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Don't use make_unique to create shared_ptr (#902)

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The code compiled because shared_ptr's constructor actually accepts
unique_ptr.
This commit is contained in:
Cheng 2024-03-27 22:13:29 +09:00 committed by GitHub
parent dc175f08d3
commit 90dfa43ff1
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GPG Key ID: B5690EEEBB952194
8 changed files with 17 additions and 17 deletions
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2
docs/src/dev/extensions.rst
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@ -223,7 +223,7 @@ Let's re-implement our operation now in terms of our :class:`Axpby` primitive.
/* const std::vector<int>& shape = */ out_shape,
/* Dtype dtype = */ out_dtype,
/* std::unique_ptr<Primitive> primitive = */
std::make_unique<Axpby>(to_stream(s), alpha, beta),
std::make_shared<Axpby>(to_stream(s), alpha, beta),
/* const std::vector<array>& inputs = */ broadcasted_inputs);
}

2
examples/extensions/axpby/axpby.cpp
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@ -61,7 +61,7 @@ array axpby(
/* const std::vector<int>& shape = */ out_shape,
/* Dtype dtype = */ out_dtype,
/* std::unique_ptr<Primitive> primitive = */
std::make_unique<Axpby>(to_stream(s), alpha, beta),
std::make_shared<Axpby>(to_stream(s), alpha, beta),
/* const std::vector<array>& inputs = */ broadcasted_inputs);
}

2
mlx/fft.cpp
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@ -95,7 +95,7 @@ array fft_impl(
return array(
out_shape,
out_type,
std::make_unique<FFT>(to_stream(s), valid_axes, inverse, real),
std::make_shared<FFT>(to_stream(s), valid_axes, inverse, real),
{astype(in, in_type, s)});
}

2
mlx/io/load.cpp
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@ -217,7 +217,7 @@ array load(std::shared_ptr<io::Reader> in_stream, StreamOrDevice s) {
auto loaded_array = array(
shape,
dtype,
std::make_unique<Load>(to_stream(s), in_stream, offset, swap_endianness),
std::make_shared<Load>(to_stream(s), in_stream, offset, swap_endianness),
std::vector<array>{});
if (col_contiguous) {
loaded_array = transpose(loaded_array, s);

2
mlx/io/safetensor.cpp
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@ -136,7 +136,7 @@ SafetensorsLoad load_safetensors(
auto loaded_array = array(
shape,
type,
std::make_unique<Load>(
std::make_shared<Load>(
to_stream(s), in_stream, offset + data_offsets.at(0), false),
std::vector<array>{});
res.insert({item.key(), loaded_array});

12
mlx/primitives.cpp
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@ -1267,7 +1267,7 @@ std::pair<std::vector<array>, std::vector<int>> FFT::vmap(
{array(
out_shape,
real_ && inverse_ ? float32 : complex64,
std::make_unique<FFT>(stream(), fft_axes, inverse_, real_),
std::make_shared<FFT>(stream(), fft_axes, inverse_, real_),
{in})},
{ax}};
}
@ -1377,7 +1377,7 @@ std::pair<std::vector<array>, std::vector<int>> Full::vmap(
assert(axes.size() == 1);
auto& in = inputs[0];
auto out =
array(in.shape(), in.dtype(), std::make_unique<Full>(stream()), {in});
array(in.shape(), in.dtype(), std::make_shared<Full>(stream()), {in});
return {{out}, axes};
}
@ -1604,7 +1604,7 @@ std::pair<std::vector<array>, std::vector<int>> Log::vmap(
{array(
in.shape(),
in.dtype(),
std::make_unique<Log>(stream(), base_),
std::make_shared<Log>(stream(), base_),
{in})},
axes};
}
@ -2259,7 +2259,7 @@ std::pair<std::vector<array>, std::vector<int>> RandomBits::vmap(
auto out = array(
shape,
get_dtype(),
std::make_unique<RandomBits>(stream(), shape, width_),
std::make_shared<RandomBits>(stream(), shape, width_),
{key});
return {{out}, {kax}};
}
@ -2493,7 +2493,7 @@ std::pair<std::vector<array>, std::vector<int>> Scan::vmap(
{array(
in.shape(),
out_dtype,
std::make_unique<Scan>(
std::make_shared<Scan>(
stream(), reduce_type_, axis_ + axis_left, reverse_, inclusive_),
{in})},
axes};
@ -3303,7 +3303,7 @@ std::pair<std::vector<array>, std::vector<int>> NumberOfElements::vmap(
array out = array(
std::vector<int>{},
dtype_,
std::make_unique<NumberOfElements>(stream(), new_axes, inverted_, dtype_),
std::make_shared<NumberOfElements>(stream(), new_axes, inverted_, dtype_),
inputs);
return {{out}, {-1}};

4
mlx/transforms.cpp
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@ -53,7 +53,7 @@ void eval(std::vector<array> outputs) {
}
auto synchronizer = array(
{}, bool_, std::make_unique<Synchronizer>(stream), std::move(outputs));
{}, bool_, std::make_shared<Synchronizer>(stream), std::move(outputs));
size_t depth_counter = 0;
recurse = [&](const array& a) {
@ -118,7 +118,7 @@ void eval(std::vector<array> outputs) {
}
std::shared_ptr<std::promise<void>> p;
if (auto it = deps.find(arr.output(0).id()); it != deps.end()) {
p = std::make_unique<std::promise<void>>();
p = std::make_shared<std::promise<void>>();
ps.push_back(p);
it->second = p->get_future().share();
}

8
tests/arg_reduce_tests.cpp
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@ -16,7 +16,7 @@ void test_arg_reduce_small(
std::vector<int> expected_output) {
auto s = default_stream(d);
auto y =
array(out_shape, uint32, std::make_unique<ArgReduce>(s, r, axis), {x});
array(out_shape, uint32, std::make_shared<ArgReduce>(s, r, axis), {x});
y.eval();
const uint32_t* ydata = y.data<uint32_t>();
for (int i = 0; i < y.size(); i++) {
@ -32,12 +32,12 @@ void test_arg_reduce_against_cpu(
auto y1 = array(
out_shape,
uint32,
std::make_unique<ArgReduce>(default_stream(Device::cpu), r, axis),
std::make_shared<ArgReduce>(default_stream(Device::cpu), r, axis),
{x});
auto y2 = array(
out_shape,
uint32,
std::make_unique<ArgReduce>(default_stream(Device::gpu), r, axis),
std::make_shared<ArgReduce>(default_stream(Device::gpu), r, axis),
{x});
y1.eval();
y2.eval();
@ -136,7 +136,7 @@ void test_arg_reduce_small_bool(
{2, 3, 4});
x.eval();
auto y =
array(out_shape, uint32, std::make_unique<ArgReduce>(s, r, axis), {x});
array(out_shape, uint32, std::make_shared<ArgReduce>(s, r, axis), {x});
y.eval();
const uint32_t* ydata = y.data<uint32_t>();
for (int i = 0; i < y.size(); i++) {