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Update TF(Vision)EncoderDecoderModel PT/TF equivalence tests (#18073)

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Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2022-07-18 15:29:14 +02:00
committed by GitHub
parent cb19c2afdc
commit 6561fbcc6e
4 changed files with 394 additions and 128 deletions
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6
tests/test_modeling_common.py
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@@ -1616,7 +1616,7 @@ class ModelTesterMixin:
# Copied from tests.test_modeling_tf_common.TFModelTesterMixin.check_pt_tf_outputs
def check_pt_tf_outputs(self, tf_outputs, pt_outputs, model_class, tol=1e-5, name="outputs", attributes=None):
"""Check the outputs from PyTorch and TensorFlow models are closed enough. Checks are done in a recursive way.
"""Check the outputs from PyTorch and TensorFlow models are close enough. Checks are done in a recursive way.
Args:
model_class: The class of the model that is currently testing. For example, `TFBertModel`,
@@ -1642,8 +1642,8 @@ class ModelTesterMixin:
# TODO: remove this method and this line after issues are fixed
tf_outputs, pt_outputs = self._postprocessing_to_ignore_test_cases(tf_outputs, pt_outputs, model_class)
tf_keys = tuple([k for k, v in tf_outputs.items() if v is not None])
pt_keys = tuple([k for k, v in pt_outputs.items() if v is not None])
tf_keys = [k for k, v in tf_outputs.items() if v is not None]
pt_keys = [k for k, v in pt_outputs.items() if v is not None]
self.assertEqual(tf_keys, pt_keys, f"{name}: Output keys differ between TF and PyTorch")