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/frameworks/ml/nn/runtime/test/specs/V1_3/
Dpad_quant8_signed.mod.py24 output0 = Output("output0", "TENSOR_FLOAT32", "{4, 8, 8, 6}") variable
26 model = Model().Operation("PAD", input0, paddings).To(output0)
30 output0: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.3, -128),
36 output0: np.pad([[[[1.0, 2.0, 3.0],
49 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", "{7}, 2.3, -128") variable
51 model = Model().Operation("PAD", input0, paddings).To(output0)
55 output0: [-128, -128, -128, -127, -126, -125, -128],
65 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 4, 7, 1}, 2.3, -128") variable
67 model = Model().Operation("PAD", input0, paddings).To(output0)
72 output0: [-128, -127, -126, -125, -128, -128, -128,
[all …]
Dgather_quant8_signed.mod.py20 output0 = Output("output0", "TENSOR_FLOAT32", "{1, 3, 2, 2}") variable
22 model = Model().Operation("GATHER", input0, axis, indices).To(output0)
26 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
36 output0: [5, 6,
46 def test(input0, axis, indices, output0, input_data, output_data): argument
47 model = Model().Operation("GATHER", input0, axis, indices).To(output0)
51 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
56 output0: output_data,
63 output0=Output("output0", "TENSOR_FLOAT32", "{2, 2}"),
74 output0=Output("output0", "TENSOR_FLOAT32", "{1, 2}"),
[all …]
Dtile_quant8_signed.mod.py19 output0 = Output("output0", "TENSOR_FLOAT32", "{6}") variable
21 model = Model().Operation("TILE", input0, multipliers).To(output0)
29 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
35 output0: output_values,
42 output0 = Output("output0", "TENSOR_FLOAT32", "{4, 3}") variable
44 model = Model().Operation("TILE", input0, multipliers).To(output0)
56 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
62 output0: output_values,
69 output0 = Output("output0", "TENSOR_FLOAT32", "{2, 6, 3}") variable
71 model = Model().Operation("TILE", input0, multipliers).To(output0)
[all …]
Dsplit_quant8_signed.mod.py20 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0, -128") variable
25 (output0, output1, output2))
30 output0: [-127, -126],
43 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 3}, 2.0, -125") variable
47 (output0, output1))
52 output0: [-127, -126, -125],
64 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 1}, 2.0, -125") variable
69 (output0, output1, output2))
74 output0: [-127, -124],
87 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", variable
[all …]
Dstrided_slice_quant8_signed.mod.py34 output0 = {output: # output 0 variable
38 Example((input0, output0))
59 output0 = {output: # output 0 variable
63 Example((input0, output0))
84 output0 = {output: # output 0 variable
88 Example((input0, output0))
109 output0 = {output: # output 0 variable
113 Example((input0, output0))
134 output0 = {output: # output 0 variable
138 Example((input0, output0))
[all …]
Dhard_swish.mod.py18 def test(name, input0, output0, input0_data, output0_data): argument
19 model = Model().Operation("HARD_SWISH", input0).To(output0)
22 output0: ["TENSOR_QUANT8_ASYMM", 0.078125, 128],
26 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.078125, 0],
30 output0: ["TENSOR_QUANT8_ASYMM", 0.03125, 0],
34 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.03125, -128],
38 output0: output0_data,
49 output0=Output("output0", "TENSOR_FLOAT32", "{40}"),
70 output0=Output("output0", "TENSOR_FLOAT32", "{1, 2, 2, 2, 5}"),
Dargmax_quant8_signed.mod.py19 output0 = Output("output", "TENSOR_INT32", "{2}") variable
21 model = Model().Operation("ARGMAX", input0, axis).To(output0)
30 output0: [1, 0],
37 output0 = Output("output", "TENSOR_INT32", "{2}") variable
39 model = Model().Operation("ARGMAX", input0, axis).To(output0)
48 output0: [1, 1],
57 output0 = Output("output", "TENSOR_INT32", "{2}") variable
59 model = Model().Operation("ARGMAX", input0, axis).To(output0)
68 output0: [1, 0],
Dargmin_quant8_signed.mod.py20 output0 = Output("output", "TENSOR_INT32", "{2}") variable
22 model = Model().Operation("ARGMIN", input0, axis).To(output0)
31 output0: [0, 1],
38 output0 = Output("output", "TENSOR_INT32", "{2}") variable
40 model = Model().Operation("ARGMIN", input0, axis).To(output0)
49 output0: [0, 0],
56 output0 = Output("output", "TENSOR_INT32", "{2}") variable
58 model = Model().Operation("ARGMIN", input0, axis).To(output0)
67 output0: [0, 1],
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)
23 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 2.0, -48],
29 output0: output_data,
37 output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
47 output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
56 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 0.5f, 0") variable
57 model = Model().Operation("MINIMUM", input0, input1).To(output0)
62 output0: [-128, 0],
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)
23 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 2.0, -48],
29 output0: output_data,
37 output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
47 output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
57 output0 = Output("output0", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 0.5f, 0") variable
58 model = Model().Operation("MAXIMUM", input0, input1).To(output0)
63 output0: [0, 127],
Dresize_nearest_neighbor_v1_3.mod.py17 half_pixel_centers, output0, input0_data, output_data): argument
20 half_pixel_centers).To(output0)
23 output0: ["TENSOR_QUANT8_ASYMM", 0.5, 128],
27 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0],
31 output0: output_data,
45 output0=Output("output0", "TENSOR_FLOAT32", "{1, 2, 2, 1}"),
58 output0=Output("output0", "TENSOR_FLOAT32", "{1, 1, 1, 1}"),
71 output0=Output("output0", "TENSOR_FLOAT32", "{1, 3, 3, 1}"),
84 output0=Output("output0", "TENSOR_FLOAT32", "{1, 2, 5, 1}"),
97 output0=Output("output0", "TENSOR_FLOAT32", "{1, 3, 3, 1}"),
[all …]
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)
21 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
25 output0: output_data,
35 output0=Output("output0", "TENSOR_FLOAT32", "{3}"),
46 output0=Output("output0", "TENSOR_FLOAT32", "{1}"),
57 output0=Output("output0", "TENSOR_FLOAT32", "{2}"),
68 output0=Output("output0", "TENSOR_FLOAT32", "{1, 3, 1}"),
Dreduce_min_quant8_signed.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)
21 output0: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1],
25 output0: output_data,
35 output0=Output("output0", "TENSOR_FLOAT32", "{3}"),
46 output0=Output("output0", "TENSOR_FLOAT32", "{1}"),
57 output0=Output("output0", "TENSOR_FLOAT32", "{2}"),
68 output0=Output("output0", "TENSOR_FLOAT32", "{1, 3, 1}"),
/frameworks/ml/nn/runtime/test/specs/V1_2/
Dgather.mod.py17 def test(input0, axis, indices, output0, input_data, output_data): argument
18 model = Model().Operation("GATHER", input0, axis, indices).To(output0)
22 output0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
27 output0: ["TENSOR_INT32"],
32 output0: ["TENSOR_FLOAT16"],
37 output0: output_data,
44 output0=Output("output0", "TENSOR_FLOAT32", "{2, 2}"),
55 output0=Output("output0", "TENSOR_FLOAT32", "{1, 2}"),
65 output0=Output("output0", "TENSOR_FLOAT32", "{1}"),
74 output0=Output("output0", "TENSOR_FLOAT32", "{2}"),
[all …]
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)
23 output0: ["TENSOR_QUANT8_ASYMM", 2.0, 80],
29 output0: output_data,
37 output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
47 output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
57 output0 = Output("output0", "TENSOR_QUANT8_ASYMM", "{2}, 0.5f, 128") variable
58 model = Model().Operation("MAXIMUM", input0, input1).To(output0)
63 output0: [128, 255],
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)
23 output0: ["TENSOR_QUANT8_ASYMM", 2.0, 80],
29 output0: output_data,
37 output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
47 output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
57 output0 = Output("output0", "TENSOR_QUANT8_ASYMM", "{2}, 0.5f, 128") variable
58 model = Model().Operation("MINIMUM", input0, input1).To(output0)
63 output0: [0, 128],
Ddequantize_v1_2.mod.py18 def test(name, input0, output0, input0_data, output0_data): argument
19 model = Model().Operation("DEQUANTIZE", input0).To(output0)
22 output0: output0_data,
31 output0=Output("output0", "TENSOR_FLOAT32", "{10}"),
39 output0=Output("output0", "TENSOR_FLOAT32", "{2, 5}"),
47 output0=Output("output0", "TENSOR_FLOAT32", "{2, 2, 2}"),
55 output0=Output("output0", "TENSOR_FLOAT32", "{2, 1, 2, 2}"),
65 output0=Output("output0", "TENSOR_FLOAT32", "{2, 3, 4}"),
82 output0=Output("output0", "TENSOR_FLOAT32", "{2, 3, 4}"),
111 output0 = {i2: # output 0 variable
[all …]
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)
21 output0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
25 output0: output_data,
35 output0=Output("output0", "TENSOR_FLOAT32", "{3}"),
46 output0=Output("output0", "TENSOR_FLOAT32", "{1}"),
57 output0=Output("output0", "TENSOR_FLOAT32", "{2}"),
68 output0=Output("output0", "TENSOR_FLOAT32", "{1, 3, 1}"),
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)
21 output0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
25 output0: output_data,
35 output0=Output("output0", "TENSOR_FLOAT32", "{3}"),
46 output0=Output("output0", "TENSOR_FLOAT32", "{1}"),
57 output0=Output("output0", "TENSOR_FLOAT32", "{2}"),
68 output0=Output("output0", "TENSOR_FLOAT32", "{1, 3, 1}"),
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)
21 output0: output_data,
30 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
40 output0=Output("output0", "TENSOR_BOOL8", "{2, 2}"),
50 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
61 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
72 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
83 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
94 output0=Output("output0", "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)
21 output0: output_data,
30 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
40 output0=Output("output0", "TENSOR_BOOL8", "{2, 2}"),
50 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
61 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
72 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
83 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
94 output0=Output("output0", "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)
21 output0: output_data,
30 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
40 output0=Output("output0", "TENSOR_BOOL8", "{2, 2}"),
50 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
61 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
72 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
83 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
94 output0=Output("output0", "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)
21 output0: output_data,
30 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
40 output0=Output("output0", "TENSOR_BOOL8", "{2, 2}"),
50 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
61 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
72 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
83 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
94 output0=Output("output0", "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)
21 output0: output_data,
30 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
40 output0=Output("output0", "TENSOR_BOOL8", "{2, 2}"),
50 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
61 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
72 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
83 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
94 output0=Output("output0", "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)
21 output0: output_data,
30 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
40 output0=Output("output0", "TENSOR_BOOL8", "{2, 2}"),
50 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
61 output0=Output("output0", "TENSOR_BOOL8", "{3}"),
72 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
83 output0=Output("output0", "TENSOR_BOOL8", "{1}"),
94 output0=Output("output0", "TENSOR_BOOL8", "{4}"),

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