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using multi_gpu consistently (#8446)

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* s|multiple_gpu|multi_gpu|g; s|multigpu|multi_gpu|g'

* doc
This commit is contained in:
Stas Bekman
2020-11-10 10:23:58 -08:00
committed by GitHub
parent b93569457f
commit 02bdfc0251
22 changed files with 117 additions and 117 deletions
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8
examples/rag/test_distributed_retriever.py
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@@ -16,7 +16,7 @@ from transformers.configuration_dpr import DPRConfig
from transformers.configuration_rag import RagConfig
from transformers.file_utils import is_datasets_available, is_faiss_available, is_psutil_available, is_torch_available
from transformers.retrieval_rag import CustomHFIndex
from transformers.testing_utils import require_torch_non_multigpu_but_fix_me
from transformers.testing_utils import require_torch_non_multi_gpu_but_fix_me
from transformers.tokenization_bart import BartTokenizer
from transformers.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.tokenization_dpr import DPRQuestionEncoderTokenizer
@@ -179,7 +179,7 @@ class RagRetrieverTest(TestCase):
retriever.init_retrieval(port)
return retriever
@require_torch_non_multigpu_but_fix_me
@require_torch_non_multi_gpu_but_fix_me
def test_pytorch_distributed_retriever_retrieve(self):
n_docs = 1
retriever = self.get_dummy_pytorch_distributed_retriever(init_retrieval=True)
@@ -195,7 +195,7 @@ class RagRetrieverTest(TestCase):
self.assertEqual(doc_dicts[1]["id"][0], "0") # max inner product is reached with first doc
self.assertListEqual(doc_ids.tolist(), [[1], [0]])
@require_torch_non_multigpu_but_fix_me
@require_torch_non_multi_gpu_but_fix_me
def test_custom_hf_index_retriever_retrieve(self):
n_docs = 1
retriever = self.get_dummy_custom_hf_index_retriever(init_retrieval=True, from_disk=False)
@@ -211,7 +211,7 @@ class RagRetrieverTest(TestCase):
self.assertEqual(doc_dicts[1]["id"][0], "0") # max inner product is reached with first doc
self.assertListEqual(doc_ids.tolist(), [[1], [0]])
@require_torch_non_multigpu_but_fix_me
@require_torch_non_multi_gpu_but_fix_me
def test_custom_pytorch_distributed_retriever_retrieve_from_disk(self):
n_docs = 1
retriever = self.get_dummy_custom_hf_index_retriever(init_retrieval=True, from_disk=True)