/frameworks/ml/nn/runtime/test/specs/V1_3/ |
D | pad_quant8_signed.mod.py | 24 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 …]
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D | gather_quant8_signed.mod.py | 20 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 …]
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D | tile_quant8_signed.mod.py | 19 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 …]
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D | split_quant8_signed.mod.py | 20 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 …]
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D | strided_slice_quant8_signed.mod.py | 34 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 …]
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D | hard_swish.mod.py | 18 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}"),
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D | argmax_quant8_signed.mod.py | 19 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],
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D | argmin_quant8_signed.mod.py | 20 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],
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D | minimum_quant8_signed.mod.py | 17 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],
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D | maximum_quant8_signed.mod.py | 17 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],
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D | resize_nearest_neighbor_v1_3.mod.py | 17 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 …]
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D | reduce_max_quant8_signed.mod.py | 17 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}"),
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D | reduce_min_quant8_signed.mod.py | 17 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}"),
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/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | gather.mod.py | 17 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 …]
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D | maximum.mod.py | 17 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],
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D | minimum.mod.py | 17 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],
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D | dequantize_v1_2.mod.py | 18 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 …]
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D | reduce_max.mod.py | 17 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}"),
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D | reduce_min.mod.py | 17 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}"),
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D | equal.mod.py | 16 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}"),
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D | less_equal.mod.py | 16 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}"),
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D | greater.mod.py | 16 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}"),
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D | not_equal.mod.py | 16 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}"),
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D | less.mod.py | 16 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}"),
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D | greater_equal.mod.py | 16 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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