lhutton1 commented on a change in pull request #10801: URL: https://github.com/apache/tvm/pull/10801#discussion_r839743527
########## File path: tests/python/contrib/test_arm_compute_lib/test_concatenate.py ########## @@ -0,0 +1,126 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. +"""Arm Compute Library integration space_to_batch_nd tests.""" + +import numpy as np + +import tvm +from tvm import relay +from tvm import testing + +from test_arm_compute_lib.infrastructure import ( + skip_runtime_test, + skip_codegen_test, + build_and_run, + verify, + verify_codegen, +) +from test_arm_compute_lib.infrastructure import Device + + +def _get_model(input_shape_a, input_shape_b, input_shape_c, axis, dtype, var_names): + """Return a model and any parameters it may have.""" + a = relay.var(next(var_names), shape=input_shape_a, dtype=dtype) + b = relay.var(next(var_names), shape=input_shape_b, dtype=dtype) + c = relay.var(next(var_names), shape=input_shape_c, dtype=dtype) + out = relay.concatenate([a, b, c], axis) + return out + + +def _get_expected_codegen(input_shape_a, input_shape_b, input_shape_c, axis, dtype): + node = { + "op": "kernel", + "name": "concatenate", + "inputs": [ + [0, 0, 0], + [0, 1, 0], + [0, 2, 0], + ], + "attrs": { + "num_outputs": "1", + "num_inputs": "3", + "dtype": [[dtype]], + "axis": [[str(axis)]], + "shape": [[[3, 234, 234, 256]]], + }, + } + + input = { + "op": "input", + "name": "", + "attrs": { + "shape": [[input_shape_a, input_shape_b, input_shape_c]], + "dtype": [[dtype, dtype, dtype]], + }, + } + + return [input, node] + + +def test_concatenate(): + Device.load("test_config.json") + + if skip_runtime_test(): + return + + device = Device() + np.random.seed(0) + + for input_shape_a, input_shape_b, input_shape_c, axis in [ + ([1, 234, 234, 256], [1, 234, 234, 256], [1, 234, 234, 256], 0), + ]: + dtype = "int32" Review comment: Yeah I was confused by this also, perhaps the documentation needs updating, thanks! -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
