Exemplos de DefaultSummarizer em Python

Exemplo n.º 1

Arquivo: exp10_run.py Projeto: mirandrom/HipoRank

]
SIMILARITIES = [
    ("cos", CosSimilarity, {"threshold": 0.3}),
]
DIRECTIONS = [
    ("edge", EdgeBased, {}),
    ("order", OrderBased, {}),
]

SCORERS = [
    ("add_f=0.0_b=1.0_s=1.0", AddScorer, {}),
]



SUMMARIZERS = [DefaultSummarizer(num_words=200)]

experiment_time = int(time.time())
results_path = Path(f"results/exp10")

for embedder_id, embedder, embedder_args in EMBEDDERS:
    Embedder = embedder(**embedder_args)
    for Summarizer, (dataset_id, dataset, dataset_args) in zip(SUMMARIZERS, DATASETS):
        DataSet = dataset(**dataset_args)
        docs = list(DataSet)
        if DEBUG:
            docs = docs[:5]
        print(f"embedding dataset {dataset_id} with {embedder_id}")
        embeds = [Embedder.get_embeddings(doc) for doc in tqdm(docs)]
        for similarity_id, similarity, similarity_args in SIMILARITIES:
            Similarity = similarity(**similarity_args)

Exemplo n.º 2

Arquivo: exp4_run.py Projeto: mirandrom/HipoRank

    #      {"model": "roberta-large-nli-mean-tokens"}
    #     ),
]
SIMILARITIES = [
    ("cos", CosSimilarity, {}),
]
DIRECTIONS = [
    ("edge", EdgeBased, {}),
]

SCORERS = [
    ("add_f=0.0_b=1.0_s=1.0", AddScorer, {}),
]


Summarizer = DefaultSummarizer(num_words=220)

experiment_time = int(time.time())
# results_path = Path(f"results/{experiment_time}")
results_path = Path(f"results/exp4")

for embedder_id, embedder, embedder_args in EMBEDDERS:
    Embedder = embedder(**embedder_args)
    for dataset_id, dataset, dataset_args in DATASETS:
        DataSet = dataset(**dataset_args)
        docs = list(DataSet)
        if DEBUG:
            docs = docs[:5]
        print(f"embedding dataset {dataset_id} with {embedder_id}")
        embeds = [Embedder.get_embeddings(doc) for doc in tqdm(docs)]
        for similarity_id, similarity, similarity_args in SIMILARITIES:

Exemplo n.º 3

    #      {"model": "roberta-large-nli-mean-tokens"}
    #     ),
]
SIMILARITIES = [
    ("cos", CosSimilarity, {}),
]
DIRECTIONS = [
    ("order", OrderBased, {}),
]

SCORERS = [
    ("add_f=0.0_b=1.0_s=1.0", AddScorer, {}),
]

SUMMARIZERS = [
    DefaultSummarizer(num_words=200),
    DefaultSummarizer(num_words=220)
]

experiment_time = int(time.time())
results_path = Path(f"results/exp8")

for embedder_id, embedder, embedder_args in EMBEDDERS:
    Embedder = embedder(**embedder_args)
    for Summarizer, (dataset_id, dataset,
                     dataset_args) in zip(SUMMARIZERS, DATASETS):
        DataSet = dataset(**dataset_args)
        docs = list(DataSet)
        if DEBUG:
            docs = docs[:5]
        print(f"embedding dataset {dataset_id} with {embedder_id}")

Exemplo n.º 4

Arquivo: exp3_run.py Projeto: mirandrom/HipoRank

    }),
]
SIMILARITIES = [
    ("cos", CosSimilarity, {}),
]
DIRECTIONS = [
    ("edge", EdgeBased, {}),
]

SCORERS = [
    ("add_f=0.0_b=1.0_s=0.5", AddScorer, {
        "section_weight": 0.5
    }),
]

Summarizer = DefaultSummarizer()

experiment_time = int(time.time())
results_path = Path(f"results/exp3")

for embedder_id, embedder, embedder_args in EMBEDDERS:
    Embedder = embedder(**embedder_args)
    for dataset_id, dataset, dataset_args in DATASETS:
        DataSet = dataset(**dataset_args)
        docs = list(DataSet)
        if DEBUG:
            docs = docs[:5]
        print(f"embedding dataset {dataset_id} with {embedder_id}")
        embeds = [Embedder.get_embeddings(doc) for doc in tqdm(docs)]
        for similarity_id, similarity, similarity_args in SIMILARITIES:
            Similarity = similarity(**similarity_args)