| /external/tensorflow/tensorflow/core/kernels/ |
| D | quantization_utils_test.cc | 34 void TestRequantizeMany(Eigen::ThreadPoolDevice* eigen_device, float input_min, in TestRequantizeMany() argument
43 QuantizedToFloat(values_quantized[value_index], input_min, input_max), in TestRequantizeMany()
54 RequantizeManyInNewRange(input_array.data(), input_array.size(), input_min, in TestRequantizeMany()
59 *eigen_device, i_tensor, input_min, input_max, output_min, output_max, in TestRequantizeMany()
70 << "]=" << values_quantized[value_index] << ", input_min=" << input_min in TestRequantizeMany()
76 void TestRequantizeMany8To32Bit(float input_min, float input_max, in TestRequantizeMany8To32Bit() argument
85 QuantizedToFloat(values_quantized[value_index], input_min, input_max), in TestRequantizeMany8To32Bit()
95 RequantizeManyInNewRange(input_array.data(), input_array.size(), input_min, in TestRequantizeMany8To32Bit()
106 << "]=" << values_quantized[value_index] << ", input_min=" << input_min in TestRequantizeMany8To32Bit()
230 const float input_min = ranges[range_index][0]; in TestRequantizeManyInNewRangeEigenVsNonEigen() local
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| D | quantized_activation_ops_test.cc | 45 const float input_min = -128.0f; in TEST_F() local
52 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
58 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
76 const float input_min = -128.0f; in TEST_F() local
83 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
89 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
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| D | quantized_pooling_ops_test.cc | 51 const float input_min = 0.0f; in TEST_F() local
62 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
72 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
96 const float input_min = 0.0f; in TEST_F() local
107 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
117 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
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| D | quantized_bias_add_op_test.cc | 51 const float input_min = 0.0f; in TEST_F() local
59 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
77 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
101 const float input_min = -2164.25f; in TEST_F() local
119 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
159 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
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| D | quantized_bias_add_op.cc | 41 const float input_min = context->input(2).flat<float>()(0); in Compute() local
71 GetOutputMinAndMaxForQuantizedAdd(input_min, input_max, bias_min, in Compute()
75 bias_ui8_array.size(), input_min, input_max, in Compute()
80 context->template eigen_device<CPUDevice>(), input, input_min, in Compute()
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| D | quantized_batch_norm_op.cc | 31 void ReferenceBatchNorm(const Tensor& input, const float input_min, in ReferenceBatchNorm() argument
57 QuantizedToFloat(input_flat(input_index), input_min, input_max); in ReferenceBatchNorm()
94 void FixedPointBatchNorm(const Tensor& input, const float input_min, in FixedPointBatchNorm() argument
150 RequantizeInNewRange<T1, T2>(input_flat(input_index), input_min, in FixedPointBatchNorm()
176 const float input_min = context->input(1).flat<float>()(0); in Compute() local
212 FixedPointBatchNorm<T1, T2>(input, input_min, input_max, mean, mean_min, in Compute()
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| D | quantized_concat_op.cc | 41 const float input_min = (*input_min_and_max)[input_index].first; in Copy() local
43 if (input_min == output_min && input_max == output_max) { in Copy()
52 QuantizedToFloatStruct<T> q2f(input_min, input_max); in Copy()
87 const float input_min = input_mins[i].flat<float>()(0); in CalculateInputAndOutputRange() local
89 input_mins_and_maxes->emplace_back(input_min, input_max); in CalculateInputAndOutputRange()
90 overall_min = std::min(overall_min, input_min); in CalculateInputAndOutputRange()
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| D | quantized_batch_norm_op_test.cc | 61 const float input_min = -128.0f; in TEST_F() local
72 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
100 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
158 const float input_min = -128.0f; in TEST_F() local
169 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
197 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
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| D | quantize_and_dequantize_op.h | 43 auto input_min = input_min_tensor->scalar<T>(); in Compute() local
46 input_min.device(d) = input.minimum(); in Compute()
49 d.memcpyDeviceToHost(&min_range, input_min.data(), sizeof(T)); in Compute()
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| D | quantization_utils.cc | 20 void GetOutputMinAndMaxForQuantizedAdd(float input_min, float input_max, in GetOutputMinAndMaxForQuantizedAdd() argument
36 std::max(input_max, std::max(-input_min, std::max(smaller_input_max, in GetOutputMinAndMaxForQuantizedAdd()
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| D | meta_support.cc | 257 float input_min, float input_max, float output_min, in Requantize() argument
269 params.kernel.input_range_min = input_min; in Requantize()
272 CalculateRangeScale<int32_t>(input_min, input_max); in Requantize()
348 float input_min, float input_max, float bias_min, in QuantizedBiasAdd() argument
363 params.kernel.input_range_min = input_min; in QuantizedBiasAdd()
366 CalculateRangeScale<uint8_t>(input_min, input_max); in QuantizedBiasAdd()
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| D | meta_support.h | 80 float input_min, float input_max, float output_min,
100 float input_min, float input_max, float bias_min,
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| D | quantized_instance_norm.cc | 277 float input_min = context->input(1).flat<float>()(0); in Compute() local
279 float input_scale = (input_max - input_min) / 255.0f; in Compute()
281 OP_REQUIRES(context, input_min < input_max, in Compute()
283 "input_min must be less than input_max : ", input_min, in Compute()
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| D | quantization_utils.h | 796 void GetOutputMinAndMaxForQuantizedAdd(float input_min, float input_max,
805 const Tensor& input, float input_min, in QuantizedAddUsingEigen() argument
814 GetOutputMinAndMaxForQuantizedAdd(input_min, input_max, smaller_input_min, in QuantizedAddUsingEigen()
826 QuantizedToFloatStruct<T1> input_q2f(input_min, input_max); in QuantizedAddUsingEigen()
853 float input_min, float input_max, const Tensor& smaller_input, in QuantizedAdd() argument
860 GetOutputMinAndMaxForQuantizedAdd(input_min, input_max, smaller_input_min, in QuantizedAdd()
886 input_value, input_min, input_max, total_min, total_max); in QuantizedAdd()
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| /external/tensorflow/tensorflow/core/graph/ |
| D | quantize_training.cc | 54 float input_min; member
63 input_min(min), in EdgeToConvert()
80 bool* range_given, float* input_min, float* input_max) { in FindType() argument
95 *input_min = 0; in FindType()
100 *input_min = 0; in FindType()
105 *input_min = -1; in FindType()
113 FindType(graph, edge->src(), signed_input, range_given, input_min, in FindType()
123 FindType(graph, edge->src(), signed_input, range_given, input_min, in FindType()
498 std::vector<Node*>* added_variables, Node** input_min, in MakeInputMinMax() argument
504 input_min_tensor.flat<float>()(0) = edge.input_min; in MakeInputMinMax()
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | fake_quantize_ops.cc | 106 float input_min, input_max; in FakeQuantWithMinMaxArgsOp() local
107 OP_REQUIRES_OK(ctx, ctx->GetAttr("min", &input_min)); in FakeQuantWithMinMaxArgsOp()
109 CpuNudge(input_min, input_max, quant_min_, quant_max_, &nudged_input_min_, in FakeQuantWithMinMaxArgsOp()
154 float input_min, input_max, scale; in FakeQuantWithMinMaxArgsGradOp() local
155 OP_REQUIRES_OK(ctx, ctx->GetAttr("min", &input_min)); in FakeQuantWithMinMaxArgsGradOp()
157 CpuNudge(input_min, input_max, quant_min, quant_max, &nudged_input_min_, in FakeQuantWithMinMaxArgsGradOp()
209 xla::ComputationDataHandle input_min = ctx->Input(1); in Compile() local
214 XlaNudge(b, data_type, input_min, input_max, quant_min_, quant_max_, in Compile()
250 xla::ComputationDataHandle input_min = ctx->Input(2); in Compile() local
255 XlaNudge(b, data_type, input_min, input_max, quant_min_, quant_max_, in Compile()
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| D | quantize_and_dequantize_op.cc | 50 xla::ComputationDataHandle input_min, input_max; in Compile() local
55 input_min = XlaHelpers::FloatLiteral(b, data_type, input_min_value); in Compile()
60 input_min = in Compile()
65 xla::ComputationDataHandle m = b->Max(b->Abs(input_min), b->Abs(input_max)); in Compile()
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | fake_quant_ops_test.py | 82 def _TestOp(self, input_min, input_max, num_bits, narrow_range, argument
116 min=input_min,
180 def _TestOp(self, input_min, input_max, num_bits, narrow_range, argument
210 min=input_min,
281 def _TestOp(self, input_min, input_max, num_bits, narrow_range, argument
324 min_placeholder: input_min,
386 def _TestOp(self, input_min, input_max, num_bits, narrow_range, argument
428 min_placeholder: input_min,
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_Requantize.pbtxt | 4 name: "input_min"
55 [input_min, input_max] are scalar floats that specify the range for the float
56 interpretation of the 'input' data. For example, if input_min is -1.0f and
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| D | api_def_QuantizedReshape.pbtxt | 10 name: "input_min"
24 This value is copied from input_min.
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| D | api_def_RequantizationRange.pbtxt | 4 name: "input_min"
33 summary: "Given a quantized tensor described by (input, input_min, input_max), outputs a"
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| D | api_def_QuantizeDownAndShrinkRange.pbtxt | 4 name: "input_min"
44 [input_min, input_max] are scalar floats that specify the range for the float
45 interpretation of the 'input' data. For example, if input_min is -1.0f and
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| D | api_def_QuantizeAndDequantizeV2.pbtxt | 10 name: "input_min"
57 1. m = max(abs(input_min), abs(input_max)) if range_given is true,
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| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| D | reduce_test.cc | 614 auto input_min = FLT_MAX; in XLA_TEST_F() local
616 [&](int64, int64, float* v) { input_min = std::min(input_min, *v); }); in XLA_TEST_F()
617 ComputeAndCompareR0<float>(&builder, input_min, {}, ErrorSpec(0.0001)); in XLA_TEST_F()
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| /external/tensorflow/tensorflow/tools/graph_transforms/ |
| D | quantize_nodes.cc | 315 float input_min; in QuantizePlaceholders() local
319 &input_min, &input_max, in QuantizePlaceholders()
345 min_tensor.flat<float>()(0) = input_min; in QuantizePlaceholders()
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