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# see also: https://github.com/hjacobs/connexion-example
swagger: '2.0'
info:
title: BERT-viz API
version: "0.0.1"
consumes:
- application/json
produces:
- application/json
basePath: /api
# ===============================================================================
## DEFINE API ##
# ===============================================================================
paths:
/get-model-details:
get:
tags: [All]
operationId: main.get_model_details
summary: Get necessary information about the model, such as number of layers and heads
parameters:
- name: model
description: Short string representing pretrained model, such as 'bert-base-uncased'
in: query
type: string
responses:
200:
description: Returns information about the model
/attend+meta:
get:
tags: [All]
operationId: main.get_attentions_and_preds
summary: Get the attention information, BERT Embeddings, and spacy meta info for an input sentence
parameters:
- name: model
description: Which pretrained transformer information is requested from
in: query
type: string
- name: sentence
description: Sentence to analyze
in: query
type: string
- name: layer
description: Layer to get attentions at
in: query
type: number
responses:
200:
description: Returns attentions, embeddings, and metadata
/update-mask:
post:
tags: [All]
operationId: main.update_masked_attention
summary: Get the masked attention information of tokens given indices to mask
parameters:
- name: payload
description: Main contents
in: body
schema:
$ref: '#/definitions/maskPayload'
responses:
200:
description: Update BERT's masked behavior for passed tokens
definitions:
maskPayload:
type: object
properties:
model:
type: string
description: Which model to get results from
tokens:
type: array
items:
type: string
description: Main sentence tokens to analyze
sentence:
type: string
description: The original sentence the tokens came from, for extracting metadata
mask:
type: array
items:
type: number
description: Indices of tokens to mask
layer:
type: number
description: Layer to get results for
required:
- model
- tokens
- sentence
- mask
- layer |