experiments/STT-tensorflow
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Use tflite::SafeCast when casting float to int32.

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PiperOrigin-RevId: 251571788
This commit is contained in:
Suharsh Sivakumar 2019-06-04 20:52:22 -07:00 committed by TensorFlower Gardener
parent 0054b6aaa2
commit a495211a78
2 changed files with 5 additions and 3 deletions
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1
tensorflow/lite/tools/optimize/BUILD
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@ -19,6 +19,7 @@ cc_library(
deps = [ deps = [
"//tensorflow/lite:framework", "//tensorflow/lite:framework",
"//tensorflow/lite/c:c_api_internal", "//tensorflow/lite/c:c_api_internal",
"//tensorflow/lite/kernels/internal:quantization_util",
"//tensorflow/lite/kernels/internal:round", "//tensorflow/lite/kernels/internal:round",
"//tensorflow/lite/kernels/internal:tensor_utils", "//tensorflow/lite/kernels/internal:tensor_utils",
"//tensorflow/lite/kernels/internal:types", "//tensorflow/lite/kernels/internal:types",

7
tensorflow/lite/tools/optimize/quantization_utils.cc
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@ -20,6 +20,7 @@ limitations under the License.
#include "absl/memory/memory.h" #include "absl/memory/memory.h"
#include "third_party/eigen3/Eigen/Core" #include "third_party/eigen3/Eigen/Core"
#include "tensorflow/lite/c/c_api_internal.h" #include "tensorflow/lite/c/c_api_internal.h"
#include "tensorflow/lite/kernels/internal/quantization_util.h"
#include "tensorflow/lite/kernels/internal/round.h" #include "tensorflow/lite/kernels/internal/round.h"
#include "tensorflow/lite/kernels/internal/tensor_utils.h" #include "tensorflow/lite/kernels/internal/tensor_utils.h"
#include "tensorflow/lite/kernels/internal/types.h" #include "tensorflow/lite/kernels/internal/types.h"
@ -304,8 +305,8 @@ TfLiteStatus SymmetricPerLayerBiasQuantize(ModelT* model, TensorT* tensor,
for (int32_t i = 0; i < float_data_size; i++) { for (int32_t i = 0; i < float_data_size; i++) {
float scaling_factor_inv = (scaling_factor == 0) ? 0 : 1.0 / scaling_factor; float scaling_factor_inv = (scaling_factor == 0) ? 0 : 1.0 / scaling_factor;
const int32_t quantized_value = const int32_t quantized_value = tflite::SafeCast<int32_t>(
static_cast<int32_t>(TfLiteRound(float_data[i] * scaling_factor_inv)); TfLiteRound(float_data[i] * scaling_factor_inv));
final_buffer[i] = std::min(kScale, std::max(-kScale, quantized_value)); final_buffer[i] = std::min(kScale, std::max(-kScale, quantized_value));
} }
@ -341,7 +342,7 @@ TfLiteStatus SymmetricPerChannelBiasQuantize(ModelT* model, TensorT* tensor,
channel_idx++) { channel_idx++) {
float scaling_factor = scales[channel_idx]; float scaling_factor = scales[channel_idx];
float scaling_factor_inv = (scaling_factor == 0) ? 0 : 1.0 / scaling_factor; float scaling_factor_inv = (scaling_factor == 0) ? 0 : 1.0 / scaling_factor;
const int32_t quantized_value = static_cast<int32_t>( const int32_t quantized_value = tflite::SafeCast<int32_t>(
TfLiteRound(float_data[channel_idx] * scaling_factor_inv)); TfLiteRound(float_data[channel_idx] * scaling_factor_inv));
final_buffer[channel_idx] = final_buffer[channel_idx] =
std::min(kScale, std::max(-kScale, quantized_value)); std::min(kScale, std::max(-kScale, quantized_value));