| /external/tensorflow/tensorflow/lite/micro/kernels/ |
| D | pooling_test.cc | 100 std::initializer_list<T> input_data, const float input_min, in TestAveragePoolingQuantized() argument
117 CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min, in TestAveragePoolingQuantized()
242 std::initializer_list<T> input_data, float input_min, in TestMaxPoolQuantized() argument
260 CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min, in TestMaxPoolQuantized()
342 const float input_min = -15.9375; in TF_LITE_MICRO_TEST() local
351 F2Q(0., input_min, input_max), in TF_LITE_MICRO_TEST()
352 F2Q(-6., input_min, input_max), in TF_LITE_MICRO_TEST()
353 F2Q(2., input_min, input_max), in TF_LITE_MICRO_TEST()
354 F2Q(4., input_min, input_max), in TF_LITE_MICRO_TEST()
355 F2Q(3., input_min, input_max), in TF_LITE_MICRO_TEST()
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| D | fully_connected_test.cc | 99 const int* input_dims_data, const T* input_data, const float input_min, in TestFullyConnectedQuantized() argument
116 CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min, in TestFullyConnectedQuantized()
264 const float input_min = -63.5f; in TF_LITE_MICRO_TEST() local
274 F2Q(1, input_min, input_max), F2Q(2, input_min, input_max), in TF_LITE_MICRO_TEST()
275 F2Q(3, input_min, input_max), F2Q(4, input_min, input_max), in TF_LITE_MICRO_TEST()
276 F2Q(5, input_min, input_max), F2Q(6, input_min, input_max), in TF_LITE_MICRO_TEST()
277 F2Q(7, input_min, input_max), F2Q(8, input_min, input_max), in TF_LITE_MICRO_TEST()
278 F2Q(-9, input_min, input_max), F2Q(-10, input_min, input_max), in TF_LITE_MICRO_TEST()
279 F2Q(1, input_min, input_max), F2Q(2, input_min, input_max), in TF_LITE_MICRO_TEST()
280 F2Q(3, input_min, input_max), F2Q(4, input_min, input_max), in TF_LITE_MICRO_TEST()
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| D | mul_test.cc | 99 const float input_min, const float input_max, in TestMulQuantized() argument
117 input_min, input_max), in TestMulQuantized()
119 input_min, input_max), in TestMulQuantized()
178 const float input_min = -1; in TF_LITE_MICRO_TEST() local
186 F2QS(-0.8, input_min, input_max), in TF_LITE_MICRO_TEST()
187 F2QS(0.2, input_min, input_max), in TF_LITE_MICRO_TEST()
188 F2QS(0.9, input_min, input_max), in TF_LITE_MICRO_TEST()
189 F2QS(0.7, input_min, input_max), in TF_LITE_MICRO_TEST()
193 F2QS(0.6, input_min, input_max), in TF_LITE_MICRO_TEST()
194 F2QS(0.4, input_min, input_max), in TF_LITE_MICRO_TEST()
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| D | softmax_test.cc | 90 float input_min, float input_max, in TestSoftmaxQuantized() argument
103 CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min, in TestSoftmaxQuantized()
157 std::initializer_list<int8_t> input_data, float input_min, float input_max, in TestSoftmaxQuantizedSigned() argument
169 CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min, in TestSoftmaxQuantizedSigned()
256 const float input_min = -63.5f; in TF_LITE_MICRO_TEST() local
265 F2Q(1.0, input_min, input_max), in TF_LITE_MICRO_TEST()
266 F2Q(2.0, input_min, input_max), in TF_LITE_MICRO_TEST()
267 F2Q(3.0, input_min, input_max), in TF_LITE_MICRO_TEST()
268 F2Q(4.0, input_min, input_max), in TF_LITE_MICRO_TEST()
269 F2Q(5.0, input_min, input_max), in TF_LITE_MICRO_TEST()
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| D | concatenation_test.cc | 90 std::initializer_list<uint8_t> input2_data, float input_min, in TestConcatenateQuantizedTwoInputs() argument
103 input_min, input_max), in TestConcatenateQuantizedTwoInputs()
105 input_min, input_max), in TestConcatenateQuantizedTwoInputs()
200 const float input_min = -12.7f; in TF_LITE_MICRO_TEST() local
206 F2Q(1.0, input_min, input_max), in TF_LITE_MICRO_TEST()
207 F2Q(3.0, input_min, input_max), in TF_LITE_MICRO_TEST()
208 F2Q(4.0, input_min, input_max), in TF_LITE_MICRO_TEST()
209 F2Q(7.0, input_min, input_max), in TF_LITE_MICRO_TEST()
213 F2Q(1.1, input_min, input_max), in TF_LITE_MICRO_TEST()
214 F2Q(3.1, input_min, input_max), in TF_LITE_MICRO_TEST()
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| /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 | mkl_quantized_pooling_ops_test.cc | 81 const float input_min = 0.0f; in TEST_F() local
92 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
110 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
150 const float input_min = 0.0f; in TEST_F() local
161 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
178 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 | mkl_requantization_range_per_channel_op.cc | 46 const Tensor& input_min = ctx->input(kInputMinIndex); in Compute() local
51 ctx, input_min.dim_size(0) == depth, in Compute()
53 depth, " was ", input_min.dim_size(0))); in Compute()
59 const float* input_min_data = input_min.flat<float>().data(); 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 | 60 const float input_min = -128.0f; in TEST_F() local
71 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
99 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
157 const float input_min = -128.0f; in TEST_F() local
168 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); in TEST_F()
196 AddInputFromArray<float>(TensorShape({1}), {input_min}); in TEST_F()
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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 | quantize_and_dequantize_op.h | 167 auto input_min = input_min_tensor->scalar<T>(); in Compute() local
170 input_min.device(d) = input.minimum(); in Compute()
172 d.memcpyDeviceToHost(&min_range, input_min.data(), sizeof(T)); in Compute()
208 auto input_min = input_min_tensor->vec<T>(); in Compute() local
219 input_min.device(d) = input.minimum(reduce_dims); in Compute()
221 d.memcpyDeviceToHost(min_range.data(), input_min.data(), in Compute()
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_QuantizeAndDequantizeV2.pbtxt | 10 name: "input_min"
92 If range_given == False, the initial input_min, input_max will be determined
94 the specified values of input_min, input_max are used.
96 Note: If the input_min, input_max are specified, they do not need to equal the
102 [input_min, input_max] range to a range that lies within the representable
105 It determines the scale from one of input_min and input_max, then updates the
110 * if the output is signed, num_bits = 8, [input_min, input_max] = [-10.0,
113 * if the output is signed, num_bits = 8, [input_min, input_max] = [-10.0,
115 would update input_min to be 128.0 / 12.7 = -10.07874
116 * if the output is unsigned, input_min is forced to be 0, and only the
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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()
504 std::vector<Node*>* added_variables, Node** input_min, in MakeInputMinMax() argument
510 input_min_tensor.flat<float>()(0) = edge.input_min; in MakeInputMinMax()
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | QuantizeAndDequantizeV2.pbtxt | 8 name: "input_min"
58 name: "input_min"
109 name: "input_min"
161 name: "input_min"
226 name: "input_min"
298 name: "input_min"
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| D | QuantizeAndDequantizeV3.pbtxt | 8 name: "input_min"
55 name: "input_min"
103 name: "input_min"
152 name: "input_min"
208 name: "input_min"
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| D | QuantizeAndDequantize.pbtxt | 33 name: "input_min"
89 name: "input_min"
148 name: "input_min"
207 name: "input_min"
267 name: "input_min"
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | fake_quantize_ops.cc | 89 xla::XlaBuilder* b, xla::XlaOp input, xla::XlaOp input_min, in BuildFakeQuantCustomCall() argument
97 std::vector<xla::XlaOp> args = {input, input_min, input_max, num_bits_arg, in BuildFakeQuantCustomCall()
190 float input_min, input_max, scale; in FakeQuantWithMinMaxArgsGradOp() local
191 OP_REQUIRES_OK(ctx, ctx->GetAttr("min", &input_min)); in FakeQuantWithMinMaxArgsGradOp()
193 CpuNudge(input_min, input_max, quant_min, quant_max, &nudged_input_min_, in FakeQuantWithMinMaxArgsGradOp()
243 xla::XlaOp input_min = ctx->Input(1); in Compile() local
250 b, input, input_min, input_max, num_bits_, narrow_range_)); in Compile()
256 XlaNudge(b, data_type, input_min, input_max, quant_min_, quant_max_, in Compile()
296 xla::XlaOp input_min = ctx->Input(2); in Compile() local
301 XlaNudge(b, data_type, input_min, input_max, quant_min_, quant_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/lite/kernels/ |
| D | activations_test.cc | 314 void TestQuantizedHardSwish(TensorType tensor_type, int size, float input_min, in TestQuantizedHardSwish() argument
318 GenerateUniformRandomVector(size, input_min, input_max, random_engine, in TestQuantizedHardSwish()
328 /*input=*/{tensor_type, {1, 1, 1, size}, input_min, input_max}, in TestQuantizedHardSwish()
340 std::max(input_max - input_min, output_max - output_min) * (1.5f / 256.f); in TestQuantizedHardSwish()
346 void TestQuantizedHardSwishBias(TensorType tensor_type, float input_min, in TestQuantizedHardSwishBias() argument
352 const float input_scale = (input_max - input_min) / quantized_type_range; in TestQuantizedHardSwishBias()
358 ASSERT_LE(input_min, -3.0f); in TestQuantizedHardSwishBias()
362 (-3.0f - input_min) / input_scale); in TestQuantizedHardSwishBias()
365 (3.0f - input_min) / input_scale); in TestQuantizedHardSwishBias()
370 input_min + in TestQuantizedHardSwishBias()
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