Commit 2e26eb5d authored by Brian Pickrell's avatar Brian Pickrell
Browse files

Added new random_seed op and some tests. New ref_ops_test...

Added new random_seed op and some tests.  New ref_ops_test rand_uniform_and_seed_test tests random_seed and rand_uniform together as a set.
parent 315a2b95
...@@ -184,6 +184,7 @@ register_migraphx_ops( ...@@ -184,6 +184,7 @@ register_migraphx_ops(
quant_dot quant_dot
quantizelinear quantizelinear
rand_uniform rand_uniform
random_seed
recip recip
reduce_max reduce_max
reduce_mean reduce_mean
......
...@@ -92,17 +92,9 @@ struct rand_uniform ...@@ -92,17 +92,9 @@ struct rand_uniform
argument result{dyn_out.computed_shape}; argument result{dyn_out.computed_shape};
auto local_seed(seed); auto local_seed(seed);
if(use_auto_seed) if(args.size() > 1)
local_seed = std::chrono::system_clock::now().time_since_epoch().count();
else
{ {
if(args.size() > 1) local_seed = args[1].at<uint32_t>(0);
{
if(args.at(1).get_shape().element_space() > 0)
{
visit_all(args[1])([&](auto data) { local_seed = data[0]; });
}
}
} }
// If a seed argument was not defined, use the value from the seed attribute, // If a seed argument was not defined, use the value from the seed attribute,
// or the default. // or the default.
......
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#ifndef MIGRAPHX_GUARD_OPERATORS_RANDOM_SEED_HPP
#define MIGRAPHX_GUARD_OPERATORS_RANDOM_SEED_HPP
#include <migraphx/check_shapes.hpp>
#include <migraphx/argument.hpp>
#include <migraphx/par_for.hpp>
#include <migraphx/reflect.hpp>
#include <random>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace op {
/**
* Generates a random seed for the use of random number generators. Generating the seed
* at runtime guarantees there will be a different random sequence on every execution.
* This operation has no inputs or attributes, and outputs an unsigned integer tensor with
* a single value.
*/
struct random_seed
{
shape::type_t dtype = shape::type_t::uint32_type;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(
f(self.dtype, "dtype"));
}
std::string name() const { return "random_seed"; }
shape compute_shape(std::vector<shape> inputs) const
{
(void) inputs;
return migraphx::shape(dtype, {1});
}
argument compute(const shape& output_shape, std::vector<argument> args) const
{
(void) args;
argument result(output_shape);
result.visit([&](auto output) {
std::generate(output.begin(), output.end(), [&]() { return uint32_t(std::chrono::system_clock::now().time_since_epoch().count()); });
});
return result;
}
};
} // namespace op
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif
...@@ -2232,6 +2232,12 @@ TEST_CASE(rand_uniform_2args) ...@@ -2232,6 +2232,12 @@ TEST_CASE(rand_uniform_2args)
expect_shape(s1, migraphx::make_op("rand_uniform", {{"seed", 1}}), s1, s2); expect_shape(s1, migraphx::make_op("rand_uniform", {{"seed", 1}}), s1, s2);
} }
TEST_CASE(random_seed)
{
migraphx::shape s{migraphx::shape::uint32_type, {1}};
expect_shape(s, migraphx::make_op("random_seed"));
}
TEST_CASE(quant_convolution_shape) TEST_CASE(quant_convolution_shape)
{ {
migraphx::shape output{migraphx::shape::int32_type, {4, 4, 1, 1}}; migraphx::shape output{migraphx::shape::int32_type, {4, 4, 1, 1}};
......
...@@ -6542,6 +6542,60 @@ TEST_CASE(rand_uniform_dyn_test) ...@@ -6542,6 +6542,60 @@ TEST_CASE(rand_uniform_dyn_test)
EXPECT(migraphx::verify::verify_range(result_vec, rand_samples, 100000)); EXPECT(migraphx::verify::verify_range(result_vec, rand_samples, 100000));
} }
TEST_CASE(rand_uniform_and_seed_test)
{
migraphx::program p;
auto* mm = p.get_main_module();
size_t sample_size(20000);
// Shape of the random data
migraphx::shape rs{migraphx::shape::float_type, {{1, 2}, {2, sample_size + 1}}};
auto input = mm->add_parameter("Input_1", rs);
// Runtime randomization seed
auto seed_input = mm->add_instruction(migraphx::make_op("random_seed"));
mm->add_instruction(migraphx::make_op("rand_uniform"),
input,
seed_input);
p.compile(migraphx::make_target("ref"));
// Create a dummy input to hold the random data
migraphx::shape input_fixed_shape1{migraphx::shape::float_type, {sample_size}};
migraphx::parameter_map params0;
params0["Input_1"] = migraphx::argument(input_fixed_shape1);
auto result = p.eval(params0).back();
std::vector<float> result_vec(sample_size);
result.visit([&](auto output) { result_vec.assign(output.begin(), output.end()); });
// Compare result with the STL's mt19937 generator. Expected verify_range error ~0.4
std::mt19937 gen(0);
std::uniform_real_distribution<> dis(0.0, 1.0);
std::vector<float> rand_samples(sample_size);
std::generate(rand_samples.begin(), rand_samples.end(), [&]() { return dis(gen); });
EXPECT(migraphx::verify::verify_range(result_vec, rand_samples, 1.e8));
}
TEST_CASE(random_seed_test)
{
migraphx::program p;
auto* mm = p.get_main_module();
mm->add_instruction(migraphx::make_op("random_seed"));
p.compile(migraphx::make_target("ref"));
auto result = p.eval({}).back();
std::vector<uint32_t> result_vec1(1);
result.visit([&](auto output) { result_vec1.assign(output.begin(), output.end()); });
std::vector<uint64_t> result_vec2(1);
result = p.eval({}).back();
result.visit([&](auto output) { result_vec2.assign(output.begin(), output.end()); });
EXPECT(result_vec1[0] != result_vec2[0]);
}
TEST_CASE(recip_test) TEST_CASE(recip_test)
{ {
migraphx::program p; migraphx::program p;
......
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