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/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
Dless.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
20 input1: input1_data,
32 input1_data=[10, 7, 5],
42 input1_data=[10, 5],
52 input1_data=[129], # effectively 2
63 input1_data=[131], # effectively 2
74 input1_data=[200],
85 input1_data=[0],
96 input1_data=[False, False, True, True],
Dgreater_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
20 input1: input1_data,
32 input1_data=[10, 7, 5],
42 input1_data=[10, 5],
52 input1_data=[129], # effectively 2
63 input1_data=[131], # effectively 2
74 input1_data=[200],
85 input1_data=[0],
96 input1_data=[False, False, True, True],
Dequal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
20 input1: input1_data,
32 input1_data=[10, 7, 5],
42 input1_data=[10, 5],
52 input1_data=[129], # effectively 2
63 input1_data=[131], # effectively 2
74 input1_data=[200],
85 input1_data=[0],
96 input1_data=[False, False, True, True],
Dless_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
20 input1: input1_data,
32 input1_data=[10, 7, 5],
42 input1_data=[10, 5],
52 input1_data=[129], # effectively 2
63 input1_data=[131], # effectively 2
74 input1_data=[200],
85 input1_data=[0],
96 input1_data=[False, False, True, True],
Dgreater.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
20 input1: input1_data,
32 input1_data=[10, 7, 5],
42 input1_data=[10, 5],
52 input1_data=[129], # effectively 2
63 input1_data=[131], # effectively 2
74 input1_data=[200],
85 input1_data=[0],
96 input1_data=[False, False, True, True],
Dnot_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
20 input1: input1_data,
32 input1_data=[10, 7, 5],
42 input1_data=[10, 5],
52 input1_data=[129], # effectively 2
63 input1_data=[131], # effectively 2
74 input1_data=[200],
85 input1_data=[0],
96 input1_data=[False, False, True, True],
Dselect_v1_2.mod.py16 def test(name, input0, input1, input2, output0, input0_data, input1_data, input2_data, output_data): argument
25 input1: input1_data,
37 input1_data=[1, 2, 3],
49 input1_data=[1, 2, 3, 4],
61 input1_data=[1, 2, 3, 4, 5, 6, 7, 8],
Dlogical_and.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
21 input1: input1_data,
31 input1_data=[True, False, True, False],
41 input1_data=[True],
Dlogical_or.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
21 input1: input1_data,
31 input1_data=[True, False, True, False],
41 input1_data=[False],
Dmaximum.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
28 input1: input1_data,
39 input1_data=[-1.0, 0.0, 1.0, 12.0, -3.0, -1.43],
49 input1_data=[0.5, 2.0],
Dminimum.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
28 input1: input1_data,
39 input1_data=[-1.0, 0.0, 1.0, 12.0, -3.0, -1.43],
49 input1_data=[0.5, 2.0],
/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
Dgreater_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
20 input1: input1_data,
30 input1_data=[1], # effectively 2
40 input1_data=[3], # effectively 2
50 input1_data=[72],
60 input1_data=[-128],
Dgreater_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
20 input1: input1_data,
30 input1_data=[1], # effectively 2
40 input1_data=[3], # effectively 2
50 input1_data=[72],
60 input1_data=[-128],
Dnot_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
20 input1: input1_data,
30 input1_data=[1], # effectively 2
40 input1_data=[3], # effectively 2
50 input1_data=[72],
60 input1_data=[-128],
Dequal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
20 input1: input1_data,
30 input1_data=[1], # effectively 2
40 input1_data=[3], # effectively 2
50 input1_data=[72],
60 input1_data=[-128],
Dless_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
20 input1: input1_data,
30 input1_data=[1], # effectively 2
40 input1_data=[3], # effectively 2
50 input1_data=[72],
60 input1_data=[-128],
Dless_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
20 input1: input1_data,
30 input1_data=[1], # effectively 2
40 input1_data=[3], # effectively 2
50 input1_data=[72],
60 input1_data=[-128],
Dselect_quant8_signed.mod.py16 def test(name, input0, input1, input2, output0, input0_data, input1_data, input2_data, output_data): argument
25 input1: input1_data,
37 input1_data=[1, 2, 3],
49 input1_data=[1, 2, 3, 4],
61 input1_data=[1, 2, 3, 4, 5, 6, 7, 8],
Dmaximum_quant8_signed.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
28 input1: input1_data,
39 input1_data=[-1.0, 0.0, 1.0, 12.0, -3.0, -1.43],
49 input1_data=[0.5, 2.0],
Dminimum_quant8_signed.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
28 input1: input1_data,
39 input1_data=[-1.0, 0.0, 1.0, 12.0, -3.0, -1.43],
49 input1_data=[0.5, 2.0],
/packages/modules/NeuralNetworks/runtime/test/specs/AIDL_V2/
Dbatch_matmul.mod.py16 def test(name, input0, input1, adj0, adj1, output, input0_data, input1_data, argument
27 input1: input1_data,
41 input1_data=[7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18],
53 input1_data=[7, 11, 15, 8, 12, 16, 9, 13, 17, 10, 14, 18],
65 input1_data=[7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18],
77 input1_data=[7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,