1# 2# Copyright (C) 2018 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 20row1 = 52 21row2 = 40 22col = 230 23output_row = row1 + row2 24 25input1 = Input("input1", "TENSOR_FLOAT32", "{%d, %d}" % (row1, col)) # input tensor 1 26input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row2, col)) # input tensor 2 27axis0 = Int32Scalar("axis0", 0) 28output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (output_row, col)) # output 29model = model.Operation("CONCATENATION", input1, input2, axis0).To(output) 30model = model.RelaxedExecution(True) 31 32# Example 1. 33input1_values = [x for x in range(row1 * col)] 34input2_values = (lambda s1 = row1 * col, s2 = row2 * col: 35 [x + s1 for x in range(s2)])() 36input0 = {input1: input1_values, 37 input2: input2_values} 38output_values = [x for x in range(output_row * col)] 39output0 = {output: output_values} 40 41# Instantiate an example 42Example((input0, output0)) 43