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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+"""
+Utilities for converting data types into structured JSON for dumping.
+"""
+
+import inspect
+import os
+import traceback
+from collections.abc import Sequence
+from typing import Any
+
+import torch._logging._internal
+
+
+INTERN_TABLE: dict[str, int] = {}
+
+
+DUMPED_FILES: set[str] = set()
+
+
+def intern_string(s: str | None) -> int:
+    if s is None:
+        return -1
+
+    r = INTERN_TABLE.get(s)
+    if r is None:
+        r = len(INTERN_TABLE)
+        INTERN_TABLE[s] = r
+        torch._logging._internal.trace_structured(
+            "str", lambda: (s, r), suppress_context=True
+        )
+    return r
+
+
+def dump_file(filename: str) -> None:
+    if "eval_with_key" not in filename:
+        return
+    if filename in DUMPED_FILES:
+        return
+    DUMPED_FILES.add(filename)
+    from torch.fx.graph_module import _loader
+
+    torch._logging._internal.trace_structured(
+        "dump_file",
+        metadata_fn=lambda: {
+            "name": filename,
+        },
+        payload_fn=lambda: _loader.get_source(filename),
+    )
+
+
+def from_traceback(tb: Sequence[traceback.FrameSummary]) -> list[dict[str, Any]]:
+    # dict naming convention here coincides with
+    # python/combined_traceback.cpp
+    r = [
+        {
+            "line": frame.lineno,
+            "name": frame.name,
+            "filename": intern_string(frame.filename),
+            "loc": frame.line,
+        }
+        for frame in tb
+    ]
+    return r
+
+
+def get_user_stack(num_frames: int) -> list[dict[str, Any]]:
+    from torch._guards import TracingContext
+    from torch.utils._traceback import CapturedTraceback
+
+    user_tb = TracingContext.extract_stack()
+    if user_tb:
+        return from_traceback(user_tb[-1 * num_frames :])
+
+    tb = CapturedTraceback.extract().summary()
+
+    # Filter out frames that are within the torch/ codebase
+    torch_filepath = os.path.dirname(inspect.getfile(torch)) + os.path.sep
+    for i, frame in enumerate(reversed(tb)):
+        if torch_filepath not in frame.filename:
+            # Only display `num_frames` frames in the traceback
+            filtered_tb = tb[len(tb) - i - num_frames : len(tb) - i]
+            return from_traceback(filtered_tb)
+
+    return from_traceback(tb[-1 * num_frames :])
+
+
+def get_framework_stack(
+    num_frames: int = 25, cpp: bool = False
+) -> list[dict[str, Any]]:
+    """
+    Returns the traceback for the user stack and the framework stack
+    """
+    from torch.fx.experimental.symbolic_shapes import uninteresting_files
+    from torch.utils._traceback import CapturedTraceback
+
+    tb = CapturedTraceback.extract(cpp=cpp).summary()
+    tb = [
+        frame
+        for frame in tb
+        if (
+            (
+                frame.filename.endswith(".py")
+                and frame.filename not in uninteresting_files()
+            )
+            or ("at::" in frame.name or "torch::" in frame.name)
+        )
+    ]
+
+    return from_traceback(tb[-1 * num_frames :])