Safetensor support (#215)

Co-authored-by: Awni Hannun <awni@apple.com>
This commit is contained in:
Diogo 2023-12-27 05:06:55 -05:00 committed by GitHub
parent 6b0d30bb85
commit 1f6ab6a556
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
17 changed files with 476 additions and 52 deletions

4
.gitignore vendored
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@ -6,6 +6,10 @@ __pycache__/
# C extensions
*.so
# tensor files
*.safe
*.safetensors
# Metal libraries
*.metallib
venv/

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@ -98,6 +98,15 @@ elseif (MLX_BUILD_METAL)
${QUARTZ_LIB})
endif()
MESSAGE(STATUS "Downloading json")
FetchContent_Declare(json URL https://github.com/nlohmann/json/releases/download/v3.11.3/json.tar.xz)
FetchContent_MakeAvailable(json)
target_include_directories(
mlx PUBLIC
$<BUILD_INTERFACE:${json_SOURCE_DIR}/single_include/nlohmann>
$<INSTALL_INTERFACE:include/json>
)
find_library(ACCELERATE_LIBRARY Accelerate)
if (MLX_BUILD_ARM AND ACCELERATE_LIBRARY)
message(STATUS "Accelerate found ${ACCELERATE_LIBRARY}")
@ -152,6 +161,8 @@ if (MLX_BUILD_BENCHMARKS)
add_subdirectory(${CMAKE_CURRENT_LIST_DIR}/benchmarks/cpp)
endif()
# ----------------------------- Installation -----------------------------
include(GNUInstallDirs)

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@ -83,6 +83,7 @@ Operations
save
savez
savez_compressed
save_safetensors
sigmoid
sign
sin

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@ -8,7 +8,6 @@ target_sources(
${CMAKE_CURRENT_SOURCE_DIR}/fft.cpp
${CMAKE_CURRENT_SOURCE_DIR}/ops.cpp
${CMAKE_CURRENT_SOURCE_DIR}/graph_utils.cpp
${CMAKE_CURRENT_SOURCE_DIR}/load.cpp
${CMAKE_CURRENT_SOURCE_DIR}/primitives.cpp
${CMAKE_CURRENT_SOURCE_DIR}/random.cpp
${CMAKE_CURRENT_SOURCE_DIR}/scheduler.cpp
@ -19,7 +18,7 @@ target_sources(
)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/backend/common)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/io)
if (MLX_BUILD_ACCELERATE)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/backend/accelerate)
else()

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@ -5,7 +5,7 @@
#include <utility>
#include "mlx/allocator.h"
#include "mlx/load.h"
#include "mlx/io/load.h"
#include "mlx/primitives.h"
namespace mlx::core {

6
mlx/io/CMakeLists.txt Normal file
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@ -0,0 +1,6 @@
target_sources(
mlx
PRIVATE
${CMAKE_CURRENT_SOURCE_DIR}/load.cpp
${CMAKE_CURRENT_SOURCE_DIR}/safetensor.cpp
)

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@ -6,7 +6,7 @@
#include <limits>
#include <sstream>
#include "mlx/load.h"
#include "mlx/io/load.h"
#include "mlx/ops.h"
#include "mlx/primitives.h"
#include "mlx/utils.h"

189
mlx/io/safetensor.cpp Normal file
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@ -0,0 +1,189 @@
#include "mlx/io/safetensor.h"
#include <stack>
namespace mlx::core {
std::string dtype_to_safetensor_str(Dtype t) {
switch (t) {
case float32:
return ST_F32;
case bfloat16:
return ST_BF16;
case float16:
return ST_F16;
case int64:
return ST_I64;
case int32:
return ST_I32;
case int16:
return ST_I16;
case int8:
return ST_I8;
case uint64:
return ST_U64;
case uint32:
return ST_U32;
case uint16:
return ST_U16;
case uint8:
return ST_U8;
case bool_:
return ST_BOOL;
case complex64:
return ST_C64;
}
}
Dtype dtype_from_safetensor_str(std::string str) {
if (str == ST_F32) {
return float32;
} else if (str == ST_F16) {
return float16;
} else if (str == ST_BF16) {
return bfloat16;
} else if (str == ST_I64) {
return int64;
} else if (str == ST_I32) {
return int32;
} else if (str == ST_I16) {
return int16;
} else if (str == ST_I8) {
return int8;
} else if (str == ST_U64) {
return uint64;
} else if (str == ST_U32) {
return uint32;
} else if (str == ST_U16) {
return uint16;
} else if (str == ST_U8) {
return uint8;
} else if (str == ST_BOOL) {
return bool_;
} else if (str == ST_C64) {
return complex64;
} else {
throw std::runtime_error("[safetensor] unsupported dtype " + str);
}
}
/** Load array from reader in safetensor format */
std::unordered_map<std::string, array> load_safetensors(
std::shared_ptr<io::Reader> in_stream,
StreamOrDevice s) {
////////////////////////////////////////////////////////
// Open and check file
if (!in_stream->good() || !in_stream->is_open()) {
throw std::runtime_error(
"[load_safetensors] Failed to open " + in_stream->label());
}
uint64_t jsonHeaderLength = 0;
in_stream->read(reinterpret_cast<char*>(&jsonHeaderLength), 8);
if (jsonHeaderLength <= 0) {
throw std::runtime_error(
"[load_safetensors] Invalid json header length " + in_stream->label());
}
// Load the json metadata
char rawJson[jsonHeaderLength];
in_stream->read(rawJson, jsonHeaderLength);
auto metadata = json::parse(rawJson, rawJson + jsonHeaderLength);
// Should always be an object on the top-level
if (!metadata.is_object()) {
throw std::runtime_error(
"[load_safetensors] Invalid json metadata " + in_stream->label());
}
size_t offset = jsonHeaderLength + 8;
// Load the arrays using metadata
std::unordered_map<std::string, array> res;
for (const auto& item : metadata.items()) {
if (item.key() == "__metadata__") {
// ignore metadata for now
continue;
}
std::string dtype = item.value().at("dtype");
std::vector<int> shape = item.value().at("shape");
std::vector<size_t> data_offsets = item.value().at("data_offsets");
Dtype type = dtype_from_safetensor_str(dtype);
auto loaded_array = array(
shape,
type,
std::make_unique<Load>(
to_stream(s), in_stream, offset + data_offsets.at(0), false),
std::vector<array>{});
res.insert({item.key(), loaded_array});
}
return res;
}
std::unordered_map<std::string, array> load_safetensors(
const std::string& file,
StreamOrDevice s) {
return load_safetensors(std::make_shared<io::FileReader>(file), s);
}
/** Save array to out stream in .npy format */
void save_safetensors(
std::shared_ptr<io::Writer> out_stream,
std::unordered_map<std::string, array> a,
std::optional<bool> retain_graph_) {
////////////////////////////////////////////////////////
// Check file
if (!out_stream->good() || !out_stream->is_open()) {
throw std::runtime_error(
"[save_safetensors] Failed to open " + out_stream->label());
}
////////////////////////////////////////////////////////
// Check array map
json parent;
parent["__metadata__"] = json::object({
{"format", "mlx"},
});
size_t offset = 0;
for (auto& [key, arr] : a) {
arr.eval(retain_graph_.value_or(arr.is_tracer()));
if (arr.nbytes() == 0) {
throw std::invalid_argument(
"[save_safetensors] cannot serialize an empty array key: " + key);
}
if (!arr.flags().contiguous) {
throw std::invalid_argument(
"[save_safetensors] cannot serialize a non-contiguous array key: " +
key);
}
json child;
child["dtype"] = dtype_to_safetensor_str(arr.dtype());
child["shape"] = arr.shape();
child["data_offsets"] = std::vector<size_t>{offset, offset + arr.nbytes()};
parent[key] = child;
offset += arr.nbytes();
}
auto header = parent.dump();
uint64_t header_len = header.length();
out_stream->write(reinterpret_cast<char*>(&header_len), 8);
out_stream->write(header.c_str(), header_len);
for (auto& [key, arr] : a) {
out_stream->write(arr.data<char>(), arr.nbytes());
}
}
void save_safetensors(
const std::string& file_,
std::unordered_map<std::string, array> a,
std::optional<bool> retain_graph) {
// Open and check file
std::string file = file_;
// Add .safetensors to file name if it is not there
if (file.length() < 12 ||
file.substr(file.length() - 12, 12) != ".safetensors")
file += ".safetensors";
// Serialize array
save_safetensors(std::make_shared<io::FileWriter>(file), a, retain_graph);
}
} // namespace mlx::core

32
mlx/io/safetensor.h Normal file
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@ -0,0 +1,32 @@
// Copyright © 2023 Apple Inc.
#pragma once
#include <json.hpp>
#include "mlx/io/load.h"
#include "mlx/ops.h"
#include "mlx/primitives.h"
using json = nlohmann::json;
namespace mlx::core {
#define ST_F16 "F16"
#define ST_BF16 "BF16"
#define ST_F32 "F32"
#define ST_BOOL "BOOL"
#define ST_I8 "I8"
#define ST_I16 "I16"
#define ST_I32 "I32"
#define ST_I64 "I64"
#define ST_U8 "U8"
#define ST_U16 "U16"
#define ST_U32 "U32"
#define ST_U64 "U64"
// Note: Complex numbers aren't in the spec yet so this could change -
// https://github.com/huggingface/safetensors/issues/389
#define ST_C64 "C64"
} // namespace mlx::core

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@ -7,7 +7,7 @@
#include "array.h"
#include "device.h"
#include "load.h"
#include "io/load.h"
#include "stream.h"
namespace mlx::core {
@ -1057,4 +1057,20 @@ array dequantize(
int bits = 4,
StreamOrDevice s = {});
/** Load array map from .safetensors file format */
std::unordered_map<std::string, array> load_safetensors(
std::shared_ptr<io::Reader> in_stream,
StreamOrDevice s = {});
std::unordered_map<std::string, array> load_safetensors(
const std::string& file,
StreamOrDevice s = {});
void save_safetensors(
std::shared_ptr<io::Writer> in_stream,
std::unordered_map<std::string, array>,
std::optional<bool> retain_graph = std::nullopt);
void save_safetensors(
const std::string& file,
std::unordered_map<std::string, array>,
std::optional<bool> retain_graph = std::nullopt);
} // namespace mlx::core

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@ -4,7 +4,7 @@
#include "array.h"
#include "device.h"
#include "load.h"
#include "io/load.h"
#include "stream.h"
#define DEFINE_GRADS() \

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@ -6,12 +6,11 @@
#include <cstring>
#include <fstream>
#include <stdexcept>
#include <string>
#include <string_view>
#include <unordered_map>
#include <vector>
#include "mlx/load.h"
#include "mlx/io/load.h"
#include "mlx/ops.h"
#include "mlx/utils.h"
#include "python/src/load.h"
@ -161,40 +160,68 @@ class PyFileReader : public io::Reader {
py::object tell_func_;
};
DictOrArray mlx_load_helper(py::object file, StreamOrDevice s) {
py::module_ zipfile = py::module_::import("zipfile");
// Assume .npz file if it is zipped
if (is_zip_file(zipfile, file)) {
// Output dictionary filename in zip -> loaded array
std::unordered_map<std::string, array> array_dict;
// Create python ZipFile object
ZipFileWrapper zipfile_object(zipfile, file);
for (const std::string& st : zipfile_object.namelist()) {
// Open zip file as a python file stream
py::object sub_file = zipfile_object.open(st);
// Create array from python fille stream
auto arr = load(std::make_shared<PyFileReader>(sub_file), s);
// Remove .npy from file if it is there
auto key = st;
if (st.length() > 4 && st.substr(st.length() - 4, 4) == ".npy")
key = st.substr(0, st.length() - 4);
// Add array to dict
array_dict.insert({key, arr});
}
std::unordered_map<std::string, array> mlx_load_safetensor_helper(
py::object file,
StreamOrDevice s) {
if (py::isinstance<py::str>(file)) { // Assume .safetensors file path string
return {load_safetensors(py::cast<std::string>(file), s)};
} else if (is_istream_object(file)) {
// If we don't own the stream and it was passed to us, eval immediately
for (auto& [key, arr] : array_dict) {
auto arr = load_safetensors(std::make_shared<PyFileReader>(file), s);
{
py::gil_scoped_release gil;
arr.eval();
for (auto& [key, arr] : arr) {
arr.eval();
}
}
return {arr};
}
return {array_dict};
} else if (py::isinstance<py::str>(file)) { // Assume .npy file path string
throw std::invalid_argument(
"[load_safetensors] Input must be a file-like object, or string");
}
std::unordered_map<std::string, array> mlx_load_npz_helper(
py::object file,
StreamOrDevice s) {
py::module_ zipfile = py::module_::import("zipfile");
if (!is_zip_file(zipfile, file)) {
throw std::invalid_argument(
"[load_npz] Input must be a zip file or a file-like object that can be "
"opened with zipfile.ZipFile");
}
// Output dictionary filename in zip -> loaded array
std::unordered_map<std::string, array> array_dict;
// Create python ZipFile object
ZipFileWrapper zipfile_object(zipfile, file);
for (const std::string& st : zipfile_object.namelist()) {
// Open zip file as a python file stream
py::object sub_file = zipfile_object.open(st);
// Create array from python fille stream
auto arr = load(std::make_shared<PyFileReader>(sub_file), s);
// Remove .npy from file if it is there
auto key = st;
if (st.length() > 4 && st.substr(st.length() - 4, 4) == ".npy")
key = st.substr(0, st.length() - 4);
// Add array to dict
array_dict.insert({key, arr});
}
// If we don't own the stream and it was passed to us, eval immediately
for (auto& [key, arr] : array_dict) {
py::gil_scoped_release gil;
arr.eval();
}
return {array_dict};
}
array mlx_load_npy_helper(py::object file, StreamOrDevice s) {
if (py::isinstance<py::str>(file)) { // Assume .npy file path string
return {load(py::cast<std::string>(file), s)};
} else if (is_istream_object(file)) {
// If we don't own the stream and it was passed to us, eval immediately
@ -205,9 +232,41 @@ DictOrArray mlx_load_helper(py::object file, StreamOrDevice s) {
}
return {arr};
}
throw std::invalid_argument(
"[load] Input must be a file-like object, string, or pathlib.Path");
"[load_npy] Input must be a file-like object, or string");
}
DictOrArray mlx_load_helper(
py::object file,
std::optional<std::string> format,
StreamOrDevice s) {
if (!format.has_value()) {
std::string fname;
if (py::isinstance<py::str>(file)) {
fname = py::cast<std::string>(file);
} else if (is_istream_object(file)) {
fname = file.attr("name").cast<std::string>();
} else {
throw std::invalid_argument(
"[load] Input must be a file-like object, or string");
}
size_t ext = fname.find_last_of('.');
if (ext == std::string::npos) {
throw std::invalid_argument(
"[load] Could not infer file format from extension");
}
format.emplace(fname.substr(ext + 1));
}
if (format.value() == "safetensors") {
return mlx_load_safetensor_helper(file, s);
} else if (format.value() == "npz") {
return mlx_load_npz_helper(file, s);
} else if (format.value() == "npy") {
return mlx_load_npy_helper(file, s);
} else {
throw std::invalid_argument("[load] Unknown file format " + format.value());
}
}
///////////////////////////////////////////////////////////////////////////////
@ -305,7 +364,7 @@ void mlx_save_helper(
}
throw std::invalid_argument(
"[save] Input must be a file-like object, string, or pathlib.Path");
"[save] Input must be a file-like object, or string");
}
void mlx_savez_helper(
@ -361,3 +420,25 @@ void mlx_savez_helper(
return;
}
void mlx_save_safetensor_helper(
py::object file,
py::dict d,
std::optional<bool> retain_graph) {
auto arrays_map = d.cast<std::unordered_map<std::string, array>>();
if (py::isinstance<py::str>(file)) {
save_safetensors(py::cast<std::string>(file), arrays_map, retain_graph);
return;
} else if (is_ostream_object(file)) {
auto writer = std::make_shared<PyFileWriter>(file);
{
py::gil_scoped_release gil;
save_safetensors(writer, arrays_map, retain_graph);
}
return;
}
throw std::invalid_argument(
"[save_safetensors] Input must be a file-like object, or string");
}

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@ -3,6 +3,8 @@
#pragma once
#include <pybind11/pybind11.h>
#include <optional>
#include <string>
#include <unordered_map>
#include <variant>
#include "mlx/ops.h"
@ -12,7 +14,18 @@ using namespace mlx::core;
using DictOrArray = std::variant<array, std::unordered_map<std::string, array>>;
DictOrArray mlx_load_helper(py::object file, StreamOrDevice s);
std::unordered_map<std::string, array> mlx_load_safetensor_helper(
py::object file,
StreamOrDevice s);
void mlx_save_safetensor_helper(
py::object file,
py::dict d,
std::optional<bool> retain_graph = std::nullopt);
DictOrArray mlx_load_helper(
py::object file,
std::optional<std::string> format,
StreamOrDevice s);
void mlx_save_helper(
py::object file,
array a,

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@ -2867,11 +2867,9 @@ void init_ops(py::module_& m) {
Args:
file (str): File to which the array is saved
arr (array): Array to be saved.
retain_graph (bool, optional): Optional argument to retain graph
during array evaluation before saving. If not provided the graph
is retained if we are during a function transformation. Default:
None
retain_graph (bool, optional): Whether or not to retain the graph
during array evaluation. If left unspecified the graph is retained
only if saving is done in a function transformation. Default: ``None``
)pbdoc");
m.def(
"savez",
@ -2932,18 +2930,45 @@ void init_ops(py::module_& m) {
&mlx_load_helper,
"file"_a,
py::pos_only(),
"format"_a = none,
py::kw_only(),
"stream"_a = none,
R"pbdoc(
load(file: str, /, *, stream: Union[None, Stream, Device] = None) -> Union[array, Dict[str, array]]
load(file: str, /, format: Optional[str] = None, *, stream: Union[None, Stream, Device] = None) -> Union[array, Dict[str, array]]
Load array(s) from a binary file in ``.npy`` or ``.npz`` format.
Load array(s) from a binary file in ``.npy``, ``.npz``, or ``.safetensors`` format.
Args:
file (file, str): File in which the array is saved
file (file, str): File in which the array is saved.
format (str, optional): Format of the file. If ``None``, the format
is inferred from the file extension. Supported formats: ``npy``,
``npz``, and ``safetensors``. Default: ``None``.
Returns:
result (array, dict): The loaded array if ``.npy`` file or a dict mapping name to array if ``.npz`` file
result (array, dict):
A single array if loading from a ``.npy`` file or a dict mapping
names to arrays if loading from a ``.npz`` or ``.safetensors`` file.
)pbdoc");
m.def(
"save_safetensors",
&mlx_save_safetensor_helper,
"file"_a,
"arrays"_a,
py::pos_only(),
"retain_graph"_a = std::nullopt,
py::kw_only(),
R"pbdoc(
save_safetensors(file: str, arrays: Dict[str, array], /, retain_graph: Optional[bool] = None)
Save array(s) to a binary file in ``.safetensors`` format.
For more information on the format see https://huggingface.co/docs/safetensors/index.
Args:
file (file, str): File in which the array is saved>
arrays (dict(str, array)): The dictionary of names to arrays to be saved.
retain_graph (bool, optional): Whether or not to retain the graph
during array evaluation. If left unspecified the graph is retained
only if saving is done in a function transformation. Default: ``None``.
)pbdoc");
m.def(
"where",

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@ -64,6 +64,33 @@ class TestLoad(mlx_tests.MLXTestCase):
load_arr_mlx_npy = np.load(save_file_mlx)
self.assertTrue(np.array_equal(load_arr_mlx_npy, save_arr_npy))
def test_save_and_load_safetensors(self):
if not os.path.isdir(self.test_dir):
os.mkdir(self.test_dir)
for dt in self.dtypes + ["bfloat16"]:
with self.subTest(dtype=dt):
for i, shape in enumerate([(1,), (23,), (1024, 1024), (4, 6, 3, 1, 2)]):
with self.subTest(shape=shape):
save_file_mlx = os.path.join(
self.test_dir, f"mlx_{dt}_{i}_fs.safetensors"
)
save_dict = {
"test": mx.random.normal(shape=shape, dtype=getattr(mx, dt))
if dt in ["float32", "float16", "bfloat16"]
else mx.ones(shape, dtype=getattr(mx, dt))
}
with open(save_file_mlx, "wb") as f:
mx.save_safetensors(f, save_dict)
with open(save_file_mlx, "rb") as f:
load_dict = mx.load(f)
self.assertTrue("test" in load_dict)
self.assertTrue(
mx.array_equal(load_dict["test"], save_dict["test"])
)
def test_save_and_load_fs(self):
if not os.path.isdir(self.test_dir):

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@ -14,6 +14,26 @@ std::string get_temp_file(const std::string& name) {
return std::filesystem::temp_directory_path().append(name);
}
TEST_CASE("test save_safetensors") {
std::string file_path = get_temp_file("test_arr.safetensors");
auto map = std::unordered_map<std::string, array>();
map.insert({"test", array({1.0, 2.0, 3.0, 4.0})});
map.insert({"test2", ones({2, 2})});
save_safetensors(file_path, map);
auto safeDict = load_safetensors(file_path);
CHECK_EQ(safeDict.size(), 2);
CHECK_EQ(safeDict.count("test"), 1);
CHECK_EQ(safeDict.count("test2"), 1);
array test = safeDict.at("test");
CHECK_EQ(test.dtype(), float32);
CHECK_EQ(test.shape(), std::vector<int>({4}));
CHECK(array_equal(test, array({1.0, 2.0, 3.0, 4.0})).item<bool>());
array test2 = safeDict.at("test2");
CHECK_EQ(test2.dtype(), float32);
CHECK_EQ(test2.shape(), std::vector<int>({2, 2}));
CHECK(array_equal(test2, ones({2, 2})).item<bool>());
}
TEST_CASE("test single array serialization") {
// Basic test
{