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/frameworks/ml/nn/runtime/test/specs/V1_3/
Dminimum_quant8_signed.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
18 model = Model().Operation("MINIMUM", input0, input1).To(output0)
22 input1: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.0, -28],
28 input1: input1_data,
36 input1=Input("input1", "TENSOR_FLOAT32", "{3, 1, 2}"),
46 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
55 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0f, 0") variable
57 model = Model().Operation("MINIMUM", input0, input1).To(output0)
61 input1: [0, 72],
Dmaximum_quant8_signed.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
18 model = Model().Operation("MAXIMUM", input0, input1).To(output0)
22 input1: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.0, -28],
28 input1: input1_data,
36 input1=Input("input1", "TENSOR_FLOAT32", "{3, 1, 2}"),
46 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
56 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0f, 0") variable
58 model = Model().Operation("MAXIMUM", input0, input1).To(output0)
62 input1: [0, 72],
Ddiv_int32.mod.py18 input1 = Input("input1", "TENSOR_INT32", "{2, 2, 4, 6}") variable
20 model = model.Operation("DIV", input0, input1, 0).To(output)
40 input1: [
82 input1 = Input("input1", "TENSOR_INT32", "{1}") variable
84 model = Model("by_zero").Operation("DIV", input0, input1, 0).To(output)
87 input1: [0],
Dnot_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
17 model = Model().Operation("NOT_EQUAL", input0, input1).To(output0)
20 input1: input1_data,
27 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 2.0, 0)),
37 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.0, 1)),
47 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.49725, 112)),
57 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.64771, -97)),
Dless_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
17 model = Model().Operation("LESS_EQUAL", input0, input1).To(output0)
20 input1: input1_data,
27 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 2.0, 0)),
37 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.0, 1)),
47 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.49725, 112)),
57 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.64771, -97)),
Dgreater_equal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
17 model = Model().Operation("GREATER_EQUAL", input0, input1).To(output0)
20 input1: input1_data,
27 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 2.0, 0)),
37 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.0, 1)),
47 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.49725, 112)),
57 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.64771, -97)),
Dless_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
17 model = Model().Operation("LESS", input0, input1).To(output0)
20 input1: input1_data,
27 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 2.0, 0)),
37 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.0, 1)),
47 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.49725, 112)),
57 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.64771, -97)),
Dequal_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
17 model = Model().Operation("EQUAL", input0, input1).To(output0)
20 input1: input1_data,
27 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 2.0, 0)),
37 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.0, 1)),
47 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.49725, 112)),
57 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.64771, -97)),
Dgreater_quant8_signed.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
17 model = Model().Operation("GREATER", input0, input1).To(output0)
20 input1: input1_data,
27 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 2.0, 0)),
37 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.0, 1)),
47 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.49725, 112)),
57 input1=Input("input1", ("TENSOR_QUANT8_ASYMM_SIGNED", [1], 1.64771, -97)),
Dselect_quant8_signed.mod.py16 def test(name, input0, input1, input2, output0, input0_data, input1_data, input2_data, output_data): argument
17 model = Model().Operation("SELECT", input0, input1, input2).To(output0)
19 input1: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.5, 1],
25 input1: input1_data,
33 input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
45 input1=Input("input1", "TENSOR_FLOAT32", "{2, 2}"),
57 input1=Input("input1", "TENSOR_FLOAT32", "{2, 1, 2, 1, 2}"),
Dconcat_quant8_signed.mod.py20 input1 = Input("input1", "TENSOR_FLOAT32", "{2, 1, 2}") variable
26 model = Model().Operation("CONCATENATION", input0, input1, input2, input3, axis).To(output0)
31 input1: [1.1, 3.1, 4.1, 7.1],
37 input1: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.05, -128],
46 input1: [1.1, 3.1, 4.1, 7.1],
52 input1: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.05, -128],
84 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d}, 0.5f, -128" % (row1, col)) variable
88 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output)
94 input0 = {input1: [x - 128 for x in input1_values],
111 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d}, 0.5f, -128" % (row, col1)) variable
[all …]
Dsub_quant8_signed.mod.py41 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED",
46 model = Model().Operation("SUB", input0, input1, activation).To(output0)
49 input1: input1_values,
66 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 2}, 1.0, -128") variable
70 model = Model("quant8").Operation("SUB", input0, input1, activation).To(output0)
80 input1: input1_values,
88 input1 = Input("input1", "TENSOR_QUANT8_ASYMM_SIGNED", shape) variable
92 model = Model("quant8").Operation("SUB", input0, input1, activation).To(output0)
102 input1: input1_values,
/frameworks/ml/nn/runtime/test/specs/V1_2/
Dmaximum.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
18 model = Model().Operation("MAXIMUM", input0, input1).To(output0)
22 input1: ["TENSOR_QUANT8_ASYMM", 1.0, 100],
28 input1: input1_data,
36 input1=Input("input1", "TENSOR_FLOAT32", "{3, 1, 2}"),
46 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
56 input1 = Input("input1", "TENSOR_QUANT8_ASYMM", "{2}, 1.0f, 128") variable
58 model = Model().Operation("MAXIMUM", input0, input1).To(output0)
62 input1: [128, 200],
Dminimum.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
18 model = Model().Operation("MINIMUM", input0, input1).To(output0)
22 input1: ["TENSOR_QUANT8_ASYMM", 1.0, 100],
28 input1: input1_data,
36 input1=Input("input1", "TENSOR_FLOAT32", "{3, 1, 2}"),
46 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
56 input1 = Input("input1", "TENSOR_QUANT8_ASYMM", "{2}, 1.0f, 128") variable
58 model = Model().Operation("MINIMUM", input0, input1).To(output0)
62 input1: [128, 200],
Dequal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
17 model = Model().Operation("EQUAL", input0, input1).To(output0)
20 input1: input1_data,
29 input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
39 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
49 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 2.0, 128)),
60 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.0, 129)),
71 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
82 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
93 input1=Input("input1", "TENSOR_BOOL8", "{4}"),
Dless_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
17 model = Model().Operation("LESS_EQUAL", input0, input1).To(output0)
20 input1: input1_data,
29 input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
39 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
49 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 2.0, 128)),
60 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.0, 129)),
71 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
82 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
93 input1=Input("input1", "TENSOR_BOOL8", "{4}"),
Dgreater.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
17 model = Model().Operation("GREATER", input0, input1).To(output0)
20 input1: input1_data,
29 input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
39 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
49 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 2.0, 128)),
60 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.0, 129)),
71 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
82 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
93 input1=Input("input1", "TENSOR_BOOL8", "{4}"),
Dnot_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
17 model = Model().Operation("NOT_EQUAL", input0, input1).To(output0)
20 input1: input1_data,
29 input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
39 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
49 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 2.0, 128)),
60 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.0, 129)),
71 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
82 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
93 input1=Input("input1", "TENSOR_BOOL8", "{4}"),
Dless.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
17 model = Model().Operation("LESS", input0, input1).To(output0)
20 input1: input1_data,
29 input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
39 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
49 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 2.0, 128)),
60 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.0, 129)),
71 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
82 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
93 input1=Input("input1", "TENSOR_BOOL8", "{4}"),
Dgreater_equal.mod.py16 def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True): argument
17 model = Model().Operation("GREATER_EQUAL", input0, input1).To(output0)
20 input1: input1_data,
29 input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
39 input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
49 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 2.0, 128)),
60 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.0, 129)),
71 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
82 input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
93 input1=Input("input1", "TENSOR_BOOL8", "{4}"),
Dconcat_mixed_quant.mod.py20 input1 = Input("input1", "TENSOR_FLOAT32", "{2, 1, 2}") variable
26 model = Model().Operation("CONCATENATION", input0, input1, input2, input3, axis).To(output0)
31 input1: [1.1, 3.1, 4.1, 7.1],
37 input1: ["TENSOR_QUANT8_ASYMM", 0.05, 0],
46 input1: [1.1, 3.1, 4.1, 7.1],
52 input1: ["TENSOR_QUANT8_ASYMM", 0.05, 0],
Dselect_v1_2.mod.py16 def test(name, input0, input1, input2, output0, input0_data, input1_data, input2_data, output_data): argument
17 model = Model().Operation("SELECT", input0, input1, input2).To(output0)
19 input1: ["TENSOR_QUANT8_ASYMM", 1.5, 129],
25 input1: input1_data,
33 input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
45 input1=Input("input1", "TENSOR_FLOAT32", "{2, 2}"),
57 input1=Input("input1", "TENSOR_FLOAT32", "{2, 1, 2, 1, 2}"),
Dsub_v1_2_broadcast.mod.py19 input1 = Input("input1", "TENSOR_FLOAT32", "{2, 2}") variable
23 model = Model().Operation("SUB", input0, input1, activation).To(output0)
33 input1: input1_values,
40 input1 = Input("input1", "TENSOR_QUANT8_ASYMM", "{2, 2}, 1.0, 0") variable
44 model = Model("quant8").Operation("SUB", input0, input1, activation).To(output0)
54 input1: input1_values,
Dlogical_or.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
18 model = Model().Operation("LOGICAL_OR", input0, input1).To(output0)
21 input1: input1_data,
28 input1=Input("input1", "TENSOR_BOOL8", "{1, 1, 1, 4}"),
38 input1=Input("input1", "TENSOR_BOOL8", "{1, 1}"),
Dlogical_and.mod.py17 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
18 model = Model().Operation("LOGICAL_AND", input0, input1).To(output0)
21 input1: input1_data,
28 input1=Input("input1", "TENSOR_BOOL8", "{1, 1, 1, 4}"),
38 input1=Input("input1", "TENSOR_BOOL8", "{1, 1}"),

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