SUMIN/HuggingFace_transformer
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Restore TF embeddings and attention layers to their previous version (#9890)

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* Refacto BERT

* Restore all the concerned models

* Remove print

* Update template

* Apply Sylvain's and Morgan's comments

* Fix cast

* Put the cast inside call

* Remove cond in ebds

* Fix funnel

* Restore previous dot product (attention_scores) computation

* Add ConvBERT and BART

* Make all the S2S models ONNX compliant

* Fix test

* Fix check copies
This commit is contained in:
Julien Plu
2021-02-08 12:36:30 +01:00
committed by GitHub
parent 8bb52bd240
commit 31563e056d
20 changed files with 754 additions and 1966 deletions
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10
tests/test_modeling_tf_common.py
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@@ -866,7 +866,8 @@ class TFModelTesterMixin:
for model_class in self.all_model_classes:
model = model_class(config)
inputs = copy.deepcopy(self._prepare_for_class(inputs_dict, model_class))
inputs = copy.deepcopy(inputs_dict)
if not self.is_encoder_decoder:
input_ids = inputs["input_ids"]
del inputs["input_ids"]
@@ -882,6 +883,8 @@ class TFModelTesterMixin:
inputs["inputs_embeds"] = model.get_input_embeddings()(encoder_input_ids)
inputs["decoder_inputs_embeds"] = model.get_input_embeddings()(decoder_input_ids)
inputs = self._prepare_for_class(inputs, model_class)
model(inputs)
def test_graph_mode_with_inputs_embeds(self):
@@ -890,7 +893,8 @@ class TFModelTesterMixin:
for model_class in self.all_model_classes:
model = model_class(config)
inputs = copy.deepcopy(self._prepare_for_class(inputs_dict, model_class))
inputs = copy.deepcopy(inputs_dict)
if not self.is_encoder_decoder:
input_ids = inputs["input_ids"]
del inputs["input_ids"]
@@ -906,6 +910,8 @@ class TFModelTesterMixin:
inputs["inputs_embeds"] = model.get_input_embeddings()(encoder_input_ids)
inputs["decoder_inputs_embeds"] = model.get_input_embeddings()(decoder_input_ids)
inputs = self._prepare_for_class(inputs, model_class)
@tf.function
def run_in_graph_mode():
return model(inputs)