experiments/STT-tensorflow
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Merge pull request #26118 from amitsrivastava78:patch-23

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PiperOrigin-RevId: 236405002
This commit is contained in:
TensorFlower Gardener 2019-03-01 17:17:56 -08:00
commit a3262818d9
1 changed files with 7 additions and 6 deletions
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13
tensorflow/lite/tools/optimize/quantize_weights.cc
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@ -52,14 +52,15 @@ std::vector<ConsumerOpInfo> GetTensorConsumers(const ModelT* model,
// TODO(suharshs): If this proves to be too slow, avoid calling it per tensor,
// instead doing one sweep for the entire model.
std::vector<ConsumerOpInfo> consumer_ops;
for (int op_idx = 0; op_idx < subgraph->operators.size(); ++op_idx) {
for (size_t op_idx = 0; op_idx < subgraph->operators.size(); ++op_idx) {
OperatorT* op = subgraph->operators[op_idx].get();
if (op == nullptr) {
continue;
}
for (int i = 0; i < op->inputs.size(); ++i) {
for (size_t i = 0; i < op->inputs.size(); ++i) {
if (op->inputs[i] == tensor_idx) {
consumer_ops.push_back({op, op_idx, i});
consumer_ops.push_back(
{op, static_cast<int>(op_idx), static_cast<int>(i)});
}
}
}
@ -193,7 +194,7 @@ TfLiteStatus InsertQuantizableInputTensorsFromOperator(
// Returns the index of the Dequantize op_code.
// If a Dequantize op_code doesn't exist, adds it and returns its index.
int32_t GetOrInsertDequantizeOpCodeIndex(ModelT* model) {
for (int i = 0; i < model->operator_codes.size(); ++i) {
for (size_t i = 0; i < model->operator_codes.size(); ++i) {
if (model->operator_codes[i]->builtin_code == BuiltinOperator_DEQUANTIZE) {
return i;
}
@ -231,7 +232,7 @@ void MakeTensor(const string& name, const std::vector<int32_t>& shape,
// Updates operator code versions for the operators with INT8 inputs.
void UpdateInt8OperatorVersions(ModelT* model) {
for (int i = 0; i < model->operator_codes.size(); ++i) {
for (size_t i = 0; i < model->operator_codes.size(); ++i) {
const BuiltinOperator& op_code = model->operator_codes[i]->builtin_code;
if (op_code == BuiltinOperator_CONV_2D || op_code == BuiltinOperator_SVDF ||
op_code == BuiltinOperator_EMBEDDING_LOOKUP ||
@ -267,7 +268,7 @@ TfLiteStatus QuantizeWeightsInternal(flatbuffers::FlatBufferBuilder* builder,
std::vector<std::unique_ptr<OperatorT>> new_operators;
std::unordered_map<int32_t, TensorT*> tensor_map;
for (int i = 0; i < subgraph->operators.size(); ++i) {
for (size_t i = 0; i < subgraph->operators.size(); ++i) {
OperatorT* op = subgraph->operators[i].get();
TF_LITE_ENSURE_STATUS(InsertQuantizableInputTensorsFromOperator(
model.get(), op, weights_min_num_elements, &tensor_map));