temp for testing

.circleci/config.yml

@@ -336,10 +336,11 @@ jobs:
             pip install typing_extensions
             python setup.py generate_stubs
             << parameters.extra_env >> python -m build --wheel
+            << parameters.extra_env >> MLX_BUILD_COMMON=1 python -m build --wheel
             auditwheel show dist/*
             auditwheel repair dist/* --plat manylinux_2_31_x86_64
       - run:
-          name: Upload package
+          name: Upload packages
           command: |
             source env/bin/activate
             twine upload wheelhouse/*

docs/src/install.rst

@@ -38,8 +38,16 @@ and SM 7.0 (Volta) and up. To install MLX with CUDA support, run:
 
 .. code-block:: shell
 
-    pip install mlx-cuda
+    pip install "mlx[cuda]"
 
+CPU only (Linux)
+^^^^^^^^^^^^^^^^
+
+For a CPU-only version of MLX that runs on Linux use:
+
+.. code-block:: shell
+
+    pip install "mlx[cpu]"
 
 Troubleshooting
 ^^^^^^^^^^^^^^^

mlx/distributed/ring/ring.cpp

@@ -22,20 +22,78 @@
 #include "mlx/backend/cpu/encoder.h"
 #include "mlx/distributed/distributed.h"
 #include "mlx/distributed/distributed_impl.h"
-#include "mlx/dtype_utils.h"
 #include "mlx/threadpool.h"
 
 #ifndef SOL_TCP
 #define SOL_TCP IPPROTO_TCP
 #endif
 
+#define SWITCH_TYPE(x, ...)  \
+  switch ((x).dtype()) {     \
+    case bool_: {            \
+      using T = bool;        \
+      __VA_ARGS__;           \
+    } break;                 \
+    case int8: {             \
+      using T = int8_t;      \
+      __VA_ARGS__;           \
+    } break;                 \
+    case int16: {            \
+      using T = int16_t;     \
+      __VA_ARGS__;           \
+    } break;                 \
+    case int32: {            \
+      using T = int32_t;     \
+      __VA_ARGS__;           \
+    } break;                 \
+    case int64: {            \
+      using T = int64_t;     \
+      __VA_ARGS__;           \
+    } break;                 \
+    case uint8: {            \
+      using T = uint8_t;     \
+      __VA_ARGS__;           \
+    } break;                 \
+    case uint16: {           \
+      using T = uint16_t;    \
+      __VA_ARGS__;           \
+    } break;                 \
+    case uint32: {           \
+      using T = uint32_t;    \
+      __VA_ARGS__;           \
+    } break;                 \
+    case uint64: {           \
+      using T = uint64_t;    \
+      __VA_ARGS__;           \
+    } break;                 \
+    case bfloat16: {         \
+      using T = bfloat16_t;  \
+      __VA_ARGS__;           \
+    } break;                 \
+    case float16: {          \
+      using T = float16_t;   \
+      __VA_ARGS__;           \
+    } break;                 \
+    case float32: {          \
+      using T = float;       \
+      __VA_ARGS__;           \
+    } break;                 \
+    case float64: {          \
+      using T = double;      \
+      __VA_ARGS__;           \
+    } break;                 \
+    case complex64: {        \
+      using T = complex64_t; \
+      __VA_ARGS__;           \
+    } break;                 \
+  }
+
 namespace mlx::core::distributed::ring {
 
 constexpr const size_t ALL_SUM_SIZE = 8 * 1024 * 1024;
 constexpr const size_t ALL_SUM_BUFFERS = 2;
 constexpr const int CONN_ATTEMPTS = 5;
 constexpr const int CONN_WAIT = 1000;
-constexpr const int INIT_TIMEOUT = 20000;
 
 using GroupImpl = mlx::core::distributed::detail::GroupImpl;
 using json = nlohmann::json;
@@ -445,7 +503,6 @@ std::vector<int> make_connections(
 
   return sockets;
 }
-
 template <typename T>
 struct SumOp {
   void operator()(const T* input, T* output, size_t N) {
@@ -493,27 +550,19 @@ class RingGroup : public GroupImpl {
     size_ = nodes.size();
     int connect_to = (rank_ + 1) % size_;
 
-    // Initialize the ring by making all the connections
+    // We define the connection order by having the rank_ == size_ - 1 connect
+    // first and accept after.
+    if (rank_ < connect_to) {
       log_info(verbose_, "Rank", rank_, "accepting");
+      sockets_left_ = std::move(accept_connections(nodes[rank_]));
       log_info(verbose_, "Rank", rank_, "connecting to", connect_to);
-    auto sl = std::async(std::launch::async, accept_connections, nodes[rank_]);
+      sockets_right_ = std::move(make_connections(nodes[connect_to], verbose));
-    auto sr = std::async(
+    } else {
-        std::launch::async, make_connections, nodes[connect_to], verbose);
+      log_info(verbose_, "Rank", rank_, "connecting to", connect_to);
-    std::future_status status_sl, status_sr;
+      sockets_right_ = std::move(make_connections(nodes[connect_to], verbose));
-    for (int i = 0; i < 10; i++) {
+      log_info(verbose_, "Rank", rank_, "accepting");
-      status_sl = sl.wait_for(std::chrono::milliseconds(INIT_TIMEOUT / 10));
+      sockets_left_ = std::move(accept_connections(nodes[rank_]));
-      status_sr = sl.wait_for(std::chrono::milliseconds(INIT_TIMEOUT / 10));
-      if (status_sl == std::future_status::ready &&
-          status_sr == std::future_status::ready) {
-        break;
     }
-    }
-    if (status_sl != std::future_status::ready ||
-        status_sr != std::future_status::ready) {
-      throw std::runtime_error("[ring] Ring initialization timed out");
-    }
-    sockets_left_ = std::move(sl.get());
-    sockets_right_ = std::move(sr.get());
 
     // Failure if we couldn't make right or left sockets
     if (sockets_right_.empty()) {
@@ -579,24 +628,18 @@ class RingGroup : public GroupImpl {
   }
 
   void all_sum(const array& input, array& output, Stream stream) override {
-    dispatch_all_types(output.dtype(), [&](auto type_tag) {
+    SWITCH_TYPE(
-      using T = MLX_GET_TYPE(type_tag);
+        output, all_reduce<T, SumOp<T>>(input, output, stream, SumOp<T>()));
-      all_reduce<T, SumOp<T>>(input, output, stream, SumOp<T>());
-    });
   }
 
   void all_max(const array& input, array& output, Stream stream) override {
-    dispatch_all_types(output.dtype(), [&](auto type_tag) {
+    SWITCH_TYPE(
-      using T = MLX_GET_TYPE(type_tag);
+        output, all_reduce<T, MaxOp<T>>(input, output, stream, MaxOp<T>()));
-      all_reduce<T, MaxOp<T>>(input, output, stream, MaxOp<T>());
-    });
   }
 
   void all_min(const array& input, array& output, Stream stream) override {
-    dispatch_all_types(output.dtype(), [&](auto type_tag) {
+    SWITCH_TYPE(
-      using T = MLX_GET_TYPE(type_tag);
+        output, all_reduce<T, MinOp<T>>(input, output, stream, MinOp<T>()));
-      all_reduce<T, MinOp<T>>(input, output, stream, MinOp<T>());
-    });
   }
 
   std::shared_ptr<GroupImpl> split(int color, int key = -1) override {

python/tests/mpi_test_distributed.py

@@ -4,7 +4,6 @@ import unittest
 
 import mlx.core as mx
 import mlx_distributed_tests
-import mlx_tests
 
 
 class TestMPIDistributed(mlx_distributed_tests.MLXDistributedCommonTestCase):
@@ -151,4 +150,4 @@ class TestMPIDistributed(mlx_distributed_tests.MLXDistributedCommonTestCase):
 
 
 if __name__ == "__main__":
-    mlx_tests.MLXTestRunner()
+    unittest.main()

python/tests/ring_test_distributed.py

@@ -4,7 +4,6 @@ import unittest
 
 import mlx.core as mx
 import mlx_distributed_tests
-import mlx_tests
 
 
 class TestRingDistributed(mlx_distributed_tests.MLXDistributedCommonTestCase):

setup.py

@@ -5,10 +5,11 @@ import os
 import platform
 import re
 import subprocess
+from functools import partial
 from pathlib import Path
 from subprocess import run
 
-from setuptools import Command, Extension, find_namespace_packages, setup
+from setuptools import Command, Extension, setup
 from setuptools.command.build_ext import build_ext
 
 
@@ -165,19 +166,27 @@ with open(Path(__file__).parent / "README.md", encoding="utf-8") as f:
 # The information here can also be placed in setup.cfg - better separation of
 # logic and declaration, and simpler if you include description/version in a file.
 if __name__ == "__main__":
-    packages = find_namespace_packages(
-        where="python", exclude=["src", "tests", "tests.*"]
-    )
     package_dir = {"": "python"}
     package_data = {"mlx": ["lib/*", "include/*", "share/*"], "mlx.core": ["*.pyi"]}
-    install_requires = []
+    packages = [
+        "mlx",
+        "mlx.nn",
+        "mlx.optimizers",
+    ]
+
+    is_release = "PYPI_RELEASE" in os.environ
+    build_macos = platform.system() == "Darwin"
     build_cuda = "MLX_BUILD_CUDA=ON" in os.environ.get("CMAKE_ARGS", "")
+    build_common = "MLX_BUILD_COMMON" in os.environ
+
+    install_requires = []
     if build_cuda:
         install_requires = ["nvidia-cublas-cu12", "nvidia-cuda-nvrtc-cu12"]
+    version = get_version()
 
-    setup(
+    _setup = partial(
-        name="mlx-cuda" if build_cuda else "mlx",
+        setup,
-        version=get_version(),
+        version=version,
         author="MLX Contributors",
         author_email="mlx@group.apple.com",
         description="A framework for machine learning on Apple silicon.",
@@ -185,12 +194,14 @@ if __name__ == "__main__":
         long_description_content_type="text/markdown",
         license="MIT",
         url="https://github.com/ml-explore/mlx",
-        packages=packages,
         package_dir=package_dir,
         package_data=package_data,
-        include_package_data=True,
+        zip_safe=False,
+        python_requires=">=3.9",
         install_requires=install_requires,
-        extras_require={
+    )
+
+    extras = {
         "dev": [
             "nanobind==2.4.0",
             "numpy",
@@ -199,15 +210,41 @@ if __name__ == "__main__":
             "torch",
             "typing_extensions",
         ],
-        },
+    }
     entry_points = {
         "console_scripts": [
             "mlx.launch = mlx.distributed_run:main",
             "mlx.distributed_config = mlx.distributed_run:distributed_config",
         ]
-        },
+    }
+
+    test = "-awni-test"
+    if not is_release or build_macos:
+        _setup(
+            name="mlx" + test,
+            include_package_data=True,
+            packages=packages,
+            extras_require=extras,
+            entry_points=entry_points,
+            ext_modules=[CMakeExtension("mlx.core")],
+            cmdclass={"build_ext": CMakeBuild, "generate_stubs": GenerateStubs},
+        )
+    elif build_common:
+        extras["cpu"] = [f"mlx-cpu{test}=={version}"]
+        extras["cuda"] = [f"mlx-cuda{test}=={version}"]
+        _setup(
+            name="mlx" + test,
+            packages=["mlx"],
+            extras_require=extras,
+            entry_points=entry_points,
+            exclude_package_data=package_data,
+        )
+    else:
+        _setup(
+            name="mlx-cuda" if build_cuda else "mlx-cpu" + test,
+            include_package_data=True,
+            packages=packages,
+            extras_require=extras,
             ext_modules=[CMakeExtension("mlx.core")],
             cmdclass={"build_ext": CMakeBuild, "generate_stubs": GenerateStubs},
-        zip_safe=False,
-        python_requires=">=3.9",
         )