/frameworks/native/libs/math/include/math/ |
D | TMatHelpers.h | 218 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() [all …]
|
D | mat2.h | 284 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]);
|
D | mat3.h | 314 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/ |
D | concat_float_2.mod.py | 22 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)]
|
D | concat_quant8_2.mod.py | 22 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)]
|
D | avg_pool_float_4.mod.py | 22 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)]
|
D | avg_pool_quant8_2.mod.py | 22 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)]
|
D | avg_pool_float_2.mod.py | 22 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)]
|
D | avg_pool_quant8_3.mod.py | 22 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)]
|
D | avg_pool_float_3.mod.py | 22 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/ |
D | concat_float16_2.mod.py | 22 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)]
|
D | avg_pool_v1_2.mod.py | 40 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 [all …]
|
D | max_pool_v1_2.mod.py | 40 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/ |
D | concat_float_2_relaxed.mod.py | 22 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)]
|
D | avg_pool_float_3_relaxed.mod.py | 22 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)]
|
D | avg_pool_float_4_relaxed.mod.py | 22 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)]
|
D | avg_pool_float_2_relaxed.mod.py | 22 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/ |
D | Matrix.java | 98 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 [all …]
|
/frameworks/ml/nn/runtime/test/specs/V1_3/ |
D | avg_pool_quant8_signed.mod.py | 41 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 [all …]
|
D | max_pool_quant8_signed.mod.py | 38 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 [all …]
|
D | concat_quant8_signed.mod.py | 81 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/ |
D | AppearAnimationUtils.java | 116 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 [all …]
|
/frameworks/base/packages/PrintSpooler/src/com/android/printspooler/widget/ |
D | PrintOptionsLayout.java | 72 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/ |
D | rsMatrix2x2.h | 28 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()
|
D | rsMatrix3x3.h | 28 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()
|