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#!/bin/bash | ||
# Copyright (c) 2024, NVIDIA CORPORATION. | ||
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set -euo pipefail | ||
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package_dir=$1 | ||
wheel_dir_relative_path=$2 | ||
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cd "${package_dir}" | ||
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rapids-logger "validate packages with 'pydistcheck'" | ||
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pydistcheck \ | ||
--inspect \ | ||
"$(echo ${wheel_dir_relative_path}/*.whl)" | ||
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rapids-logger "validate packages with 'twine'" | ||
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twine check \ | ||
--strict \ | ||
"$(echo ${wheel_dir_relative_path}/*.whl)" |
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/* | ||
* Copyright (c) 2024, NVIDIA CORPORATION. | ||
* | ||
* Licensed 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. | ||
*/ | ||
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#include <benchmarks/common/generate_input.hpp> | ||
#include <benchmarks/fixture/benchmark_fixture.hpp> | ||
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#include <cudf_test/column_wrapper.hpp> | ||
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#include <cudf/strings/find.hpp> | ||
#include <cudf/strings/find_multiple.hpp> | ||
#include <cudf/strings/strings_column_view.hpp> | ||
#include <cudf/utilities/default_stream.hpp> | ||
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#include <nvbench/nvbench.cuh> | ||
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static void bench_find_string(nvbench::state& state) | ||
{ | ||
auto const n_rows = static_cast<cudf::size_type>(state.get_int64("num_rows")); | ||
auto const row_width = static_cast<cudf::size_type>(state.get_int64("row_width")); | ||
auto const hit_rate = static_cast<cudf::size_type>(state.get_int64("hit_rate")); | ||
auto const target_count = static_cast<cudf::size_type>(state.get_int64("targets")); | ||
auto const api = state.get_string("api"); | ||
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auto const stream = cudf::get_default_stream(); | ||
auto const col = create_string_column(n_rows, row_width, hit_rate); | ||
auto const input = cudf::strings_column_view(col->view()); | ||
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// Note that these all match the first row of the raw_data in create_string_column. | ||
// This is so the hit_rate can properly accounted for. | ||
std::vector<std::string> const target_data( | ||
{" abc", "W43", "0987 5W43", "123 abc", "23 abc", "3 abc", "7 5W43", "87 5W43", "987 5W43"}); | ||
auto h_targets = std::vector<std::string>{}; | ||
for (cudf::size_type i = 0; i < target_count; i++) { | ||
h_targets.emplace_back(target_data[i % target_data.size()]); | ||
} | ||
cudf::test::strings_column_wrapper targets(h_targets.begin(), h_targets.end()); | ||
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state.set_cuda_stream(nvbench::make_cuda_stream_view(stream.value())); | ||
auto const chars_size = input.chars_size(stream); | ||
state.add_global_memory_reads<nvbench::int8_t>(chars_size); | ||
if (api == "find") { | ||
state.add_global_memory_writes<nvbench::int32_t>(input.size()); | ||
} else { | ||
state.add_global_memory_writes<nvbench::int8_t>(input.size()); | ||
} | ||
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if (api == "find") { | ||
state.exec(nvbench::exec_tag::sync, [&](nvbench::launch& launch) { | ||
cudf::strings::find_multiple(input, cudf::strings_column_view(targets)); | ||
}); | ||
} else if (api == "contains") { | ||
state.exec(nvbench::exec_tag::sync, [&](nvbench::launch& launch) { | ||
cudf::strings::contains_multiple(input, cudf::strings_column_view(targets)); | ||
}); | ||
} | ||
} | ||
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NVBENCH_BENCH(bench_find_string) | ||
.set_name("find_multiple") | ||
.add_string_axis("api", {"find", "contains"}) | ||
.add_int64_axis("targets", {10, 20, 40}) | ||
.add_int64_axis("row_width", {32, 64, 128, 256}) | ||
.add_int64_axis("num_rows", {32768, 262144, 2097152}) | ||
.add_int64_axis("hit_rate", {20, 80}); // percentage |
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