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Fix for TFlite quantized mean operator.

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PiperOrigin-RevId: 337326316
Change-Id: I04a50cfff4a3e0a90c4e36d604cd442f34a8d988
This commit is contained in:
A. Unique TensorFlower 2020-10-15 09:43:01 -07:00 committed by TensorFlower Gardener
parent 98a5b7deef
commit 10524e08b3
1 changed files with 2 additions and 3 deletions
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5
tensorflow/lite/kernels/internal/reference/reduce.h
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@ -381,8 +381,7 @@ inline bool QuantizedMeanOrSum(const T* input_data, int32_t input_zero_point,
const float scale = input_scale / output_scale;
if (compute_sum) {
// TODO(b/116341117): Eliminate float and do this completely in 8bit.
const float bias =
-input_zero_point * scale * num_elements_in_axis + 0.5f;
const float bias = -input_zero_point * scale * num_elements_in_axis;
for (size_t idx = 0; idx < num_outputs; ++idx) {
const U value =
static_cast<U>(TfLiteRound(temp_sum[idx] * scale + bias)) +
@ -390,7 +389,7 @@ inline bool QuantizedMeanOrSum(const T* input_data, int32_t input_zero_point,
output_data[idx] = static_cast<T>(value);
}
} else {
const float bias = -input_zero_point * scale + 0.5f;
const float bias = -input_zero_point * scale;
for (size_t idx = 0; idx < num_outputs; ++idx) {
float float_mean = static_cast<float>(temp_sum[idx]) /
static_cast<float>(num_elements_in_axis);