/frameworks/ml/nn/runtime/test/specs/V1_0/ |
D | mobilenet_quantized.mod.py | 139 i1 = Parameter("op1", "TENSOR_INT32", "{32}, 0.000220113914111, 0", [18729, 13775, 11414, -1774, 12… 140 i2 = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{32, 3, 3, 3}, 0.0281745810062, 112", [95, 32, 209, 1… 142 i4 = Parameter("op4", "TENSOR_INT32", "{512}, 0.000443405413534, 0", [1496, 2937, -3899, 3591, 7857… 143 i5 = Parameter("op5", "TENSOR_QUANT8_ASYMM", "{1, 3, 3, 512}, 0.0188454780728, 140", [118, 132, 157… 145 i7 = Parameter("op7", "TENSOR_INT32", "{512}, 0.000162604788784, 0", [-16901, 4449, 3965, -23286, -… 146 i8 = Parameter("op8", "TENSOR_QUANT8_ASYMM", "{512, 1, 1, 512}, 0.00691097788513, 136", [126, 134, … 148 i10 = Parameter("op10", "TENSOR_INT32", "{512}, 0.000354939606041, 0", [11394, -1999, 4880, -2676, … 149 i11 = Parameter("op11", "TENSOR_QUANT8_ASYMM", "{1, 3, 3, 512}, 0.0150855332613, 132", [126, 152, 1… 151 i13 = Parameter("op13", "TENSOR_INT32", "{512}, 0.000200755792321, 0", [-4877, 721, 678, 4292, 1007… 152 i14 = Parameter("op14", "TENSOR_QUANT8_ASYMM", "{512, 1, 1, 512}, 0.00853246077895, 115", [116, 122… [all …]
|
D | mobilenet_224_gender_basic_fixed.mod.py | 138 i1 = Parameter("op1", "TENSOR_FLOAT32", "{16}", [0.247857, 0.75021, 0.741359, 1.36951, -0.799518, 0… 139 i2 = Parameter("op2", "TENSOR_FLOAT32", "{16, 3, 3, 3}", [0.652068, -0.440708, -0.370313, 0.0371835… 141 i4 = Parameter("op4", "TENSOR_FLOAT32", "{128}", [-0.604559, 0.937928, -0.974893, -0.53343, 1.28805… 142 i5 = Parameter("op5", "TENSOR_FLOAT32", "{1, 3, 3, 128}", [-0.371999, -0.346798, 0.0479857, 0.35729… 144 i7 = Parameter("op7", "TENSOR_FLOAT32", "{128}", [-0.239844, 0.432217, -0.153807, 0.0767933, -0.275… 145 i8 = Parameter("op8", "TENSOR_FLOAT32", "{128, 1, 1, 128}", [-0.172699, 0.0449607, -0.00371321, 0.0… 147 i10 = Parameter("op10", "TENSOR_FLOAT32", "{128}", [0.870905, 0.732366, -0.669046, 1.08174, 0.91615… 148 i11 = Parameter("op11", "TENSOR_FLOAT32", "{1, 3, 3, 128}", [-0.0338548, -0.209956, 0.299, -0.58708… 150 i13 = Parameter("op13", "TENSOR_FLOAT32", "{128}", [0.546519, 0.196527, 1.33245, 0.223313, -0.06860… 151 i14 = Parameter("op14", "TENSOR_FLOAT32", "{128, 1, 1, 128}", [0.0492167, -0.0080753, 0.106292, 0.0… [all …]
|
/frameworks/ml/nn/runtime/test/specs/V1_3/ |
D | strided_slice_quant8_signed.mod.py | 19 begins = Parameter("begins", "TENSOR_INT32", "{2}", [1, 0]) 20 ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, 2]) 21 strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1]) 44 begins = Parameter("begins", "TENSOR_INT32", "{2}", [0, 0]) 45 ends = Parameter("ends", "TENSOR_INT32", "{2}", [1, 3]) 46 strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1]) 69 begins = Parameter("begins", "TENSOR_INT32", "{1}", [1]) 70 ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) 71 strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) 94 begins = Parameter("begins", "TENSOR_INT32", "{1}", [-3]) [all …]
|
D | conv2d_quant8_signed.mod.py | 21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 43 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 2, 3, 4, 5, 6, 7, 8, 9]) 44 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 72 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) 73 b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 94 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 2, 3, 4, 5, 6, 7, 8, 9]) 95 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 124 f3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) 125 b3 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) [all …]
|
D | depthwise_conv2d_quant8_signed.mod.py | 21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) 49 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]) 50 b2 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [0,0,0,0]) 78 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… 79 b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) 106 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]) 107 b2 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [0,0,0,0]) 135 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) 136 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) [all …]
|
D | transpose_conv2d_quant8_signed.mod.py | 21 w1 = Parameter("op2", "TENSOR_FLOAT32", "{16, 1, 1, 1}", [1] * 16) # weight 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{16}", [0] * 16) # bias 55 w1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 3, 3, 1}", [1, 3, 5, 7, 9, 11, 13, 15, 17, 2, 4, 6, 8,… 56 b1 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [-1.5, -2]) # bias 105 w2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [9, 5, 6, 9, 8, 5, 3, 1, 4]) # weight 106 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [-1000]) # bias 137 w3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,… 138 b3 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) # bias 163 w4 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,… 164 b4 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) # bias [all …]
|
D | transpose_quant8_signed.mod.py | 21 w1 = Parameter("op2", "TENSOR_FLOAT32", "{16, 1, 1, 1}", [1] * 16) # weight 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{16}", [0] * 16) # bias 55 w1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 3, 3, 1}", [1, 3, 5, 7, 9, 11, 13, 15, 17, 2, 4, 6, 8,… 56 b1 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [-1.5, -2]) # bias 105 w2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [9, 5, 6, 9, 8, 5, 3, 1, 4]) # weight 106 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [-1000]) # bias 138 w3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,… 139 b3 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) # bias 164 w4 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,… 165 b4 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) # bias [all …]
|
D | fully_connected_quant8_signed.mod.py | 19 weights = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{3, 10}, 0.5f, -1", 23 bias = Parameter("b0", "TENSOR_INT32", "{3}, 0.25f, 0", [4, 8, 12]) 42 weights = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5}, 0.2, -128", [-118, -108, -108, -1… 43 bias = Parameter("b0", "TENSOR_INT32", "{1}, 0.04, 0", [10]) 84 weights = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1}, 0.5f, -128", [-126]) 85 bias = Parameter("b0", "TENSOR_INT32", "{1}, 0.25f, 0", [4]) 124 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 1}", [2]) 125 bias = Parameter("b0", "TENSOR_FLOAT32", "{1}", [4]) 150 p1 = Parameter("scores", "TENSOR_FLOAT32", "{1, 2}", [0.90, 0.10]) # scores 151 p2 = Parameter("roi", "TENSOR_FLOAT32", "{1, 8}", [1, 1, 10, 10, 0, 0, 10, 10]) # roi [all …]
|
D | space_to_batch_quant8_signed.mod.py | 19 block = Parameter("block_size", "TENSOR_INT32", "{2}", [2, 2]) 20 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) 49 block = Parameter("block_size", "TENSOR_INT32", "{2}", [3, 2]) 50 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) 77 block = Parameter("block_size", "TENSOR_INT32", "{2}", [3, 2]) 78 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 1, 2, 4]) 109 block = Parameter("block_size", "TENSOR_INT32", "{2}", [3, 2]) 110 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) 139 pad1 = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) 176 pad3 = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) [all …]
|
D | pad_quant8_signed.mod.py | 20 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [1, 2, 48 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) 61 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, 84 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, 104 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, 126 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [1, 2, 151 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1])
|
D | grouped_conv2d_quant8_signed.mod.py | 21 w1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 1}", [1, 2, 2, 1, 4, 3, 2, 1]) # weight 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [10, -33.5]) # bias 70 w2 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 3, 1}", [100, 20, 1, 200, 10, 2, 200, 30, 1, 100, 2… 71 b2 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [500, -1000]) # bias 106 w3 = Parameter("op2", "TENSOR_FLOAT32", "{6, 1, 1, 3}", [1, 2, 3, 2, 1, 0, 2, 3, 3, 6, 6, 6, 9, 8, … 107 b3 = Parameter("op3", "TENSOR_FLOAT32", "{6}", [10, -20, 30, -40, 50, -60]) # bias
|
/frameworks/ml/nn/runtime/test/specs/V1_1/ |
D | mobilenet_224_gender_basic_fixed_relaxed.mod.py | 154 i1 = Parameter("op1", "TENSOR_FLOAT32", "{16}", [0.247857, 0.75021, 0.741359, 1.36951, -0.799518, 0… 155 i2 = Parameter("op2", "TENSOR_FLOAT32", "{16, 3, 3, 3}", [0.652068, -0.440708, -0.370313, 0.0371835… 157 i4 = Parameter("op4", "TENSOR_FLOAT32", "{128}", [-0.604559, 0.937928, -0.974893, -0.53343, 1.28805… 158 i5 = Parameter("op5", "TENSOR_FLOAT32", "{1, 3, 3, 128}", [-0.371999, -0.346798, 0.0479857, 0.35729… 160 i7 = Parameter("op7", "TENSOR_FLOAT32", "{128}", [-0.239844, 0.432217, -0.153807, 0.0767933, -0.275… 161 i8 = Parameter("op8", "TENSOR_FLOAT32", "{128, 1, 1, 128}", [-0.172699, 0.0449607, -0.00371321, 0.0… 163 i10 = Parameter("op10", "TENSOR_FLOAT32", "{128}", [0.870905, 0.732366, -0.669046, 1.08174, 0.91615… 164 i11 = Parameter("op11", "TENSOR_FLOAT32", "{1, 3, 3, 128}", [-0.0338548, -0.209956, 0.299, -0.58708… 166 i13 = Parameter("op13", "TENSOR_FLOAT32", "{128}", [0.546519, 0.196527, 1.33245, 0.223313, -0.06860… 167 i14 = Parameter("op14", "TENSOR_FLOAT32", "{128, 1, 1, 128}", [0.0492167, -0.0080753, 0.106292, 0.0… [all …]
|
D | strided_slice_qaunt8_11.mod.py | 3 begins = Parameter("begins", "TENSOR_INT32", "{2}", [0, 0]) 4 ends = Parameter("ends", "TENSOR_INT32", "{2}", [1, 3]) 5 strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1])
|
/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | transpose_conv2d.mod.py | 21 w1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 3, 3, 1}", [1, 3, 5, 7, 9, 11, 13, 15, 17, 2, 4, 6, 8,… 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [-1.5, -2]) # bias 70 w2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [9, 5, 6, 9, 8, 5, 3, 1, 4]) # weight 71 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [-1000]) # bias 102 w3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,… 103 b3 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) # bias 128 w4 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,… 129 b4 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) # bias 156 w5 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,… 157 b5 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) # bias [all …]
|
D | conv2d_v1_2.mod.py | 21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 49 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 4, 7, 2, 5, 8, 3, 6, 9]) 50 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [-200]) 77 f3 = Parameter("op2", "TENSOR_FLOAT32", "{3, 1, 1, 3}", [0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.… 78 b3 = Parameter("op3", "TENSOR_FLOAT32", "{3}", [0., 0., 0.]) 105 f4 = Parameter("op2", "TENSOR_FLOAT32", "{3, 1, 1, 3}", [1., 4., 7., 2., 5., 8., 3., 6., 9.]) 106 b4 = Parameter("op3", "TENSOR_FLOAT32", "{3}", [0., 0., 0.]) 145 f5 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 2, 3}", [-0.966213, -0.467474, -0.82203, -0.579455,… 146 b5 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0.]) [all …]
|
D | quantized_lstm.mod.py | 120 input_to_input_weights = Parameter("inputToInputWeights", InputWeightsType, 122 input_to_forget_weights = Parameter("inputToForgetWeights", InputWeightsType, 124 input_to_cell_weights = Parameter("inputToCellWeights", InputWeightsType, 126 input_to_output_weights = Parameter("inputToOutputWeights", InputWeightsType, 131 recurrent_to_input_weights = Parameter("recurrentToInputWeights", RecurrentWeightsType, 133 recurrent_to_forget_weights = Parameter("recurrentToForgetWeights", RecurrentWeightsType, 135 recurrent_to_cell_weights = Parameter("recurrentToCellWeights", RecurrentWeightsType, 137 recurrent_to_output_weights = Parameter("recurrentToOutputWeights", RecurrentWeightsType, 141 input_gate_bias = Parameter("inputGateBias", BiasType, 143 forget_gate_bias = Parameter("forgetGateBias", BiasType, [all …]
|
D | conv2d_dilation.mod.py | 21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 43 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 2, 3, 4, 5, 6, 7, 8, 9]) 44 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 72 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) 73 b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 94 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 2, 3, 4, 5, 6, 7, 8, 9]) 95 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 124 f3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) 125 b3 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0])
|
D | depthwise_conv2d_dilation.mod.py | 21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) 48 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]) 49 b2 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [0,0,0,0]) 76 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… 77 b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) 103 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]) 104 b2 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [0,0,0,0]) 130 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) 131 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0])
|
D | conv2d_per_channel.mod.py | 18 f1 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{3, 1, 1, 2}", 20 b1 = Parameter("op3", "TENSOR_INT32", "{3}", [4, 4, 4]) 33 f2 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{3, 1, 1, 2}", 35 b2 = Parameter("op3", "TENSOR_INT32", "{3}", [4, 4, 4]) 48 p1 = Parameter("scores", "TENSOR_QUANT8_ASYMM", "{1, 2}, 0.1f, 128", [137, 129]) # scores 49 p2 = Parameter("roi", "TENSOR_QUANT16_ASYMM", "{1, 8}, 0.125f, 0", [1, 1, 10, 10, 0, 0, 10, 10]) # … 62 w = Parameter("weights", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{3, 1, 1, 2}", 64 b = Parameter("bias", "TENSOR_INT32", "{3}", [4, 4, 4])
|
D | depthwise_conv2d_v1_2.mod.py | 21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) 60 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1, 2, 3, 4, -9, 10, -11, 12, 5, 6, 7, 8, 1… 61 b2 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) 88 f3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 2}", [.25, 0, .25, 1, .25, 0, .25, 1]) 89 b3 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [100, 200]) 116 f4 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0, 10, 50, .25, 1, 20, 50, .25, 0, 30… 117 b4 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [6000, 7000, 8000, 9000]) 151 f9 = Parameter( 157 b9 = Parameter("op3", ("TENSOR_INT32", [4], input_scale * filter_scale, 0),
|
D | depthwise_conv2d_per_channel.mod.py | 18 f1 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{1, 2, 2, 2}", 21 b1 = Parameter("op3", "TENSOR_INT32", "{2}", [0, 0]) 34 f2 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{1, 2, 2, 4}", 37 b2 = Parameter("op3", "TENSOR_INT32", "{4}", [4, 4, 4, 4]) 53 f3 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{1, 2, 2, 4}", 56 b3 = Parameter("op3", "TENSOR_INT32", "{4}", [4, 4, 4, 4])
|
D | fully_connected_v1_2.mod.py | 20 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 1}", [2]) 21 bias = Parameter("b0", "TENSOR_FLOAT32", "{1}", [4]) 52 p1 = Parameter("scores", "TENSOR_FLOAT32", "{1, 2}", [0.90, 0.10]) # scores 53 p2 = Parameter("roi", "TENSOR_FLOAT32", "{1, 8}", [1, 1, 10, 10, 0, 0, 10, 10]) # roi 67 w = Parameter("weights", "TENSOR_FLOAT32", "{1, 3}", [1, 2, 3]) # weights 68 b = Parameter("bias", "TENSOR_FLOAT32", "{1}", [1]) # bias
|
D | grouped_conv2d.mod.py | 21 w1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 1}", [1, 2, 2, 1, 4, 3, 2, 1]) # weight 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [10, -33.5]) # bias 70 w2 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 3, 1}", [100, 20, 1, 200, 10, 2, 200, 30, 1, 100, 2… 71 b2 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [500, -1000]) # bias 106 w3 = Parameter("op2", "TENSOR_FLOAT32", "{6, 1, 1, 3}", [1, 2, 3, 2, 1, 0, 2, 3, 3, 6, 6, 6, 9, 8, … 107 b3 = Parameter("op3", "TENSOR_FLOAT32", "{6}", [10, -20, 30, -40, 50, -60]) # bias
|
/frameworks/opt/calendar/src/com/android/calendarcommon2/ |
D | ICalendar.java | 237 private LinkedHashMap<String, ArrayList<Parameter>> mParamsMap = 238 new LinkedHashMap<String, ArrayList<Parameter>>(); 287 public void addParameter(Parameter param) { in addParameter() 288 ArrayList<Parameter> params = mParamsMap.get(param.name); in addParameter() 290 params = new ArrayList<Parameter>(); in addParameter() 310 public List<Parameter> getParameters(String name) { in getParameters() 320 public Parameter getFirstParameter(String name) { in getFirstParameter() 321 ArrayList<Parameter> params = mParamsMap.get(name); in getFirstParameter() 343 for (Parameter param : getParameters(parameterName)) { in toString() 357 public static class Parameter { class in ICalendar [all …]
|
/frameworks/base/startop/view_compiler/ |
D | dex_testcase_generator.cc | 72 returnParam.BuildReturn(Value::Parameter(0)); in GenerateSimpleTestCases() 85 Instruction::InvokeVirtual(string_length.id, result, Value::Parameter(0))); in GenerateSimpleTestCases() 97 Instruction::Op::kBranchEqz, /*dest=*/{}, Value::Parameter(0), else_target)); in GenerateSimpleTestCases() 118 Instruction::Op::kBranchNEqz, /*dest=*/{}, Value::Parameter(0), else_target)); in GenerateSimpleTestCases() 206 Instruction::Op::kBranchEqz, /*dest=*/{}, Value::Parameter(0), else_target)); in GenerateSimpleTestCases() 226 Instruction::Op::kBranchEqz, /*dest=*/{}, Value::Parameter(0), else_target)); in GenerateSimpleTestCases() 253 to_string.id, result, Value::Parameter(0), Value::Parameter(1))); in GenerateSimpleTestCases() 267 substring.id, result, Value::Parameter(0), Value::Parameter(1))); in GenerateSimpleTestCases() 280 Instruction::Cast(Value::Parameter(0), Value::Type(type_def->orig_index))); in GenerateSimpleTestCases() 281 method.BuildReturn(Value::Parameter(0), /*is_object=*/true); in GenerateSimpleTestCases() [all …]
|