Update for pyo3 0.21.

candle-examples/Cargo.toml

@@ -25,7 +25,7 @@ hf-hub = { workspace = true, features = ["tokio"] }
 image = { workspace = true }
 intel-mkl-src = { workspace = true, optional = true }
 num-traits = { workspace = true }
-pyo3 = { version = "0.20.0", features = ["auto-initialize"], optional = true }
+pyo3 = { version = "0.21.0", features = ["auto-initialize"], optional = true }
 rayon = { workspace = true }
 rubato = { version = "0.15.0", optional = true }
 safetensors = { workspace = true }

candle-pyo3/Cargo.toml

@@ -20,10 +20,10 @@ candle-nn = { workspace = true }
 candle-onnx = { workspace = true, optional = true }
 half = { workspace = true }
 intel-mkl-src = { workspace = true, optional = true }
-pyo3 = { version = "0.20.0", features = ["extension-module", "abi3-py38"] }
+pyo3 = { version = "0.21.0", features = ["extension-module", "abi3-py38"] }
 
 [build-dependencies]
-pyo3-build-config = "0.20"
+pyo3-build-config = "0.21"
 
 [features]
 default = []

candle-pyo3/py_src/candle/__init__.pyi

@@ -26,21 +26,21 @@ class i64(DType):
  pass
 
 @staticmethod
-def ones(*shape: Shape, dtype: Optional[DType] = None, device: Optional[Device] = None) -> Tensor:
+def ones(shape: Sequence[int], dtype: Optional[DType] = None, device: Optional[Device] = None) -> Tensor:
  """
  Creates a new tensor filled with ones.
  """
  pass
 
 @staticmethod
-def rand(*shape: Shape, device: Optional[Device] = None) -> Tensor:
+def rand(shape: Sequence[int], device: Optional[Device] = None) -> Tensor:
  """
  Creates a new tensor with random values.
  """
  pass
 
 @staticmethod
-def randn(*shape: Shape, device: Optional[Device] = None) -> Tensor:
+def randn(shape: Sequence[int], device: Optional[Device] = None) -> Tensor:
  """
  Creates a new tensor with random values from a normal distribution.
  """
@@ -67,7 +67,7 @@ class u8(DType):
  pass
 
 @staticmethod
-def zeros(*shape: Shape, dtype: Optional[DType] = None, device: Optional[Device] = None) -> Tensor:
+def zeros(shape: Sequence[int], dtype: Optional[DType] = None, device: Optional[Device] = None) -> Tensor:
  """
  Creates a new tensor filled with zeros.
  """
@@ -208,12 +208,6 @@ class Tensor:
  """
  pass
 
- def abs(self) -> Tensor:
- """
- Performs the `abs` operation on the tensor.
- """
- pass
-
  def argmax_keepdim(self, dim: int) -> Tensor:
  """
  Returns the indices of the maximum value(s) across the selected dimension.
@@ -232,7 +226,7 @@ class Tensor:
  """
  pass
 
- def broadcast_as(self, *shape: Shape) -> Tensor:
+ def broadcast_as(self, shape: Sequence[int]) -> Tensor:
  """
  Broadcasts the tensor to the given shape.
  """
@@ -244,7 +238,7 @@ class Tensor:
  """
  pass
 
- def broadcast_left(self, *shape: Shape) -> Tensor:
+ def broadcast_left(self, shape: Sequence[int]) -> Tensor:
  """
  Broadcasts the tensor to the given shape, adding new dimensions on the left.
  """
@@ -324,12 +318,6 @@ class Tensor:
  """
  pass
 
- def gather(self, index, dim):
- """
- Gathers values along an axis specified by dim.
- """
- pass
-
  def get(self, index: int) -> Tensor:
  """
  Gets the value at the specified index.
@@ -397,13 +385,6 @@ class Tensor:
  """
  pass
 
- @property
- def nelement(self) -> int:
- """
- Gets the tensor's element count.
- """
- pass
-
  def powf(self, p: float) -> Tensor:
  """
  Performs the `pow` operation on the tensor with the given exponent.
@@ -429,7 +410,7 @@ class Tensor:
  """
  pass
 
- def reshape(self, *shape: Shape) -> Tensor:
+ def reshape(self, shape: Sequence[int]) -> Tensor:
  """
  Reshapes the tensor to the given shape.
  """
@@ -491,12 +472,6 @@ class Tensor:
  """
  pass
 
- def to(self, *args, **kwargs) -> Tensor:
- """
- Performs Tensor dtype and/or device conversion.
- """
- pass
-
  def to_device(self, device: Union[str, Device]) -> Tensor:
  """
  Move the tensor to a new device.
@@ -509,12 +484,6 @@ class Tensor:
  """
  pass
 
- def to_torch(self) -> torch.Tensor:
- """
- Converts candle's tensor to pytorch's tensor
- """
- pass
-
  def transpose(self, dim1: int, dim2: int) -> Tensor:
  """
  Returns a tensor that is a transposed version of the input, the given dimensions are swapped.

candle-pyo3/py_src/candle/nn/__init__.pyi

@@ -0,0 +1,19 @@
+# Generated content DO NOT EDIT
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union, Sequence
+from os import PathLike
+from candle.typing import _ArrayLike, Device, Scalar, Index, Shape
+from candle import Tensor, DType, QTensor
+
+@staticmethod
+def silu(tensor: Tensor) -> Tensor:
+ """
+ Applies the Sigmoid Linear Unit (SiLU) function to a given tensor.
+ """
+ pass
+
+@staticmethod
+def softmax(tensor: Tensor, dim: int) -> Tensor:
+ """
+ Applies the Softmax function to a given tensor.#
+ """
+ pass

candle-pyo3/py_src/candle/utils/__init__.pyi

@@ -33,19 +33,15 @@ def has_mkl() -> bool:
  pass
 
 @staticmethod
-def load_ggml(
- path: Union[str, PathLike], device: Optional[Device] = None
-) -> Tuple[Dict[str, QTensor], Dict[str, Any], List[str]]:
+def load_ggml(path: Union[str, PathLike]) -> Tuple[Dict[str, QTensor], Dict[str, Any], List[str]]:
  """
  Load a GGML file. Returns a tuple of three objects: a dictionary mapping tensor names to tensors,
  a dictionary mapping hyperparameter names to hyperparameter values, and a vocabulary.
  """
  pass
 
 @staticmethod
-def load_gguf(
- path: Union[str, PathLike], device: Optional[Device] = None
-) -> Tuple[Dict[str, QTensor], Dict[str, Any]]:
+def load_gguf(path: Union[str, PathLike]) -> Tuple[Dict[str, QTensor], Dict[str, Any]]:
  """
  Loads a GGUF file. Returns a tuple of two dictionaries: the first maps tensor names to tensors,
  and the second maps metadata keys to metadata values.