/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/ |
D | quantize_test.cc | 128 const float values[] = {-63.5, -63, -62.5, -62, -61.5, in TF_LITE_MICRO_TEST() local 135 dims, values, dims, values, values_quantized, scale, zero_point, output); in TF_LITE_MICRO_TEST() 141 const float values[] = {-128, -127, -126, -125, -124, in TF_LITE_MICRO_TEST() local 148 dims, values, dims, values, values_quantized, scale, zero_point, output); in TF_LITE_MICRO_TEST() 154 const float values[] = {-64, -62, -60, -58, -56, 54, 56, 58, 60, 62}; in TF_LITE_MICRO_TEST() local 162 tflite::testing::TestRequantize(dims, values, input_quantized, input_scale, in TF_LITE_MICRO_TEST() 163 input_zero_point, dims, values, in TF_LITE_MICRO_TEST() 171 const float values[] = {-32, -31, -30, -29, -28, 27, 28, 29, 30, 31}; in TF_LITE_MICRO_TEST() local 179 tflite::testing::TestRequantize(dims, values, input_quantized, input_scale, in TF_LITE_MICRO_TEST() 180 input_zero_point, dims, values, in TF_LITE_MICRO_TEST() [all …]
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D | dequantize_test.cc | 106 const float values[] = {-63.5, -63, -62.5, -62, -61.5, in TF_LITE_MICRO_TEST() local 112 tflite::testing::TestDequantizeToFloat(dims, values, input_quantized, scale, in TF_LITE_MICRO_TEST() 113 zero_point, dims, values, output); in TF_LITE_MICRO_TEST() 119 const float values[] = {-63.5, -63, -62.5, -62, -61.5, in TF_LITE_MICRO_TEST() local 125 tflite::testing::TestDequantizeToFloat(dims, values, input_quantized, scale, in TF_LITE_MICRO_TEST() 126 zero_point, dims, values, output); in TF_LITE_MICRO_TEST() 132 const float values[] = {-63.5, -63, -62.5, -62, -61.5, in TF_LITE_MICRO_TEST() local 138 tflite::testing::TestDequantizeToFloat(dims, values, input_quantized, scale, in TF_LITE_MICRO_TEST() 139 zero_point, dims, values, output); in TF_LITE_MICRO_TEST()
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D | detection_postprocess.cc | 345 void DecreasingPartialArgSort(const float* values, int num_values, in DecreasingPartialArgSort() argument 350 [&values](const int i, const int j) { return values[i] > values[j]; }); in DecreasingPartialArgSort() 353 int SelectDetectionsAboveScoreThreshold(const float* values, int size, in SelectDetectionsAboveScoreThreshold() argument 358 if (values[i] >= threshold) { in SelectDetectionsAboveScoreThreshold() 359 keep_values[counter] = values[i]; in SelectDetectionsAboveScoreThreshold()
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/tflite-micro-3.4.0-2.7.6/.github/assets/ |
D | write_json.py | 11 def write_json(output_file, values): argument 13 json_dict = {values[0]: values[1]} 23 if args.values[0] == 'random': args.values[1] = random.randrange(1000) 24 write_json(args.file, args.values)
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/ |
D | micro_utils_test.cc | 88 float values[] = {-10.3, -3.1, -2.1, -1.9, -0.9, 0.1, 0.9, 1.85, 2.9, 4.1}; in TF_LITE_MICRO_TEST() local 90 constexpr int length = sizeof(values) / sizeof(float); in TF_LITE_MICRO_TEST() 92 tflite::Quantize(values, quantized, length, 0.5, 1); in TF_LITE_MICRO_TEST() 99 float values[] = {-10.3, -3.1, -2.1, -1.9, -0.9, 0.1, 0.9, 1.85, 2.9, 4.1}; in TF_LITE_MICRO_TEST() local 101 constexpr int length = sizeof(values) / sizeof(float); in TF_LITE_MICRO_TEST() 103 tflite::Quantize(values, quantized, length, 0.5, 127); in TF_LITE_MICRO_TEST() 110 float values[] = {-10.3, -3.1, -2.1, -1.9, -0.9, 0.1, 0.9, 1.85, 2.9, 4.1}; in TF_LITE_MICRO_TEST() local 112 constexpr int length = sizeof(values) / sizeof(float); in TF_LITE_MICRO_TEST() 114 tflite::SymmetricQuantize(values, quantized, length, 0.5); in TF_LITE_MICRO_TEST()
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D | micro_utils.h | 97 void SignedSymmetricPerChannelQuantize(const float* values, 106 void SymmetricQuantizeCalculateScales(const float* values, TfLiteIntArray* dims, in SymmetricQuantizeCalculateScales() argument 113 min = fminf(min, values[i]); in SymmetricQuantizeCalculateScales() 114 max = fmaxf(max, values[i]); in SymmetricQuantizeCalculateScales() 119 static_cast<int32_t>(roundf(values[i] / *scale)); in SymmetricQuantizeCalculateScales() 128 void Dequantize(const T* values, const int size, const float scale, in Dequantize() argument 131 dequantized_values[i] = (values[i] - zero_point) * scale; in Dequantize()
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D | micro_utils.cc | 36 void SignedSymmetricPerChannelQuantize(const float* values, in SignedSymmetricPerChannelQuantize() argument 65 min = fminf(min, values[idx]); in SignedSymmetricPerChannelQuantize() 66 max = fmaxf(max, values[idx]); in SignedSymmetricPerChannelQuantize() 73 static_cast<int32_t>(roundf(values[idx] / scaling_factors[channel])); in SignedSymmetricPerChannelQuantize()
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/examples/micro_speech/apollo3/ |
D | captured_data_to_wav.py | 41 values = np.array(new_data_to_array(data)).astype(float) variable 46 wav = values / np.max(np.abs(values))
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/experimental/microfrontend/lib/ |
D | frontend_memmap_main.c | 48 if (output.values != NULL) { in main() 51 printf("%d ", output.values[i]); in main()
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D | frontend_main.c | 58 if (output.values != NULL) { in main() 61 printf("%d ", output.values[i]); in main()
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D | frontend_test.cc | 74 TF_LITE_MICRO_EXPECT_EQ(output.values[i], expected[i]); in TF_LITE_MICRO_TEST() 99 TF_LITE_MICRO_EXPECT_EQ(output.values[i], expected[i]); in TF_LITE_MICRO_TEST() 126 TF_LITE_MICRO_EXPECT(output.values == nullptr); in TF_LITE_MICRO_TEST()
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D | frontend.c | 24 output.values = NULL; in FrontendProcessSamples() 63 output.values = logged_filterbank; in FrontendProcessSamples()
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D | filterbank_io.c | 17 static void PrintArray(FILE* fp, const char* name, const int16_t* values, in PrintArray() argument 22 fprintf(fp, "%d", values[i]); in PrintArray()
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D | frontend.h | 42 const uint16_t* values; member
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D | README.md | 4 input, and produces filter banks (a vector of values). 34 printf("%d ", output.values[i]); // Print the feature vector. 41 a feature vector, the returned size will be 0 and the values pointer will be
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/memory_planner/ |
D | greedy_memory_planner.cc | 43 void ReverseSortInPlace(int* values, int* ids, int size) { in ReverseSortInPlace() argument 48 if (values[i - 1] < values[i]) { in ReverseSortInPlace() 49 const int value_temp = values[i - 1]; in ReverseSortInPlace() 50 values[i - 1] = values[i]; in ReverseSortInPlace() 51 values[i] = value_temp; in ReverseSortInPlace()
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D | greedy_memory_planner_test.cc | 24 void ReverseSortInPlace(int* values, int* ids, int size);
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/tflite-micro-3.4.0-2.7.6/third_party/flatbuffers/ |
D | BUILD.bazel | 11 values = {"cpu": "freebsd"}, 16 values = {"cpu": "x64_windows"},
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/tools/make/ext_libs/ |
D | stm32_bare_lib.patch | 11 -// supported on many microcontrollers) and as a consequence prints values with 28 -// supported on many microcontrollers) and as a consequence prints values with 64 - // values in this array.
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/examples/micro_speech/micro_features/ |
D | micro_features_generator.cc | 103 ((frontend_output.values[i] * value_scale) + (value_div / 2)) / in GenerateMicroFeatures()
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/vexriscv/doc/ |
D | DepthwiseConv2D_int8.md | 136 integer model, accumulating intermediate values at the output tensor will cause 137 overflow: the product of two `int8` values is in the range of `int16` and there 138 are `H * W` values to be accumulated, the range of the value before quantization 145 array with size equals to the output tensor to accumulate the values. 235 those `C` values and store them into the output tensor. However, we are running
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/tools/make/targets/ |
D | hexagon_makefile.inc | 15 # without providing a version. Valid values may vary depending on tools
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/schema/ |
D | schema_generated.h | 434 static const TensorType values[] = { in EnumValuesTensorType() local 452 return values; in EnumValuesTensorType() 492 static const QuantizationDetails values[] = { in EnumValuesQuantizationDetails() local 496 return values; in EnumValuesQuantizationDetails() 565 …erifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers… 575 static const DimensionType values[] = { 579 return values; 607 static const SparseIndexVector values[] = { 613 return values; 708 …erifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers… [all …]
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/examples/person_detection/ |
D | training_a_model.md | 158 pixel values from 0 to 255 integers into -1.0 to +1.0 floating point numbers 169 values we found through experimentation for this particular model. You can 199 partially-trained model's predictions are to the correct values, and lower 200 values are better. This will show a lot of variation but should on average 311 constants, after loading their values from a checkpoint file. The command below 441 filtered by one or more rectangular filters to produce intermediate values. 442 These values are then combined using pointwise convolutions. This dramatically
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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/examples/micro_speech/train/ |
D | README.md | 137 input samples are treated as being between -1 and +1 as real values (encoded as 142 The results are stored as unsigned eight-bit values, where 0 represents a real
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