| # |
| # Copyright (C) 2018 The Android Open Source Project |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| input_scale, input_offset = 0.05, 100 |
| output_scale, output_offset = 1.0 / 128, 128 # Required. |
| |
| def dequantize(x): |
| return (x - input_offset) * input_scale |
| |
| def quantize(x): |
| return max(0, min(255, int(round(x / output_scale)) + output_offset)) |
| |
| input0 = Input("input0", "TENSOR_QUANT8_ASYMM", "{256}, %g, %d" % (input_scale, input_offset)) |
| output0 = Output("output0", "TENSOR_QUANT8_ASYMM", "{256}, %g, %d" % (output_scale, output_offset)) |
| |
| model = Model().Operation("TANH", input0).To(output0) |
| |
| input_values = list(range(256)) |
| output_values = [quantize(math.tanh(dequantize(x))) for x in input_values] |
| |
| Example({ |
| input0: input_values, |
| output0: output_values, |
| }) |
