experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Remove unused variable, and replace reinterpret_casts with static_casts.

Browse Source 
PiperOrigin-RevId: 310221007
Change-Id: I027cfa4838239f666b18404482bb7b392075ca3d
This commit is contained in:
Robert David 2020-05-06 13:52:11 -07:00 committed by TensorFlower Gardener
parent fc689523bc
commit 4a3236c75c
1 changed files with 7 additions and 8 deletions

15
tensorflow/lite/micro/kernels/xtensa_hifimini/svdf.cc
View File

@ -352,15 +352,15 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
// Calculate effective scales.
auto* input_params =
reinterpret_cast<TfLiteAffineQuantization*>(input->quantization.params);
auto* weights_feature_params = reinterpret_cast<TfLiteAffineQuantization*>(
static_cast<TfLiteAffineQuantization*>(input->quantization.params);
auto* weights_feature_params = static_cast<TfLiteAffineQuantization*>(
weights_feature->quantization.params);
auto* state_params = reinterpret_cast<TfLiteAffineQuantization*>(
auto* state_params = static_cast<TfLiteAffineQuantization*>(
activation_state->quantization.params);
auto* weight_time_params = reinterpret_cast<TfLiteAffineQuantization*>(
weights_time->quantization.params);
auto* weight_time_params =
static_cast<TfLiteAffineQuantization*>(weights_time->quantization.params);
auto* output_params =
reinterpret_cast<TfLiteAffineQuantization*>(output->quantization.params);
static_cast<TfLiteAffineQuantization*>(output->quantization.params);
const float effective_scale_1 = input_params->scale->data[0] *
weights_feature_params->scale->data[0] /
state_params->scale->data[0];
@ -392,8 +392,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
}
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
auto* params = reinterpret_cast<TfLiteSVDFParams*>(node->builtin_data);
auto* op_data = reinterpret_cast<OpData*>(node->user_data);
auto* params = static_cast<TfLiteSVDFParams*>(node->builtin_data);
const TfLiteTensor* input = GetInput(context, node, kInputTensor);
const TfLiteTensor* weights_feature =