| /external/tensorflow/tensorflow/lite/kernels/ |
| D | select_test.cc | 87 SelectOpModel model({1, 1, 1, 4}, {1, 1, 1, 4}, {1, 1, 1, 4}, in TEST() local
90 model.PopulateTensor<bool>(model.input1(), {true, false, true, false}); in TEST()
91 model.PopulateTensor<bool>(model.input2(), {false, false, false, false}); in TEST()
92 model.PopulateTensor<bool>(model.input3(), {true, true, true, true}); in TEST()
93 model.Invoke(); in TEST()
95 EXPECT_THAT(model.GetOutput<bool>(), in TEST()
97 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 1, 4})); in TEST()
101 SelectOpModel model({1, 1, 1, 4}, {1, 1, 1, 4}, {1, 1, 1, 4}, in TEST() local
104 model.PopulateTensor<bool>(model.input1(), {true, false, true, false}); in TEST()
105 model.PopulateTensor<float>(model.input2(), {0.1, 0.2, 0.3, 0.4}); in TEST()
[all …]
|
| D | comparisons_test.cc | 103 ComparisonOpModel model({1, 1, 1, 4}, {1, 1, 1, 4}, TensorType_BOOL, in TEST() local
105 model.PopulateTensor<bool>(model.input1(), {true, false, true, false}); in TEST()
106 model.PopulateTensor<bool>(model.input2(), {true, true, false, false}); in TEST()
107 model.Invoke(); in TEST()
109 EXPECT_THAT(model.GetOutput(), ElementsAre(true, false, false, true)); in TEST()
110 EXPECT_THAT(model.GetOutputShape(), ElementsAre(1, 1, 1, 4)); in TEST()
114 ComparisonOpModel model({1, 1, 1, 4}, {1, 1, 1, 4}, TensorType_FLOAT32, in TEST() local
116 model.PopulateTensor<float>(model.input1(), {0.1, 0.9, 0.7, 0.3}); in TEST()
117 model.PopulateTensor<float>(model.input2(), {0.1, 0.2, 0.6, 0.5}); in TEST()
118 model.Invoke(); in TEST()
[all …]
|
| D | mirror_pad_test.cc | 54 BaseMirrorPadOpModel<int> model( in TEST() local
57 model.PopulateTensor<int>(model.input_tensor_id(), {1, 2, 3, 4, 5, 6}); in TEST()
58 model.PopulateTensor<int>(model.padding_matrix_tensor_id(), {0, 0, 0, 0}); in TEST()
59 model.Invoke(); in TEST()
60 EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6})); in TEST()
64 BaseMirrorPadOpModel<int> model( in TEST() local
67 model.PopulateTensor<int>(model.input_tensor_id(), {1, 2, 3, 4, 5, 6}); in TEST()
68 model.PopulateTensor<int>(model.padding_matrix_tensor_id(), {0, 1, 0, 1}); in TEST()
69 model.Invoke(); in TEST()
70 EXPECT_THAT(model.GetOutput(), in TEST()
[all …]
|
| D | pack_test.cc | 61 PackOpModel<float> model({TensorType_FLOAT32, {2}}, 0, 3); in TEST() local
62 model.SetInput(0, {1, 4}); in TEST()
63 model.SetInput(1, {2, 5}); in TEST()
64 model.SetInput(2, {3, 6}); in TEST()
65 model.Invoke(); in TEST()
66 EXPECT_THAT(model.GetOutputShape(), ElementsAre(3, 2)); in TEST()
67 EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 4, 2, 5, 3, 6})); in TEST()
71 PackOpModel<float> model({TensorType_FLOAT32, {2}}, 1, 3); in TEST() local
72 model.SetInput(0, {1, 4}); in TEST()
73 model.SetInput(1, {2, 5}); in TEST()
[all …]
|
| D | reverse_test.cc | 57 ReverseOpModel<float> model({TensorType_FLOAT32, {4}}, in TEST() local
59 model.PopulateTensor<float>(model.input(), {1, 2, 3, 4}); in TEST()
60 model.PopulateTensor<int32_t>(model.axis(), {0}); in TEST()
61 model.Invoke(); in TEST()
63 EXPECT_THAT(model.GetOutputShape(), ElementsAre(4)); in TEST()
64 EXPECT_THAT(model.GetOutput(), ElementsAreArray({4, 3, 2, 1})); in TEST()
68 ReverseOpModel<float> model({TensorType_FLOAT32, {4, 3, 2}}, in TEST() local
70 model.PopulateTensor<float>(model.input(), in TEST()
73 model.PopulateTensor<int32_t>(model.axis(), {1}); in TEST()
74 model.Invoke(); in TEST()
[all …]
|
| D | reverse_sequence_test.cc | 59 ReverseSequenceOpModel<float> model({TensorType_FLOAT32, {4, 3, 2}}, in TEST() local
61 model.PopulateTensor<float>(model.input(), in TEST()
64 model.PopulateTensor<int32_t>(model.seq_lengths(), {3, 2, 3, 3}); in TEST()
65 model.Invoke(); in TEST()
66 EXPECT_THAT(model.GetOutputShape(), ElementsAre(4, 3, 2)); in TEST()
68 model.GetOutput(), in TEST()
74 ReverseSequenceOpModel<float> model({TensorType_FLOAT32, {4, 3, 2}}, in TEST() local
76 model.PopulateTensor<float>(model.input(), in TEST()
79 model.PopulateTensor<int32_t>(model.seq_lengths(), {3, 4}); in TEST()
80 model.Invoke(); in TEST()
[all …]
|
| D | range_test.cc | 56 RangeOpModel<int32_t> model(TensorType_INT32); in TEST() local
57 model.PopulateTensor<int32_t>(model.start(), {0}); in TEST()
58 model.PopulateTensor<int32_t>(model.limit(), {4}); in TEST()
59 model.PopulateTensor<int32_t>(model.delta(), {1}); in TEST()
60 model.Invoke(); in TEST()
61 EXPECT_THAT(model.GetOutputShape(), ElementsAre(4)); in TEST()
62 EXPECT_THAT(model.GetOutput(), ElementsAre(0, 1, 2, 3)); in TEST()
66 RangeOpModel<int32_t> model(TensorType_INT32); in TEST() local
67 model.PopulateTensor<int32_t>(model.start(), {2}); in TEST()
68 model.PopulateTensor<int32_t>(model.limit(), {9}); in TEST()
[all …]
|
| D | segment_sum_test.cc | 51 SegmentSumOpModel<int32_t> model({TensorType_INT32, {3, 4}}, in TEST() local
53 model.PopulateTensor<int32_t>(model.data(), in TEST()
55 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 0, 1}); in TEST()
56 model.Invoke(); in TEST()
57 EXPECT_THAT(model.GetOutput(), ElementsAreArray({5, 5, 5, 5, 5, 6, 7, 8})); in TEST()
58 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2, 4})); in TEST()
62 SegmentSumOpModel<int32_t> model({TensorType_INT32, {3}}, in TEST() local
64 model.PopulateTensor<int32_t>(model.data(), {1, 2, 3}); in TEST()
65 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 0, 1}); in TEST()
66 model.Invoke(); in TEST()
[all …]
|
| D | floor_mod_test.cc | 55 FloorModModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TEST() local
58 model.PopulateTensor<int32_t>(model.input1(), {10, 9, 11, 3}); in TEST()
59 model.PopulateTensor<int32_t>(model.input2(), {2, 2, 3, 4}); in TEST()
60 model.Invoke(); in TEST()
61 EXPECT_THAT(model.GetOutputShape(), ElementsAre(1, 2, 2, 1)); in TEST()
62 EXPECT_THAT(model.GetOutput(), ElementsAre(0, 1, 2, 3)); in TEST()
66 FloorModModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TEST() local
69 model.PopulateTensor<int32_t>(model.input1(), {10, -9, -11, 7}); in TEST()
70 model.PopulateTensor<int32_t>(model.input2(), {2, 2, -3, -4}); in TEST()
71 model.Invoke(); in TEST()
[all …]
|
| D | arg_min_max_test.cc | 126 void ValidateOutput(const ArgBaseOpModel& model, in ValidateOutput() argument
129 EXPECT_THAT(model.GetInt32Output(), ElementsAreArray(expected_output)); in ValidateOutput()
131 EXPECT_THAT(model.GetInt64Output(), ElementsAreArray(expected_output)); in ValidateOutput()
143 ArgMaxOpModel model({1, 1, 1, 4}, TensorType_FLOAT32, 3, AxisType(), in TEST_P() local
145 model.PopulateTensor<float>(model.input(), {0.1, 0.9, 0.7, 0.3}); in TEST_P()
146 model.Invoke(); in TEST_P()
148 ValidateOutput(model, {1}); in TEST_P()
149 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 1})); in TEST_P()
153 ArgMaxOpModel model({1, 1, 1, 4}, TensorType_UINT8, 3, AxisType(), in TEST_P() local
155 model.PopulateTensor<uint8_t>(model.input(), {1, 9, 7, 3}); in TEST_P()
[all …]
|
| D | pow_test.cc | 58 PowOpModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TEST() local
61 model.PopulateTensor<int32_t>(model.input1(), {12, 2, 7, 8}); in TEST()
62 model.PopulateTensor<int32_t>(model.input2(), {1, 2, 3, 1}); in TEST()
63 model.Invoke(); in TEST()
64 EXPECT_THAT(model.GetOutputShape(), ElementsAre(1, 2, 2, 1)); in TEST()
65 EXPECT_THAT(model.GetOutput(), ElementsAre(12, 4, 343, 8)); in TEST()
69 PowOpModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TEST() local
72 model.PopulateTensor<int32_t>(model.input1(), {0, 2, -7, 8}); in TEST()
73 model.PopulateTensor<int32_t>(model.input2(), {1, 2, 3, 0}); in TEST()
74 model.Invoke(); in TEST()
[all …]
|
| D | floor_div_test.cc | 55 FloorDivModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TEST() local
58 model.PopulateTensor<int32_t>(model.input1(), {10, 9, 11, 3}); in TEST()
59 model.PopulateTensor<int32_t>(model.input2(), {2, 2, 3, 4}); in TEST()
60 model.Invoke(); in TEST()
61 EXPECT_THAT(model.GetOutputShape(), ElementsAre(1, 2, 2, 1)); in TEST()
62 EXPECT_THAT(model.GetOutput(), ElementsAre(5, 4, 3, 0)); in TEST()
66 FloorDivModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TEST() local
69 model.PopulateTensor<int32_t>(model.input1(), {10, -9, -11, 7}); in TEST()
70 model.PopulateTensor<int32_t>(model.input2(), {2, 2, -3, -4}); in TEST()
71 model.Invoke(); in TEST()
[all …]
|
| D | one_hot_test.cc | 70 OneHotOpModel<float> model({3}, depth, TensorType_FLOAT32); in TEST() local
71 model.SetIndices({0, 1, 2}); in TEST()
72 model.Invoke(); in TEST()
74 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({3, 3})); in TEST()
75 EXPECT_THAT(model.GetOutput(), in TEST()
81 OneHotOpModel<int> model({3}, depth, TensorType_INT32); in TEST() local
82 model.SetIndices({0, 1, 2}); in TEST()
83 model.Invoke(); in TEST()
85 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({3, 3})); in TEST()
86 EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 0, 0, 0, 1, 0, 0, 0, 1})); in TEST()
[all …]
|
| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | sequential_test.py | 45 model = keras.models.Sequential()
46 model.add(keras.layers.Dense(1, input_dim=2))
47 model.add(keras.layers.Dropout(0.3, name='dp'))
48 model.add(keras.layers.Dense(2, kernel_regularizer='l2',
50 self.assertEqual(len(model.layers), 3)
51 self.assertEqual(len(model.weights), 2 * 2)
52 self.assertEqual(model.get_layer(name='dp').name, 'dp')
56 model = keras.models.Sequential()
57 model.add(keras.Input(shape=(2,), name='input_layer'))
58 model.add(keras.layers.Dense(1))
[all …]
|
| D | deferred_sequential_test.py | 43 model = get_model()
44 model(np.random.random((2, 6)))
45 self.assertLen(model.weights, 4)
46 self.assertTrue(model._is_graph_network)
47 self.assertLen(model.inputs, 1)
48 self.assertLen(model.outputs, 1)
49 self.assertEqual(model.inputs[0].shape.as_list(), [2, 6])
50 self.assertEqual(model.outputs[0].shape.as_list(), [2, 2])
53 model(np.random.random((3, 6)))
54 self.assertLen(model.inputs, 1)
[all …]
|
| /external/tensorflow/tensorflow/lite/micro/kernels/ |
| D | floor_mod_test.cc | 32 FloorMod<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TF_LITE_MICRO_TEST() local
35 model.PopulateTensor<int32_t>(model.input1(), {10, 9, 11, 3}); in TF_LITE_MICRO_TEST()
36 model.PopulateTensor<int32_t>(model.input2(), {2, 2, 3, 4}); in TF_LITE_MICRO_TEST()
37 EXPECT_THAT(model.GetOutput(), ElementsAre(0, 1, 2, 3)); in TF_LITE_MICRO_TEST()
43 FloorMod<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TF_LITE_MICRO_TEST() local
46 model.PopulateTensor<int32_t>(model.input1(), {10, -9, -11, 7}); in TF_LITE_MICRO_TEST()
47 model.PopulateTensor<int32_t>(model.input2(), {2, 2, -3, -4}); in TF_LITE_MICRO_TEST()
48 EXPECT_THAT(model.GetOutput(), ElementsAre(0, 1, -2, -1)); in TF_LITE_MICRO_TEST()
54 FloorMod<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TF_LITE_MICRO_TEST() local
56 model.PopulateTensor<int32_t>(model.input1(), {10, -9, -11, 7}); in TF_LITE_MICRO_TEST()
[all …]
|
| D | floor_div_test.cc | 32 FloorDivModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TF_LITE_MICRO_TEST() local
35 model.PopulateTensor<int32_t>(model.input1(), {10, 9, 11, 3}); in TF_LITE_MICRO_TEST()
36 model.PopulateTensor<int32_t>(model.input2(), {2, 2, 3, 4}); in TF_LITE_MICRO_TEST()
37 EXPECT_THAT(model.GetOutput(), ElementsAre(5, 4, 3, 0)); in TF_LITE_MICRO_TEST()
43 FloorDivModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TF_LITE_MICRO_TEST() local
46 model.PopulateTensor<int32_t>(model.input1(), {10, -9, -11, 7}); in TF_LITE_MICRO_TEST()
47 model.PopulateTensor<int32_t>(model.input2(), {2, 2, -3, -4}); in TF_LITE_MICRO_TEST()
48 EXPECT_THAT(model.GetOutput(), ElementsAre(5, -5, 3, -2)); in TF_LITE_MICRO_TEST()
54 FloorDivModel<int32_t> model({TensorType_INT32, {1, 2, 2, 1}}, in TF_LITE_MICRO_TEST() local
56 model.PopulateTensor<int32_t>(model.input1(), {10, -9, -11, 7}); in TF_LITE_MICRO_TEST()
[all …]
|
| /external/tensorflow/tensorflow/lite/delegates/gpu/gl/kernels/ |
| D | elementwise_test.cc | 43 SingleOpModel model({/*type=*/ToString(op_type), /*attributes=*/{}}, in TEST() local
46 ASSERT_TRUE(model.PopulateTensor(0, {0.0, -6.2, 2.0, 4.0})); in TEST()
47 ASSERT_OK(model.Invoke(*NewElementwiseNodeShader(op_type))); in TEST()
48 EXPECT_THAT(model.GetOutput(0), in TEST()
55 SingleOpModel model({/*type=*/ToString(op_type), /*attributes=*/{}}, in TEST() local
58 ASSERT_TRUE(model.PopulateTensor(0, {0.0, 3.1415926, -3.1415926, 1})); in TEST()
59 ASSERT_OK(model.Invoke(*NewElementwiseNodeShader(op_type))); in TEST()
60 EXPECT_THAT(model.GetOutput(0), in TEST()
67 SingleOpModel model({/*type=*/ToString(op_type), /*attributes=*/{}}, in TEST() local
70 ASSERT_TRUE(model.PopulateTensor(0, {0.0, -6.2, 2.0, 4.0})); in TEST()
[all …]
|
| /external/XNNPACK/bench/ |
| D | f32-gemm-e2e.cc | 76 …emm_4x12__aarch64_neonfma_cortex_a53(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_gemm_4x12__aarch64_neonfma_cortex_a53() argument
77 GEMMEnd2EndBenchmark(state, model, in f32_gemm_4x12__aarch64_neonfma_cortex_a53()
85 …gemm_4x8__aarch64_neonfma_cortex_a53(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_gemm_4x8__aarch64_neonfma_cortex_a53() argument
86 GEMMEnd2EndBenchmark(state, model, in f32_gemm_4x8__aarch64_neonfma_cortex_a53()
94 …gemm_4x8__aarch64_neonfma_cortex_a55(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_gemm_4x8__aarch64_neonfma_cortex_a55() argument
95 GEMMEnd2EndBenchmark(state, model, in f32_gemm_4x8__aarch64_neonfma_cortex_a55()
103 …gemm_4x8__aarch64_neonfma_cortex_a57(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_gemm_4x8__aarch64_neonfma_cortex_a57() argument
104 GEMMEnd2EndBenchmark(state, model, in f32_gemm_4x8__aarch64_neonfma_cortex_a57()
112 …gemm_4x8__aarch64_neonfma_cortex_a75(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_gemm_4x8__aarch64_neonfma_cortex_a75() argument
113 GEMMEnd2EndBenchmark(state, model, in f32_gemm_4x8__aarch64_neonfma_cortex_a75()
[all …]
|
| D | qs8-gemm-e2e.cc | 79 …ukernel_1x16c4__aarch64_neondot_ld32(benchmark::State& state, models::ExecutionPlanFactory model) { in qs8_gemm_minmax_ukernel_1x16c4__aarch64_neondot_ld32() argument
80 GEMMEnd2EndBenchmark(state, model, in qs8_gemm_minmax_ukernel_1x16c4__aarch64_neondot_ld32()
88 …ukernel_1x16c4__aarch64_neondot_ld64(benchmark::State& state, models::ExecutionPlanFactory model) { in qs8_gemm_minmax_ukernel_1x16c4__aarch64_neondot_ld64() argument
89 GEMMEnd2EndBenchmark(state, model, in qs8_gemm_minmax_ukernel_1x16c4__aarch64_neondot_ld64()
99 …l_4x16c4__aarch64_neondot_cortex_a55(benchmark::State& state, models::ExecutionPlanFactory model) { in qs8_gemm_minmax_ukernel_4x16c4__aarch64_neondot_cortex_a55() argument
100 GEMMEnd2EndBenchmark(state, model, in qs8_gemm_minmax_ukernel_4x16c4__aarch64_neondot_cortex_a55()
108 …ukernel_4x16c4__aarch64_neondot_ld32(benchmark::State& state, models::ExecutionPlanFactory model) { in qs8_gemm_minmax_ukernel_4x16c4__aarch64_neondot_ld32() argument
109 GEMMEnd2EndBenchmark(state, model, in qs8_gemm_minmax_ukernel_4x16c4__aarch64_neondot_ld32()
117 …ukernel_4x16c4__aarch64_neondot_ld64(benchmark::State& state, models::ExecutionPlanFactory model) { in qs8_gemm_minmax_ukernel_4x16c4__aarch64_neondot_ld64() argument
118 GEMMEnd2EndBenchmark(state, model, in qs8_gemm_minmax_ukernel_4x16c4__aarch64_neondot_ld64()
[all …]
|
| D | f32-dwconv-e2e.cc | 74 …id f32_dwconv_up4x9__aarch64_neonfma(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_dwconv_up4x9__aarch64_neonfma() argument
75 DWConvEnd2EndBenchmark(state, model, in f32_dwconv_up4x9__aarch64_neonfma()
80 …nv_up4x9__aarch64_neonfma_cortex_a55(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_dwconv_up4x9__aarch64_neonfma_cortex_a55() argument
81 DWConvEnd2EndBenchmark(state, model, in f32_dwconv_up4x9__aarch64_neonfma_cortex_a55()
91 static void f32_dwconv_up4x9__neon(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_dwconv_up4x9__neon() argument
92 DWConvEnd2EndBenchmark(state, model, in f32_dwconv_up4x9__neon()
97 …tic void f32_dwconv_up4x9__neon_acc2(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_dwconv_up4x9__neon_acc2() argument
98 DWConvEnd2EndBenchmark(state, model, in f32_dwconv_up4x9__neon_acc2()
103 static void f32_dwconv_up8x9__neon(benchmark::State& state, models::ExecutionPlanFactory model) { in f32_dwconv_up8x9__neon() argument
104 DWConvEnd2EndBenchmark(state, model, in f32_dwconv_up8x9__neon()
[all …]
|
| /external/cpuinfo/src/arm/linux/ |
| D | chipset.c | 152 uint32_t model = 0; in match_msm_apq() local
159 model = model * 10 + digit; in match_msm_apq()
166 .model = model, in match_msm_apq()
218 uint32_t model = 0; in match_sdm() local
225 model = model * 10 + digit; in match_sdm()
232 .model = model, in match_sdm()
265 uint32_t model = 0; in match_sm() local
272 model = model * 10 + digit; in match_sm()
279 .model = model, in match_sm()
346 uint32_t model = 0; in match_samsung_exynos() local
[all …]
|
| /external/tensorflow/tensorflow/lite/tools/optimize/ |
| D | quantization_wrapper_utils_custom_test.cc | 31 auto model = absl::make_unique<ModelT>(); in TEST() local
46 model->subgraphs.push_back(std::move(subgraph)); in TEST()
56 model->subgraphs[0]->tensors.push_back(std::move(tensor)); in TEST()
58 model->subgraphs[0]->operators.push_back(std::move(lstm_op)); in TEST()
59 model->operator_codes.push_back(std::move(lstm_op_code)); in TEST()
60 model->buffers.push_back(std::move(buffer)); in TEST()
64 tflite::optimize::AddIntermediateTensorsToFusedOp(&builder, model.get()); in TEST()
67 EXPECT_EQ(model->operator_codes.size(), 1); in TEST()
68 EXPECT_EQ(model->subgraphs.size(), 1); in TEST()
69 EXPECT_EQ(model->subgraphs[0]->operators.size(), 1); in TEST()
[all …]
|
| D | modify_model_interface_test.cc | 33 auto model = absl::make_unique<ModelT>(); in CreateQuantizedModelSingleInputOutput() local
43 model->subgraphs.push_back(std::move(subgraph)); in CreateQuantizedModelSingleInputOutput()
74 model->subgraphs[0]->operators.push_back(std::move(quant_op)); in CreateQuantizedModelSingleInputOutput()
75 model->subgraphs[0]->operators.push_back(std::move(fc_op)); in CreateQuantizedModelSingleInputOutput()
76 model->subgraphs[0]->operators.push_back(std::move(dequant_op)); in CreateQuantizedModelSingleInputOutput()
78 model->operator_codes.push_back(std::move(quant_op_code)); in CreateQuantizedModelSingleInputOutput()
79 model->operator_codes.push_back(std::move(fc_op_code)); in CreateQuantizedModelSingleInputOutput()
80 model->operator_codes.push_back(std::move(dequant_op_code)); in CreateQuantizedModelSingleInputOutput()
83 model->subgraphs[0]->inputs = {0}; in CreateQuantizedModelSingleInputOutput()
84 model->subgraphs[0]->outputs = {3}; in CreateQuantizedModelSingleInputOutput()
[all …]
|
| /external/tensorflow/tensorflow/lite/kernels/perception/ |
| D | max_pool_with_argmax_test.cc | 102 EXPECT_DEATH_IF_SUPPORTED(MaxpoolingWithArgMaxOpModel model( in TEST()
113 MaxpoolingWithArgMaxOpModel model( in TEST() local
120 model.SetInput({0, 13, 2, 0, 0, 1, 4, 0}); in TEST()
121 model.Invoke(); in TEST()
123 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 2, 1})); in TEST()
124 EXPECT_THAT(model.GetOutput(), ElementsAreArray({13, 4})); in TEST()
125 EXPECT_THAT(model.GetIndicesShape(), ElementsAreArray({1, 1, 2, 1})); in TEST()
126 EXPECT_THAT(model.GetIndices(), ElementsAreArray({1, 6})); in TEST()
130 MaxpoolingWithArgMaxOpModel model( in TEST() local
138 model.SetInput({1, 0, 0, 2, 3, 0, 0, 4, 5, 0, 0, 6, 7, 0, 0, 8}); in TEST()
[all …]
|