1# 2# Copyright (C) 2017 The Android Open Source Project 3# 4# Licensed under the Apache License, Version 2.0 (the "License"); 5# you may not use this file except in compliance with the License. 6# You may obtain a copy of the License at 7# 8# http://www.apache.org/licenses/LICENSE-2.0 9# 10# Unless required by applicable law or agreed to in writing, software 11# distributed under the License is distributed on an "AS IS" BASIS, 12# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13# See the License for the specific language governing permissions and 14# limitations under the License. 15 16# conv_quant8.mod.py with biases and filter being constants 17 18model = Model() 19i1 = Input("op1", "TENSOR_QUANT8_ASYMM", "{1, 3, 3, 1}, 0.5f, 0") 20f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 0.5f, 0", 21 [2, 2, 2, 2]) 22b1 = Parameter("op3", "TENSOR_INT32", "{1}, 0.25f, 0", [4]) 23pad0 = Int32Scalar("pad0", 0) 24act = Int32Scalar("act", 0) 25stride = Int32Scalar("stride", 1) 26# output dimension: 27# (i1.height - f1.height + 1) x (i1.width - f1.width + 1) 28output = Output("op4", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 1.f, 0") 29 30model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, 31 stride, act).To(output) 32 33# Example 1. Input in operand 0, 34input0 = { 35 i1: # input 0 36 [8, 8, 8, 8, 4, 8, 8, 8, 8] 37} 38# (i1 (conv) f1) + b1 39output0 = { 40 output: # output 0 41 [15, 15, 15, 15] 42} 43 44# Instantiate an example 45Example((input0, output0)) 46