Initializer capable of adapting its scale to the shape of weights.
With distribution="normal", samples are drawn from a truncated normal
distribution centered on zero, with stddev = sqrt(scale / n) where n is:
number of input units in the weight tensor, if mode = "fan_in"
number of output units, if mode = "fan_out"
average of the numbers of input and output units, if mode = "fan_avg"
initializer_variance_scaling(
scale = 1,
mode = c("fan_in", "fan_out", "fan_avg"),
distribution = c("normal", "uniform", "truncated_normal", "untruncated_normal"),
seed = NULL
)scale |
Scaling factor (positive float). |
mode |
One of "fan_in", "fan_out", "fan_avg". |
distribution |
One of "truncated_normal", "untruncated_normal" and "uniform". For backward compatibility, "normal" will be accepted and converted to "untruncated_normal". |
seed |
Integer used to seed the random generator. |
With distribution="uniform", samples are drawn from a uniform distribution
within -limit, limit, with limit = sqrt(3 * scale / n).
Other initializers:
initializer_constant(),
initializer_glorot_normal(),
initializer_glorot_uniform(),
initializer_he_normal(),
initializer_he_uniform(),
initializer_identity(),
initializer_lecun_normal(),
initializer_lecun_uniform(),
initializer_ones(),
initializer_orthogonal(),
initializer_random_normal(),
initializer_random_uniform(),
initializer_truncated_normal(),
initializer_zeros()
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