TensorFlow 1 version
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View source on GitHub
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Sets the value of a variable, from a Numpy array.
tf.keras.backend.set_value(
x, value
)
backend.set_value is the compliment of backend.get_value, and provides
a generic interface for assigning to variables while abstracting away the
differences between TensorFlow 1.x and 2.x semantics.
K = tf.keras.backend # Common keras conventionv = K.variable(1.)
# reassignK.set_value(v, 2.)print(K.get_value(v))2.0
# incrementK.set_value(v, K.get_value(v) + 1)print(K.get_value(v))3.0
Variable semantics in TensorFlow 2 are eager execution friendly. The above code is roughly equivalent to:
v = tf.Variable(1.)v.assign(2.)print(v.numpy())2.0
v.assign_add(1.)print(v.numpy())3.0
Arguments | |
|---|---|
x
|
Variable to set to a new value. |
value
|
Value to set the tensor to, as a Numpy array (of the same shape). |
TensorFlow 1 version
View source on GitHub