tf.raw_ops.QuantizedBatchNormWithGlobalNormalization

Quantized Batch normalization.

tf.raw_ops.QuantizedBatchNormWithGlobalNormalization(
    t,
    t_min,
    t_max,
    m,
    m_min,
    m_max,
    v,
    v_min,
    v_max,
    beta,
    beta_min,
    beta_max,
    gamma,
    gamma_min,
    gamma_max,
    out_type,
    variance_epsilon,
    scale_after_normalization,
    name=None
)

This op is deprecated and will be removed in the future. Prefer tf.nn.batch_normalization.

tA Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16. A 4D input Tensor.
t_minA Tensor of type float32. The value represented by the lowest quantized input.
t_maxA Tensor of type float32. The value represented by the highest quantized input.
mA Tensor. Must have the same type as t. A 1D mean Tensor with size matching the last dimension of t. This is the first output from tf.nn.moments, or a saved moving average thereof.
m_minA Tensor of type float32. The value represented by the lowest quantized mean.
m_maxA Tensor of type float32. The value represented by the highest quantized mean.
vA Tensor. Must have the same type as t. A 1D variance Tensor with size matching the last dimension of t. This is the second output from tf.nn.moments, or a saved moving average thereof.
v_minA Tensor of type float32. The value represented by the lowest quantized variance.
v_maxA Tensor of type float32. The value represented by the highest quantized variance.
betaA Tensor. Must have the same type as t. A 1D beta Tensor with size matching the last dimension of t. An offset to be added to the normalized tensor.
beta_minA Tensor of type float32. The value represented by the lowest quantized offset.
beta_maxA Tensor of type float32. The value represented by the highest quantized offset.
gammaA Tensor. Must have the same type as t. A 1D gamma Tensor with size matching the last dimension of t. If "scale_after_normalization" is true, this tensor will be multiplied with the normalized tensor.
gamma_minA Tensor of type float32. The value represented by the lowest quantized gamma.
gamma_maxA Tensor of type float32. The value represented by the highest quantized gamma.
out_typeA tf.DType from: tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16.
variance_epsilonA float. A small float number to avoid dividing by 0.
scale_after_normalizationA bool. A bool indicating whether the resulted tensor needs to be multiplied with gamma.
nameA name for the operation (optional).

A tuple of Tensor objects (result, result_min, result_max).
resultA Tensor of type out_type.
result_minA Tensor of type float32.
result_maxA Tensor of type float32.