/external/tensorflow/tensorflow/core/kernels/ |
H A D | quantization_utils.cc | 20 void GetOutputMinAndMaxForQuantizedAdd(float input_min, float input_max, argument 36 std::max(input_max, std::max(-input_min, std::max(smaller_input_max,
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H A D | quantized_activation_ops_test.cc | 45 const float input_min = -128.0f; local 52 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 58 AddInputFromArray<float>(TensorShape({1}), {input_min}); 76 const float input_min = -128.0f; local 83 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 89 AddInputFromArray<float>(TensorShape({1}), {input_min});
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H A D | quantize_and_dequantize_op.h | 43 auto input_min = input_min_tensor->scalar<T>(); local 46 input_min.device(d) = input.minimum(); 49 d.memcpyDeviceToHost(&min_range, input_min.data(), sizeof(T));
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H A D | quantized_bias_add_op.cc | 41 const float input_min = context->input(2).flat<float>()(0); variable 71 GetOutputMinAndMaxForQuantizedAdd(input_min, input_max, bias_min, 75 bias_ui8_array.size(), input_min, input_max, 80 context->template eigen_device<CPUDevice>(), input, input_min,
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H A D | quantized_bias_add_op_test.cc | 51 const float input_min = 0.0f; local 59 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 77 AddInputFromArray<float>(TensorShape({1}), {input_min}); 101 const float input_min = -2164.25f; local 119 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 159 AddInputFromArray<float>(TensorShape({1}), {input_min});
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H A D | quantized_pooling_ops_test.cc | 51 const float input_min = 0.0f; local 62 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 72 AddInputFromArray<float>(TensorShape({1}), {input_min}); 96 const float input_min = 0.0f; local 107 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 117 AddInputFromArray<float>(TensorShape({1}), {input_min});
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H A D | quantized_batch_norm_op_test.cc | 61 const float input_min = -128.0f; local 72 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 100 AddInputFromArray<float>(TensorShape({1}), {input_min}); 158 const float input_min = -128.0f; local 169 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 197 AddInputFromArray<float>(TensorShape({1}), {input_min});
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H A D | quantized_batch_norm_op.cc | 31 void ReferenceBatchNorm(const Tensor& input, const float input_min, argument 57 QuantizedToFloat(input_flat(input_index), input_min, input_max); 94 void FixedPointBatchNorm(const Tensor& input, const float input_min, argument 150 RequantizeInNewRange<T1, T2>(input_flat(input_index), input_min, 176 const float input_min = context->input(1).flat<float>()(0); variable 212 FixedPointBatchNorm<T1, T2>(input, input_min, input_max, mean, mean_min,
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H A D | quantized_concat_op.cc | 41 const float input_min = (*input_min_and_max)[input_index].first; local 43 if (input_min == output_min && input_max == output_max) { 52 QuantizedToFloatStruct<T> q2f(input_min, input_max); 87 const float input_min = input_mins[i].flat<float>()(0); local 89 input_mins_and_maxes->emplace_back(input_min, input_max); 90 overall_min = std::min(overall_min, input_min);
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H A D | meta_support.cc | 257 float input_min, float input_max, float output_min, 269 params.kernel.input_range_min = input_min; 272 CalculateRangeScale<int32_t>(input_min, input_max); 348 float input_min, float input_max, float bias_min, 363 params.kernel.input_range_min = input_min; 366 CalculateRangeScale<uint8_t>(input_min, input_max); 256 Requantize(OpKernelContext* tf_context, const qint32* input, int count, float input_min, float input_max, float output_min, float output_max, quint8* output) argument 346 QuantizedBiasAdd(OpKernelContext* tf_context, const quint8* input, int input_count, const quint8* bias, int bias_count, float input_min, float input_max, float bias_min, float bias_max, float output_min, float output_max, qint32* output) argument
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H A D | quantized_instance_norm.cc | 277 float input_min = context->input(1).flat<float>()(0); variable 279 float input_scale = (input_max - input_min) / 255.0f; 281 OP_REQUIRES(context, input_min < input_max, 283 "input_min must be less than input_max : ", input_min,
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H A D | quantization_utils_test.cc | 34 void TestRequantizeMany(Eigen::ThreadPoolDevice* eigen_device, float input_min, argument 43 QuantizedToFloat(values_quantized[value_index], input_min, input_max), 54 RequantizeManyInNewRange(input_array.data(), input_array.size(), input_min, 59 *eigen_device, i_tensor, input_min, input_max, output_min, output_max, 70 << "]=" << values_quantized[value_index] << ", input_min=" << input_min 76 void TestRequantizeMany8To32Bit(float input_min, float input_max, argument 85 QuantizedToFloat(values_quantized[value_index], input_min, input_max), 95 RequantizeManyInNewRange(input_array.data(), input_array.size(), input_min, 106 << "]=" << values_quantized[value_index] << ", input_min 230 const float input_min = ranges[range_index][0]; local 282 const float input_min = -100.0f; local 525 const float input_min = ranges[range_index][0]; local 547 const float input_min = -0.739539f; local 582 const float input_min = ranges[range_index][0]; local 625 const float input_min = 0.0f; local 655 const float input_min = 0.0f; local 678 const float input_min = -128.0f; local [all...] |
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
H A D | quantize_and_dequantize_op.cc | 46 // m = max(abs(input_min), abs(input_max)) if range_given is true, 50 xla::ComputationDataHandle input_min, input_max; variable 55 input_min = XlaHelpers::FloatLiteral(b, data_type, input_min_value); 60 input_min = 65 xla::ComputationDataHandle m = b->Max(b->Abs(input_min), b->Abs(input_max));
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H A D | fake_quantize_ops.cc | 106 float input_min, input_max; local 107 OP_REQUIRES_OK(ctx, ctx->GetAttr("min", &input_min)); 109 CpuNudge(input_min, input_max, quant_min_, quant_max_, &nudged_input_min_, 154 float input_min, input_max, scale; local 155 OP_REQUIRES_OK(ctx, ctx->GetAttr("min", &input_min)); 157 CpuNudge(input_min, input_max, quant_min, quant_max, &nudged_input_min_, 209 xla::ComputationDataHandle input_min = ctx->Input(1); variable 214 XlaNudge(b, data_type, input_min, input_max, quant_min_, quant_max_, 250 xla::ComputationDataHandle input_min = ctx->Input(2); variable 255 XlaNudge(b, data_type, input_min, input_ma [all...] |
/external/tensorflow/tensorflow/compiler/xla/tests/ |
H A D | reduce_test.cc | 614 auto input_min = FLT_MAX; local 616 [&](int64, int64, float* v) { input_min = std::min(input_min, *v); }); 617 ComputeAndCompareR0<float>(&builder, input_min, {}, ErrorSpec(0.0001));
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/external/tensorflow/tensorflow/tools/graph_transforms/ |
H A D | quantize_nodes.cc | 309 // If the user has passed in the input_min and input_max args, then we need to 315 float input_min; local 318 TF_RETURN_IF_ERROR(ExtractRangeFromParams(context, "input_min", "input_max", 319 &input_min, &input_max, 345 min_tensor.flat<float>()(0) = input_min; 657 // If input_min and input max have been passed in, then we convert all float
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/external/tensorflow/tensorflow/core/graph/ |
H A D | quantize_training.cc | 54 float input_min; member in struct:tensorflow::__anon26313::EdgeToConvert 63 input_min(min), 80 bool* range_given, float* input_min, float* input_max) { 95 *input_min = 0; 100 *input_min = 0; 105 *input_min = -1; 113 FindType(graph, edge->src(), signed_input, range_given, input_min, 123 FindType(graph, edge->src(), signed_input, range_given, input_min, 498 std::vector<Node*>* added_variables, Node** input_min, 501 // Make constant nodes for the input_min an 79 FindType(const Graph* graph, const Node* node, bool* signed_input, bool* range_given, float* input_min, float* input_max) argument 496 MakeInputMinMax(Graph* graph, const string& name_prefix, const EdgeToConvert& edge, std::vector<Node*>* added_variables, Node** input_min, Node** input_max) argument 534 Node* input_min; local 628 float input_min = 0; local [all...] |