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+#
+# Copyright (C) 2018 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()
+
+row = 212
+col1 = 60
+col2 = 30
+output_col = col1 + col2
+
+input1 = Input("input1", "TENSOR_FLOAT32", "{%d, %d}" % (row, col1)) # input tensor 1
+input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row, col2)) # input tensor 2
+axis1 = Int32Scalar("axis1", 1)
+output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (row, output_col)) # output
+model = model.Operation("CONCATENATION", input1, input2, axis1).To(output)
+model = model.RelaxedExecution(True)
+
+# Example 1.
+input1_values = [x for x in range(row * col1)]
+input2_values = [-x for x in range(row * col2)]
+input0 = {input1: input1_values,
+ input2: input2_values}
+
+output_values = [x for x in range(row * output_col)]
+for r in range(row):
+ for c1 in range(col1):
+ output_values[r * output_col + c1] = input1_values[r * col1 + c1]
+ for c2 in range(col2):
+ output_values[r * output_col + col1 + c2] = input2_values[r * col2 + c2]
+
+output0 = {output: output_values}
+
+# Instantiate an example
+Example((input0, output0))