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Speed up TF tests by reducing hidden layer counts (#24595)

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* hidden layers, huh, what are they good for (absolutely nothing)

* Some tests break with 1 hidden layer, use 2

* Use 1 hidden layer in a few slow models

* Use num_hidden_layers=2 everywhere

* Slightly higher tol for groupvit

* Slightly higher tol for groupvit
This commit is contained in:
Matt
2023-06-30 16:30:33 +01:00
committed by GitHub
parent 3441ad7d43
commit 134caef31a
47 changed files with 67 additions and 85 deletions
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14
tests/models/groupvit/test_modeling_tf_groupvit.py
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@@ -150,6 +150,10 @@ class TFGroupViTVisionModelTest(TFModelTesterMixin, unittest.TestCase):
test_head_masking = False
test_onnx = False
def check_pt_tf_outputs(self, tf_outputs, pt_outputs, model_class, tol=1e-4, name="outputs", attributes=None):
# We override with a slightly higher tol value, as this model tends to diverge a bit more
super().check_pt_tf_outputs(tf_outputs, pt_outputs, model_class, tol, name, attributes)
def setUp(self):
self.model_tester = TFGroupViTVisionModelTester(self)
self.config_tester = ConfigTester(
@@ -381,7 +385,7 @@ class TFGroupViTTextModelTester:
use_labels=True,
vocab_size=99,
hidden_size=32,
num_hidden_layers=5,
num_hidden_layers=2,
num_attention_heads=4,
intermediate_size=37,
dropout=0.1,
@@ -459,6 +463,10 @@ class TFGroupViTTextModelTest(TFModelTesterMixin, unittest.TestCase):
test_head_masking = False
test_onnx = False
def check_pt_tf_outputs(self, tf_outputs, pt_outputs, model_class, tol=1e-4, name="outputs", attributes=None):
# We override with a slightly higher tol value, as this model tends to diverge a bit more
super().check_pt_tf_outputs(tf_outputs, pt_outputs, model_class, tol, name, attributes)
def setUp(self):
self.model_tester = TFGroupViTTextModelTester(self)
self.config_tester = ConfigTester(self, config_class=GroupViTTextConfig, hidden_size=37)
@@ -581,6 +589,10 @@ class TFGroupViTModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.Test
test_attention_outputs = False
test_onnx = False
def check_pt_tf_outputs(self, tf_outputs, pt_outputs, model_class, tol=1e-4, name="outputs", attributes=None):
# We override with a slightly higher tol value, as this model tends to diverge a bit more
super().check_pt_tf_outputs(tf_outputs, pt_outputs, model_class, tol, name, attributes)
def setUp(self):
self.model_tester = TFGroupViTModelTester(self)