experiments/STT-tensorflow
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minor spelling tweaks

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This commit is contained in:
Kazuaki Ishizaki 2020-03-19 02:33:15 +09:00
parent 56944a8148
commit 50ae62b65a
6 changed files with 9 additions and 9 deletions
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2
tensorflow/lite/examples/label_image/label_image.cc
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@ -132,7 +132,7 @@ void PrintProfilingInfo(const profiling::ProfileEvent* e,
uint32_t subgraph_index, uint32_t op_index, uint32_t subgraph_index, uint32_t op_index,
TfLiteRegistration registration) { TfLiteRegistration registration) {
// output something like // output something like
// time (ms) , Node xxx, OpCode xxx, symblic name // time (ms) , Node xxx, OpCode xxx, symbolic name
// 5.352, Node 5, OpCode 4, DEPTHWISE_CONV_2D // 5.352, Node 5, OpCode 4, DEPTHWISE_CONV_2D
LOG(INFO) << std::fixed << std::setw(10) << std::setprecision(3) LOG(INFO) << std::fixed << std::setw(10) << std::setprecision(3)

4
tensorflow/lite/external_cpu_backend_context.h
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@ -25,7 +25,7 @@ namespace tflite {
// This is the base class for TF Lite internal backend contexts (like a // This is the base class for TF Lite internal backend contexts (like a
// RUY-based cpu backend context class). A derived internal backend context is // RUY-based cpu backend context class). A derived internal backend context is
// generally a collection of utilities (i.e. a thread pool etc.) for TF Lite to // generally a collection of utilities (i.e. a thread pool etc.) for TF Lite to
// use certain keneral libraries, such as Gemmlowp, RUY, etc., to implement TF // use certain kernel libraries, such as Gemmlowp, RUY, etc., to implement TF
// Lite operators. // Lite operators.
class TfLiteInternalBackendContext { class TfLiteInternalBackendContext {
public: public:
@ -68,7 +68,7 @@ class TfLiteInternalBackendContext {
// the #thread info in the global cpu backend context (i.e. 'global_ctxt' above) // the #thread info in the global cpu backend context (i.e. 'global_ctxt' above)
// that affects how much parallelism an interpreter invocation will use. // that affects how much parallelism an interpreter invocation will use.
// Therefore, if different number of threads are used among different // Therefore, if different number of threads are used among different
// interpreters, don't call 'SetNumThreads' consectutively but call it // interpreters, don't call 'SetNumThreads' consecutively but call it
// separately between each interpreter's invocation as illustrated above. // separately between each interpreter's invocation as illustrated above.
// //
// Note: it is the responsibility of the user of this context (i.e. a // Note: it is the responsibility of the user of this context (i.e. a

2
tensorflow/lite/graph_info.h
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@ -41,7 +41,7 @@ class GraphInfo {
// num_nodes(). // num_nodes().
virtual const TfLiteNode& node(size_t index) const = 0; virtual const TfLiteNode& node(size_t index) const = 0;
// Returns an implementation-speicfic node index which may be different from // Returns an implementation-specific node index which may be different from
// index. // index.
virtual size_t node_index(size_t index) const = 0; virtual size_t node_index(size_t index) const = 0;

2
tensorflow/lite/interpreter.cc
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@ -136,7 +136,7 @@ void Interpreter::SetExternalContext(TfLiteExternalContextType type,
// If it's overwritten here, we will release the resource of the internally // If it's overwritten here, we will release the resource of the internally
// owned external context. // owned external context.
// Note: the 'max thread count' info associated with the overwritten context // Note: the 'max thread count' info associated with the overwritten context
// will be lost here, and such info is now detemined by the new context, thus // will be lost here, and such info is now determined by the new context, thus
// affecting how much parallelism a TFLite op would have. // affecting how much parallelism a TFLite op would have.
if (kTfLiteCpuBackendContext == type && if (kTfLiteCpuBackendContext == type &&
external_contexts_[kTfLiteCpuBackendContext] == external_contexts_[kTfLiteCpuBackendContext] ==

2
tensorflow/lite/model_test.cc
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@ -71,7 +71,7 @@ class TrivialResolver : public OpResolver {
TfLiteRegistration* constant_return_; TfLiteRegistration* constant_return_;
}; };
TEST(BasicFlatBufferModel, TestNonExistantFiles) { TEST(BasicFlatBufferModel, TestNonExistentFiles) {
ASSERT_TRUE(!FlatBufferModel::BuildFromFile("/tmp/tflite_model_1234")); ASSERT_TRUE(!FlatBufferModel::BuildFromFile("/tmp/tflite_model_1234"));
} }

6
tensorflow/lite/util.h
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@ -44,7 +44,7 @@ TfLiteIntArray* ConvertVectorToTfLiteIntArray(const std::vector<int>& input);
// Converts an array (of the given size) to a `TfLiteIntArray`. The caller // Converts an array (of the given size) to a `TfLiteIntArray`. The caller
// takes ownership of the returned pointer, and must make sure 'dims' has at // takes ownership of the returned pointer, and must make sure 'dims' has at
// least 'rank' elemnts. // least 'rank' elements.
TfLiteIntArray* ConvertArrayToTfLiteIntArray(const int rank, const int* dims); TfLiteIntArray* ConvertArrayToTfLiteIntArray(const int rank, const int* dims);
// Checks whether a `TfLiteIntArray` and an int array have matching elements. // Checks whether a `TfLiteIntArray` and an int array have matching elements.
@ -66,8 +66,8 @@ TfLiteStatus GetSizeOfType(TfLiteContext* context, const TfLiteType type,
size_t* bytes); size_t* bytes);
// Creates a stub TfLiteRegistration instance with the provided // Creates a stub TfLiteRegistration instance with the provided
// `custom_op_name`. The op will fail if invoked, and is useful as a placeholde // `custom_op_name`. The op will fail if invoked, and is useful as a
// to defer op resolution. // placeholder to defer op resolution.
// Note that `custom_op_name` must remain valid for the returned op's lifetime.. // Note that `custom_op_name` must remain valid for the returned op's lifetime..
TfLiteRegistration CreateUnresolvedCustomOp(const char* custom_op_name); TfLiteRegistration CreateUnresolvedCustomOp(const char* custom_op_name);