# 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. import tvm from tvm import te import numpy as np from tvm.contrib import random def test_randint(): m = 1024 n = 1024 A = random.randint(-127, 128, size=(m, n), dtype='int32') s = te.create_schedule(A.op) def verify(target="llvm"): if not tvm.runtime.enabled(target): print("skip because %s is not enabled..." % target) return if not tvm.get_global_func("tvm.contrib.random.randint", True): print("skip because extern function is not available") return ctx = tvm.cpu(0) f = tvm.build(s, [A], target) a = tvm.nd.array(np.zeros((m, n), dtype=A.dtype), ctx) f(a) na = a.asnumpy() assert abs(np.mean(na)) < 0.2 assert np.min(na) == -127 assert np.max(na) == 127 verify() def test_uniform(): m = 1024 n = 1024 A = random.uniform(0, 1, size=(m, n)) s = te.create_schedule(A.op) def verify(target="llvm"): if not tvm.runtime.enabled(target): print("skip because %s is not enabled..." % target) return if not tvm.get_global_func("tvm.contrib.random.uniform", True): print("skip because extern function is not available") return ctx = tvm.cpu(0) f = tvm.build(s, [A], target) a = tvm.nd.array(np.zeros((m, n), dtype=A.dtype), ctx) f(a) na = a.asnumpy() assert abs(np.mean(na) - 0.5) < 1e-2 assert abs(np.min(na) - 0.0) < 1e-3 assert abs(np.max(na) - 1.0) < 1e-3 verify() def test_normal(): m = 1024 n = 1024 A = random.normal(3, 4, size=(m, n)) s = te.create_schedule(A.op) def verify(target="llvm"): if not tvm.runtime.enabled(target): print("skip because %s is not enabled..." % target) return if not tvm.get_global_func("tvm.contrib.random.normal", True): print("skip because extern function is not available") return ctx = tvm.cpu(0) f = tvm.build(s, [A], target) a = tvm.nd.array(np.zeros((m, n), dtype=A.dtype), ctx) f(a) na = a.asnumpy() assert abs(np.mean(na) - 3) < 1e-2 assert abs(np.std(na) - 4) < 1e-2 verify() if __name__ == "__main__": test_randint() test_uniform() test_normal()