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Update asserts to avoid deprecated methods #2053

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Jan 21, 2025
Merged

Update asserts to avoid deprecated methods #2053

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2 changes: 1 addition & 1 deletion keras_hub/src/layers/preprocessing/masked_lm_mask_generator_test.py
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Expand Up @@ -148,7 +148,7 @@ def test_config(self):
"vocabulary_size": self.vocabulary_size,
"unselectable_token_ids": unselectable_token_ids,
}
self.assertDictContainsSubset(expected_config, config)
self.assertEqual(config, {**config, **expected_config})

# Test cloned masked_lm_masker can be run.
cloned_masked_lm_masker = MaskedLMMaskGenerator.from_config(config)
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4 changes: 2 additions & 2 deletions keras_hub/src/models/efficientnet/cba_test.py
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Expand Up @@ -10,13 +10,13 @@ def test_same_input_output_shapes(self):
layer = CBABlock(input_filters=32, output_filters=32)

output = layer(inputs)
self.assertEquals(output.shape, (1, 64, 64, 32))
self.assertEqual(output.shape, (1, 64, 64, 32))
self.assertLen(output, 1)

def test_different_input_output_shapes(self):
inputs = keras.random.normal(shape=(1, 64, 64, 32), dtype="float32")
layer = CBABlock(input_filters=32, output_filters=48)

output = layer(inputs)
self.assertEquals(output.shape, (1, 64, 64, 48))
self.assertEqual(output.shape, (1, 64, 64, 48))
self.assertLen(output, 1)
12 changes: 6 additions & 6 deletions keras_hub/src/models/efficientnet/efficientnet_backbone_test.py
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Expand Up @@ -87,24 +87,24 @@ def test_feature_pyramid_outputs(self):
height = width = 256
outputs = model(keras.ops.ones(shape=(batch_size, height, width, 3)))
levels = ["P1", "P2", "P3", "P4", "P5"]
self.assertEquals(list(outputs.keys()), levels)
self.assertEquals(
self.assertEqual(list(outputs.keys()), levels)
self.assertEqual(
outputs["P1"].shape,
(batch_size, height // 2**1, width // 2**1, 24),
)
self.assertEquals(
self.assertEqual(
outputs["P2"].shape,
(batch_size, height // 2**2, width // 2**2, 48),
)
self.assertEquals(
self.assertEqual(
outputs["P3"].shape,
(batch_size, height // 2**3, width // 2**3, 64),
)
self.assertEquals(
self.assertEqual(
outputs["P4"].shape,
(batch_size, height // 2**4, width // 2**4, 160),
)
self.assertEquals(
self.assertEqual(
outputs["P5"].shape,
(batch_size, height // 2**5, width // 2**5, 1280),
)
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6 changes: 3 additions & 3 deletions keras_hub/src/models/efficientnet/fusedmbconv_test.py
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Expand Up @@ -10,15 +10,15 @@ def test_same_input_output_shapes(self):
layer = FusedMBConvBlock(input_filters=32, output_filters=32)

output = layer(inputs)
self.assertEquals(output.shape, (1, 64, 64, 32))
self.assertEqual(output.shape, (1, 64, 64, 32))
self.assertLen(output, 1)

def test_different_input_output_shapes(self):
inputs = keras.random.normal(shape=(1, 64, 64, 32), dtype="float32")
layer = FusedMBConvBlock(input_filters=32, output_filters=48)

output = layer(inputs)
self.assertEquals(output.shape, (1, 64, 64, 48))
self.assertEqual(output.shape, (1, 64, 64, 48))
self.assertLen(output, 1)

def test_squeeze_excitation_ratio(self):
Expand All @@ -28,5 +28,5 @@ def test_squeeze_excitation_ratio(self):
)

output = layer(inputs)
self.assertEquals(output.shape, (1, 64, 64, 48))
self.assertEqual(output.shape, (1, 64, 64, 48))
self.assertLen(output, 1)
6 changes: 3 additions & 3 deletions keras_hub/src/models/efficientnet/mbconv_test.py
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Expand Up @@ -10,21 +10,21 @@ def test_same_input_output_shapes(self):
layer = MBConvBlock(input_filters=32, output_filters=32)

output = layer(inputs)
self.assertEquals(output.shape, (1, 64, 64, 32))
self.assertEqual(output.shape, (1, 64, 64, 32))
self.assertLen(output, 1)

def test_different_input_output_shapes(self):
inputs = keras.random.normal(shape=(1, 64, 64, 32), dtype="float32")
layer = MBConvBlock(input_filters=32, output_filters=48)

output = layer(inputs)
self.assertEquals(output.shape, (1, 64, 64, 48))
self.assertEqual(output.shape, (1, 64, 64, 48))
self.assertLen(output, 1)

def test_squeeze_excitation_ratio(self):
inputs = keras.random.normal(shape=(1, 64, 64, 32), dtype="float32")
layer = MBConvBlock(input_filters=32, output_filters=48, se_ratio=0.25)

output = layer(inputs)
self.assertEquals(output.shape, (1, 64, 64, 48))
self.assertEqual(output.shape, (1, 64, 64, 48))
self.assertLen(output, 1)
2 changes: 1 addition & 1 deletion keras_hub/src/tests/test_case.py
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Expand Up @@ -479,7 +479,7 @@ def run_backbone_test(
# Check name maps to classname.
name = re.sub("(.)([A-Z][a-z]+)", r"\1_\2", cls.__name__)
name = re.sub("([a-z])([A-Z])", r"\1_\2", name).lower()
self.assertRegexpMatches(backbone.name, name)
self.assertRegex(backbone.name, name)

# Check mixed precision.
if run_mixed_precision_check:
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