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for _ in range(100): |
# Without `clear_session()`, each iteration of this loop will |
# slightly increase the size of the global state managed by Keras |
model = tf.keras.Sequential([tf.keras.layers.Dense(10) for _ in range(10)]) |
for _ in range(100): |
# With `clear_session()` called at the beginning, |
# Keras starts with a blank state at each iteration |
# and memory consumption is constant over time. |
tf.keras.backend.clear_session() |
model = tf.keras.Sequential([tf.keras.layers.Dense(10) for _ in range(10)]) |
Example 2: resetting the layer name generation counter |
>>> import tensorflow as tf |
>>> layers = [tf.keras.layers.Dense(10) for _ in range(10)] |
>>> new_layer = tf.keras.layers.Dense(10) |
>>> print(new_layer.name) |
dense_10 |
>>> tf.keras.backend.set_learning_phase(1) |
>>> print(tf.keras.backend.learning_phase()) |
1 |
>>> tf.keras.backend.clear_session() |
>>> new_layer = tf.keras.layers.Dense(10) |
>>> print(new_layer.name) |
dense |
floatx function |
tf.keras.backend.floatx() |
Returns the default float type, as a string. |
E.g. 'float16', 'float32', 'float64'. |
Returns |
String, the current default float type. |
Example |
>>> tf.keras.backend.floatx() |
'float32' |
set_floatx function |
tf.keras.backend.set_floatx(value) |
Sets the default float type. |
Note: It is not recommended to set this to float16 for training, as this will likely cause numeric stability issues. Instead, mixed precision, which is using a mix of float16 and float32, can be used by calling tf.keras.mixed_precision.experimental.set_policy('mixed_float16'). See the mixed precision guide for details. |
Arguments |
value: String; 'float16', 'float32', or 'float64'. |
Example |
>>> tf.keras.backend.floatx() |
'float32' |
>>> tf.keras.backend.set_floatx('float64') |
>>> tf.keras.backend.floatx() |
'float64' |
>>> tf.keras.backend.set_floatx('float32') |
Raises |
ValueError: In case of invalid value. |
image_data_format function |
tf.keras.backend.image_data_format() |
Returns the default image data format convention. |
Returns |
A string, either 'channels_first' or 'channels_last' |
Example |
>>> tf.keras.backend.image_data_format() |
'channels_last' |
set_image_data_format function |
tf.keras.backend.set_image_data_format(data_format) |
Sets the value of the image data format convention. |
Arguments |
data_format: string. 'channels_first' or 'channels_last'. |
Example |
>>> tf.keras.backend.image_data_format() |
'channels_last' |
>>> tf.keras.backend.set_image_data_format('channels_first') |
>>> tf.keras.backend.image_data_format() |
'channels_first' |
>>> tf.keras.backend.set_image_data_format('channels_last') |
Raises |
ValueError: In case of invalid data_format value. |
epsilon function |