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/frameworks/native/libs/math/include/math/
DTMatHelpers.h218 for (size_t col = 0; col < 3; ++col) { in fastInverse3() local
220 inverted[col][row] /= det; in fastInverse3()
256 for (size_t col = 0; col < MATRIX_R::NUM_COLS; ++col) { in multiply() local
257 res[col] = lhs * rhs[col]; in multiply()
268 for (size_t col = 0; col < MATRIX::NUM_COLS; ++col) { in transpose() local
270 result[col][row] = transpose(m[row][col]); in transpose()
281 for (size_t col = 0; col < MATRIX::NUM_COLS; ++col) { in trace() local
282 result += trace(m[col][col]); in trace()
292 for (size_t col = 0; col < MATRIX::NUM_COLS; ++col) { in diag() local
293 result[col] = m[col][col]; in diag()
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Dmat2.h284 for (size_t col = 0; col < NUM_COLS; ++col) { in TMat22() local
285 m_value[col] = col_type(rhs[col]); in TMat22()
301 for (size_t col = 0; col < NUM_COLS; ++col) { in TMat22() local
303 m_value[col][row] = *rawArray++; in TMat22()
325 for (size_t col = 0; col < TMat22<T>::NUM_COLS; ++col) { variable
326 result += lhs[col] * rhs[col];
335 for (size_t col = 0; col < TMat22<T>::NUM_COLS; ++col) { variable
336 result[col] = dot(lhs, rhs[col]);
Dmat3.h314 for (size_t col = 0; col < NUM_COLS; ++col) { in TMat33() local
315 m_value[col] = col_type(rhs[col]); in TMat33()
332 for (size_t col = 0; col < NUM_COLS; ++col) { in TMat33() local
334 m_value[col][row] = *rawArray++; in TMat33()
378 for (size_t col = 0; col < TMat33<T>::NUM_COLS; ++col) { variable
379 result += lhs[col] * rhs[col];
388 for (size_t col = 0; col < TMat33<T>::NUM_COLS; ++col) { variable
389 result[col] = dot(lhs, rhs[col]);
/frameworks/ml/nn/runtime/test/specs/V1_0/
Dconcat_float_2.mod.py22 col = 230 variable
25 input1 = Input("input1", "TENSOR_FLOAT32", "{%d, %d}" % (row1, col)) # input tensor 1
26 input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row2, col)) # input tensor 2
28 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (output_row, col)) # output
32 input1_values = [x for x in range(row1 * col)]
33 input2_values = (lambda s1 = row1 * col, s2 = row2 * col:
37 output_values = [x for x in range(output_row * col)]
Dconcat_quant8_2.mod.py22 col = 300 variable
25 input1 = Input("input1", "TENSOR_QUANT8_ASYMM", "{%d, %d}, 0.5f, 0" % (row1, col))
26 input2 = Input("input2", "TENSOR_QUANT8_ASYMM", "{%d, %d}, 0.5f, 0" % (row2, col))
28 output = Output("output", "TENSOR_QUANT8_ASYMM", "{%d, %d}, 0.5f, 0" % (output_row, col))
32 input1_values = [x % 256 for x in range(row1 * col)]
33 input2_values = (lambda s1 = row1 * col, s2 = row2 * col:
37 output_values = [x % 256 for x in range(output_row * col)]
Davg_pool_float_4.mod.py22 col = 60 variable
25 i0 = Input("i0", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (bat, row, col, chn))
36 output_col = (col + 2 * pad - flt + std) // std
45 input_values = [10 for _ in range(bat * row * col * chn)]
Davg_pool_quant8_2.mod.py22 col = 60 variable
25 i0 = Input("i0", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 0.5f, 0" % (bat, row, col, chn))
36 output_col = (col + 2 * pad - flt + std) // std
45 input_values = [255 for _ in range(bat * row * col * chn)]
Davg_pool_float_2.mod.py22 col = 60 variable
25 i0 = Input("i0", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (bat, row, col, chn))
36 output_col = (col + 2 * pad - flt + std) // std
45 input_values = [1. for _ in range(bat * row * col * chn)]
Davg_pool_quant8_3.mod.py22 col = 100 variable
25 i0 = Input("i0", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 0.5f, 0" % (bat, row, col, chn))
36 output_col = (col + 2 * pad - flt + std) // std
45 input_values = [x % 4 * 2 for x in range(bat * row * col * chn)]
Davg_pool_float_3.mod.py22 col = 180 variable
25 i0 = Input("i0", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (bat, row, col, chn))
36 output_col = (col + 2 * pad - flt + std) // std
45 input_values = [x % 2 for x in range(bat * row * col * chn)]
/frameworks/ml/nn/runtime/test/specs/V1_2/
Dconcat_float16_2.mod.py22 col = 230 variable
25 input1 = Input("input1", "TENSOR_FLOAT16", "{%d, %d}" % (row1, col)) # input tensor 1
26 input2 = Input("input2", "TENSOR_FLOAT16", "{%d, %d}" % (row2, col)) # input tensor 2
28 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (output_row, col)) # output
32 input1_values = [x for x in range(row1 * col)]
33 input2_values = (lambda s1 = row1 * col, s2 = row2 * col:
37 output_values = [x for x in range(output_row * col)]
Davg_pool_v1_2.mod.py40 col = 60 variable
48 output_col = (col + 2 * pad - flt + std) // std
50 i2 = Input("op1", ("TENSOR_FLOAT32", [bat, row, col, chn]))
62 i2: [1. for _ in range(bat * row * col * chn)],
70 col = 180 variable
76 output_col = (col + 2 * pad - flt + std) // std
78 i3 = Input("op1", ("TENSOR_FLOAT32", [bat, row, col, chn]))
90 i3: [x % 2 for x in range(bat * row * col * chn)],
98 col = 60 variable
104 output_col = (col + 2 * pad - flt + std) // std
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Dmax_pool_v1_2.mod.py40 col = 70 variable
46 output_col = (col + 2 * pad - flt + std) // std
48 i2 = Input("op1", ("TENSOR_FLOAT32", [bat, row, col, chn]))
60 i2: [x % std + 1 for x in range(bat * row * col * chn)],
68 col = 70 variable
74 output_col = (col + 2 * pad - flt + std) // std
76 i3 = Input("op1", ("TENSOR_FLOAT32", [bat, row, col, chn]))
88 i3: [x % std + 1 for x in range(bat * row * col * chn)],
/frameworks/ml/nn/runtime/test/specs/V1_1/
Dconcat_float_2_relaxed.mod.py22 col = 230 variable
25 input1 = Input("input1", "TENSOR_FLOAT32", "{%d, %d}" % (row1, col)) # input tensor 1
26 input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row2, col)) # input tensor 2
28 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (output_row, col)) # output
33 input1_values = [x for x in range(row1 * col)]
34 input2_values = (lambda s1 = row1 * col, s2 = row2 * col:
38 output_values = [x for x in range(output_row * col)]
Davg_pool_float_3_relaxed.mod.py22 col = 180 variable
25 i0 = Input("i0", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (bat, row, col, chn))
36 output_col = (col + 2 * pad - flt + std) // std
46 input_values = [x % 2 for x in range(bat * row * col * chn)]
Davg_pool_float_4_relaxed.mod.py22 col = 60 variable
25 i0 = Input("i0", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (bat, row, col, chn))
36 output_col = (col + 2 * pad - flt + std) // std
46 input_values = [10 for _ in range(bat * row * col * chn)]
Davg_pool_float_2_relaxed.mod.py22 col = 60 variable
25 i0 = Input("i0", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (bat, row, col, chn))
38 output_col = (col + 2 * pad - flt + std) // std
48 input_values = [1. for _ in range(bat * row * col * chn)]
/frameworks/rs/tests/java_api/VrDemo/src/com/example/android/rs/vr/engine/
DMatrix.java98 int col = i * 4; in mult4() local
101 sum += m[col + j] * src[j]; in mult4()
109 int col = i * 4; in mult3() local
110 double sum = m[col + 3]; in mult3()
112 sum += m[col + j] * src[j]; in mult3()
120 int col = i * 4; in mult3v() local
123 sum += m[col + j] * src[j]; in mult3v()
131 int col = i * 4; in mult4() local
134 sum += m[col + j] * src[j]; in mult4()
142 int col = i * 4; in mult3() local
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/frameworks/ml/nn/runtime/test/specs/V1_3/
Davg_pool_quant8_signed.mod.py41 col = 60 variable
44 i0 = Input("i0", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d, %d, %d}, 0.5f, -128" % (bat, row, col, chn…
55 output_col = (col + 2 * pad - flt + std) // std
64 input_values = [127 for _ in range(bat * row * col * chn)]
78 col = 100 variable
81 i0 = Input("i0", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d, %d, %d}, 0.5f, -128" % (bat, row, col, chn…
92 output_col = (col + 2 * pad - flt + std) // std
101 input_values = [x % 4 * 2 - 128 for x in range(bat * row * col * chn)]
172 col = 60 variable
178 output_col = (col + 2 * pad - flt + std) // std
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Dmax_pool_quant8_signed.mod.py38 col = 70 variable
41 i0 = Input("i0", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d, %d, %d}, 0.5f, -128" % (bat, row, col, chn…
52 output_col = (col + 2 * pad - flt + std) // std
61 input_range = bat * row * col * chn
77 col = 70 variable
80 i0 = Input("i0", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d, %d, %d}, 0.5f, -128" % (bat, row, col, chn…
91 output_col = (col + 2 * pad - flt + std) // std
100 input_range = bat * row * col * chn
154 col = 70 variable
160 output_col = (col + 2 * pad - flt + std) // std
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Dconcat_quant8_signed.mod.py81 col = 300 variable
84 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d}, 0.5f, -128" % (row1, col))
85 input2 = Input("input2", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d}, 0.5f, -128" % (row2, col))
87 output = Output("output", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d}, 0.5f, -128" % (output_row, col))
91 input1_values = [x % 256 for x in range(row1 * col)]
92 input2_values = (lambda s1 = row1 * col, s2 = row2 * col:
96 output_values = [x % 256 - 128 for x in range(output_row * col)]
/frameworks/base/packages/SettingsLib/src/com/android/settingslib/animation/
DAppearAnimationUtils.java116 for (int col = 0; col < columns.length; col++) { in startAnimations()
117 long delay = columns[col]; in startAnimations()
119 if (properties.maxDelayRowIndex == row && properties.maxDelayColIndex == col) { in startAnimations()
122 creator.createAnimation(objects[row][col], delay, mDuration, in startAnimations()
155 for (int col = 0; col < columns.length; col++) { in getDelays()
156 long delay = calculateDelay(row, col); in getDelays()
157 mProperties.delays[row][col] = delay; in getDelays()
158 if (items[row][col] != null && delay > maxDelay) { in getDelays()
160 mProperties.maxDelayColIndex = col; in getDelays()
168 protected long calculateDelay(int row, int col) { in calculateDelay() argument
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/frameworks/base/packages/PrintSpooler/src/com/android/printspooler/widget/
DPrintOptionsLayout.java72 for (int col = 0; col < mColumnCount; col++) { in onMeasure()
73 final int childIndex = row * mColumnCount + col; in onMeasure()
138 for (int col = 0; col < mColumnCount; col++) { in onLayout()
142 childIndex = row * mColumnCount + (mColumnCount - col - 1); in onLayout()
144 childIndex = row * mColumnCount + col; in onLayout()
/frameworks/rs/
DrsMatrix2x2.h28 inline float get(uint32_t col, uint32_t row) const { in get()
29 return m[col*2 + row]; in get()
32 inline void set(uint32_t col, uint32_t row, float v) { in set()
33 m[col*2 + row] = v; in set()
DrsMatrix3x3.h28 inline float get(uint32_t col, uint32_t row) const { in get()
29 return m[col*3 + row]; in get()
32 inline void set(uint32_t col, uint32_t row, float v) { in set()
33 m[col*3 + row] = v; in set()

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