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/tflite-micro-3.4.0-2.7.6/third_party_static/flatbuffers/include/flatbuffers/
Dstl_emulation.h63 template <typename T> inline T *vector_data(std::vector<T> &vector) { in vector_data()
69 template <typename T> inline const T *vector_data( in vector_data()
70 const std::vector<T> &vector) { in vector_data()
74 template <typename T, typename V>
75 inline void vector_emplace_back(std::vector<T> *vector, V &&data) { in vector_emplace_back()
85 template <typename T>
86 using numeric_limits = std::numeric_limits<T>;
88 template <typename T> class numeric_limits :
89 public std::numeric_limits<T> {};
92 template <typename T> class numeric_limits :
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Dflatbuffers.h35 template<typename T> inline bool IsTheSameAs(T e, T def) { return e == def; } in IsTheSameAs()
40 template<typename T> inline bool IsFloatTheSameAs(T e, T def) { in IsFloatTheSameAs()
54 template<typename T>
55 inline bool IsOutRange(const T &v, const T &low, const T &high) { in IsOutRange()
60 template<typename T>
61 inline bool IsInRange(const T &v, const T &low, const T &high) { in IsInRange()
67 template<typename T> struct Offset {
83 template<typename T> FLATBUFFERS_CONSTEXPR size_t AlignOf() { in AlignOf()
86 return __alignof(T); in AlignOf()
89 return __alignof__(T); in AlignOf()
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Dbase.h121 template<class T> inline operator T*() const { return 0; }
289 template<typename T> FLATBUFFERS_CONSTEXPR inline bool IsConstTrue(T t) { in IsConstTrue()
344 template<typename T> T EndianSwap(T t) { in EndianSwap()
365 if (sizeof(T) == 1) { // Compile-time if-then's. in EndianSwap()
367 } else if (sizeof(T) == 2) { in EndianSwap()
368 union { T t; uint16_t i; } u = { t }; in EndianSwap()
371 } else if (sizeof(T) == 4) { in EndianSwap()
372 union { T t; uint32_t i; } u = { t }; in EndianSwap()
375 } else if (sizeof(T) == 8) { in EndianSwap()
376 union { T t; uint64_t i; } u = { t }; in EndianSwap()
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/
Dmicro_utils.h35 template <typename T>
36 T FloatToQuantizedType(const float value, const float scale, int zero_point) { in FloatToQuantizedType()
39 std::max(static_cast<int32_t>(std::numeric_limits<T>::min()), result); in FloatToQuantizedType()
41 std::min(static_cast<int32_t>(std::numeric_limits<T>::max()), result); in FloatToQuantizedType()
45 template <typename T>
46 T FloatToSymmetricQuantizedType(const float value, const float scale) { in FloatToSymmetricQuantizedType()
51 static_cast<std::int64_t>(std::numeric_limits<T>::min() + 1), result); in FloatToSymmetricQuantizedType()
52 result = std::min(static_cast<std::int64_t>(std::numeric_limits<T>::max()), in FloatToSymmetricQuantizedType()
68 template <typename T>
69 void Quantize(const float* input, T* output, int num_elements, float scale, in Quantize()
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Dtest_helpers.h168 template <typename T>
169 TfLiteTensor CreateTensor(const T* data, TfLiteIntArray* dims,
177 result.type = typeToTfLiteType<T>();
182 result.data.data = const_cast<T*>(data);
184 result.bytes = ElementCount(*dims) * sizeof(T);
188 template <typename T>
189 TfLiteTensor CreateQuantizedTensor(const T* data, TfLiteIntArray* dims,
198 template <typename T>
199 TfLiteTensor CreateQuantizedTensor(const float* input, T* quantized,
248 template <typename T>
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/kernels/internal/reference/
Dcomparisons.h26 template <typename T>
27 inline bool EqualFn(T lhs, T rhs) { in EqualFn()
31 template <typename T>
32 inline bool NotEqualFn(T lhs, T rhs) { in NotEqualFn()
36 template <typename T>
37 inline bool GreaterFn(T lhs, T rhs) { in GreaterFn()
40 template <typename T>
41 inline bool GreaterEqualFn(T lhs, T rhs) { in GreaterEqualFn()
44 template <typename T>
45 inline bool LessFn(T lhs, T rhs) { in LessFn()
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Dpad.h37 template <typename T, typename P>
39 const RuntimeShape& input_shape, const T* input_data, in PadImpl()
41 T* output_data) { in PadImpl()
87 const T pad_value = *pad_value_ptr; in PadImpl()
89 const T* in_ptr = input_data; in PadImpl()
90 T* out_ptr = output_data; in PadImpl()
117 template <typename T, typename P>
119 const RuntimeShape& input_shape, const T* input_data, in Pad()
121 T* output_data) { in Pad()
127 template <typename T>
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Dfloor_mod.h25 template <typename T>
26 T FloorMod(T input1, T input2) { in FloorMod()
32 using ModFunc = typename std::conditional<std::is_integral<T>::value, in FloorMod()
33 std::modulus<T>, FloatMod>::type; in FloorMod()
35 T trunc_mod = mod_func(input1, input2); in FloorMod()
Dprelu.h27 template <typename T>
30 const T* input_data, const RuntimeShape& alpha_shape, const T* alpha_data, in BroadcastPrelu4DSlow()
31 const RuntimeShape& output_shape, T* output_data) { in BroadcastPrelu4DSlow()
64 const int32_t quantized_min = std::numeric_limits<T>::min(); in BroadcastPrelu4DSlow()
65 const int32_t quantized_max = std::numeric_limits<T>::max(); in BroadcastPrelu4DSlow()
68 output_data[output_index] = static_cast<T>(clamped_output); in BroadcastPrelu4DSlow()
75 template <typename T>
77 const T* input_data, const RuntimeShape& alpha_shape, in Prelu()
78 const T* alpha_data, const RuntimeShape& output_shape, in Prelu()
79 T* output_data) { in Prelu()
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Dreduce.h156 template <typename T>
158 const T init_value, T* data) { in InitTensorDataForReduce()
177 template <typename T>
178 inline bool ReduceGeneric(const T* input_data, const int* input_dims, in ReduceGeneric()
179 const int input_num_dims, T* output_data, in ReduceGeneric()
183 T init_value, in ReduceGeneric()
184 T reducer(const T current, const T in)) { in ReduceGeneric()
206 return Reduce<T, T>(input_data, input_dims, output_dims, input_num_dims, in ReduceGeneric()
214 template <typename T, typename U>
215 inline bool Mean(const T* input_data, const int* input_dims, in Mean()
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Dhard_swish.h44 template <typename T>
45 inline void HardSwish(const RuntimeShape& input_shape, const T* input_data, in HardSwish()
46 const RuntimeShape& output_shape, T* output_data) { in HardSwish()
49 const T* in_end = input_data + matching_size; in HardSwish()
53 in * std::min(static_cast<T>(6), std::max(static_cast<T>(0), in + 3)) / in HardSwish()
58 template <typename T>
60 const RuntimeShape& input_shape, const T* input_data, in HardSwish()
61 const RuntimeShape& output_shape, T* output_data) { in HardSwish()
156 std::min<int16_t>(output_value, std::numeric_limits<T>::max()); in HardSwish()
158 std::max<int16_t>(output_value, std::numeric_limits<T>::min()); in HardSwish()
Dleaky_relu.h37 template <typename T>
40 const T* input_data, in QuantizeLeakyRelu()
42 T* output_data) { in QuantizeLeakyRelu()
44 static const int32_t quantized_min = std::numeric_limits<T>::min(); in QuantizeLeakyRelu()
45 static const int32_t quantized_max = std::numeric_limits<T>::max(); in QuantizeLeakyRelu()
60 const T clamped_output = in QuantizeLeakyRelu()
62 output_data[i] = static_cast<T>(clamped_output); in QuantizeLeakyRelu()
Dadd.h27 template <typename T>
29 const RuntimeShape& input1_shape, const T* input1_data, in Add()
30 const RuntimeShape& input2_shape, const T* input2_data, in Add()
31 const RuntimeShape& output_shape, T* output_data) { in Add()
32 T activation_min, activation_max; in Add()
49 template <typename T>
51 const T* input1_data, const T* input2_data, in AddElementwise()
52 T* output_data) { in AddElementwise()
53 TFLITE_DCHECK_GT(params.input1_offset, -std::numeric_limits<T>::max()); in AddElementwise()
54 TFLITE_DCHECK_GT(params.input2_offset, -std::numeric_limits<T>::max()); in AddElementwise()
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Dfloor_div.h26 template <typename T>
27 T FloorDiv(T input1, T input2) { in FloorDiv()
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/arc_mli/
Dmli_interface.h40 template <typename T>
41 T* Data();
42 template <typename T>
43 T Scale();
44 template <typename T>
45 T ZeroPoint();
46 template <typename T>
47 T ScaleFracBits();
61 template <typename T>
62 void SetData(T* data, uint32_t capacity) const;
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/
Dfloor_div.cc61 template <typename T>
66 const T* denominator_data = tflite::micro::GetTensorData<T>(input2); in EvalFloorDiv()
70 if (std::equal_to<T>()(denominator_data[i], 0)) { in EvalFloorDiv()
79 reference_ops::BroadcastBinaryFunction4DSlow<T, T, T>( in EvalFloorDiv()
81 tflite::micro::GetTensorData<T>(input1), in EvalFloorDiv()
84 tflite::micro::GetTensorData<T>(output), reference_ops::FloorDiv<T>); in EvalFloorDiv()
86 reference_ops::BinaryFunction<T, T, T>( in EvalFloorDiv()
88 tflite::micro::GetTensorData<T>(input1), in EvalFloorDiv()
91 tflite::micro::GetTensorData<T>(output), reference_ops::FloorDiv<T>); in EvalFloorDiv()
Dfloor_mod.cc66 template <typename T>
71 const T* denominator_data = tflite::micro::GetTensorData<T>(input2); in EvalFloorMod()
74 reference_ops::BroadcastBinaryFunction4DSlow<T, T, T>( in EvalFloorMod()
76 tflite::micro::GetTensorData<T>(input1), in EvalFloorMod()
79 tflite::micro::GetTensorData<T>(output), reference_ops::FloorMod<T>); in EvalFloorMod()
81 reference_ops::BinaryFunction<T, T, T>( in EvalFloorMod()
83 tflite::micro::GetTensorData<T>(input1), in EvalFloorMod()
86 tflite::micro::GetTensorData<T>(output), reference_ops::FloorMod<T>); in EvalFloorMod()
Dmicro_utils.h24 template <typename T>
25 bool operator()(const T& x, const T& y) const { in operator()
31 template <typename T>
32 bool operator()(const T& x, const T& y) const { in operator()
Dadd_n_test.cc49 template <typename T>
50 void TestAddN(int* input_dims_data, const T* const* input_data, in TestAddN()
51 int input_data_count, int* expected_dims, const T* expected_data, in TestAddN()
52 T* output_data) { in TestAddN()
73 template <typename T, int kNumInputs, int kOutputSize>
77 T input_data[kNumInputs][kOutputSize]; // quantized input storage
78 T output_data[kOutputSize]; // quantized output storage
82 template <typename T>
86 (std::numeric_limits<T>::max() - std::numeric_limits<T>::min()); in GetTolerance()
90 template <typename T, int kNumInputs, int kOutputSize>
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Delu_test.cc28 template <typename T>
33 T* input_data; // quantized input storage
34 T* output_data; // quantized output storage
70 template <typename T>
71 void TestElu(int* input_dims_data, const T* input_data, int* expected_dims, in TestElu()
72 const T* expected_data, T* output_data) { in TestElu()
90 template <typename T>
91 void TestEluQuantized(const TestEluParams<T>& params, int* input_dims_data, in TestEluQuantized()
98 const float scale = ScaleFromMinMax<T>(params.data_min, params.data_max); in TestEluQuantized()
100 ZeroPointFromMinMax<T>(params.data_min, params.data_max); in TestEluQuantized()
Dhard_swish_test.cc57 template <typename T>
58 void TestHardSwishQuantized(int size, const T* output_data, in TestHardSwishQuantized()
59 T* input_data_quantized, float* dequantized_output, in TestHardSwishQuantized()
66 const float input_scale = ScaleFromMinMax<T>(input_min, input_max); in TestHardSwishQuantized()
67 const int input_zero_point = ZeroPointFromMinMax<T>(input_min, input_max); in TestHardSwishQuantized()
68 const float output_scale = ScaleFromMinMax<T>(output_min, output_max); in TestHardSwishQuantized()
69 const int output_zero_point = ZeroPointFromMinMax<T>(output_min, output_max); in TestHardSwishQuantized()
115 Dequantize<T>(output_data, output_elements_count, output_scale, in TestHardSwishQuantized()
124 template <typename T>
125 void TestHardSwishQuantizedBias(const int size, const T* output_data, in TestHardSwishQuantizedBias()
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/kernels/internal/
Dportable_tensor.h32 template <typename T>
46 all_data_.push_back(GetTensorData<T>(t)); in VectorOfTensors()
61 T* const* data() const { return all_data_.data(); } in data()
70 std::vector<T*> all_data_;
99 template <typename T>
103 input_data_ = GetTensorData<T>(input); in SequentialTensorWriter()
104 output_ptr_ = GetTensorData<T>(output); in SequentialTensorWriter()
106 SequentialTensorWriter(const T* input_data, T* output_data) in SequentialTensorWriter()
111 memcpy(output_ptr_, &input_data_[position], sizeof(T) * len); in WriteN()
116 const T* input_data_;
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Dtensor_ctypes.h23 template <typename T>
24 inline T* GetTensorData(TfLiteTensor* tensor) { in GetTensorData()
25 return tensor != nullptr ? reinterpret_cast<T*>(tensor->data.raw) : nullptr; in GetTensorData()
28 template <typename T>
29 inline const T* GetTensorData(const TfLiteTensor* tensor) { in GetTensorData()
30 return tensor != nullptr ? reinterpret_cast<const T*>(tensor->data.raw) in GetTensorData()
Dmax.h27 template <class T>
28 inline T TfLiteMax(const T& x, const T& y) {
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/kernels/internal/reference/integer_ops/
Dmul.h25 template <typename T>
27 const T* input1_data, const T* input2_data, in MulElementwise()
28 T* output_data) { in MulElementwise()
40 output_data[i] = static_cast<T>(clamped_output); in MulElementwise()
44 template <typename T>
46 const RuntimeShape& input1_shape, const T* input1_data, in Mul()
47 const RuntimeShape& input2_shape, const T* input2_data, in Mul()
48 const RuntimeShape& output_shape, T* output_data) { in Mul()
88 template <typename T>
91 const T* input1_data, const RuntimeShape& input2_shape, in BroadcastMul4DSlow()
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