| # |
| # Copyright (C) 2017 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. |
| # |
| |
| # model |
| model = Model() |
| |
| d0 = 2 |
| d1 = 32 |
| d2 = 40 |
| d3 = 2 |
| |
| i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) |
| |
| output = Output("output", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) |
| |
| model = model.Operation("LOGISTIC", i0).To(output) |
| |
| # Example 1. Input in operand 0, |
| rng = d0 * d1 * d2 * d3 |
| input_values = (lambda r = rng: [x * (x % 2 - .5) * 2 % 512 for x in range(r)])() |
| input0 = {i0: input_values} |
| output_values = [1. / (1. + math.exp(-x)) for x in input_values] |
| output0 = {output: output_values} |
| |
| # Instantiate an example |
| Example((input0, output0)) |
