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Remove reliance on deprecated np symbols

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This commit is contained in:
Francois Chollet 2023-05-31 18:09:25 -07:00
parent 5468ab9497
commit 35d42bfdd2
6 changed files with 18 additions and 32 deletions
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6
keras_core/layers/pooling/average_pooling_test.py
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@ -112,7 +112,7 @@ class AveragePoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
((2,), (2,), "valid", "channels_last"),
)
def test_average_pooling1d(self, pool_size, strides, padding, data_format):
inputs = np.arange(24, dtype=np.float).reshape((2, 3, 4))
inputs = np.arange(24, dtype="float32").reshape((2, 3, 4))
layer = layers.AveragePooling1D(
pool_size=pool_size,
@ -136,7 +136,7 @@ class AveragePoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
((2, 3), (2, 2), "same", "channels_last"),
)
def test_average_pooling2d(self, pool_size, strides, padding, data_format):
inputs = np.arange(300, dtype=np.float).reshape((3, 5, 5, 4))
inputs = np.arange(300, dtype="float32").reshape((3, 5, 5, 4))
layer = layers.AveragePooling2D(
pool_size=pool_size,
@ -161,7 +161,7 @@ class AveragePoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
((2, 3, 2), (2, 2, 1), "valid", "channels_last"),
)
def test_average_pooling3d(self, pool_size, strides, padding, data_format):
inputs = np.arange(240, dtype=np.float).reshape((2, 3, 4, 5, 2))
inputs = np.arange(240, dtype="float32").reshape((2, 3, 4, 5, 2))
layer = layers.AveragePooling3D(
pool_size=pool_size,

10
keras_core/layers/pooling/global_average_pooling_test.py
View File

@ -95,7 +95,7 @@ class GlobalAveragePoolingCorrectnessTest(
("channels_first", False),
)
def test_global_average_pooling1d(self, data_format, keepdims):
inputs = np.arange(24, dtype=np.float).reshape((2, 3, 4))
inputs = np.arange(24, dtype="float32").reshape((2, 3, 4))
layer = layers.GlobalAveragePooling1D(
data_format=data_format,
@ -111,9 +111,9 @@ class GlobalAveragePoolingCorrectnessTest(
self.assertAllClose(outputs, expected)
if data_format == "channels_last":
mask = np.array([[1, 1, 0], [0, 1, 0]], dtype=np.int)
mask = np.array([[1, 1, 0], [0, 1, 0]], dtype="int32")
else:
mask = np.array([[1, 1, 0, 0], [0, 1, 0, 1]], dtype=np.int)
mask = np.array([[1, 1, 0, 0], [0, 1, 0, 1]], dtype="int32")
outputs = layer(inputs, mask)
expected = tf_keras_layer(inputs, mask)
self.assertAllClose(outputs, expected)
@ -124,7 +124,7 @@ class GlobalAveragePoolingCorrectnessTest(
("channels_first", False),
)
def test_global_average_pooling2d(self, data_format, keepdims):
inputs = np.arange(96, dtype=np.float).reshape((2, 3, 4, 4))
inputs = np.arange(96, dtype="float32").reshape((2, 3, 4, 4))
layer = layers.GlobalAveragePooling2D(
data_format=data_format,
@ -145,7 +145,7 @@ class GlobalAveragePoolingCorrectnessTest(
("channels_first", False),
)
def test_global_average_pooling3d(self, data_format, keepdims):
inputs = np.arange(360, dtype=np.float).reshape((2, 3, 3, 5, 4))
inputs = np.arange(360, dtype="float32").reshape((2, 3, 3, 5, 4))
layer = layers.GlobalAveragePooling3D(
data_format=data_format,

6
keras_core/layers/pooling/global_max_pooling_test.py
View File

@ -93,7 +93,7 @@ class GlobalMaxPoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
("channels_first", False),
)
def test_global_max_pooling1d(self, data_format, keepdims):
inputs = np.arange(24, dtype=np.float).reshape((2, 3, 4))
inputs = np.arange(24, dtype="float32").reshape((2, 3, 4))
layer = layers.GlobalMaxPooling1D(
data_format=data_format,
@ -114,7 +114,7 @@ class GlobalMaxPoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
("channels_first", False),
)
def test_global_max_pooling2d(self, data_format, keepdims):
inputs = np.arange(96, dtype=np.float).reshape((2, 3, 4, 4))
inputs = np.arange(96, dtype="float32").reshape((2, 3, 4, 4))
layer = layers.GlobalMaxPooling2D(
data_format=data_format,
@ -135,7 +135,7 @@ class GlobalMaxPoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
("channels_first", False),
)
def test_global_max_pooling3d(self, data_format, keepdims):
inputs = np.arange(360, dtype=np.float).reshape((2, 3, 3, 5, 4))
inputs = np.arange(360, dtype="float32").reshape((2, 3, 3, 5, 4))
layer = layers.GlobalMaxPooling3D(
data_format=data_format,

6
keras_core/layers/pooling/max_pooling_test.py
View File

@ -112,7 +112,7 @@ class MaxPoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
((2,), (2,), "valid", "channels_last"),
)
def test_max_pooling1d(self, pool_size, strides, padding, data_format):
inputs = np.arange(24, dtype=np.float).reshape((2, 3, 4))
inputs = np.arange(24, dtype="float32").reshape((2, 3, 4))
layer = layers.MaxPooling1D(
pool_size=pool_size,
@ -136,7 +136,7 @@ class MaxPoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
((2, 3), (2, 2), "same", "channels_last"),
)
def test_max_pooling2d(self, pool_size, strides, padding, data_format):
inputs = np.arange(300, dtype=np.float).reshape((3, 5, 5, 4))
inputs = np.arange(300, dtype="float32").reshape((3, 5, 5, 4))
layer = layers.MaxPooling2D(
pool_size=pool_size,
@ -161,7 +161,7 @@ class MaxPoolingCorrectnessTest(testing.TestCase, parameterized.TestCase):
((2, 3, 2), (2, 2, 1), "valid", "channels_last"),
)
def test_max_pooling3d(self, pool_size, strides, padding, data_format):
inputs = np.arange(240, dtype=np.float).reshape((2, 3, 4, 5, 2))
inputs = np.arange(240, dtype="float32").reshape((2, 3, 4, 5, 2))
layer = layers.MaxPooling3D(
pool_size=pool_size,

21
keras_core/utils/io_utils.py
View File

@ -6,12 +6,7 @@ from keras_core.api_export import keras_core_export
from keras_core.backend.common import global_state
@keras_core_export(
[
"keras_core.config.enable_interactive_logging",
"keras_core.utils.enable_interactive_logging",
]
)
@keras_core_export("keras_core.config.enable_interactive_logging")
def enable_interactive_logging():
"""Turn on interactive logging.
@ -22,12 +17,7 @@ def enable_interactive_logging():
global_state.set_global_setting("interactive_logging", True)
@keras_core_export(
[
"keras_core.config.disable_interactive_logging",
"keras_core.utils.disable_interactive_logging",
]
)
@keras_core_export("keras_core.config.disable_interactive_logging")
def disable_interactive_logging():
"""Turn off interactive logging.
@ -38,12 +28,7 @@ def disable_interactive_logging():
global_state.set_global_setting("interactive_logging", False)
@keras_core_export(
[
"keras_core.config.is_interactive_logging_enabled",
"keras_core.utils.is_interactive_logging_enabled",
]
)
@keras_core_export("keras_core.config.is_interactive_logging_enabled")
def is_interactive_logging_enabled():
"""Check if interactive logging is enabled.

1
requirements.txt
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@ -14,3 +14,4 @@ absl-py
requests
h5py
rich
build