/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
H A D | tile_quant8_signed.mod.py | 25 output_values = input_values + input_values variable 35 output0: output_values, 49 output_values = [11, 12, 13, variable 62 output0: output_values, 76 output_values = [11, 12, 13, 21, 22, 23, 11, 12, 13, variable 89 output0: output_values,
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H A D | sub_quant8_signed.mod.py | 37 output_values = [sub_quantized(a, b) for a, b in inputs] 38 size = len(output_values) 50 output0: output_values, 75 output_values = [-29, 70, variable 81 output0: output_values, 98 output_values = [max(-128, (a - b) - 128) for a, b in zip(input0_values, input1_values)] variable 103 output0: output_values,
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H A D | concat_quant8_signed.mod.py | 96 output_values = [x % 256 - 128 for x in range(output_row * col)] variable 97 output0 = {output: output_values} 123 output_values = [x for x in range(row * output_col)] variable 126 output_values[r * output_col + c1] = input1_values[r * col1 + c1] 128 output_values[r * output_col + col1 + c2] = input2_values[r * col2 + c2] 130 output0 = {output: output_values}
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H A D | relu_quant8_signed.mod.py | 63 output_values = (lambda r = rng: [x % 256 if x % 256 > 128 else 128 for x in range(r)])() variable 64 output0 = {output: output_values} 67 output0 = {output: [value - 128 for value in output_values]}
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
H A D | sub_v1_2_broadcast.mod.py | 28 output_values = [9.9, 19.8, variable 34 output0: output_values, 49 output_values = [99, 198, variable 55 output0: output_values,
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H A D | concat_float16_3.mod.py | 37 output_values = [x for x in range(row * output_col)] variable 40 output_values[r * output_col + c1] = input1_values[r * col1 + c1] 42 output_values[r * output_col + col1 + c2] = input2_values[r * col2 + c2] 44 output0 = {output: output_values}
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H A D | sub_quantized_different_scales.mod.py | 36 output_values = [sub_quantized(a, b) for a, b in inputs] 37 size = len(output_values) 49 output0: output_values,
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H A D | tile_1.mod.py | 25 output_values = input_values + input_values variable 40 output0: output_values,
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H A D | tile_2.mod.py | 26 output_values = [11, 12, 13, variable 49 output0: output_values,
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H A D | tile_3.mod.py | 26 output_values = [11, 12, 13, 21, 22, 23, 11, 12, 13, variable 49 output0: output_values,
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/ |
H A D | concat_float_3.mod.py | 37 output_values = [x for x in range(row * output_col)] variable 40 output_values[r * output_col + c1] = input1_values[r * col1 + c1] 42 output_values[r * output_col + col1 + c2] = input2_values[r * col2 + c2] 44 output0 = {output: output_values}
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H A D | concat_quant8_3.mod.py | 37 output_values = [x for x in range(row * output_col)] variable 40 output_values[r * output_col + c1] = input1_values[r * col1 + c1] 42 output_values[r * output_col + col1 + c2] = input2_values[r * col2 + c2] 44 output0 = {output: output_values}
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H A D | relu1_quant8_2.mod.py | 35 output_values = [127 if x < 127 else 129 if x > 129 else x for x in input_values] variable 36 output0 = {output: output_values}
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H A D | relu6_quant8_2.mod.py | 35 output_values = [128 if x < 128 else 134 if x > 134 else x for x in input_values] variable 36 output0 = {output: output_values}
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H A D | logistic_float_2.mod.py | 37 output_values = [1. / (1. + math.exp(-x)) for x in input_values] variable 38 output0 = {output: output_values}
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H A D | relu1_float_2.mod.py | 35 output_values = [-1 if x < -1 else 1 if x > 1 else x for x in input_values] variable 36 output0 = {output: output_values}
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H A D | relu6_float_2.mod.py | 35 output_values = [0 if x < 0 else 6 if x > 6 else x for x in input_values] variable 36 output0 = {output: output_values}
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H A D | relu_quant8_2.mod.py | 35 output_values = (lambda r = rng: [x % 256 if x % 256 > 128 else 128 for x in range(r)])() variable 36 output0 = {output: output_values}
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H A D | relu_float_2.mod.py | 35 output_values = (lambda r = rng: [x * (x % 2) for x in range(r)])() variable 36 output0 = {output: output_values}
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H A D | logistic_quant8_2.mod.py | 37 output_values = [ variable 41 output0 = {output: output_values}
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/ |
H A D | concat_float_3_relaxed.mod.py | 38 output_values = [x for x in range(row * output_col)] variable 41 output_values[r * output_col + c1] = input1_values[r * col1 + c1] 43 output_values[r * output_col + col1 + c2] = input2_values[r * col2 + c2] 45 output0 = {output: output_values}
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H A D | logistic_float_2_relaxed.mod.py | 38 output_values = [1. / (1. + math.exp(-x)) for x in input_values] variable 39 output0 = {output: output_values}
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H A D | relu1_float_2_relaxed.mod.py | 36 output_values = [-1 if x < -1 else 1 if x > 1 else x for x in input_values] variable 37 output0 = {output: output_values}
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H A D | relu6_float_2_relaxed.mod.py | 36 output_values = [0 if x < 0 else 6 if x > 6 else x for x in input_values] variable 37 output0 = {output: output_values}
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H A D | relu_float_2_relaxed.mod.py | 36 output_values = (lambda r = rng: [x * (x % 2) for x in range(r)])() variable 37 output0 = {output: output_values}
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