| # 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. |
| """Configure pytest""" |
| import numpy as np |
| import tvm |
| import tvm.testing |
| from tvm import te |
| from tvm.topi.cuda import stable_sort_by_key_thrust |
| from tvm.topi.cuda.scan import exclusive_scan, scan_thrust, schedule_scan |
| from tvm.contrib.thrust import can_use_thrust, can_use_rocthrust |
| |
| |
| thrust_check_func = {"cuda": can_use_thrust, "rocm": can_use_rocthrust} |
| |
| |
| def test_stable_sort_by_key(): |
| """Tests function test_stable_sort_by_key""" |
| size = 6 |
| keys = te.placeholder((size,), name="keys", dtype="int32") |
| values = te.placeholder((size,), name="values", dtype="int32") |
| |
| keys_out, values_out = stable_sort_by_key_thrust(keys, values) |
| |
| for target in ["cuda", "rocm"]: |
| if not tvm.testing.device_enabled(target): |
| print("Skip because %s is not enabled" % target) |
| continue |
| |
| with tvm.target.Target(target + " -libs=thrust") as tgt: |
| if not thrust_check_func[target](tgt, "tvm.contrib.thrust.stable_sort_by_key"): |
| print("skip because thrust is not enabled...") |
| return |
| |
| dev = tvm.device(target, 0) |
| s = te.create_schedule([keys_out.op, values_out.op]) |
| f = tvm.build(s, [keys, values, keys_out, values_out], target) |
| |
| keys_np = np.array([1, 4, 2, 8, 2, 7], np.int32) |
| values_np = np.random.randint(0, 10, size=(size,)).astype(np.int32) |
| keys_np_out = np.zeros(keys_np.shape, np.int32) |
| values_np_out = np.zeros(values_np.shape, np.int32) |
| keys_in = tvm.nd.array(keys_np, dev) |
| values_in = tvm.nd.array(values_np, dev) |
| keys_out = tvm.nd.array(keys_np_out, dev) |
| values_out = tvm.nd.array(values_np_out, dev) |
| f(keys_in, values_in, keys_out, values_out) |
| |
| ref_keys_out = np.sort(keys_np) |
| ref_values_out = np.array([values_np[i] for i in np.argsort(keys_np)]) |
| tvm.testing.assert_allclose(keys_out.numpy(), ref_keys_out, rtol=1e-5) |
| tvm.testing.assert_allclose(values_out.numpy(), ref_values_out, rtol=1e-5) |
| |
| |
| def test_exclusive_scan(): |
| """Tests function test_exclusive_scan""" |
| for target in ["cuda", "rocm"]: |
| if not tvm.testing.device_enabled(target): |
| print("Skip because %s is not enabled" % target) |
| continue |
| |
| with tvm.target.Target(target + " -libs=thrust") as tgt: |
| if not thrust_check_func[target](tgt, "tvm.contrib.thrust.sum_scan"): |
| print("skip because thrust is not enabled...") |
| return |
| |
| for ishape in [(10,), (10, 10), (10, 10, 10)]: |
| values = te.placeholder(ishape, name="values", dtype="int32") |
| |
| scan, reduction = exclusive_scan(values, return_reduction=True) |
| s = schedule_scan([scan, reduction]) |
| |
| dev = tvm.device(target, 0) |
| f = tvm.build(s, [values, scan, reduction], target) |
| |
| values_np = np.random.randint(0, 10, size=ishape).astype(np.int32) |
| values_np_out = np.zeros(values_np.shape, np.int32) |
| |
| if len(ishape) == 1: |
| reduction_shape = () |
| else: |
| reduction_shape = ishape[:-1] |
| |
| reduction_np_out = np.zeros(reduction_shape, np.int32) |
| |
| values_in = tvm.nd.array(values_np, dev) |
| values_out = tvm.nd.array(values_np_out, dev) |
| reduction_out = tvm.nd.array(reduction_np_out, dev) |
| f(values_in, values_out, reduction_out) |
| |
| ref_values_out = np.cumsum(values_np, axis=-1, dtype="int32") - values_np |
| tvm.testing.assert_allclose(values_out.numpy(), ref_values_out, rtol=1e-5) |
| ref_reduction_out = np.sum(values_np, axis=-1) |
| tvm.testing.assert_allclose(reduction_out.numpy(), ref_reduction_out, rtol=1e-5) |
| |
| |
| def test_inclusive_scan(): |
| """Tests function test_inclusive_scan""" |
| out_dtype = "int64" |
| |
| for target in ["cuda", "rocm"]: |
| if not tvm.testing.device_enabled(target): |
| print("Skip because %s is not enabled" % target) |
| continue |
| |
| with tvm.target.Target(target + " -libs=thrust") as tgt: |
| if not thrust_check_func[target](tgt, "tvm.contrib.thrust.sum_scan"): |
| print("skip because thrust is not enabled...") |
| return |
| |
| for ishape in [(10,), (10, 10)]: |
| values = te.placeholder(ishape, name="values", dtype="int32") |
| |
| scan = scan_thrust(values, out_dtype, exclusive=False) |
| s = tvm.te.create_schedule([scan.op]) |
| |
| dev = tvm.device(target, 0) |
| f = tvm.build(s, [values, scan], target) |
| |
| values_np = np.random.randint(0, 10, size=ishape).astype(np.int32) |
| values_np_out = np.zeros(values_np.shape, out_dtype) |
| values_in = tvm.nd.array(values_np, dev) |
| values_out = tvm.nd.array(values_np_out, dev) |
| f(values_in, values_out) |
| |
| ref_values_out = np.cumsum(values_np, axis=-1, dtype=out_dtype) |
| tvm.testing.assert_allclose(values_out.numpy(), ref_values_out, rtol=1e-5) |
| |
| |
| if __name__ == "__main__": |
| test_stable_sort_by_key() |
| test_exclusive_scan() |
| test_inclusive_scan() |