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/frameworks/ml/nn/runtime/test/specs/V1_2/
Dresize_nearest_neighbor.mod.py20 i1 = Input("in", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # input 0 variable
22 model_shape = Model("shape").Operation("RESIZE_NEAREST_NEIGHBOR", i1, 1, 1, layout).To(o1)
23 model_scale = Model("scale").Operation("RESIZE_NEAREST_NEIGHBOR", i1, 0.5, 0.5, layout).To(o1)
27 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
32 i1: [1, 2, 3, 4],
36 Example(test1, model=model_shape).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16…
37 Example(test1, model=model_scale).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16…
41 i1 = Input("in", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # input 0 variable
43 model_shape = Model("shape").Operation("RESIZE_NEAREST_NEIGHBOR", i1, 3, 3, layout).To(o1)
44 model_scale = Model("scale").Operation("RESIZE_NEAREST_NEIGHBOR", i1, 1.5, 1.5, layout).To(o1)
[all …]
Dresize_bilinear_v1_2.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
22 model_shape = Model("shape").Operation("RESIZE_BILINEAR", i1, 3, 3, layout).To(o1)
23 model_scale = Model("scale").Operation("RESIZE_BILINEAR", i1, 1.5, 1.5, layout).To(o1)
27 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
32 i1: [1.0, 1.0, 2.0, 2.0],
39 Example(test1, model=model_shape).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", quant…
40 Example(test1, model=model_scale).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", quant…
103 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
105 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
116 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
[all …]
Ddetection_postprocess.mod.py18 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores variable
26 Model("regular").Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, True, 3, 1…
29 i1: [ # class scores - two classes with background
69 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores variable
77 Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0…
80 i1: [ # class scores - two classes with background
120 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores variable
128 Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0…
131 i1: [ # class scores - two classes with background
171 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores variable
[all …]
Dl2_pool_v1_2.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
22 Model().Operation("L2_POOL_2D", i1, 0, 0, 0, 0, 1, 1, 1, 1, 0, layout).To(o1)
26 i1: [1.0, 2.0, 3.0, 4.0],
28 }).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16")
67 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
69 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
76 i1: [1],
80 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", "float16")
95 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
97 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
[all …]
Dgenerate_proposals.mod.py21 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # scores variable
29 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
32 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 100),
41 i1: [ # scores
66 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations("relaxed", quant8, "float16")
70 i1 = Input("scores", "TENSOR_FLOAT32", "{2, 4, 4, 4}") # scores variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
81 i1: ("TENSOR_QUANT8_ASYMM", 0.005, 0),
90 i1: [ # scores
211 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations("relaxed", quant8, "float16")
Dadd_v1_2.mod.py19 i1 = Input("op1", "TENSOR_FLOAT16", "{3}") # a vector of 3 float16s variable
23 model = model.Operation("ADD", i1, i2, act).To(i3)
27 input0 = {i1: # input 0
41 i1 = Input("op1", "TENSOR_FLOAT16", "{1, 2}") variable
45 model = model.Operation("ADD", i1, i2, act).To(i3)
48 input0 = {i1: # input 0
73 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
75 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
87 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
94 i1: [1, 2],
Dmul_v1_2.mod.py19 i1 = Input("op1", "TENSOR_FLOAT16", "{3}") # a vector of 3 float16s variable
23 model = model.Operation("MUL", i1, i2, act).To(i3)
27 input0 = {i1: # input 0
41 i1 = Input("op1", "TENSOR_FLOAT16", "{1, 2}") variable
45 model = model.Operation("MUL", i1, i2, act).To(i3)
48 input0 = {i1: # input 0
73 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
75 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
87 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
94 i1: [1, 2],
Dtranspose_conv2d.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # input 0 variable
26 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 2, 2, 2, act, layout).To(o1)
30 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
37 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 100),
45 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 100),
52 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 100),
59 i1: [1, 2, 3, 4],
65 }).AddNchw(i1, o1, s1, layout).AddAllActivations(o1, act).AddVariations("relaxed", quant8, quant8_m…
190 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
192 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
[all …]
Dmax_pool_v1_2.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
22 Model().Operation("MAX_POOL_2D", i1, 0, 0, 0, 0, 1, 1, 1, 1, 0, layout).To(o1)
26 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
32 i1: [1.0, 2.0, 3.0, 4.0],
34 }).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16")
123 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
125 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
136 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
142 i1: [1],
146 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", quant8, "float16")
[all …]
/frameworks/ml/nn/runtime/test/specs/V1_3/
Dresize_quant8_signed.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
22 model_shape = Model("shape").Operation("RESIZE_BILINEAR", i1, 3, 3, layout).To(o1)
23 model_scale = Model("scale").Operation("RESIZE_BILINEAR", i1, 1.5, 1.5, layout).To(o1)
27 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128),
32 i1: [1.0, 1.0, 2.0, 2.0],
39 Example(test1, model=model_shape).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefau…
40 Example(test1, model=model_scale).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefau…
103 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
105 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
116 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
[all …]
Dstrided_slice_quant8_signed.mod.py18 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 3}, 1.0, -128") variable
28 model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisM…
31 input0 = {i1: # input 0
43 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 3}, 1.0, -128") variable
53 model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisM…
56 input0 = {i1: # input 0
68 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{4}, 1.0, -128") variable
78 model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisM…
81 input0 = {i1: # input 0
93 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{4}, 1.0, -128") variable
[all …]
Dbox_with_nms_limit_quant8_signed.mod.py18 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores variable
26 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 2, 0.4, 0.5, 0.3).To(o1, o2, o…
29 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128),
36 i1: [ # scores
115 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores variable
123 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 2, 0.4, 0.5, 0.3).To(o1, o2, o3…
126 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, 0),
133 i1: [ # scores
204 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores variable
212 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, o2, o…
[all …]
Dconv2d_quant8_signed.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
24 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout, 1, 1).To(o1)
28 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
36 i1: [1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0],
38 }).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False)
71 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
75 Model().Operation("CONV_2D", i1, f1, b1, 2, 1, 1, 0, layout, 1, 1).To(o1)
79 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
87 i1: [1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0],
89 }, name="valid_padding").AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Dtranspose_quant8_signed.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{25, 1, 1, 1}") # input 0 variable
26 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 1, 32, 32, act, layout).To(o1)
30 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
38 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -28),
45 i1: [1] * 25,
54 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # input 0 variable
60 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 2, 2, 2, act, layout).To(o1)
64 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
71 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -28),
79 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -28),
[all …]
Dspace_to_batch_quant8_signed.mod.py18 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 4, 4, 1}, 1.0, -128") variable
23 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
27 i1: # input 0
48 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5, 2, 1}, 1.0, -128") variable
53 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
57 i1: # input 0
76 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 4, 2, 1}, 1.0, -128") variable
81 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
85 i1: # input 0
108 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5, 2, 1}, 1.0, -119") variable
[all …]
Ddepthwise_conv2d_quant8_signed.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 2}") variable
24 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout, 1, 1).To(o1)
28 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
36 i1: [10, 21, 10, 22, 10, 23,
43 }).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False)
77 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 2}") variable
81 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 2, 1, 1, 2, 0, layout, 1, 1).To(o1)
85 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
93 i1: [10, 21, 10, 22, 10, 23,
100 }, name="valid_padding").AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Dl2_normalization_quant8_signed.mod.py17 i1 = Input("op1", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # input 0 variable
22 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -96),
27 i1: [ 0, 3, 4,
46 Model().Operation("L2_NORMALIZATION", i1, axis).To(o1)
47 Example(example0).AddAllDimsAndAxis(i1, o1, axis).AddVariations(quant8_signed, includeDefault=False)
51 i1 = Input("op1", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # input 0 variable
56 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -96),
61 i1: [ 0, 3, 4,
80 Model().Operation("L2_NORMALIZATION", i1).To(o1)
81 Example(example0).AddAllDims(i1, o1).AddVariations(quant8_signed, includeDefault=False)
Dtranspose_conv2d_quant8_signed.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{25, 1, 1, 1}") # input 0 variable
26 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 1, 32, 32, act, layout).To(o1)
30 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
38 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -28),
45 i1: [1] * 25,
54 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # input 0 variable
60 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 2, 2, 2, act, layout).To(o1)
64 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
71 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -28),
79 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -28),
[all …]
Dspace_to_depth_quant8_signed.mod.py18 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128") variable
22 model = model.Operation("SPACE_TO_DEPTH", i1, block).To(output)
25 input0 = {i1: # input 0
37 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 4, 4, 1}, 0.5f, -128") variable
41 model = model.Operation("SPACE_TO_DEPTH", i1, block).To(output)
45 i1: # input 0
68 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 2}") variable
70 Model().Operation("SPACE_TO_DEPTH", i1, 2, layout).To(o1)
74 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -128),
80 i1: [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1],
[all …]
Ddepth_to_space_quant8_signed.mod.py18 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1, 1, 8}, 0.5f, 0") variable
22 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output)
26 i1: # input 0
38 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 4}, 0.5f, 0") variable
42 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output)
46 i1: # input 0
69 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 1, 1, 8}") variable
71 Model().Operation("DEPTH_TO_SPACE", i1, 2, layout).To(o1)
75 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
81 i1: [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1],
[all …]
Dgenerate_proposals_quant8_signed.mod.py20 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # scores variable
28 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
31 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -28),
40 i1: [ # scores
65 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations(quant8_signed, includeDefault=Fals…
70 i1 = Input("scores", "TENSOR_FLOAT32", "{2, 4, 4, 4}") # scores variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
81 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.005, -128),
90 i1: [ # scores
211 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations(quant8_signed, includeDefault=Fals…
Dmul_quant8_signed.mod.py18 i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2}, 1.0, -128") variable
22 model = model.Operation("MUL", i1, i2, act).To(i3)
25 input0 = {i1: # input 0
39 i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0, -128") variable
43 model = model.Operation("MUL", i1, i2, act).To(i3)
46 input0 = {i1: # input 0
71 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
73 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
85 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
92 i1: [1, 2],
Dadd_quant8_signed.mod.py18 i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 2.0, 0") variable
22 model = model.Operation("ADD", i1, i2, act).To(i3)
25 input0 = {i1: # input 0
39 i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2}, 2.0, 0") variable
43 model = model.Operation("ADD", i1, i2, act).To(i3)
46 input0 = {i1: # input 0
71 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
73 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
85 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
92 i1: [1, 2],
Dbatch_to_space_quant8_signed.mod.py17 i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{4, 2, 2, 1}, 1.0, 0") variable
21 model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output)
24 input0 = {i1: # input 0
36 i1 = Input("op1", "TENSOR_FLOAT32", "{4, 1, 1, 2}") variable
38 Model().Operation("BATCH_TO_SPACE_ND", i1, [2, 2], layout).To(o1)
42 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
48 i1: [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1],
50 }).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False)
/frameworks/base/core/java/android/os/
DWorkSource.java567 int i1 = 0, i2 = 0; in removeUids() local
569 while (i1 < N1 && i2 < N2) { in removeUids()
570 if (DEBUG) Log.d(TAG, "Step: target @ " + i1 + " of " + N1 + ", other @ " + i2 in removeUids()
572 if (uids2[i2] == uids1[i1]) { in removeUids()
573 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 in removeUids()
574 + ": remove " + uids1[i1]); in removeUids()
577 if (i1 < N1) System.arraycopy(uids1, i1+1, uids1, i1, N1-i1); in removeUids()
579 } else if (uids2[i2] > uids1[i1]) { in removeUids()
580 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 + ": skip i1"); in removeUids()
581 i1++; in removeUids()
[all …]

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