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/packages/modules/ExtServices/native/pHash/
Dfast_dct-inl.h107 for (int col = 0; col < block_size_; col++) { in ForwardTransform2D() local
108 ddct2d_in_out_ptr_array_[row][col] = static_cast<double>(m_in(row, col)); in ForwardTransform2D()
117 for (int col = 0; col < block_size_; col++) { in ForwardTransform2D() local
118 ddct2d_in_out_ptr_array_[row][col] *= orth_scale_factor_ * isf_squared; in ForwardTransform2D()
127 for (int col = 0; col < block_size_; col++) { in ForwardTransform2D() local
128 (*m_out)(row, col) = static_cast<Tdct>(ddct2d_in_out_ptr_array_[row][col] + 0.5) - in ForwardTransform2D()
139 for (int col = 0; col < block_size_; col++) { in ReverseTransform2D() local
140 ddct2d_in_out_ptr_array_[row][col] = static_cast<double>(m_in(row, col)); in ReverseTransform2D()
154 for (int col = 0; col < block_size_; col++) { in ReverseTransform2D() local
155 ddct2d_in_out_ptr_array_[row][col] *= orth_scale_factor_ * inv_isf_squared; in ReverseTransform2D()
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/packages/modules/NeuralNetworks/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)],
/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/
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)]
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)]
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_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_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)]
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_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)]
Dmax_pool_quant8_3.mod.py22 col = 70 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_range = bat * row * col * chn
Dmax_pool_float_3.mod.py22 col = 70 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_range = bat * row * col * chn
Dmax_pool_quant8_2.mod.py22 col = 70 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_range = bat * row * col * chn
/packages/modules/NeuralNetworks/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_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)]
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)]
Dmax_pool_float_3_relaxed.mod.py22 col = 70 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_range = bat * row * col * chn
Dmax_pool_float_2_relaxed.mod.py22 col = 70 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_range = bat * row * col * chn
/packages/modules/NeuralNetworks/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)]
/packages/services/BuiltInPrintService/jni/ipphelper/
Dipp_print.c180 ipp_t *col[2]; in _fill_job() local
354 col[++col_index] = ippNew(); in _fill_job()
355 ippAddString(col[col_index], IPP_TAG_JOB, IPP_TAG_KEYWORD, "media-source", NULL, in _fill_job()
358 col[++col_index] = ippNew(); in _fill_job()
359 ippAddString(col[col_index], IPP_TAG_JOB, IPP_TAG_KEYWORD, "media-source", NULL, in _fill_job()
367 col[++col_index] = ippNew(); in _fill_job()
372 ippAddInteger(col[col_index], IPP_TAG_JOB, IPP_TAG_INTEGER, "media-bottom-margin", 0); in _fill_job()
373 ippAddInteger(col[col_index], IPP_TAG_JOB, IPP_TAG_INTEGER, "media-top-margin", 0); in _fill_job()
374 ippAddInteger(col[col_index], IPP_TAG_JOB, IPP_TAG_INTEGER, "media-left-margin", 0); in _fill_job()
375 ippAddInteger(col[col_index], IPP_TAG_JOB, IPP_TAG_INTEGER, "media-right-margin", 0); in _fill_job()
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/packages/apps/Gallery/src/com/android/camera/
DGridViewSpecial.java504 int col = pos - (row * mColumns); in getRectForPosition() local
507 + (col * (mSpec.mCellWidth + mSpec.mCellSpacing)); in getRectForPosition()
524 int col = Math.min(mColumns - 1, in computeSelectedIndex() local
526 return (row * mColumns) + col; in computeSelectedIndex()
697 int col = mCurrentSelection - (row * mColumns); in paintSelection() local
701 int xPos = leftSpacing + (col * (mSpec.mCellWidth + spacing)); in paintSelection()
795 int col = pos - row * mColumns; in clearLoaderQueue() local
799 blk.cancelRequest(col); in clearLoaderQueue()
881 int col = index - (row * mColumns); in invalidateImage() local
884 if ((blk.mCompletedMask & (1 << col)) != 0) { in invalidateImage()
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