| /external/toybox/tests/ |
| cmp.test | 16 c" > input2
18 testing "identical files, stdout" "cmp input input2" "" "ab\nc\n" ""
19 testing "identical files, return code" "cmp input input2 && echo yes" "yes\n" "ab\nc\n" ""
21 testing "EOF, stderr" "cmp input input2 2>&1" "cmp: EOF on input2\n" "ab\nc\nx" ""
22 testing "EOF, return code" "cmp input input2 2>/dev/null || echo yes" "yes\n" "ab\nc\nx" ""
24 testing "diff, stdout" "cmp input input2" "input input2 differ: char 4, line 2\n" "ab\nx\nx" ""
25 testing "diff, return code" "cmp input input2 > /dev/null || echo yes" "yes\n" "ab\nx\nx" ""
27 testing "-s EOF, return code" "cmp -s input input2 2>&1 || echo yes" "yes\n" "ab\nc\nx" "
[all...] |
| /external/tensorflow/tensorflow/lite/kernels/ |
| floor_mod.cc | 49 T FloorMod(T input1, T input2) {
54 T trunc_mod = mod_func(input1, input2);
55 return (input1 < T(0)) == (input2 < T(0))
57 : mod_func(trunc_mod + input2, input2);
78 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
81 TF_LITE_ENSURE_TYPES_EQ(context, input1->type, input2->type);
91 data->requires_broadcast = !HaveSameShapes(input1, input2);
96 context, input1, input2, &output_size));
106 const TfLiteTensor* input1, const TfLiteTensor* input2,
139 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
[all...] |
| squared_difference.cc | 38 T SquaredDifference(T input1, T input2) {
39 const T difference = input1 - input2;
60 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
63 TF_LITE_ENSURE_EQ(context, input1->type, input2->type);
64 output->type = input2->type;
66 data->requires_broadcast = !HaveSameShapes(input1, input2);
71 context, input1, input2, &output_size));
82 const TfLiteTensor* input2, TfLiteTensor* output) {
86 GetTensorShape(input2), GetTensorData<T>(input2),
100 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
[all...] |
| comparisons.cc | 37 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
44 TF_LITE_ENSURE_TYPES_EQ(context, input1->type, input2->type);
47 bool requires_broadcast = !HaveSameShapes(input1, input2);
52 context, input1, input2, &output_size));
65 const TfLiteTensor* input2, TfLiteTensor* output, \
69 auto input2_offset = -input2->params.zero_point; \
78 QuantizeMultiplierSmallerThanOneExp(input2->params.scale, \
92 GetTensorData<input_dtype>(input1), GetTensorShape(input2), \
93 GetTensorData<input_dtype>(input2), GetTensorShape(output), \
98 GetTensorData<input_dtype>(input1), GetTensorShape(input2), \
128 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
164 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
199 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
231 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
263 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
295 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
[all...] |
| floor_div.cc | 38 T FloorDiv(T input1, T input2) {
40 static_cast<double>(input2)));
61 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
64 TF_LITE_ENSURE_EQ(context, input1->type, input2->type);
73 data->requires_broadcast = !HaveSameShapes(input1, input2);
78 context, input1, input2, &output_size));
88 const TfLiteTensor* input1, const TfLiteTensor* input2,
90 const T* denominator_data = GetTensorData<T>(input2);
93 for (int i = 0; i < NumElements(input2); ++i) {
102 GetTensorShape(input2), denominator_data, GetTensorShape(output)
118 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
[all...] |
| pow.cc | 54 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
57 TF_LITE_ENSURE_EQ(context, input1->type, input2->type);
66 data->requires_broadcast = !HaveSameShapes(input1, input2);
71 context, input1, input2, &output_size));
80 void PowImpl(const TfLiteTensor* input1, const TfLiteTensor* input2,
85 GetTensorShape(input2), GetTensorData<T>(input2),
89 GetTensorShape(input2), GetTensorData<T>(input2),
111 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2) local
[all...] |
| floor_div_test.cc | 29 FloorDivModel(const TensorData& input1, const TensorData& input2,
32 input2_ = AddInput(input2);
40 int input2() { return input2_; } function in class:tflite::__anon46027::FloorDivModel
56 model.PopulateTensor<int32_t>(model.input2(), {2, 2, 3, 4});
67 model.PopulateTensor<int32_t>(model.input2(), {2, 2, -3, -4});
77 model.PopulateTensor<int32_t>(model.input2(), {-3});
|
| pow_test.cc | 30 PowOpModel(const TensorData& input1, const TensorData& input2,
33 input2_ = AddInput(input2);
41 int input2() { return input2_; } function in class:tflite::__anon46078::PowOpModel
57 model.PopulateTensor<int32_t>(model.input2(), {1, 2, 3, 1});
68 model.PopulateTensor<int32_t>(model.input2(), {1, 2, 3, 0});
79 model.PopulateTensor<float>(model.input2(), {0.5, 2.7, 3.1, 3.2});
92 model.PopulateTensor<float>(model.input2(), {0.5, -2.7, 3.1, -3.2});
104 model.PopulateTensor<int32_t>(model.input2(), {4});
|
| mul.cc | 71 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
74 TF_LITE_ENSURE_EQ(context, input1->type, input2->type);
76 data->requires_broadcast = !HaveSameShapes(input1, input2);
81 context, input1, input2, &output_size));
100 input1->params.scale * input2->params.scale / output->params.scale;
111 const TfLiteTensor* input2, TfLiteTensor* output) {
120 GetTensorData<data_type>(input1), GetTensorShape(input2), \
121 GetTensorData<data_type>(input2), GetTensorShape(output), \
160 const TfLiteTensor* input2, TfLiteTensor* output) {
161 if (input1->type == input2->type && input1->type == output->type &
250 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
[all...] |
| div_test.cc | 28 BaseDivOpModel(const TensorData& input1, const TensorData& input2,
32 input2_ = AddInput(input2);
40 int input2() { return input2_; } function in class:tflite::__anon46012::BaseDivOpModel
67 m.PopulateTensor<float>(m.input2(), {0.5, 0.2, -1.5, 0.5});
78 m.PopulateTensor<float>(m.input2(), {0.1, 0.2, -1.5, 0.5});
92 m.PopulateTensor<float>(m.input2(), {0.1, 0.2, 0.6, 0.5, -1.1, -0.1});
109 m.PopulateTensor<float>(m.input2(), {0.1});
123 m.PopulateTensor<int32_t>(m.input2(), {5, -2, -3, 5});
133 m.PopulateTensor<int32_t>(m.input2(), {1, 2, -15, 5});
146 m.PopulateTensor<int32_t>(m.input2(), {1, 2, 6, 5, -11, -1})
[all...] |
| fill_test.cc | 29 explicit FillOpModel(const TensorData& input1, const TensorData& input2) {
31 input2_ = AddInput(input2);
39 int input2() { return input2_; } function in class:tflite::__anon46025::FillOpModel
51 m.PopulateTensor<int32_t>(m.input2(), {-11});
61 m.PopulateTensor<int64_t>(m.input2(), {2 ^ 45});
72 m.PopulateTensor<float>(m.input2(), {4.0});
81 m.PopulateTensor<float>(m.input2(), {4.0});
|
| div.cc | 61 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
64 TF_LITE_ENSURE_EQ(context, input1->type, input2->type);
65 output->type = input2->type;
67 data->requires_broadcast = !HaveSameShapes(input1, input2);
72 context, input1, input2, &output_size));
83 const TfLiteTensor* input2, TfLiteTensor* output) {
92 GetTensorData<data_type>(input1), GetTensorShape(input2), \
93 GetTensorData<data_type>(input2), GetTensorShape(output), \
133 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
137 EvalDiv<kernel_type>(context, node, params, data, input1, input2, output)
[all...] |
| floor_mod_test.cc | 29 FloorModModel(const TensorData& input1, const TensorData& input2,
32 input2_ = AddInput(input2);
40 int input2() { return input2_; } function in class:tflite::__anon46029::FloorModModel
56 model.PopulateTensor<int32_t>(model.input2(), {2, 2, 3, 4});
67 model.PopulateTensor<int32_t>(model.input2(), {2, 2, -3, -4});
77 model.PopulateTensor<int32_t>(model.input2(), {-3});
87 model.PopulateTensor<int64_t>(model.input2(), {-(1LL << 33)});
99 model.PopulateTensor<float>(model.input2(), {2, 2, 3, 4});
110 model.PopulateTensor<float>(model.input2(), {2, 2, -3, -4});
121 model.PopulateTensor<float>(model.input2(), {-3})
[all...] |
| logical.cc | 55 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
58 TF_LITE_ENSURE_EQ(context, input1->type, input2->type);
67 data->requires_broadcast = !HaveSameShapes(input1, input2);
72 context, input1, input2, &output_size));
85 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
91 GetTensorShape(input2), GetTensorData<bool>(input2),
95 GetTensorShape(input2), GetTensorData<bool>(input2),
|
| select_test.cc | 42 int input2() { return input2_; } function in class:tflite::__anon46091::SelectOpModel
64 model.PopulateTensor<bool>(model.input2(), {false, false, false, false});
78 model.PopulateTensor<float>(model.input2(), {0.1, 0.2, 0.3, 0.4});
91 model.PopulateTensor<uint8_t>(model.input2(), {1, 2, 3, 4});
104 model.PopulateTensor<int8_t>(model.input2(), {1, -2, 3, 4});
117 model.PopulateTensor<int16_t>(model.input2(), {1, 2, 3, 4});
130 model.PopulateTensor<int32_t>(model.input2(), {1, 2, 3, 4});
142 model.PopulateTensor<int32_t>(model.input2(), {1, 2, 3, 4});
154 model.PopulateTensor<int32_t>(model.input2(), {1, 2, 3, 4});
|
| squared_difference_test.cc | 29 const TensorData& input2,
32 input2_ = AddInput(input2);
41 int input2() { return input2_; } function in class:tflite::__anon46102::BaseSquaredDifferenceOpModel
68 m.PopulateTensor<float>(m.input2(), {0.5, 0.2, -1.5, 0.5});
82 m.PopulateTensor<float>(m.input2(), {1.0, 0.2, 0.6, 0.4, -1.0, -0.0});
100 m.PopulateTensor<float>(m.input2(), {0.1});
114 m.PopulateTensor<int32_t>(m.input2(), {5, -2, -3, 5});
127 m.PopulateTensor<int32_t>(m.input2(), {1, 2, 6, 5, -5, -20});
143 m.PopulateTensor<int32_t>(m.input2(), {3});
|
| add.cc | 80 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
83 TF_LITE_ENSURE_EQ(context, input1->type, input2->type);
84 output->type = input2->type;
86 data->requires_broadcast = !HaveSameShapes(input1, input2);
91 context, input1, input2, &output_size));
99 data->input2_offset = -input2->params.zero_point;
103 2 * std::max(input1->params.scale, input2->params.scale);
107 input2->params.scale / twice_max_input_scale;
140 TF_LITE_ENSURE_EQ(context, input2->params.zero_point, 0);
150 CheckedLog2(input2->params.scale, &input2_scale_log2_rounded)
304 const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2); local
[all...] |
| /external/ltp/testcases/kernel/device-drivers/v4l/user_space/ |
| test_VIDIOC_ENUMINPUT.c | 47 struct v4l2_input input2; local
84 memset(&input2, 0, sizeof(input2));
85 input2.index = input.index;
86 strncpy((char *)input2.name, (char *)input.name,
87 sizeof(input2.name));
88 input2.type = input.type;
89 input2.audioset = input.audioset;
90 input2.tuner = input.tuner;
91 input2.std = input.std
117 struct v4l2_input input2; local
139 struct v4l2_input input2; local
161 struct v4l2_input input2; local
[all...] |
| /external/compiler-rt/test/builtins/timing/ |
| divdi3.c | 16 INPUT_TYPE FUNCTION_NAME(INPUT_TYPE input1, INPUT_TYPE input2);
20 INPUT_TYPE input2[INPUT_SIZE]; local
28 input2[i] = ((((int64_t)rand() << 36) | (uint64_t)rand()) >> (rand() & 63)) + 1LL;
39 FUNCTION_NAME(input1[i], input2[i]);
|
| moddi3.c | 16 INPUT_TYPE FUNCTION_NAME(INPUT_TYPE input1, INPUT_TYPE input2);
20 INPUT_TYPE input2[INPUT_SIZE]; local
28 input2[i] = ((((int64_t)rand() << 36) | (uint64_t)rand()) >> (rand() & 63)) + 1LL;
39 FUNCTION_NAME(input1[i], input2[i]);
|
| modsi3.c | 16 INPUT_TYPE FUNCTION_NAME(INPUT_TYPE input1, INPUT_TYPE input2);
20 INPUT_TYPE input2[INPUT_SIZE]; local
28 input2[i] = rand() + 1;
39 FUNCTION_NAME(input1[i], input2[i]);
|
| muldi3.c | 16 INPUT_TYPE FUNCTION_NAME(INPUT_TYPE input1, INPUT_TYPE input2);
20 INPUT_TYPE input2[INPUT_SIZE]; local
28 input2[i] = (((int64_t)rand() << 36) | (uint64_t)rand()) >> (rand() & 63);
39 FUNCTION_NAME(input1[i], input2[i]);
|
| udivdi3.c | 16 INPUT_TYPE FUNCTION_NAME(INPUT_TYPE input1, INPUT_TYPE input2);
20 INPUT_TYPE input2[INPUT_SIZE]; local
28 input2[i] = ((((uint64_t)rand() << 36) | (uint64_t)rand()) >> (rand() & 63)) + 1LL;
39 FUNCTION_NAME(input1[i], input2[i]);
|
| umoddi3.c | 16 INPUT_TYPE FUNCTION_NAME(INPUT_TYPE input1, INPUT_TYPE input2);
20 INPUT_TYPE input2[INPUT_SIZE]; local
28 input2[i] = ((((uint64_t)rand() << 36) | (uint64_t)rand()) >> (rand() & 63)) + 1LL;
39 FUNCTION_NAME(input1[i], input2[i]);
|
| /external/libaom/libaom/test/ |
| corner_match_test.cc | 63 uint8_t *input2 = new uint8_t[w * h]; local
73 input2[i * w + j] = rnd_.Rand8();
80 input2[i * w + j] = (v / 2) + (rnd_.Rand8() & 15);
91 compute_cross_correlation_c(input1, w, x1, y1, input2, w, x2, y2);
92 double res_simd = target_func(input1, w, x1, y1, input2, w, x2, y2);
97 compute_cross_correlation_c(input1, w, x1, y1, input2, w, x2, y2);
105 target_func(input1, w, x1, y1, input2, w, x2, y2);
121 delete[] input2;
|
