Reorganize repo (#8580)

* Put models in subfolders

* Styling

* Fix imports in tests

* More fixes in test imports

* Sneaky hidden imports

* Fix imports in doc files

* More sneaky imports

* Finish fixing tests

* Fix examples

* Fix path for copies

* More fixes for examples

* Fix dummy files

* More fixes for example

* More model import fixes

* Is this why you're unhappy GitHub?

* Fix imports in conver command
This commit is contained in:
Sylvain Gugger
2020-11-16 21:43:42 -05:00
committed by GitHub
parent 901507335f
commit c89bdfbe72
381 changed files with 2651 additions and 1571 deletions

View File

@@ -25,6 +25,9 @@ import numpy as np
from transformers import BartTokenizer, T5Tokenizer
from transformers.file_utils import cached_property, is_datasets_available, is_faiss_available, is_torch_available
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.tokenization_dpr import DPRQuestionEncoderTokenizer
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
@@ -33,9 +36,6 @@ from transformers.testing_utils import (
slow,
torch_device,
)
from transformers.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.tokenization_dpr import DPRQuestionEncoderTokenizer
from transformers.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from .test_modeling_bart import ModelTester as BartModelTester
from .test_modeling_dpr import DPRModelTester
@@ -205,7 +205,7 @@ class RagTestMixin:
)
dataset.add_faiss_index("embeddings", string_factory="Flat", metric_type=faiss.METRIC_INNER_PRODUCT)
tokenizer = self.bart_tokenizer if config.generator.model_type == "bart" else self.t5_tokenizer
with patch("transformers.retrieval_rag.load_dataset") as mock_load_dataset:
with patch("transformers.models.rag.retrieval_rag.load_dataset") as mock_load_dataset:
mock_load_dataset.return_value = dataset
retriever = RagRetriever(
config,