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* Remove "using namespace mlx::core" in benchmarks/examples * Fix building example extension * A missing one in comment * Fix building on M chips
273 lines
7.6 KiB
C++
273 lines
7.6 KiB
C++
// Copyright © 2023 Apple Inc.
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#include "mlx/mlx.h"
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#include "time_utils.h"
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namespace mx = mlx::core;
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void time_creation_ops() {
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int M = 2000;
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int N = 500;
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auto shape = {M, N};
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auto full_fp32 = [&]() { return mx::full(shape, 3.3f); };
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TIME(full_fp32);
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auto zeros_fp32 = [&]() { return mx::zeros(shape, mx::float32); };
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TIME(zeros_fp32);
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auto ones_fp32 = [&]() { return mx::ones(shape, mx::float32); };
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TIME(ones_fp32);
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auto arange_fp32 = [&]() { return mx::arange(0.0, 10.0, 1e-4); };
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TIME(arange_fp32);
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}
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void time_type_conversions() {
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int M = 2000;
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int N = 500;
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auto shape = {M, N};
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auto device = mx::default_device();
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auto a = mx::zeros(shape, mx::float32);
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mx::eval(a);
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TIMEM("mx::float32 to mx::int32", mx::astype, a, mx::int32, device);
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TIMEM("mx::float32 to mx::uint32", mx::astype, a, mx::uint32, device);
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a = mx::zeros(shape, mx::int32);
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mx::eval(a);
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TIMEM("mx::int32 to mx::float32", mx::astype, a, mx::float32, device);
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a = mx::zeros(shape, mx::bool_);
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mx::eval(a);
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TIMEM("bool to mx::float32", mx::astype, a, mx::float32, device);
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TIMEM("bool to mx::int32", mx::astype, a, mx::int32, device);
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TIMEM("bool to mx::uint32", mx::astype, a, mx::uint32, device);
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}
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void time_random_generation() {
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int M = 2000;
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int N = 500;
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auto uniform = [&]() { return mx::random::uniform({M, N}, mx::float32); };
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TIME(uniform);
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auto normal = [&]() { return mx::random::normal({M, N}, mx::float32); };
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TIME(normal);
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}
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void time_unary_ops() {
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int M = 2000;
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int N = 500;
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auto device = mx::default_device();
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auto a = mx::random::normal({M, N});
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mx::eval(a);
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TIME(mlx::core::abs, a, device);
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TIME(mx::negative, a, device);
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TIME(mx::sign, a, device);
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TIME(mx::square, a, device);
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TIME(mlx::core::sqrt, a, device);
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TIME(mx::rsqrt, a, device);
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TIME(mlx::core::exp, a, device);
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a = mx::random::uniform({M, N});
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TIME(mlx::core::log, a, device);
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}
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void time_binary_ops() {
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int M = 1000, N = 100, K = 10;
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auto condition = mx::random::randint(0, 2, {M, N, K});
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auto a = mx::random::uniform({M, N, K});
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auto b = mx::random::uniform({M, N, K});
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auto device = mx::default_device();
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mx::eval(a, b);
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TIME(mx::add, a, b, device);
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TIME(mx::subtract, a, b, device);
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TIME(mx::multiply, a, b, device);
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TIME(mx::divide, a, b, device);
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TIME(mx::maximum, a, b, device);
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TIME(mx::minimum, a, b, device);
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TIME(mx::where, condition, a, b, device);
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condition = mx::array({true});
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b = mx::random::uniform({1});
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mx::eval(b);
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TIMEM("scalar", mx::add, a, b, device);
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TIMEM("vector-scalar", mx::subtract, a, b, device);
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TIMEM("scalar-vector", mx::subtract, b, a, device);
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TIMEM("scalar", mx::multiply, a, b, device);
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TIMEM("vector-scalar", mx::divide, a, b, device);
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TIMEM("scalar-vector", mx::divide, b, a, device);
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TIMEM("scalar-vector", mx::where, condition, a, b, device);
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condition = mx::broadcast_to(mx::array({true}), {1000, 100});
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a = mx::broadcast_to(mx::random::uniform({1}), {1000, 100});
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b = mx::broadcast_to(mx::random::uniform({1}), {1000, 100});
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mx::eval(a, b);
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TIMEM("scalar-scalar broadcast", mx::add, a, b, device);
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TIMEM("scalar-scalar broadcast", mx::subtract, a, b, device);
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TIMEM("scalar-scalar broadcast", mx::multiply, a, b, device);
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TIMEM("scalar-scalar broadcast", mx::divide, a, b, device);
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TIMEM("scalar-scalar broadcast", mx::where, condition, a, b, device);
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}
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void time_strided_ops() {
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int M = 50, N = 50, O = 50, P = 50;
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auto a = mx::random::uniform({M, N, O, P});
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auto b = mx::random::uniform({M, N, O, P});
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auto device = mx::default_device();
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mx::eval(a, b);
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TIMEM("non-strided", mx::add, a, b, device);
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a = mx::transpose(a, {1, 0, 2, 3});
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b = mx::transpose(b, {3, 2, 0, 1});
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mx::eval(a, b);
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TIMEM("strided", mx::add, a, b, device);
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}
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void time_comparisons() {
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int M = 1000, N = 100, K = 10;
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auto a = mx::random::uniform({M, N, K});
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auto b = mx::random::uniform({M, N, K});
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auto device = mx::default_device();
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mx::eval(a, b);
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TIME(mx::equal, a, b, device);
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TIME(mx::greater, a, b, device);
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TIME(mx::greater_equal, a, b, device);
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TIME(mx::less, a, b, device);
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TIME(mx::less_equal, a, b, device);
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}
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void time_matvec() {
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int M = 2000, N = 200;
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auto a = mx::random::uniform({M, N});
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auto b = mx::random::uniform({N});
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auto c = mx::random::uniform({M});
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mx::eval(a, b, c);
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auto matvec = [&]() { return mx::matmul(a, b); };
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TIME(matvec);
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auto matvec_transpose = [&]() { return mx::matmul(mx::transpose(a), c); };
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TIME(matvec_transpose);
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}
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void time_matmul() {
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int M = 1000, N = 1000, K = 1000;
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auto a = mx::random::uniform({M, K});
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auto b = mx::random::uniform({K, N});
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auto device = mx::default_device();
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mx::eval(a, b);
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TIME(mx::matmul, a, b, device);
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auto transpose_matmul = [&]() { return mx::matmul(mx::transpose(a), b); };
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TIME(transpose_matmul);
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}
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void time_reductions() {
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auto a = mx::random::normal({10000, 1000});
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mx::eval(a);
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auto sum_all = [&a]() { return mx::sum(a, false); };
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TIME(sum_all);
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auto sum_along_0 = [&a]() { return mx::sum(a, 0, false); };
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TIME(sum_along_0);
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auto sum_along_1 = [&a]() { return mx::sum(a, 1, false); };
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TIME(sum_along_1);
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auto prod_all = [&a]() { return mx::prod(a, false); };
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TIME(prod_all);
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auto all_true = [&a]() { return mx::all(a, false); };
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TIME(all_true);
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auto all_along_0 = [&a]() { return mx::all(a, 0, false); };
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TIME(all_along_0);
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auto all_along_1 = [&a]() { return mx::all(a, 1, false); };
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TIME(all_along_1);
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auto any_true = [&a]() { return mx::any(a, false); };
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TIME(any_true);
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auto argmin_along_0 = [&a]() { return mx::argmin(a, 0, false); };
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TIME(argmin_along_0);
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auto argmin_along_1 = [&a]() { return mx::argmin(a, 1, false); };
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TIME(argmin_along_1);
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}
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void time_gather_scatter() {
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auto a = mx::random::normal({1000, 768});
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mx::eval(a);
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auto indices = mx::random::randint(0, 1000, {256});
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mx::eval(indices);
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auto embedding_lookup = [&a, &indices]() { return mx::take(a, indices, 0); };
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TIME(embedding_lookup);
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indices = mx::random::randint(0, 768 * 1000, {256 * 768});
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mx::eval(indices);
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auto single_element_lookup = [&a, &indices]() {
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return mx::take(a, indices);
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};
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TIME(single_element_lookup);
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indices = mx::random::randint(0, 1000, {256});
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auto updates = mx::random::normal({256, 1, 768});
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mx::eval(indices, updates);
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auto embedding_update = [&a, &indices, &updates]() {
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return scatter(a, indices, updates, 0);
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};
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TIME(embedding_update);
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auto embedding_add = [&a, &indices, &updates]() {
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return scatter_add(a, indices, updates, 0);
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};
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TIME(embedding_add);
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a = mx::reshape(a, {-1});
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indices = mx::random::randint(0, 768 * 1000, {768 * 256});
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updates = mx::random::normal({256 * 768, 1});
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mx::eval(a, indices, updates);
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auto single_element_update = [&a, &indices, &updates]() {
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return scatter(a, indices, updates, 0);
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};
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TIME(single_element_update);
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auto single_element_add = [&a, &indices, &updates]() {
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return scatter_add(a, indices, updates, 0);
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};
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TIME(single_element_add);
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}
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void time_divmod() {
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auto a = mx::random::normal({1000});
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auto b = mx::random::normal({1000});
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mx::eval({a, b});
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auto divmod_fused = [&a, &b]() { return mx::divmod(a, b); };
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TIME(divmod_fused);
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auto divmod_separate = [&a, &b]() {
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return std::vector<mx::array>{mx::floor_divide(a, b), mx::remainder(a, b)};
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};
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TIME(divmod_separate);
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}
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int main() {
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std::cout << "Benchmarks for " << mx::default_device() << std::endl;
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time_creation_ops();
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time_type_conversions();
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time_unary_ops();
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time_binary_ops();
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time_strided_ops();
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time_random_generation();
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time_comparisons();
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time_matvec();
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time_matmul();
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time_reductions();
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time_gather_scatter();
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time_divmod();
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}
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