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"""Functions for initializing the Julia environment and installing deps.""" | |
import sys | |
import subprocess | |
import warnings | |
from pathlib import Path | |
import os | |
from julia.api import JuliaError | |
from .version import __version__, __symbolic_regression_jl_version__ | |
juliainfo = None | |
julia_initialized = False | |
def _load_juliainfo(): | |
"""Execute julia.core.JuliaInfo.load(), and store as juliainfo.""" | |
global juliainfo | |
if juliainfo is None: | |
from julia.core import JuliaInfo | |
try: | |
juliainfo = JuliaInfo.load(julia="julia") | |
except FileNotFoundError: | |
env_path = os.environ["PATH"] | |
raise FileNotFoundError( | |
f"Julia is not installed in your PATH. Please install Julia and add it to your PATH.\n\nCurrent PATH: {env_path}", | |
) | |
return juliainfo | |
def _get_julia_env_dir(): | |
# Have to manually get env dir: | |
try: | |
julia_env_dir_str = subprocess.run( | |
["julia", "-e using Pkg; print(Pkg.envdir())"], | |
capture_output=True, | |
env=os.environ, | |
).stdout.decode() | |
except FileNotFoundError: | |
env_path = os.environ["PATH"] | |
raise FileNotFoundError( | |
f"Julia is not installed in your PATH. Please install Julia and add it to your PATH.\n\nCurrent PATH: {env_path}", | |
) | |
return Path(julia_env_dir_str) | |
def _set_julia_project_env(julia_project, is_shared): | |
if is_shared: | |
if is_julia_version_greater_eq(version=(1, 7, 0)): | |
os.environ["JULIA_PROJECT"] = "@" + str(julia_project) | |
else: | |
julia_env_dir = _get_julia_env_dir() | |
os.environ["JULIA_PROJECT"] = str(julia_env_dir / julia_project) | |
else: | |
os.environ["JULIA_PROJECT"] = str(julia_project) | |
def _get_io_arg(quiet): | |
io = "devnull" if quiet else "stderr" | |
io_arg = f"io={io}" if is_julia_version_greater_eq(version=(1, 6, 0)) else "" | |
return io_arg | |
def install(julia_project=None, quiet=False): # pragma: no cover | |
""" | |
Install PyCall.jl and all required dependencies for SymbolicRegression.jl. | |
Also updates the local Julia registry. | |
""" | |
import julia | |
_julia_version_assertion() | |
# Set JULIA_PROJECT so that we install in the pysr environment | |
processed_julia_project, is_shared = _process_julia_project(julia_project) | |
_set_julia_project_env(processed_julia_project, is_shared) | |
julia.install(quiet=quiet) | |
Main = init_julia(julia_project, quiet=quiet) | |
io_arg = _get_io_arg(quiet) | |
if is_shared: | |
# Install SymbolicRegression.jl: | |
_add_sr_to_julia_project(Main, io_arg) | |
Main.eval("using Pkg") | |
Main.eval(f"Pkg.instantiate({io_arg})") | |
Main.eval(f"Pkg.precompile({io_arg})") | |
if not quiet: | |
warnings.warn( | |
"It is recommended to restart Python after installing PySR's dependencies," | |
" so that the Julia environment is properly initialized." | |
) | |
def _import_error(): | |
raise ImportError( | |
""" | |
Required dependencies are not installed or built. Run the following code in the Python REPL: | |
>>> import pysr | |
>>> pysr.install() | |
""" | |
) | |
def _process_julia_project(julia_project): | |
if julia_project is None: | |
is_shared = True | |
processed_julia_project = f"pysr-{__version__}" | |
elif julia_project[0] == "@": | |
is_shared = True | |
processed_julia_project = julia_project[1:] | |
else: | |
is_shared = False | |
processed_julia_project = Path(julia_project) | |
return processed_julia_project, is_shared | |
def is_julia_version_greater_eq(juliainfo=None, version=(1, 6, 0)): | |
"""Check if Julia version is greater than specified version.""" | |
if juliainfo is None: | |
juliainfo = _load_juliainfo() | |
current_version = ( | |
juliainfo.version_major, | |
juliainfo.version_minor, | |
juliainfo.version_patch, | |
) | |
return current_version >= version | |
def _check_for_conflicting_libraries(): # pragma: no cover | |
"""Check whether there are conflicting modules, and display warnings.""" | |
# See https://github.com/pytorch/pytorch/issues/78829: importing | |
# pytorch before running `pysr.fit` causes a segfault. | |
torch_is_loaded = "torch" in sys.modules | |
if torch_is_loaded: | |
warnings.warn( | |
"`torch` was loaded before the Julia instance started. " | |
"This may cause a segfault when running `PySRRegressor.fit`. " | |
"To avoid this, please run `pysr.julia_helpers.init_julia()` *before* " | |
"importing `torch`. " | |
"For updates, see https://github.com/pytorch/pytorch/issues/78829" | |
) | |
def init_julia(julia_project=None, quiet=False): | |
"""Initialize julia binary, turning off compiled modules if needed.""" | |
global julia_initialized | |
if not julia_initialized: | |
_check_for_conflicting_libraries() | |
from julia.core import JuliaInfo, UnsupportedPythonError | |
_julia_version_assertion() | |
processed_julia_project, is_shared = _process_julia_project(julia_project) | |
_set_julia_project_env(processed_julia_project, is_shared) | |
try: | |
info = JuliaInfo.load(julia="julia") | |
except FileNotFoundError: | |
env_path = os.environ["PATH"] | |
raise FileNotFoundError( | |
f"Julia is not installed in your PATH. Please install Julia and add it to your PATH.\n\nCurrent PATH: {env_path}", | |
) | |
if not info.is_pycall_built(): | |
_import_error() | |
Main = None | |
try: | |
from julia import Main as _Main | |
Main = _Main | |
except UnsupportedPythonError: | |
# Static python binary, so we turn off pre-compiled modules. | |
from julia.core import Julia | |
jl = Julia(compiled_modules=False) | |
from julia import Main as _Main | |
Main = _Main | |
if julia_initialized: | |
Main.eval("using Pkg") | |
io_arg = _get_io_arg(quiet) | |
# Can't pass IO to Julia call as it evaluates to PyObject, so just directly | |
# use Main.eval: | |
Main.eval( | |
f'Pkg.activate("{_escape_filename(processed_julia_project)}",' | |
f"shared = Bool({int(is_shared)}), " | |
f"{io_arg})" | |
) | |
julia_initialized = True | |
return Main | |
def _add_sr_to_julia_project(Main, io_arg): | |
Main.eval("using Pkg") | |
Main.sr_spec = Main.PackageSpec( | |
name="SymbolicRegression", | |
url="https://github.com/MilesCranmer/SymbolicRegression.jl", | |
rev="v" + __symbolic_regression_jl_version__, | |
) | |
Main.clustermanagers_spec = Main.PackageSpec( | |
name="ClusterManagers", | |
url="https://github.com/JuliaParallel/ClusterManagers.jl", | |
rev="14e7302f068794099344d5d93f71979aaf4fbeb3", | |
) | |
Main.eval(f"Pkg.add([sr_spec, clustermanagers_spec], {io_arg})") | |
def _escape_filename(filename): | |
"""Turn a path into a string with correctly escaped backslashes.""" | |
str_repr = str(filename) | |
str_repr = str_repr.replace("\\", "\\\\") | |
return str_repr | |
def _julia_version_assertion(): | |
if not is_julia_version_greater_eq(version=(1, 6, 0)): | |
raise NotImplementedError( | |
"PySR requires Julia 1.6.0 or greater. " | |
"Please update your Julia installation." | |
) | |
def _backend_version_assertion(Main): | |
try: | |
backend_version = Main.eval("string(SymbolicRegression.PACKAGE_VERSION)") | |
expected_backend_version = __symbolic_regression_jl_version__ | |
if backend_version != expected_backend_version: # pragma: no cover | |
warnings.warn( | |
f"PySR backend (SymbolicRegression.jl) version {backend_version} " | |
"does not match expected version {expected_backend_version}. " | |
"Things may break. " | |
"Please update your PySR installation with " | |
"`python -c 'import pysr; pysr.install()'`." | |
) | |
except JuliaError: # pragma: no cover | |
warnings.warn( | |
"You seem to have an outdated version of SymbolicRegression.jl. " | |
"Things may break. " | |
"Please update your PySR installation with " | |
"`python -c 'import pysr; pysr.install()'`." | |
) | |
def _load_cluster_manager(Main, cluster_manager): | |
Main.eval(f"import ClusterManagers: addprocs_{cluster_manager}") | |
return Main.eval(f"addprocs_{cluster_manager}") | |
def _update_julia_project(Main, is_shared, io_arg): | |
try: | |
if is_shared: | |
_add_sr_to_julia_project(Main, io_arg) | |
Main.eval(f"Pkg.resolve({io_arg})") | |
except (JuliaError, RuntimeError) as e: | |
raise ImportError(_import_error()) from e | |
def _load_backend(Main): | |
try: | |
# Load namespace, so that various internal operators work: | |
Main.eval("using SymbolicRegression") | |
except (JuliaError, RuntimeError) as e: | |
raise ImportError(_import_error()) from e | |
_backend_version_assertion(Main) | |
# Load Julia package SymbolicRegression.jl | |
from julia import SymbolicRegression | |
return SymbolicRegression | |