Home
last modified time | relevance | path

Searched refs:input0 (Results 1 – 25 of 537) sorted by relevance

12345678910>>...22

/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
H A Dpad_quant8_signed.mod.py19 input0 = Input("input0", "TENSOR_FLOAT32", "{1, 1, 2, 3}") variable
26 model = Model().Operation("PAD", input0, paddings).To(output0)
29 input0: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.3, -128),
34 input0: [1.0, 2.0, 3.0,
51 model = Model().Operation("PAD", input0, paddings).To(output0)
54 input0: [-127, -126, -125],
70 input0: [-127, -126, -125,
93 input0: [-127, -126, -125,
114 input0: [-127, -126, -125,
136 input0: [-127, -126, -125,
[all …]
H A Dgather_quant8_signed.mod.py17 input0 = Input("input0", "TENSOR_FLOAT32", "{1, 3, 2}") variable
25 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
30 input0: [1, 2,
50 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
55 input0: input_data,
60 input0=Input("input0", "TENSOR_FLOAT32", "{2, 2}"),
71 input0=Input("input0", "TENSOR_FLOAT32", "{2, 2}"),
81 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
90 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
99 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2}"),
[all …]
H A Dargmax_quant8_signed.mod.py17 input0 = Input("input0", "TENSOR_FLOAT32", "{2, 2}") variable
21 model = Model().Operation("ARGMAX", input0, axis).To(output0)
24 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.0, 0],
28 input0: [1.0, 2.0,
35 input0 = Input("input0", "TENSOR_FLOAT32", "{2, 2}") variable
39 model = Model().Operation("ARGMAX", input0, axis).To(output0)
42 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.0, 0],
46 input0: [1.0, 2.0,
55 input0 = Input("input0", "TENSOR_FLOAT32", "{2, 2}") variable
62 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.0, 0],
[all …]
H A Dargmin_quant8_signed.mod.py18 input0 = Input("input0", "TENSOR_FLOAT32", "{2, 2}") variable
22 model = Model().Operation("ARGMIN", input0, axis).To(output0)
25 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.0, 0],
29 input0: [1.0, 2.0,
36 input0 = Input("input0", "TENSOR_FLOAT32", "{2, 2}") variable
40 model = Model().Operation("ARGMIN", input0, axis).To(output0)
43 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.0, 0],
47 input0: [1.0, 2.0,
54 input0 = Input("input0", "TENSOR_FLOAT32", "{2, 2}") variable
61 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 1.0, 0],
[all …]
H A Dstrided_slice_quant8_signed.mod.py31 input0 = {i1: # input 0 variable
38 Example((input0, output0))
56 input0 = {i1: # input 0 variable
81 input0 = {i1: # input 0 variable
106 input0 = {i1: # input 0 variable
131 input0 = {i1: # input 0 variable
156 input0 = {i1: # input 0 variable
181 input0 = {i1: # input 0 variable
206 input0 = {i1: # input 0 variable
231 input0 = {i1: # input 0 variable
[all …]
H A Dtile_quant8_signed.mod.py17 input0 = Input("input0", "TENSOR_FLOAT32", "{3}") variable
21 model = Model().Operation("TILE", input0, multipliers).To(output0)
28 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
33 input0: input_values,
40 input0 = Input("input0", "TENSOR_FLOAT32", "{2, 3}") variable
44 model = Model().Operation("TILE", input0, multipliers).To(output0)
55 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
60 input0: input_values,
67 input0 = Input("input0", "TENSOR_FLOAT32", "{1, 2, 3}") variable
82 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
[all …]
H A Dsplit_quant8_signed.mod.py17 input0 = Input("input0", "TENSOR_QUANT8_ASYMM_SIGNED", "{6}, 1.0, -128") variable
24 model = Model().Operation("SPLIT", input0, axis, num_splits).To(
28 input_dict = {input0: [-127, -126, -125, -124, -123, -122]}
40 input0 = Input("input0", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 3}, 2.0, -125") variable
46 model = Model().Operation("SPLIT", input0, axis, num_splits).To(
50 input_dict = {input0: [-127, -126, -125, -124, -123, -122]}
61 input0 = Input("input0", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 3}, 2.0, -125") variable
68 model = Model().Operation("SPLIT", input0, axis, num_splits).To(
72 input_dict = {input0: [-127, -126, -125, -124, -123, -122]}
92 model = Model().Operation("SPLIT", input0, axis, num_splits).To(
[all …]
H A Dresize_nearest_neighbor_v1_3.mod.py22 input0: ["TENSOR_QUANT8_ASYMM", 0.5, 128],
26 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0],
30 input0: input0_data,
39 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 5, 1}"),
52 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2, 1}"),
65 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2, 1}"),
78 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2, 1}"),
91 input0=Input("input0", "TENSOR_FLOAT32", "{1, 4, 4, 1}"),
104 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2, 1}"),
117 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2, 1}"),
[all …]
H A Dhard_swish.mod.py18 def test(name, input0, output0, input0_data, output0_data): argument
19 model = Model().Operation("HARD_SWISH", input0).To(output0)
21 input0: ["TENSOR_QUANT8_ASYMM", 0.078125, 128],
25 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.078125, 0],
29 input0: ["TENSOR_QUANT8_ASYMM", 0.078125, 128],
33 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.078125, 0],
37 input0: input0_data,
48 input0=Input("input0", "TENSOR_FLOAT32", "{40}"),
69 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2, 2, 5}"),
H A 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)
21 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
27 input0: input0_data,
35 input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
45 input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
55 input0 = Input("input0", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0f, 0") variable
58 model = Model().Operation("MAXIMUM", input0, input1).To(output0)
61 input0: [-68, 0],
H A 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)
21 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
27 input0: input0_data,
35 input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
45 input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
54 input0 = Input("input0", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0f, 0") variable
57 model = Model().Operation("MINIMUM", input0, input1).To(output0)
60 input0: [-68, 0],
H A Dreduce_max_quant8_signed.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
18 model = Model().Operation("REDUCE_MAX", input0, axes, keep_dims).To(output0)
20 input0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
24 input0: input_data,
29 input0=Input("input0", "TENSOR_FLOAT32", "{3, 2}"),
42 input0=Input("input0", "TENSOR_FLOAT32", "{1}"),
51 input0=Input("input0", "TENSOR_FLOAT32", "{4, 3, 2}"),
62 input0=Input("input0", "TENSOR_FLOAT32", "{4, 3, 2}"),
/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
H A Dgather.mod.py21 input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
26 input0: ["TENSOR_INT32"],
31 input0: ["TENSOR_FLOAT16"],
36 input0: input_data,
41 input0=Input("input0", "TENSOR_FLOAT32", "{2, 2}"),
52 input0=Input("input0", "TENSOR_FLOAT32", "{2, 2}"),
62 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
71 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
80 input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2}"),
93 input0=Input("input0", "TENSOR_FLOAT32", "{4, 1}"),
[all …]
H A 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)
21 input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
27 input0: input0_data,
35 input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
45 input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
55 input0 = Input("input0", "TENSOR_QUANT8_ASYMM", "{2}, 1.0f, 128") variable
58 model = Model().Operation("MAXIMUM", input0, input1).To(output0)
61 input0: [60, 128],
H A 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)
21 input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
27 input0: input0_data,
35 input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
45 input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
55 input0 = Input("input0", "TENSOR_QUANT8_ASYMM", "{2}, 1.0f, 128") variable
58 model = Model().Operation("MINIMUM", input0, input1).To(output0)
61 input0: [60, 128],
H A Ddequantize_v1_2.mod.py18 def test(name, input0, output0, input0_data, output0_data): argument
19 model = Model().Operation("DEQUANTIZE", input0).To(output0)
21 input0: input0_data,
30 input0=Input("input0", "TENSOR_QUANT8_ASYMM", "{10}, 0.5, 127"),
38 input0=Input("input0", "TENSOR_QUANT8_ASYMM", "{2, 5}, 0.5, 127"),
46 input0=Input("input0", "TENSOR_QUANT8_SYMM", "{2, 2, 2}, 0.5, 0"),
54 input0=Input("input0", "TENSOR_QUANT8_SYMM", "{2, 1, 2, 2}, 0.5, 0"),
62 input0=Input(
78 input0=Input(
108 input0 = {i1: # input 0 variable
[all …]
H A 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)
19 input0: input0_data,
28 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
38 input0=Input("input0", "TENSOR_FLOAT32", "{2, 1}"),
48 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
59 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
70 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
81 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
92 input0=Input("input0", "TENSOR_BOOL8", "{4}"),
H A 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)
19 input0: input0_data,
28 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
38 input0=Input("input0", "TENSOR_FLOAT32", "{2, 1}"),
48 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
59 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
70 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
81 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
92 input0=Input("input0", "TENSOR_BOOL8", "{4}"),
H A 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)
19 input0: input0_data,
28 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
38 input0=Input("input0", "TENSOR_FLOAT32", "{2, 1}"),
48 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
59 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
70 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
81 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
92 input0=Input("input0", "TENSOR_BOOL8", "{4}"),
H A 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)
19 input0: input0_data,
28 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
38 input0=Input("input0", "TENSOR_FLOAT32", "{2, 1}"),
48 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
59 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
70 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
81 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
92 input0=Input("input0", "TENSOR_BOOL8", "{4}"),
H A 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)
19 input0: input0_data,
28 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
38 input0=Input("input0", "TENSOR_FLOAT32", "{2, 1}"),
48 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
59 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
70 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
81 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
92 input0=Input("input0", "TENSOR_BOOL8", "{4}"),
H A 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)
19 input0: input0_data,
28 input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
38 input0=Input("input0", "TENSOR_FLOAT32", "{2, 1}"),
48 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
59 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
70 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
81 input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
92 input0=Input("input0", "TENSOR_BOOL8", "{4}"),
H A Dexpand_dims.mod.py17 input0 = Input("input0", "TENSOR_FLOAT32", "{2, 2}") variable
24 model0 = Model().Operation("EXPAND_DIMS", input0, 0).To(output0)
25 model1 = Model().Operation("EXPAND_DIMS", input0, 1).To(output1)
26 model2 = Model().Operation("EXPAND_DIMS", input0, 2).To(output2)
27 model3 = Model().Operation("EXPAND_DIMS", input0, -1).To(output3)
36 input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
41 input0: ["TENSOR_INT32"],
46 input0: data,
H A Dreduce_max.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
18 model = Model().Operation("REDUCE_MAX", input0, axes, keep_dims).To(output0)
20 input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
24 input0: input_data,
29 input0=Input("input0", "TENSOR_FLOAT32", "{3, 2}"),
42 input0=Input("input0", "TENSOR_FLOAT32", "{1}"),
51 input0=Input("input0", "TENSOR_FLOAT32", "{4, 3, 2}"),
62 input0=Input("input0", "TENSOR_FLOAT32", "{4, 3, 2}"),
H A Dreduce_min.mod.py17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
18 model = Model().Operation("REDUCE_MIN", input0, axes, keep_dims).To(output0)
20 input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
24 input0: input_data,
29 input0=Input("input0", "TENSOR_FLOAT32", "{3, 2}"),
42 input0=Input("input0", "TENSOR_FLOAT32", "{1}"),
51 input0=Input("input0", "TENSOR_FLOAT32", "{4, 3, 2}"),
62 input0=Input("input0", "TENSOR_FLOAT32", "{4, 3, 2}"),

12345678910>>...22