Normalizes x by mean and variance. — op_batch_normalization • keras3

This op is typically used by the batch normalization step in a neural network. It normalizes the input tensor along the given axis.

Usage

op_batch_normalization(
  x,
  mean,
  variance,
  axis,
  offset = NULL,
  scale = NULL,
  epsilon = 0.001
)

Arguments

x: Input tensor.
mean: A mean vector of the same length as the axis dimension of the input thensor.
variance: A variance vector of the same length as the axis dimension of the input tensor.
axis: Integer, the axis that should be normalized.
offset: An offset vector of the same length as the axis dimension of the input tensor. If not NULL, offset is added to the normalized tensor. Defaults to NULL.
scale: A scale vector of the same length as the axis dimension of the input tensor. If not NULL, the normalized tensor is multiplied by scale. Defaults to NULL.
epsilon: Small float added to variance to avoid dividing by zero. Defaults to 1e-3.

Value

The normalized tensor.

Examples

x <- op_convert_to_tensor(rbind(c(0.1, 0.2, 0.3),
                                c(0.4, 0.5, 0.6),
                                c(0.7, 0.8, 0.9)))
op_batch_normalization(
  x,
  mean = c(0.4, 0.5, 0.6),
  variance = c(0.67, 0.67, 0.67),
  axis = -1
)

## tf.Tensor(
## [[-0.36623513 -0.36623513 -0.36623513]
##  [ 0.          0.          0.        ]
##  [ 0.36623513  0.36623513  0.36623513]], shape=(3, 3), dtype=float64)

See also

https://www.tensorflow.org/api_docs/python/tf/keras/ops/batch_normalization

Other nn ops:
op_average_pool()
op_binary_crossentropy()
op_categorical_crossentropy()
op_conv()
op_conv_transpose()
op_ctc_loss()
op_depthwise_conv()
op_elu()
op_gelu()
op_hard_sigmoid()
op_hard_silu()
op_leaky_relu()
op_log_sigmoid()
op_log_softmax()
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op_moments()
op_multi_hot()
op_normalize()
op_one_hot()
op_relu()
op_relu6()
op_selu()
op_separable_conv()
op_sigmoid()
op_silu()
op_softmax()
op_softplus()
op_softsign()
op_sparse_categorical_crossentropy()

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op_fft2()
op_flip()
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op_floor_divide()
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op_full()
op_full_like()
op_gelu()
op_get_item()
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op_greater_equal()
op_hard_sigmoid()
op_hard_silu()
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op_log()
op_log10()
op_log1p()
op_log2()
op_log_sigmoid()
op_log_softmax()
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op_norm()
op_normalize()
op_not_equal()
op_one_hot()
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op_ones_like()
op_outer()
op_pad()
op_power()
op_prod()
op_qr()
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op_size()
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op_slice_update()
op_softmax()
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op_solve()
op_solve_triangular()
op_sort()
op_sparse_categorical_crossentropy()
op_split()
op_sqrt()
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