| /external/tensorflow/tensorflow/core/kernels/ |
| quantization_utils.cc | 20 void GetOutputMinAndMaxForQuantizedAdd(float input_min, float input_max,
36 std::max(input_max, std::max(-input_min, std::max(smaller_input_max,
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| 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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| 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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| 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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| mkl_requantization_range_per_channel_op.cc | 46 const Tensor& input_min = ctx->input(kInputMinIndex); variable
51 ctx, input_min.dim_size(0) == depth,
52 errors::InvalidArgument("input_min has incorrect size, expected ",
53 depth, " was ", input_min.dim_size(0)));
59 const float* input_min_data = input_min.flat<float>().data();
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| 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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| quantization_utils_test.cc | 34 void TestRequantizeMany(Eigen::ThreadPoolDevice* eigen_device, float input_min,
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,
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=" << input_mi
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...] |
| meta_support.h | 75 // Take an array of numbers from the range [input_min, input_max] quantized
80 float input_min, float input_max, float output_min,
94 // [input_min, input_max], and [bias_min, bias_max] accordingly, as uint8
100 float input_min, float input_max, float bias_min,
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| mkl_quantized_pooling_ops_test.cc | 81 const float input_min = 0.0f; local
92 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
110 AddInputFromArray<float>(TensorShape({1}), {input_min});
150 const float input_min = 0.0f; local
161 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
178 AddInputFromArray<float>(TensorShape({1}), {input_min});
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| quantized_batch_norm_op.cc | 31 void ReferenceBatchNorm(const Tensor& input, const float input_min,
57 QuantizedToFloat(input_flat(input_index), input_min, input_max);
94 void FixedPointBatchNorm(const Tensor& input, const float input_min,
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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| 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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| 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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| 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);
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| quantize_and_dequantize_op.h | 114 auto input_min = input_min_tensor->scalar<T>(); local
117 input_min.device(d) = input.minimum();
119 d.memcpyDeviceToHost(&min_range, input_min.data(), sizeof(T));
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| 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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| quantization_utils.h | [all...] |
| mkl_concat_op.cc | 249 float input_min = input_mins[0].flat<float>()(0); local
256 if (fabs(input_min - min) > eps || fabs(input_max - max) > eps) {
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| /external/tensorflow/tensorflow/lite/experimental/micro/kernels/ |
| fully_connected_test.cc | 103 std::initializer_list<uint8_t> input_data, float input_min, float input_max,
121 CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min,
266 const float input_min = -63.5f; local
280 F2Q(1, input_min, input_max), F2Q(2, input_min, input_max),
281 F2Q(3, input_min, input_max), F2Q(4, input_min, input_max),
282 F2Q(5, input_min, input_max), F2Q(6, input_min, input_max),
283 F2Q(7, input_min, input_max), F2Q(8, input_min, input_max)
337 const float input_min = -63.5f; local
408 const float input_min = -127.0f; local
505 const float input_min = -63.5f; local
576 const float input_min = -127.0f; local
[all...] |
| depthwise_conv_test.cc | 110 std::initializer_list<uint8_t> input_data, float input_min, float input_max,
128 CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min,
228 const float input_min = -63.5f; local
243 F2Q(1, input_min, input_max),
244 F2Q(2, input_min, input_max),
245 F2Q(7, input_min, input_max),
246 F2Q(8, input_min, input_max),
247 F2Q(3, input_min, input_max),
248 F2Q(4, input_min, input_max),
249 F2Q(9, input_min, input_max)
336 const float input_min = -63.5f; local
415 const float input_min = 0; local
[all...] |
| softmax_test.cc | 91 float input_min, float input_max,
104 CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min,
191 const float input_min = -63.5f; local
200 F2Q(1.0, input_min, input_max),
201 F2Q(2.0, input_min, input_max),
202 F2Q(3.0, input_min, input_max),
203 F2Q(4.0, input_min, input_max),
204 F2Q(5.0, input_min, input_max),
206 input_min, input_max, // Input quantized range.
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| /external/tensorflow/tensorflow/core/graph/ |
| quantize_training.cc | 54 float input_min; member in struct:tensorflow::__anon45051::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,
504 std::vector<Node*>* added_variables, Node** input_min,
507 // Make constant nodes for the input_min and input_max if the range i
540 Node* input_min; local
634 float input_min = 0; local
[all...] |
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| fake_quantize_ops.cc | 100 float input_min, input_max; local
101 OP_REQUIRES_OK(ctx, ctx->GetAttr("min", &input_min));
103 CpuNudge(input_min, input_max, quant_min_, quant_max_, &nudged_input_min_,
148 float input_min, input_max, scale; local
149 OP_REQUIRES_OK(ctx, ctx->GetAttr("min", &input_min));
151 CpuNudge(input_min, input_max, quant_min, quant_max, &nudged_input_min_,
202 xla::XlaOp input_min = ctx->Input(1); variable
207 XlaNudge(b, data_type, input_min, input_max, quant_min_, quant_max_,
245 xla::XlaOp input_min = ctx->Input(2); variable
250 XlaNudge(b, data_type, input_min, input_max, quant_min_, quant_max_
[all...] |
| /external/tensorflow/tensorflow/compiler/tests/ |
| fake_quant_ops_test.py | 82 def _TestOp(self, input_min, input_max, num_bits, narrow_range,
116 min=input_min,
180 def _TestOp(self, input_min, input_max, num_bits, narrow_range,
210 min=input_min,
281 def _TestOp(self, input_min, input_max, num_bits, narrow_range,
324 min_placeholder: input_min,
386 def _TestOp(self, input_min, input_max, num_bits, narrow_range,
428 min_placeholder: input_min,
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| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| reduce_test.cc | 609 auto input_min = FLT_MAX; local
611 [&](int64, int64, float* v) { input_min = std::min(input_min, *v); });
612 ComputeAndCompareR0<float>(&builder, input_min, {}, ErrorSpec(0.0001));
[all...] |
| /external/tensorflow/tensorflow/tools/graph_transforms/ |
| quantize_nodes.cc | 308 // If the user has passed in the input_min and input_max args, then we need to
314 float input_min; local
317 TF_RETURN_IF_ERROR(ExtractRangeFromParams(context, "input_min", "input_max",
318 &input_min, &input_max,
344 min_tensor.flat<float>()(0) = input_min;
656 // If input_min and input max have been passed in, then we convert all float
[all...] |
