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/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
Dresize_nearest_neighbor_v1_3.mod.py17 half_pixel_centers, output0, input0_data, output_data): argument
31 output0: output_data,
47 output_data=[2, 4, 2, 4],
60 output_data=[4],
73 output_data=[1, 2, 2, 3, 4, 4, 3, 4, 4],
86 output_data=[1, 1, 2, 2, 2, 3, 3, 4, 4, 4],
99 output_data=[1, 3, 4, 9, 11, 12, 13, 15, 16],
112 output_data=[1, 2, 1, 2, 3, 4, 3, 4, 3, 4],
125 output_data=[1, 1, 2, 2, 1, 1, 2, 2, 3, 3, 4, 4, 3, 3, 4, 4],
138 output_data=[
[all …]
Dgather_quant8_signed.mod.py46 def test(input0, axis, indices, output0, input_data, output_data): argument
56 output0: output_data,
66 output_data=[0.7, 0.8,
77 output_data=[0.7, 0.8],
86 output_data=[2],
95 output_data=[2, 1],
105 output_data=[-2.0, 0.2,
117 output_data=[0.2, 0.8],
127 output_data=[4, 5, 6,
138 output_data=[3, 1,
Dresize_bilinear_v1_3.mod.py25 output_data, argument
44 output0: output_data,
60 output_data=[
233 output_data=[
321 output_data=[
492 output_data=[1],
505 output_data=[1, 1.5, 2, 2, 2.5, 3, 3, 3.5, 4],
518 output_data=[1, 3, 7, 9],
531 output_data=[1, 2.5, 4, 7, 8.5, 10, 13, 14.5, 16],
Dreduce_min_quant8_signed.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
25 output0: output_data,
36 output_data=[-2, 3, -6],
47 output_data=[9.527],
58 output_data=[0.1, 0.2],
69 output_data=[0.1, 0.3, 0.5],
Dreduce_max_quant8_signed.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
25 output0: output_data,
36 output_data=[-1, 4, 5],
47 output_data=[9.527],
58 output_data=[2.3, 2.4],
69 output_data=[2.0, 2.2, 2.4],
Dequal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
21 output0: output_data,
31 output_data=[False, True, False],
41 output_data=[False, True, False],
51 output_data=[False],
61 output_data=[False],
Dgreater_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
21 output0: output_data,
31 output_data=[False, True, True],
41 output_data=[False, True, True],
51 output_data=[True],
61 output_data=[False],
Dgreater_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
21 output0: output_data,
31 output_data=[False, False, True],
41 output_data=[False, False, True],
51 output_data=[True],
61 output_data=[False],
Dless_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
21 output0: output_data,
31 output_data=[True, False, False],
41 output_data=[True, False, False],
51 output_data=[False],
61 output_data=[True],
Dless_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
21 output0: output_data,
31 output_data=[True, True, False],
41 output_data=[True, True, False],
51 output_data=[False],
61 output_data=[True],
Dnot_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
21 output0: output_data,
31 output_data=[True, False, True],
41 output_data=[True, False, True],
51 output_data=[True],
61 output_data=[True],
/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
Dgather.mod.py17 def test(input0, axis, indices, output0, input_data, output_data): argument
37 output0: output_data,
47 output_data=[0.7, 0.8,
58 output_data=[0.7, 0.8],
67 output_data=[2],
76 output_data=[2, 1],
86 output_data=[-2.0, 0.2,
98 output_data=[0.2, 0.8],
108 output_data=[4, 5, 6,
119 output_data=[3, 1,
Dnot_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
21 output0: output_data,
33 output_data=[True, False, True],
43 output_data=[True, False, False, True],
53 output_data=[True, False, True],
64 output_data=[True, False, True],
75 output_data=[True],
86 output_data=[True],
97 output_data=[False, True, True, False],
Dgreater_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
21 output0: output_data,
33 output_data=[False, True, True],
43 output_data=[False, True, True, True],
53 output_data=[False, True, True],
64 output_data=[False, True, True],
75 output_data=[True],
86 output_data=[False],
97 output_data=[True, True, False, True],
Dequal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
21 output0: output_data,
33 output_data=[False, True, False],
43 output_data=[False, True, True, False],
53 output_data=[False, True, False],
64 output_data=[False, True, False],
75 output_data=[False],
86 output_data=[False],
97 output_data=[True, False, False, True],
Dgreater.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
21 output0: output_data,
33 output_data=[False, False, True],
43 output_data=[False, False, False, True],
53 output_data=[False, False, True],
64 output_data=[False, False, True],
75 output_data=[True],
86 output_data=[False],
97 output_data=[False, True, False, False],
Dless.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
21 output0: output_data,
33 output_data=[True, False, False],
43 output_data=[True, False, False, False],
53 output_data=[True, False, False],
64 output_data=[True, False, False],
75 output_data=[False],
86 output_data=[True],
97 output_data=[False, False, True, False],
Dless_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
21 output0: output_data,
33 output_data=[True, True, False],
43 output_data=[True, True, True, False],
53 output_data=[True, True, False],
64 output_data=[True, True, False],
75 output_data=[False],
86 output_data=[True],
97 output_data=[True, False, True, True],
Dslice.mod.py32 output_data=[2, 3]),
41 output_data=[4, 5]),
50 output_data=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]),
59 output_data=[2, 3, 4]),
68 output_data=[3, 3, 3]),
77 output_data=[3, 3, 3, 5, 5, 5]),
86 output_data=[3, 3, 3, 5, 5, 5]),
95 output_data=[3, 3, 3, 5, 5, 5]),
105 test_case.output: test_case.output_data,
Dlog_softmax.mod.py19 def test(input0, output0, input_data, beta, axis, output_data): argument
23 output0: output_data,
33 output_data=[-4.14297, -10.14297, -2.14297, -.142971,
46 output_data=[-.00247565, -6.00247,
59 output_data=[-.00247565, -2.12692, -.00671534, -.000123374,
70 output_data=[-4.14297, -10.14297, -2.14297, -.142971,
Dreduce_sum.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
21 output0: output_data,
32 output_data=[-1 - 2, 3 + 4, 5 - 6],
43 output_data=[9.527],
54 output_data=[14.4, 15.6],
65 output_data=[8.4, 10.0, 11.6],
Dreduce_prod.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
21 output0: output_data,
32 output_data=[-1 * -2, 3 * 4, 5 * -6],
43 output_data=[9.527],
54 output_data=[3.16234143225e+4, 1.9619905536e+4],
65 output_data=[7.74592e+2, 1.197504e+3, 6.6889152e+2],
Dunidirectional_sequence_rnn.mod.py21 recurrent_weights_data, bias_data, hidden_state_data, output_data): argument
33 output: output_data
113 output_data = [ variable
159 output_data=output_data)
182 output_data=convert_to_time_major(output_data, num_batches, max_time,
Dreduce_max.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
25 output0: output_data,
36 output_data=[-1, 4, 5],
47 output_data=[9.527],
58 output_data=[2.3, 2.4],
69 output_data=[2.0, 2.2, 2.4],
Dreduce_min.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
25 output0: output_data,
36 output_data=[-2, 3, -6],
47 output_data=[9.527],
58 output_data=[0.1, 0.2],
69 output_data=[0.1, 0.3, 0.5],

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