/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | resize_nearest_neighbor.mod.py | 20 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 …]
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D | resize_bilinear_v1_2.mod.py | 20 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 …]
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D | detection_postprocess.mod.py | 18 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 …]
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D | l2_pool_v1_2.mod.py | 20 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 …]
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D | generate_proposals.mod.py | 21 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")
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D | add_v1_2.mod.py | 19 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],
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D | mul_v1_2.mod.py | 19 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],
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D | prelu.mod.py | 18 i1 = Input("input", "TENSOR_FLOAT32", "{1, 2, 2, 3}") variable 21 Model().Operation("PRELU", i1, a1).To(o1) 25 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128), 32 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128), 39 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128), 46 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128), 53 i1: [ 0, 0, 0,
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/frameworks/ml/nn/runtime/test/specs/V1_3/ |
D | resize_quant8_signed.mod.py | 20 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 …]
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D | strided_slice_quant8_signed.mod.py | 18 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 …]
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D | box_with_nms_limit_quant8_signed.mod.py | 18 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 …]
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D | conv2d_quant8_signed.mod.py | 20 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 …]
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D | transpose_quant8_signed.mod.py | 20 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 …]
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D | space_to_batch_quant8_signed.mod.py | 18 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 …]
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D | l2_normalization_quant8_signed.mod.py | 17 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)
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D | depthwise_conv2d_quant8_signed.mod.py | 20 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 …]
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D | space_to_depth_quant8_signed.mod.py | 18 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 …]
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D | depth_to_space_quant8_signed.mod.py | 18 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 …]
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D | transpose_conv2d_quant8_signed.mod.py | 20 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 …]
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D | generate_proposals_quant8_signed.mod.py | 20 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…
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D | mul_quant8_signed.mod.py | 18 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],
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D | add_quant8_signed.mod.py | 18 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],
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D | batch_to_space_quant8_signed.mod.py | 17 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)
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D | prelu_quant8_signed.mod.py | 17 i1 = Input("input", "TENSOR_FLOAT32", "{1, 2, 2, 3}") variable 20 Model().Operation("PRELU", i1, a1).To(o1) 24 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0), 31 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0), 38 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0), 45 i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0), 52 i1: [ 0, 0, 0,
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/frameworks/base/core/java/android/os/ |
D | WorkSource.java | 629 int i1 = 0, i2 = 0; in removeUids() local 631 while (i1 < N1 && i2 < N2) { in removeUids() 632 if (DEBUG) Log.d(TAG, "Step: target @ " + i1 + " of " + N1 + ", other @ " + i2 in removeUids() 634 if (uids2[i2] == uids1[i1]) { in removeUids() 635 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 in removeUids() 636 + ": remove " + uids1[i1]); in removeUids() 639 if (i1 < N1) System.arraycopy(uids1, i1+1, uids1, i1, N1-i1); in removeUids() 641 } else if (uids2[i2] > uids1[i1]) { in removeUids() 642 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 + ": skip i1"); in removeUids() 643 i1++; in removeUids() [all …]
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