tf.raw_ops.QuantizedBatchNormWithGlobalNormalization

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Quantized Batch normalization.

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tf.compat.v1.raw_ops.QuantizedBatchNormWithGlobalNormalization

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. Prefertf.nn.batch_normalization.

Args
t	A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16. A 4D input Tensor.
t_min	A Tensor of type float32. The value represented by the lowest quantized input.
t_max	A Tensor of type float32. The value represented by the highest quantized input.
m	A 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_min	A Tensor of type float32. The value represented by the lowest quantized mean.
m_max	A Tensor of type float32. The value represented by the highest quantized mean.
v	A 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_min	A Tensor of type float32. The value represented by the lowest quantized variance.
v_max	A Tensor of type float32. The value represented by the highest quantized variance.
beta	A 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_min	A Tensor of type float32. The value represented by the lowest quantized offset.
beta_max	A Tensor of type float32. The value represented by the highest quantized offset.
gamma	A 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_min	A Tensor of type float32. The value represented by the lowest quantized gamma.
gamma_max	A Tensor of type float32. The value represented by the highest quantized gamma.
out_type	A tf.DType from: tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16.
variance_epsilon	A float. A small float number to avoid dividing by 0.
scale_after_normalization	A bool. A bool indicating whether the resulted tensor needs to be multiplied with gamma.
name	A name for the operation (optional).

Returns
A tuple of Tensor objects (result, result_min, result_max).
result	A Tensor of type out_type.
result_min	A Tensor of type float32.
result_max	A Tensor of type float32.

tf.raw_ops.QuantizedBatchNormWithGlobalNormalization | TensorFlow v2.16.1 (original) (raw)

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