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Increase FARM to Version 0.6.2 (#755)

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* Increase farm version

* Fix test
This commit is contained in:
Timo Moeller 2021-01-21 10:15:41 +01:00 committed by GitHub
parent 725c03220f
commit 7522d2d1b0
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5 changed files with 12 additions and 6 deletions
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2
haystack/reader/farm.py
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@ -508,7 +508,7 @@ class FARMReader(BaseReader):
# Create DataLoader that can be passed to the Evaluator
tic = perf_counter()
indices = range(len(farm_input))
dataset, tensor_names = self.inferencer.processor.dataset_from_dicts(farm_input, indices=indices)
dataset, tensor_names, problematic_ids = self.inferencer.processor.dataset_from_dicts(farm_input, indices=indices)
data_loader = NamedDataLoader(dataset=dataset, batch_size=self.inferencer.batch_size, tensor_names=tensor_names)
evaluator = Evaluator(data_loader=data_loader, tasks=self.inferencer.processor.tasks, device=device)

2
haystack/retriever/dense.py
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@ -179,7 +179,7 @@ class DensePassageRetriever(BaseRetriever):
"""
dataset, tensor_names, baskets = self.processor.dataset_from_dicts(
dataset, tensor_names, problematic_ids, baskets = self.processor.dataset_from_dicts(
dicts, indices=[i for i in range(len(dicts))], return_baskets=True
)

8
haystack/summarizer/transformers.py
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@ -2,6 +2,8 @@ import logging
from typing import Any, Dict, List, Optional
from transformers import pipeline
from transformers.models.auto.modeling_auto import AutoModelForSeq2SeqLM
from transformers import AutoTokenizer
from haystack import Document
from haystack.summarizer.base import BaseSummarizer
@ -73,7 +75,11 @@ class TransformersSummarizer(BaseSummarizer):
into a single text. This separator appears between those subsequent docs.
"""
self.summarizer = pipeline("summarization", model=model_name_or_path, tokenizer=tokenizer, device=use_gpu)
# TODO AutoModelForSeq2SeqLM is only necessary with transformers==4.1.1, with newer versions use the pipeline directly
if tokenizer is None:
tokenizer = model_name_or_path
model = AutoModelForSeq2SeqLM.from_pretrained(pretrained_model_name_or_path=model_name_or_path)
self.summarizer = pipeline("summarization", model=model, tokenizer=tokenizer, device=use_gpu)
self.max_length = max_length
self.min_length = min_length
self.clean_up_tokenization_spaces = clean_up_tokenization_spaces

2
requirements.txt
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@ -1,4 +1,4 @@
farm==0.5.0
farm==0.6.2
--find-links=https://download.pytorch.org/whl/torch_stable.html
fastapi
uvicorn

4
test/test_dpr_retriever.py
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@ -113,6 +113,6 @@ def test_dpr_saving_and_loading(retriever, document_store):
assert loaded_retriever.query_tokenizer.do_lower_case == True
assert loaded_retriever.passage_tokenizer.vocab_size == 30522
assert loaded_retriever.query_tokenizer.vocab_size == 30522
assert loaded_retriever.passage_tokenizer.max_len == 512
assert loaded_retriever.query_tokenizer.max_len == 512
assert loaded_retriever.passage_tokenizer.model_max_length == 512
assert loaded_retriever.query_tokenizer.model_max_length == 512