| /aosp12/frameworks/av/media/libeffects/loudness/dsp/core/ |
| H A D | interpolator_base-inl.h | 55 bool InterpolatorBase<T, Algorithm>::Initialize(const vector<T> &x_data, in Initialize() argument
58 if (x_data.size() != y_data.size()) { in Initialize()
60 " (%d)", x_data.size(), y_data.size()); in Initialize()
63 return Initialize(&x_data[0], &y_data[0], x_data.size()); in Initialize()
99 const T *x_data, const T *y_data, int data_length) { in Initialize() argument
108 x_data_ = x_data; in Initialize()
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| H A D | basic-inl.h | 27 int SearchIndex(const T x_data[], in SearchIndex() argument
35 if (x_data[i] > x) { in SearchIndex()
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| H A D | interpolator_base.h | 60 bool Initialize(const T *x_data, const T *y_data, int data_length);
66 bool Initialize(const vector<T> &x_data, const vector<T> &y_data);
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| H A D | basic.h | 37 int SearchIndex(const T x_data[],
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| /aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
| H A D | while_sum_of_powers.mod.py | 92 def Test(x_data, n_data, sum_data): argument
103 x: x_data,
112 Test(x_data=[2, 3], n_data=0, sum_data=[1, 1])
113 Test(x_data=[2, 3], n_data=1, sum_data=[1 + 2, 1 + 3])
114 Test(x_data=[2, 3], n_data=2, sum_data=[1 + 2 + 4, 1 + 3 + 9])
115 Test(x_data=[2, 3], n_data=3, sum_data=[1 + 2 + 4 + 8, 1 + 3 + 9 + 27])
116 Test(x_data=[2, 3], n_data=4, sum_data=[1 + 2 + 4 + 8 + 16, 1 + 3 + 9 + 27 + 81])
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| H A D | while_sum_of_powers_quant8.mod.py | 98 def Test(x_data, n_data, sum_data): argument
109 x: quantize(x_data, 0.5, 128),
115 Test(x_data=[2, 3], n_data=0, sum_data=[1, 1])
116 Test(x_data=[2, 3], n_data=1, sum_data=[1 + 2, 1 + 3])
117 Test(x_data=[2, 3], n_data=2, sum_data=[1 + 2 + 4, 1 + 3 + 9])
118 Test(x_data=[2, 3], n_data=3, sum_data=[1 + 2 + 4 + 8, 1 + 3 + 9 + 27])
119 Test(x_data=[2, 3], n_data=4, sum_data=[1 + 2 + 4 + 8 + 16, 1 + 3 + 9 + 27 + 81])
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| H A D | while_sum_of_powers_quant8_signed.mod.py | 98 def Test(x_data, n_data, sum_data): argument
109 x: quantize(x_data, 0.5, 12),
115 Test(x_data=[2, 3], n_data=0, sum_data=[1, 1])
116 Test(x_data=[2, 3], n_data=1, sum_data=[1 + 2, 1 + 3])
117 Test(x_data=[2, 3], n_data=2, sum_data=[1 + 2 + 4, 1 + 3 + 9])
118 Test(x_data=[2, 3], n_data=3, sum_data=[1 + 2 + 4 + 8, 1 + 3 + 9 + 27])
119 Test(x_data=[2, 3], n_data=4, sum_data=[1 + 2 + 4 + 8 + 16, 1 + 3 + 9 + 27 + 81])
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| H A D | if_simple.mod.py | 31 def Test(x_data, y_data, z_data, name): argument
42 example = Example({x: [x_data], y: y_data, z: z_data}, name=name)
46 Test(x_data=True, y_data=input_data, z_data=output_add, name="true")
47 Test(x_data=False, y_data=input_data, z_data=output_sub, name="false")
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| H A D | if_constant.mod.py | 20 x_data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] variable
23 True: [x + y for (x, y) in zip(x_data, y_data)],
24 False: [x - y for (x, y) in zip(x_data, y_data)],
49 x: x_data,
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| H A D | if_no_value.mod.py | 20 x_data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] variable
44 example = Example({x: x_data, y: y_data, z: y_data})
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| H A D | if_same_branch_model.mod.py | 32 x_data, y_data, z_data = x, y, z
43 example = Example({x: [x_data], y: y_data, z: z_data}, name=name)
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| /aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3_cts_only/ |
| H A D | if_simple_unknown_dimension.mod.py | 32 def Test(x_data, y_data, z_data, name): argument
43 example = Example({x: [x_data], y: y_data, z: z_data}, name=name)
47 Test(x_data=True, y_data=input_data, z_data=output_add, name="true")
48 Test(x_data=False, y_data=input_data, z_data=output_sub, name="false")
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| H A D | if_simple_unknown_rank.mod.py | 32 def Test(x_data, y_data, z_data, name): argument
43 example = Example({x: [x_data], y: y_data, z: z_data}, name=name)
47 Test(x_data=True, y_data=input_data, z_data=output_add, name="true")
48 Test(x_data=False, y_data=input_data, z_data=output_sub, name="false")
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| /aosp12/system/extras/partition_tools/ |
| H A D | lpdump.cc | 345 auto x_data = ParseLinearExtentData(pt, *std::get<1>(x)); in PrintMetadata() local
347 return x_data < y_data; in PrintMetadata()
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