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

2026-09-24 13:22:23 +07:00
commit 642cc11a9f
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+# mypy: allow-untyped-defs
+import contextlib
+
+import torch
+
+
+# Common testing utilities for use in public testing APIs.
+# NB: these should all be importable without optional dependencies
+# (like numpy and expecttest).
+
+
+def wrapper_set_seed(op, *args, **kwargs):
+    """Wrapper to set seed manually for some functions like dropout
+    See: https://github.com/pytorch/pytorch/pull/62315#issuecomment-896143189 for more details.
+    """
+    with freeze_rng_state():
+        torch.manual_seed(42)
+        output = op(*args, **kwargs)
+
+        if isinstance(output, torch.Tensor) and output.device.type == "lazy":
+            # We need to call mark step inside freeze_rng_state so that numerics
+            # match eager execution
+            torch._lazy.mark_step()  # type: ignore[attr-defined]
+
+        return output
+
+
+@contextlib.contextmanager
+def freeze_rng_state():
+    # no_dispatch needed for test_composite_compliance
+    # Some OpInfos use freeze_rng_state for rng determinism, but
+    # test_composite_compliance overrides dispatch for all torch functions
+    # which we need to disable to get and set rng state
+    with torch.utils._mode_utils.no_dispatch(), torch._C._DisableFuncTorch():
+        rng_state = torch.get_rng_state()
+        if torch.accelerator.is_available():
+            accelerator = torch.accelerator.current_accelerator(check_available=True)
+            if accelerator is not None:
+                accelerator_rng_state = torch.get_device_module(
+                    accelerator.type
+                ).get_rng_state()
+    try:
+        yield
+    finally:
+        # Modes are not happy with torch.cuda.set_rng_state
+        # because it clones the state (which could produce a Tensor Subclass)
+        # and then grabs the new tensor's data pointer in generator.set_state.
+        #
+        # In the long run torch.cuda.set_rng_state should probably be
+        # an operator.
+        #
+        # NB: Mode disable is to avoid running cross-ref tests on this seeding
+        with torch.utils._mode_utils.no_dispatch(), torch._C._DisableFuncTorch():
+            if torch.accelerator.is_available():
+                accelerator = torch.accelerator.current_accelerator(
+                    check_available=True
+                )
+                if accelerator is not None:
+                    torch.get_device_module(accelerator.type).set_rng_state(
+                        accelerator_rng_state  # type: ignore[possibly-undefined]
+                    )
+            torch.set_rng_state(rng_state)