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 17# model 18model = Model() 19 20row = 212 21col1 = 60 22col2 = 30 23output_col = col1 + col2 24 25input1 = Input("input1", "TENSOR_FLOAT32", "{%d, %d}" % (row, col1)) # input tensor 1 26input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row, col2)) # input tensor 2 27axis1 = Int32Scalar("axis1", 1) 28output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (row, output_col)) # output 29model = model.Operation("CONCATENATION", input1, input2, axis1).To(output) 30 31# Example 1. 32input1_values = [x for x in range(row * col1)] 33input2_values = [-x for x in range(row * col2)] 34input0 = {input1: input1_values, 35 input2: input2_values} 36 37output_values = [x for x in range(row * output_col)] 38for r in range(row): 39 for c1 in range(col1): 40 output_values[r * output_col + c1] = input1_values[r * col1 + c1] 41 for c2 in range(col2): 42 output_values[r * output_col + col1 + c2] = input2_values[r * col2 + c2] 43 44output0 = {output: output_values} 45 46# Instantiate an example 47Example((input0, output0)) 48