float`):
The score of the label predicted by the model.
"""
label: str
score: float
class ConversationalOutputConversation(TypedDict):
"""Dictionary containing the "conversation" part of a [`~InferenceClient.conversational`] task.
Args:
generated_responses (`List[str]`):
A list of the responses from the model.
past_user_inputs (`List[str]`):
A list of the inputs from the user. Must be the same length as `generated_responses`.
"""
generated_responses: List[str]
past_user_inputs: List[str]
class ConversationalOutput(TypedDict):
"""Dictionary containing the output of a [`~InferenceClient.conversational`] task.
Args:
generated_text (`str`):
The last response from the model.
conversation (`ConversationalOutputConversation`):
The past conversation.
warnings (`List[str]`):
A list of warnings associated with the process.
"""
conversation: ConversationalOutputConversation
generated_text: str
warnings: List[str]
class FillMaskOutput(TypedDict):
"""Dictionary containing information about a [`~InferenceClient.fill_mask`] task.
Args:
score (`float`):
The probability of the token.
token (`int`):
The id of the token.
token_str (`str`):
The string representation of the token.
sequence (`str`):
The actual sequence of tokens that ran against the model (may contain special tokens).
"""
score: float
token: int
token_str: str
sequence: str
class ImageSegmentationOutput(TypedDict):
"""Dictionary containing information about a [`~InferenceClient.image_segmentation`] task. In practice, image segmentation returns a
list of `ImageSegmentationOutput` with 1 item per mask.
Args:
label (`str`):
The label corresponding to the mask.
mask (`Image`):
An Image object representing the mask predicted by the model.
score (`float`):
The score associated with the label for this mask.
"""
label: str
mask: "Image"
score: float
class ObjectDetectionOutput(TypedDict):
"""Dictionary containing information about a [`~InferenceClient.object_detection`] task.
Args:
label (`str`):
The label corresponding to the detected object.
box (`dict`):
A dict response of bounding box coordinates of
the detected object: xmin, ymin, xmax, ymax
score (`float`):
The score corresponding to the detected object.
"""
label: str
box: dict
score: float
class QuestionAnsweringOutput(TypedDict):
"""Dictionary containing information about a [`~InferenceClient.question_answering`] task.
Args:
score (`float`):
A float that represents how likely that the answer is correct.
start (`int`):
The index (string wise) of the start of the answer within context.
end (`int`):
The index (string wise) of the end of the answer within context.
answer (`str`):
A string that is the answer within the text.
"""
score: float
start: int
end: int
answer: str
class TableQuestionAnsweringOutput(TypedDict):
"""Dictionary containing information about a [`~InferenceClient.table_question_answering`] task.
Args:
answer (`str`):
The plaintext answer.
coordinates (`List[List[int]]`):
A list of coordinates of the cells referenced in the answer.
cells (`List[int]`):
A list of coordinates of the cells contents.
aggregator (`str`):
The aggregator used to get the answer.
"""
answer: str
coordinates: List[List[int]]
cells: List[List[int]]
aggregator: str
class TokenClassificationOutput(TypedDict):
"""Dictionary containing the output of a [`~InferenceClient.token_classification`] task.
Args:
entity_group (`str`):
The type for the entity being recognized (model specific).
score (`float`):
The score of the label predicted by the model.
word (`str`):
The string that was captured.
start (`int`):
The offset stringwise where the answer is located. Useful to disambiguate if word occurs multiple times.
end (`int`):
The offset stringwise where the answer is located. Useful to disambiguate if word occurs multiple times.
"""
entity_group: str
score: float
word: str
start: int
end: int