Initial import: grid-bot — grid trading bot for BTC-USDT on Cifra Markets
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# Generated content DO NOT EDIT
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@staticmethod
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def deserialize(bytes):
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"""
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Opens a safetensors lazily and returns tensors as asked
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Args:
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data (`bytes`):
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The byte content of a file
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Returns:
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(`List[str, Dict[str, Dict[str, any]]]`):
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The deserialized content is like:
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[("tensor_name", {"shape": [2, 3], "dtype": "F32", "data": b"\0\0.." }), (...)]
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"""
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pass
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@staticmethod
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def serialize(tensor_dict, metadata=None):
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"""
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Serializes raw data.
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Args:
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tensor_dict (`Dict[str, Dict[Any]]`):
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The tensor dict is like:
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{"tensor_name": {"dtype": "F32", "shape": [2, 3], "data": b"\0\0"}}
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metadata (`Dict[str, str]`, *optional*):
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The optional purely text annotations
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Returns:
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(`bytes`):
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The serialized content.
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"""
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pass
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@staticmethod
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def serialize_file(tensor_dict, filename, metadata=None):
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"""
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Serializes raw data into file.
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Args:
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tensor_dict (`Dict[str, Dict[Any]]`):
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The tensor dict is like:
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{"tensor_name": {"dtype": "F32", "shape": [2, 3], "data": b"\0\0"}}
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filename (`str`, or `os.PathLike`):
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The name of the file to write into.
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metadata (`Dict[str, str]`, *optional*):
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The optional purely text annotations
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Returns:
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(`NoneType`):
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On success return None
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"""
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pass
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class safe_open:
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"""
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Opens a safetensors lazily and returns tensors as asked
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Args:
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filename (`str`, or `os.PathLike`):
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The filename to open
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framework (`str`):
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The framework you want you tensors in. Supported values:
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`pt`, `tf`, `flax`, `numpy`.
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device (`str`, defaults to `"cpu"`):
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The device on which you want the tensors.
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"""
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def __init__(self, filename, framework, device=...):
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pass
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def __enter__(self):
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"""
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Start the context manager
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"""
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pass
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def __exit__(self, _exc_type, _exc_value, _traceback):
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"""
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Exits the context manager
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"""
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pass
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def get_slice(self, name):
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"""
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Returns a full slice view object
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Args:
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name (`str`):
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The name of the tensor you want
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Returns:
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(`PySafeSlice`):
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A dummy object you can slice into to get a real tensor
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Example:
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```python
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from safetensors import safe_open
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with safe_open("model.safetensors", framework="pt", device=0) as f:
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tensor_part = f.get_slice("embedding")[:, ::8]
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```
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"""
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pass
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def get_tensor(self, name):
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"""
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Returns a full tensor
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Args:
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name (`str`):
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The name of the tensor you want
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Returns:
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(`Tensor`):
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The tensor in the framework you opened the file for.
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Example:
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```python
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from safetensors import safe_open
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with safe_open("model.safetensors", framework="pt", device=0) as f:
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tensor = f.get_tensor("embedding")
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```
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"""
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pass
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def keys(self):
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"""
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Returns the names of the tensors in the file.
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Returns:
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(`List[str]`):
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The name of the tensors contained in that file
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"""
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pass
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def metadata(self):
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"""
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Return the special non tensor information in the header
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Returns:
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(`Dict[str, str]`):
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The freeform metadata.
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"""
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pass
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def offset_keys(self):
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"""
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Returns the names of the tensors in the file, ordered by offset.
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Returns:
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(`List[str]`):
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The name of the tensors contained in that file
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"""
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pass
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class SafetensorError(Exception):
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"""
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Custom Python Exception for Safetensor errors.
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"""
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