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class Sampling(layers.Layer):

"""Uses (mean, log_var) to sample z, the vector encoding a digit."""

def call(self, inputs):

mean, log_var = inputs

batch = tf.shape(mean)[0]

dim = tf.shape(mean)[1]

return mean + tf.exp(0.5 * log_var) * epsilon

class Sampling(layers.Layer):

"""Uses (mean, log_var) to sample z, the vector encoding a digit."""

def call(self, inputs):

mean, log_var = inputs

batch = tf.shape(mean)[0]

dim = tf.shape(mean)[1]

return mean + tf.exp(0.5 * log_var) * epsilon

class Sampling(layers.Layer):

"""Uses (mean, log_var) to sample z, the vector encoding a digit."""

def call(self, inputs):

mean, log_var = inputs

batch = tf.shape(mean)[0]

dim = tf.shape(mean)[1]

return mean + tf.exp(0.5 * log_var) * epsilon

Real-Time Grounding

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Security

Efficiency

Speed

Accuracy

Status:

Updating:

Security

Efficiency

Speed

Accuracy

Status:

Updating:

Security

Efficiency

Speed

Accuracy

Status:

Updating:

Abstention Logic

Prevents unreliable results from going live

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