# 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. """Test code for L2 normalization""" import numpy as np import tvm import topi from topi.util import get_const_tuple import topi.testing def verify_l2_normalize(ishape, eps, axis=None): A = tvm.placeholder(ishape, name='A') B = topi.nn.l2_normalize(A, eps, axis) dtype = A.dtype a_np = np.random.uniform(size=ishape).astype(dtype) b_np = topi.testing.l2_normalize_python(a_np, eps, axis) def check_device(device): ctx = tvm.context(device, 0) if not ctx.exist: print("Skip because %s is not enabled" % device) return print("Running on target: %s" % device) with tvm.target.create(device): if device == 'llvm': s = topi.generic.schedule_l2_normalize([B]) else: s = topi.cuda.schedule_l2_normalize([B]) a = tvm.nd.array(a_np, ctx) b = tvm.nd.array(np.zeros(get_const_tuple(B.shape), dtype=dtype), ctx) f = tvm.build(s, [A, B], device) f(a, b) tvm.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5) for device in ['llvm', 'cuda', 'opencl', 'metal', 'rocm', 'vulkan', 'nvptx']: check_device(device) def test_l2_normalize(): verify_l2_normalize((1, 3, 20, 20), 0.001) verify_l2_normalize((1, 3, 20, 20), 0.001, (1,)) verify_l2_normalize((1, 3, 20, 20), 0.001, (1, 2)) verify_l2_normalize((1, 3, 20, 20), 0.001, (2, 3)) verify_l2_normalize((1, 3, 20, 20), 0.001, (0, 3)) verify_l2_normalize((1, 3, 20, 20), 0.001, (0, 2, 3)) if __name__ == "__main__": test_l2_normalize()