/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | resize_nearest_neighbor.mod.py | 21 o1 = Output("out", "TENSOR_FLOAT32", "{1, 1, 1, 1}") # output 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) 28 o1: ("TENSOR_QUANT8_ASYMM", 0.25, 128) 33 o1: [1] 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… 42 o1 = Output("out", "TENSOR_FLOAT32", "{1, 3, 3, 1}") # output 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 …]
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D | detection_postprocess.mod.py | 22 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{1, 3}") # scores out variable 26 …STPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, True, 3, 1, 1, 0.0, 0.5, False).To(o1, o2, o3, o4) 56 o1: [0.95, 0.93, 0.0], 73 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{1, 3}") # scores out variable 77 …TPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0, 0.5, False).To(o1, o2, o3, o4) 107 o1: [0.95, 0.9, 0.3], 124 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{1, 3}") # scores out variable 128 …TPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0, 0.5, False).To(o1, o2, o3, o4) 158 o1: [0.95, 0.9, 0.3], 175 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{1, 3}") # scores out variable [all …]
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D | resize_bilinear_v1_2.mod.py | 21 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 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) 28 o1: ("TENSOR_QUANT8_ASYMM", 0.01, 0) 33 o1: [1.0, 1.0, 1.0, 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… 96 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable 100 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2) 114 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 128), [all …]
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D | prelu.mod.py | 20 o1 = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 3}") variable 21 Model().Operation("PRELU", i1, a1).To(o1) 27 o1: ("TENSOR_QUANT8_ASYMM", 0.5, 120) 34 o1: ("TENSOR_QUANT8_ASYMM", 0.25, 120) 41 o1: ("TENSOR_QUANT8_ASYMM", 0.125, 120) 48 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 120) 57 o1: [ 0, 0, 0,
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D | box_with_nms_limit_gaussian.mod.py | 22 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{18}") # scores out 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… 31 o1: ("TENSOR_QUANT8_ASYMM", 0.01, 0), 82 o1: [ 118 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{10}") # scores out variable 122 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 2, 0.4, 0.5, 0.3).To(o1, o2, o3… 127 o1: ("TENSOR_QUANT8_ASYMM", 0.01, 128), 178 o1: [
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D | box_with_nms_limit_linear.mod.py | 22 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{16}") # scores out variable 26 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 1, 0.4, 1.0, 0.3).To(o1, o2, o… 31 o1: ("TENSOR_QUANT8_ASYMM", 0.01, 0), 82 o1: [ 116 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{15}") # scores out variable 120 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 8, 1, 0.4, 0.5, 0.3).To(o1, o2, o3… 125 o1: ("TENSOR_QUANT8_ASYMM", 0.01, 128), 176 o1: [
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D | box_with_nms_limit_hard.mod.py | 22 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{12}") # scores out variable 26 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, o2, o… 31 o1: ("TENSOR_QUANT8_ASYMM", 0.01, 0), 82 o1: [0.95, 0.85, 0.75, 0.95, 0.7, 0.95, 0.9, 0.85, 0.75, 0.95, 0.8, 0.7], 109 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{10}") # scores out variable 113 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 0, 0.4, 0.5, 0.3).To(o1, o2, o3… 118 o1: ("TENSOR_QUANT8_ASYMM", 0.01, 128), 169 o1: [0.95, 0.85, 0.75, 0.95, 0.7, 0.95, 0.9, 0.85, 0.95, 0.8],
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D | transpose_conv2d.mod.py | 25 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 5, 5, 2}") # output variable 26 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 2, 2, 2, act, layout).To(o1) 33 o1: ("TENSOR_QUANT8_ASYMM", 0.5, 0) 40 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 80) 48 o1: ("TENSOR_QUANT8_ASYMM", 0.5, 80) 55 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 80) 60 o1: [-0.5, 0, 1.5, 2, 5.5, 8, 4.5, 6, 8.5, 10, 65 }).AddNchw(i1, o1, s1, layout).AddAllActivations(o1, act).AddVariations("relaxed", quant8, quant8_m… 183 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable 187 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2) [all …]
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D | l2_pool_v1_2.mod.py | 21 o1 = Output("op4", "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) 27 o1: [1.0, 2.0, 3.0, 4.0] 28 }).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16") 60 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable 64 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2) 77 o1: [], 88 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable 92 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2) 105 o1: [],
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D | conv2d_dilation.mod.py | 23 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable 24 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout, 1, 1).To(o1) 31 o1: ("TENSOR_QUANT8_ASYMM", 0.125, 0) 37 o1: [.875, .875, .875, .875] 38 }).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16") 74 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable 75 Model().Operation("CONV_2D", i1, f1, b1, 2, 1, 1, 0, layout, 1, 1).To(o1) 82 o1: ("TENSOR_QUANT8_ASYMM", 0.125, 0) 88 o1: [.875, .875, .875, .875] 89 }, name="valid_padding").AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16")
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D | depthwise_conv2d_dilation.mod.py | 23 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable 24 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout, 1, 1).To(o1) 31 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 0) 39 o1: [11, 3, 7.2, 10.6, 43 }).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", quant8) 78 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable 79 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 2, 1, 1, 2, 0, layout, 1, 1).To(o1) 86 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 0) 94 o1: [11, 3, 7.2, 10.6, 98 }, name="valid_padding").AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", quant8)
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D | generate_proposals.mod.py | 25 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{4}") # scores out variable 29 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3) 36 o1: ("TENSOR_QUANT8_ASYMM", 0.01, 100), 56 o1: [0.95, 0.9, 0.85, 0.8], # scores out 74 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{30}") # scores out variable 78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3) 85 o1: ("TENSOR_QUANT8_ASYMM", 0.005, 0), 168 o1: [ # scores out
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D | max_pool_v1_2.mod.py | 21 o1 = Output("op4", "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) 27 o1: ("TENSOR_QUANT8_ASYMM", 0.5, 0) 33 o1: [1.0, 2.0, 3.0, 4.0] 34 }).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16") 116 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable 120 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2) 134 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 128), 143 o1: [], 154 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable [all …]
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D | concat_zero_sized.mod.py | 22 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable 26 model = Model().Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1… 41 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 128), 50 o1: [], 61 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable 65 model = Model().Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1… 81 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 128), 92 o1: [],
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D | grouped_conv2d.mod.py | 24 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # output 0 variable 25 Model().Operation("GROUPED_CONV_2D", i1, w1, b1, 0, 0, 0, 0, 1, 1, 2, act, layout).To(o1) 32 o1: ("TENSOR_QUANT8_ASYMM", 0.5, 80) 39 o1: ("TENSOR_QUANT8_ASYMM", 0.05, 80) 47 o1: ("TENSOR_QUANT8_ASYMM", 0.5, 80) 54 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 80) 61 o1: [33, -0.5, 65 }).AddNchw(i1, o1, layout).AddAllActivations(o1, act).AddVariations("relaxed", quant8, quant8_mult_…
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D | depthwise_conv2d_invalid_filter_dims.mod.py | 25 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable 26 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout).To(o1) 33 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 0) 41 o1: ("TENSOR_QUANT8_ASYMM", 0.1, 0) 47 o1: [0.] * (1 * 2 * 2 * 4) 48 }).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", channelQuant8,
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/frameworks/ml/nn/runtime/test/specs/V1_3/ |
D | resize_quant8_signed.mod.py | 21 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 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) 28 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128) 33 o1: [1.0, 1.0, 1.0, 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… 96 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out variable 100 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2) 114 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0), [all …]
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D | box_with_nms_limit_quant8_signed.mod.py | 22 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{18}") # scores out 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… 31 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128), 82 o1: [ 119 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{10}") # scores out 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… 128 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, 0), 179 o1: [ 208 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{12}") # scores out 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 …]
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D | l2_normalization_quant8_signed.mod.py | 18 o1 = Output("op2", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # output 0 variable 23 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 1.0 / 128, 0) 35 o1: [0.00, 0.60, 0.80, 46 Model().Operation("L2_NORMALIZATION", i1, axis).To(o1) 47 Example(example0).AddAllDimsAndAxis(i1, o1, axis).AddVariations(quant8_signed, includeDefault=False) 52 o1 = Output("op2", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # output 0 variable 57 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 1.0 / 128, 0) 69 o1: [0.00, 0.60, 0.80, 80 Model().Operation("L2_NORMALIZATION", i1).To(o1) 81 Example(example0).AddAllDims(i1, o1).AddVariations(quant8_signed, includeDefault=False)
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D | transpose_conv2d_quant8_signed.mod.py | 25 o1 = Output("op4", "TENSOR_FLOAT32", "{25, 32, 32, 16}") # output variable 26 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 1, 32, 32, act, layout).To(o1) 33 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128) 41 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -48) 46 o1: ([1] * 16 + [0] * (32 * 32 - 1) * 16) * 25 59 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 5, 5, 2}") # output variable 60 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 2, 2, 2, act, layout).To(o1) 67 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128) 74 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -48) 82 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -48) [all …]
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D | transpose_quant8_signed.mod.py | 25 o1 = Output("op4", "TENSOR_FLOAT32", "{25, 32, 32, 16}") # output variable 26 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 1, 32, 32, act, layout).To(o1) 33 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128) 41 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -48) 46 o1: ([1] * 16 + [0] * (32 * 32 - 1) * 16) * 25 59 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 5, 5, 2}") # output variable 60 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 2, 2, 2, act, layout).To(o1) 67 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128) 74 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -48) 82 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -48) [all …]
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D | prelu_quant8_signed.mod.py | 19 o1 = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 3}") variable 20 Model().Operation("PRELU", i1, a1).To(o1) 26 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -8) 33 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -8) 40 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -8) 47 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -8) 56 o1: [ 0, 0, 0,
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D | generate_proposals_quant8_signed.mod.py | 24 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{4}") # scores out variable 28 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3) 35 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -28), 55 o1: [0.95, 0.9, 0.85, 0.8], # scores out 74 o1 = Output("scoresOut", "TENSOR_FLOAT32", "{30}") # scores out variable 78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3) 85 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.005, -128), 168 o1: [ # scores out
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D | conv2d_quant8_signed.mod.py | 23 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable 24 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout, 1, 1).To(o1) 31 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128) 37 o1: [.875, .875, .875, .875] 38 }).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False) 74 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable 75 Model().Operation("CONV_2D", i1, f1, b1, 2, 1, 1, 0, layout, 1, 1).To(o1) 82 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128) 88 o1: [.875, .875, .875, .875] 89 }, name="valid_padding").AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False) [all …]
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D | grouped_conv2d_quant8_signed.mod.py | 24 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # output 0 variable 25 Model().Operation("GROUPED_CONV_2D", i1, w1, b1, 0, 0, 0, 0, 1, 1, 2, act, layout).To(o1) 32 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -48) 39 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.05, -48) 47 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -48) 54 o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -48) 61 o1: [33, -0.5, 65 }).AddNchw(i1, o1, layout).AddAllActivations(o1, act).AddVariations(quant8_signed, quant8_mult_gt_1…
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