Initial import: grid-bot — grid trading bot for BTC-USDT on Cifra Markets

2026-09-24 13:22:23 +07:00
commit 642cc11a9f
18968 changed files with 5683248 additions and 0 deletions
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+# mypy: allow-untyped-defs
+"""JIT-related state.
+
+This module stores various pieces of Python-global state relating to the JIT.
+
+This is not intended to be imported directly; please the exposed
+functionalities in `torch.jit`.
+"""
+
+import os
+import weakref
+from typing import Any
+
+import torch
+
+
+class EnabledProxy:
+    """Stores whether the JIT is enabled or not.
+
+    This is just a wrapper for a bool, so that we get reference semantics
+    """
+
+    def __init__(self) -> None:
+        self.enabled = self.parse_env(
+            "PYTORCH_JIT", True, "> Using PyTorch JIT", "> PyTorch JIT DISABLED"
+        )
+
+    def parse_env(self, name, default, true_message, false_message):
+        value = os.environ.get(name)
+        if value is None:
+            return default
+        if value.lower() in {"1", "true", "yes"}:
+            return True
+        elif value.lower() in {"0", "false", "no"}:
+            return False
+        if value == "1v":
+            print(true_message)
+            return True
+        elif value == "0v":
+            print(false_message)
+            return False
+        raise ValueError(f"Unknown setting of {name}. Try using 0 or 1.")
+
+    def __bool__(self) -> bool:
+        return self.enabled
+
+
+_enabled = EnabledProxy()
+
+
+def disable() -> None:
+    _enabled.enabled = False
+
+
+def enable() -> None:
+    _enabled.enabled = True
+
+
+# The Python CompilationUnit. All functions and modules defined in Python will
+# live in here. It's defined in Python because doing in cpp creates static
+# destruction order issues.
+_python_cu = torch._C.CompilationUnit()
+
+
+# python class => ScriptClass mapping
+_script_classes: dict[type[Any], type[Any]] = {}
+_name_to_pyclass: dict[str, type[Any]] = {}
+
+
+def _add_script_class(python_class, script_class) -> None:
+    _script_classes[python_class] = script_class
+    _name_to_pyclass[script_class.qualified_name()] = python_class
+
+
+def _get_script_class(python_class):
+    override = getattr(python_class, "_jit_override_qualname", None)
+    if override is not None:
+        python_class = _get_python_class(override)
+    return _script_classes.get(python_class)
+
+
+def _get_python_class(qualified_name):
+    return _name_to_pyclass.get(qualified_name)
+
+
+def _clear_class_state() -> None:
+    _script_classes.clear()
+    _name_to_pyclass.clear()
+
+
+# Caching: we currently cache compilation of free functions and overloaded functions.
+# To cache free functions we hold a weak ref to the function object and
+# map to the compiled fn's qualified name.
+# To cache overloaded functions we hold a weak ref to the function obj and
+# map to all of its overloaded compiled fns.
+# In the future we could consider caching more types of objects so that
+# aliasing is preserved across separate compilations of the same object.
+
+_jit_caching_layer: weakref.WeakKeyDictionary = weakref.WeakKeyDictionary()
+_jit_function_overload_caching: weakref.WeakKeyDictionary = weakref.WeakKeyDictionary()
+
+
+def _try_get_jit_cached_overloads(key):
+    qual_names = _jit_function_overload_caching.get(key, None)
+    if qual_names:
+        return [_python_cu.find_function(qual_name) for qual_name in qual_names]
+    else:
+        return None
+
+
+def _set_jit_overload_cache(key, compiled_fns) -> None:
+    _jit_function_overload_caching[key] = [fn.qualified_name for fn in compiled_fns]
+
+
+def _try_get_jit_cached_function(key):
+    if getattr(key, "__disable_jit_function_caching__", False) is True:
+        return None
+    qual_name = _jit_caching_layer.get(key, None)
+    if qual_name:
+        return _python_cu.find_function(qual_name)
+    else:
+        return None
+
+
+def _set_jit_function_cache(key, value) -> None:
+    # only free functions currently supported
+    if not isinstance(value, torch.jit.ScriptFunction):
+        raise AssertionError(f"Expected ScriptFunction, got {type(value)}")
+    _jit_caching_layer[key] = value.qualified_name