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/frameworks/ml/nn/runtime/test/specs/V1_0/
Dmobilenet_quantized.mod.py139 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 …]
Dmobilenet_224_gender_basic_fixed.mod.py138 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/
Dstrided_slice_quant8_signed.mod.py19 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 …]
Dconv2d_quant8_signed.mod.py21 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 …]
Ddepthwise_conv2d_quant8_signed.mod.py21 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 …]
Dtranspose_conv2d_quant8_signed.mod.py21 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 …]
Dtranspose_quant8_signed.mod.py21 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 …]
Dfully_connected_quant8_signed.mod.py19 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 …]
Dspace_to_batch_quant8_signed.mod.py19 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 …]
Dpad_quant8_signed.mod.py20 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])
Dgrouped_conv2d_quant8_signed.mod.py21 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/
Dmobilenet_224_gender_basic_fixed_relaxed.mod.py154 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 …]
Dstrided_slice_qaunt8_11.mod.py3 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/
Dtranspose_conv2d.mod.py21 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 …]
Dconv2d_v1_2.mod.py21 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 …]
Dquantized_lstm.mod.py120 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 …]
Dconv2d_dilation.mod.py21 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])
Ddepthwise_conv2d_dilation.mod.py21 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])
Dconv2d_per_channel.mod.py18 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])
Ddepthwise_conv2d_v1_2.mod.py21 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),
Ddepthwise_conv2d_per_channel.mod.py18 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])
Dfully_connected_v1_2.mod.py20 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
Dgrouped_conv2d.mod.py21 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/
DICalendar.java237 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
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/frameworks/base/startop/view_compiler/
Ddex_testcase_generator.cc72 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()
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