2 # Copyright (C) 2017 The Android Open Source Project
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
8 # http://www.apache.org/licenses/LICENSE-2.0
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.
23 output_row = row1 + row2
25 input1 = Input("input1", "TENSOR_FLOAT32", "{%d, %d}" % (row1, col)) # input tensor 1
26 input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row2, col)) # input tensor 2
27 axis0 = Int32Scalar("axis0", 0)
28 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (output_row, col)) # output
29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output)
32 input1_values = [x for x in range(row1 * col)]
33 input2_values = (lambda s1 = row1 * col, s2 = row2 * col:
34 [x + s1 for x in range(s2)])()
35 input0 = {input1: input1_values,
36 input2: input2_values}
37 output_values = [x for x in range(output_row * col)]
38 output0 = {output: output_values}
40 # Instantiate an example
41 Example((input0, output0))