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Merged
mergify merged 1 commit into from
May 13, 2025
Merged

Automated sync from github.com/tensorflow/tensorflow #3100

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8 changes: 5 additions & 3 deletions tensorflow/lite/kernels/internal/reference/floor.h
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Original file line number Diff line number Diff line change
Expand Up @@ -23,13 +23,15 @@ namespace tflite {

namespace reference_ops {

inline void Floor(const RuntimeShape& input_shape, const float* input_data,
const RuntimeShape& output_shape, float* output_data) {
template <typename T>
inline void Floor(const RuntimeShape& input_shape, const T* input_data,
const RuntimeShape& output_shape, T* output_data) {
const int flat_size = MatchingFlatSize(input_shape, output_shape);

for (int i = 0; i < flat_size; i++) {
int offset = i;
output_data[offset] = std::floor(input_data[offset]);
output_data[offset] =
static_cast<T>(std::floor(static_cast<float>(input_data[offset])));
}
}

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9 changes: 5 additions & 4 deletions tensorflow/lite/kernels/internal/reference/logistic.h
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Expand Up @@ -27,8 +27,9 @@ limitations under the License.
namespace tflite {
namespace reference_ops {

inline void Logistic(const RuntimeShape& input_shape, const float* input_data,
const RuntimeShape& output_shape, float* output_data) {
template <typename T>
inline void Logistic(const RuntimeShape& input_shape, const T* input_data,
const RuntimeShape& output_shape, T* output_data) {
const float cutoff_upper = 16.619047164916992188f;
const float cutoff_lower = -9.f;

Expand All @@ -43,7 +44,7 @@ inline void Logistic(const RuntimeShape& input_shape, const float* input_data,
// optimized kernels. (check the definition of scalar_logistic_op<float>)

for (int i = 0; i < flat_size; i++) {
float val = input_data[i];
T val = input_data[i];
float result;
if (val > cutoff_upper) {
result = 1.0f;
Expand All @@ -52,7 +53,7 @@ inline void Logistic(const RuntimeShape& input_shape, const float* input_data,
} else {
result = 1.f / (1.f + std::exp(-val));
}
output_data[i] = result;
output_data[i] = static_cast<T>(result);
}
}

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7 changes: 4 additions & 3 deletions tensorflow/lite/kernels/internal/reference/round.h
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Expand Up @@ -34,15 +34,16 @@ inline float RoundToNearest(float value) {
}
}

inline void Round(const RuntimeShape& input_shape, const float* input_data,
const RuntimeShape& output_shape, float* output_data) {
template <typename Scalar>
inline void Round(const RuntimeShape& input_shape, const Scalar* input_data,
const RuntimeShape& output_shape, Scalar* output_data) {
const int flat_size = MatchingFlatSize(input_shape, output_shape);
for (int i = 0; i < flat_size; ++i) {
// Note that this implementation matches that of tensorFlow tf.round
// and corresponds to the bankers rounding method.
// cfenv (for fesetround) is not yet supported universally on Android, so
// using a work around.
output_data[i] = RoundToNearest(input_data[i]);
output_data[i] = static_cast<Scalar>(RoundToNearest(input_data[i]));
}
}

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9 changes: 4 additions & 5 deletions tensorflow/lite/kernels/internal/reference/tanh.h
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Expand Up @@ -26,14 +26,13 @@ limitations under the License.
namespace tflite {
namespace reference_ops {

inline void Tanh(const RuntimeShape& input_shape, const float* input_data,
const RuntimeShape& output_shape, float* output_data) {
template <typename T>
inline void Tanh(const RuntimeShape& input_shape, const T* input_data,
const RuntimeShape& output_shape, T* output_data) {
const int flat_size = MatchingFlatSize(input_shape, output_shape);

for (int i = 0; i < flat_size; i++) {
float val = input_data[i];
float result = std::tanh(val);
output_data[i] = result;
output_data[i] = static_cast<T>(std::tanh(input_data[i]));
}
}

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