# 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. """Concatenate tests for Arm(R) Ethos(TM)-N""" import numpy as np import tvm from tvm import relay from tvm.testing import requires_ethosn from . import infrastructure as tei def _get_inputs(shapes): inputs = {} for i, shape in enumerate(shapes): inputs["in" + str(i)] = tvm.nd.array( np.random.randint(0, high=256, size=shape, dtype="uint8") ) return inputs def _get_model(shapes, dtype, axis): tup = [] for i, shape in enumerate(shapes): a = relay.var("in" + str(i), shape=shape, dtype=dtype) tup.append(a) zeroi = relay.const(1, "int32") zerof = relay.const(0.5, "float32") con = relay.qnn.op.concatenate( tup, input_scales=[zerof] * len(shapes), input_zero_points=[zeroi] * len(shapes), output_scale=zerof, output_zero_point=zeroi, axis=axis, ) return con @requires_ethosn def test_concatenate(): trials = [ ([(1, 4), (1, 6)], 1), ([(1, 16, 4), (1, 16, 4)], 1), ([(1, 25, 4, 16)] * 3, 3), ([(1, 25, 4, 16), (1, 25, 5, 16), (1, 25, 6, 16)], 2), ] for shapes, axis in trials: outputs = [] inputs = _get_inputs(shapes) for npu in [False, True]: model = _get_model(shapes, "uint8", axis) mod = tei.make_module(model, {}) outputs.append(tei.build_and_run(mod, inputs, 1, {}, npu=npu)) tei.verify(outputs, 0) @requires_ethosn def test_concatenate_failure(): trials = [ ([(1, 4, 4, 4, 4), (1, 4, 4, 4, 4)], "uint8", 1, "dimensions=5, dimensions must be <= 4;"), ( [(1, 4, 4, 4), (1, 4, 4, 4)], "uint8", 3, "Concatenation along the channels dimension (axis 3) requires input tensors with a multiple of 16 channels;", ), ( [(1, 4, 4, 4), (1, 4, 4, 4)], "int8", 2, "dtype='int8', dtype must be either uint8 or int32; dtype='int8', dtype must be either uint8 or int32;", ), ( [(2, 4, 4, 4), (2, 4, 4, 4)], "uint8", 2, "batch size=2, batch size must = 1; batch size=2, batch size must = 1;", ), ( [(1, 4, 4, 4), (1, 4, 4, 4)], "uint8", 0, "Concatenation cannot be performed along batch axis (axis 0);", ), ] for shapes, dtype, axis, err_msg in trials: model = _get_model(shapes, dtype, axis) mod = tei.make_ethosn_partition(model) tei.test_error(mod, {}, err_msg)