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
+import sys
+
+import torch._C
+import torch.cuda
+from torch.backends import (
+    _get_fp32_precision_getter,
+    _set_fp32_precision_setter,
+    PropModule,
+)
+
+
+try:
+    from torch._C import _cudnn
+except ImportError:
+    # Uses of all the functions below should be guarded by torch.backends.cudnn.is_available(),
+    # so it's safe to not emit any checks here.
+    _cudnn = None  # type: ignore[assignment]
+
+
+def get_cudnn_mode(mode):
+    if mode == "RNN_RELU":
+        # pyrefly: ignore [missing-attribute]
+        return int(_cudnn.RNNMode.rnn_relu)
+    elif mode == "RNN_TANH":
+        # pyrefly: ignore [missing-attribute]
+        return int(_cudnn.RNNMode.rnn_tanh)
+    elif mode == "LSTM":
+        # pyrefly: ignore [missing-attribute]
+        return int(_cudnn.RNNMode.lstm)
+    elif mode == "GRU":
+        # pyrefly: ignore [missing-attribute]
+        return int(_cudnn.RNNMode.gru)
+    else:
+        raise ValueError(f"Unknown mode: {mode}")  # noqa: TRY002
+
+
+# NB: We don't actually need this class anymore (in fact, we could serialize the
+# dropout state for even better reproducibility), but it is kept for backwards
+# compatibility for old models.
+class Unserializable:
+    def __init__(self, inner):
+        self.inner = inner
+
+    def get(self):
+        return self.inner
+
+    def __getstate__(self):
+        return "<unserializable>"
+
+    def __setstate__(self, state):
+        self.inner = None
+
+
+# we would like to use ContextProp from backends here but the
+# frozen flags appears to be overzealous
+class ContextProp:
+    def __init__(self, getter, setter):
+        self.getter = getter
+        self.setter = setter
+
+    def __get__(self, obj, objtype):
+        return self.getter()
+
+    def __set__(self, obj, val):
+        self.setter(val)
+
+
+def init_dropout_state(dropout, train, dropout_seed, dropout_state):
+    dropout_desc_name = "desc_" + str(torch.cuda.current_device())
+    dropout_p = dropout if train else 0
+    if (dropout_desc_name not in dropout_state) or (
+        dropout_state[dropout_desc_name].get() is None
+    ):
+        if dropout_p == 0:
+            dropout_state[dropout_desc_name] = Unserializable(None)
+        else:
+            dropout_state[dropout_desc_name] = Unserializable(
+                torch._cudnn_init_dropout_state(  # type: ignore[call-arg]
+                    dropout_p,
+                    train,
+                    dropout_seed,
+                    # pyrefly: ignore [unexpected-keyword]
+                    self_ty=torch.uint8,
+                    device=torch.device("cuda"),
+                )
+            )
+    dropout_ts = dropout_state[dropout_desc_name].get()
+    return dropout_ts
+
+
+class CudnnRNNModule(PropModule):
+    def __init__(self, m, name):
+        super().__init__(m, name)
+        self.m.Unserializable = Unserializable
+        self.m.get_cudnn_mode = get_cudnn_mode
+        self.m.init_dropout_state = init_dropout_state
+
+    @staticmethod
+    def init_dropout_state(dropout, train, dropout_seed, dropout_state):
+        dropout_desc_name = "desc_" + str(torch.cuda.current_device())
+        dropout_p = dropout if train else 0
+        if (dropout_desc_name not in dropout_state) or (
+            dropout_state[dropout_desc_name].get() is None
+        ):
+            if dropout_p == 0:
+                dropout_state[dropout_desc_name] = Unserializable(None)
+            else:
+                dropout_state[dropout_desc_name] = Unserializable(
+                    torch._cudnn_init_dropout_state(  # type: ignore[call-arg]
+                        dropout_p,
+                        train,
+                        dropout_seed,
+                        # pyrefly: ignore [unexpected-keyword]
+                        self_ty=torch.uint8,
+                        device=torch.device("cuda"),
+                    )
+                )
+        dropout_ts = dropout_state[dropout_desc_name].get()
+        return dropout_ts
+
+    fp32_precision = ContextProp(
+        _get_fp32_precision_getter("cuda", "rnn"),
+        _set_fp32_precision_setter("cuda", "rnn"),
+    )
+
+
+sys.modules[__name__] = CudnnRNNModule(sys.modules[__name__], __name__)