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View source on GitHub |
Outputs random values from a truncated normal distribution.
tf.random.stateless_parameterized_truncated_normal(
shape, seed, means=0.0, stddevs=1.0, minvals=-2.0, maxvals=2.0, name=None
)
The generated values follow a normal distribution with specified mean and standard deviation, except that values whose magnitude is more than 2 standard deviations from the mean are dropped and re-picked.
Examples:
Sample from a Truncated normal, with deferring shape parameters that broadcast.
means = 0.
stddevs = tf.math.exp(tf.random.uniform(shape=[2, 3]))
minvals = [-1., -2., -1000.]
maxvals = [[10000.], [1.]]
y = tf.random.stateless_parameterized_truncated_normal(
shape=[10, 2, 3], seed=[7, 17],
means=means, stddevs=stddevs, minvals=minvals, maxvals=maxvals)
y.shape
TensorShape([10, 2, 3])
Returns | |
---|---|
A tensor of the specified shape filled with random truncated normal values. |