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Initializer that generates a truncated normal distribution.
These values are similar to values from a `random_normal_initializer`
except that values more than two standard deviations from the mean
are discarded and re-drawn. This is the recommended initializer for
neural network weights and filters.
Args:
mean: a python scalar or a scalar tensor. Mean of the random values
to generate.
stddev: a python scalar or a scalar tensor. Standard deviation of the
random values to generate.
seed: A Python integer. Used to create random seeds. See
[`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
for behavior.
dtype: The data type. Only floating point types are supported.
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#### `tf.truncated_normal_initializer.__call__(shape, dtype=None, partition_info=None)` {#truncated_normal_initializer.__call__}
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#### `tf.truncated_normal_initializer.__init__(mean=0.0, stddev=1.0, seed=None, dtype=tf.float32)` {#truncated_normal_initializer.__init__}
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