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Ci test tf super slow (#8007)

Browse Source 
* Test TF GPU CI

* Change cache

* Fix missing torch requirement

* Fix some model tests


Style

* LXMERT

* MobileBERT

* Longformer skip test

* XLNet

* The rest of the tests

* RAG goes OOM in multi gpu setup

* YAML test files

* Last fixes

* Skip doctests

* Fill mask tests

* Yaml files

* Last test fix

* Style

* Update cache

* Change ONNX tests to slow + use tiny model
This commit is contained in:
Lysandre Debut
2020-10-30 14:25:48 +00:00
committed by GitHub
parent 7e36deec7a
commit 10f8c63620
25 changed files with 562 additions and 126 deletions
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10
tests/test_onnx.py
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@@ -95,26 +95,28 @@ class OnnxExportTestCase(unittest.TestCase):
@require_torch
@require_tokenizers
@slow
def test_infer_dynamic_axis_pytorch(self):
"""
Validate the dynamic axis generated for each parameters are correct
"""
from transformers import BertModel
model = BertModel(BertConfig.from_pretrained("bert-base-cased"))
tokenizer = BertTokenizerFast.from_pretrained("bert-base-cased")
model = BertModel(BertConfig.from_pretrained("lysandre/tiny-bert-random"))
tokenizer = BertTokenizerFast.from_pretrained("lysandre/tiny-bert-random")
self._test_infer_dynamic_axis(model, tokenizer, "pt")
@require_tf
@require_tokenizers
@slow
def test_infer_dynamic_axis_tf(self):
"""
Validate the dynamic axis generated for each parameters are correct
"""
from transformers import TFBertModel
model = TFBertModel(BertConfig.from_pretrained("bert-base-cased"))
tokenizer = BertTokenizerFast.from_pretrained("bert-base-cased")
model = TFBertModel(BertConfig.from_pretrained("lysandre/tiny-bert-random"))
tokenizer = BertTokenizerFast.from_pretrained("lysandre/tiny-bert-random")
self._test_infer_dynamic_axis(model, tokenizer, "tf")
def _test_infer_dynamic_axis(self, model, tokenizer, framework):