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Go: Update generated wrapper functions for TensorFlow ops.

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PiperOrigin-RevId: 173739110
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A. Unique TensorFlower 2017-10-27 17:39:28 -07:00 committed by TensorFlower Gardener
parent 48df7c9729
commit ca56fa49a7
1 changed files with 6 additions and 6 deletions
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12
tensorflow/go/op/wrappers.go
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@ -1904,10 +1904,10 @@ func DequantizeMode(value string) DequantizeAttr {
// If the mode is 'MIN_FIRST', then this approach is used:
//
// ```c++
// number_of_steps = 1 << (# of bits in T)
// range_adjust = number_of_steps / (number_of_steps - 1)
// num_discrete_values = 1 << (# of bits in T)
// range_adjust = num_discrete_values / (num_discrete_values - 1)
// range = (range_max - range_min) * range_adjust
// range_scale = range / number_of_steps
// range_scale = range / num_discrete_values
// const double offset_input = static_cast<double>(input) - lowest_quantized;
// result = range_min + ((input - numeric_limits<T>::min()) * range_scale)
// ```
@ -13766,10 +13766,10 @@ func QuantizeV2RoundMode(value string) QuantizeV2Attr {
// If the mode is 'MIN_FIRST', then this approach is used:
//
// ```
// number_of_steps = 1 << (# of bits in T)
// range_adjust = number_of_steps / (number_of_steps - 1)
// num_discrete_values = 1 << (# of bits in T)
// range_adjust = num_discrete_values / (num_discrete_values - 1)
// range = (range_max - range_min) * range_adjust
// range_scale = number_of_steps / range
// range_scale = num_discrete_values / range
// quantized = round(input * range_scale) - round(range_min * range_scale) +
// numeric_limits<T>::min()
// quantized = max(quantized, numeric_limits<T>::min())