experiments/STT-tensorflow
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Make few implicit casts explicit to resolve clang warnings

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PiperOrigin-RevId: 308693807
Change-Id: I9bfff0da006c029370561111d1cae37675e4eda0
This commit is contained in:
A. Unique TensorFlower 2020-04-27 14:04:48 -07:00 committed by TensorFlower Gardener
parent f5e6c392b7
commit 6177daf885
1 changed files with 8 additions and 6 deletions
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14
tensorflow/lite/micro/micro_utils.cc
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@ -105,10 +105,10 @@ int8_t FloatToSymmetricQuantizedInt8(const float value, const float scale) {
int32_t FloatToSymmetricQuantizedInt32(const float value, const float scale) {
float quantized = round(value / scale);
if (quantized > INT_MAX) {
quantized = INT_MAX;
if (static_cast<int>(quantized) > INT_MAX) {
quantized = static_cast<float>(INT_MAX);
} else if (quantized < INT_MIN) {
quantized = INT_MIN;
quantized = static_cast<float> INT_MIN;
}
return static_cast<int>(quantized);
@ -249,13 +249,15 @@ void SignedSymmetricQuantize(const float* values, TfLiteIntArray* dims,
max = fmaxf(max, values[i]);
}
*scaling_factor = fmaxf(fabs(min), fabs(max)) / kSymmetricInt32Scale;
*scaling_factor =
fmaxf(fabs(min), fabs(max)) / static_cast<float>(kSymmetricInt32Scale);
for (int i = 0; i < input_size; i++) {
const int32_t quantized_value =
static_cast<int32_t>(roundf(values[i] / *scaling_factor));
// Clamp: just in case some odd numeric offset.
quantized_values[i] = fminf(kSymmetricInt32Scale,
fmaxf(-kSymmetricInt32Scale, quantized_value));
quantized_values[i] = fminf(
static_cast<float>(kSymmetricInt32Scale),
fmaxf(static_cast<float>(-kSymmetricInt32Scale), quantized_value));
}
}