chore: import upstream snapshot with attribution

2026-07-13 13:30:25 +08:00
commit f19b2512d7
562 changed files with 38082 additions and 0 deletions
@@ -0,0 +1,89 @@
+import numpy as np
+
+
+class Tensor(object):
+    """
+    a base class for tensor object
+    """
+    __array_ufunc__ = None
+
+    def __init__(self, value, function=None):
+        """
+        construct Tensor object
+        Parameters
+        ----------
+        value : array_like
+            value of this tensor
+        function : Function
+            function output this tensor
+        """
+        if not isinstance(value, (int, float, np.number, np.ndarray)):
+            raise TypeError(
+                "Unsupported class for Tensor: {}".format(type(value))
+            )
+        self.value = value
+        self.function = function
+
+    def __format__(self, *args, **kwargs):
+        return self.__repr__()
+
+    def __repr__(self):
+        if isinstance(self.value, np.ndarray):
+            return (
+                "{0}(shape={1.shape}, dtype={1.dtype})"
+                .format(self.__class__.__name__, self.value)
+            )
+        else:
+            return (
+                "{0}(value={1})".format(self.__class__.__name__, self.value)
+            )
+
+    @property
+    def ndim(self):
+        if hasattr(self.value, "ndim"):
+            return self.value.ndim
+        else:
+            return 0
+
+    @property
+    def shape(self):
+        if hasattr(self.value, "shape"):
+            return self.value.shape
+        else:
+            return ()
+
+    @property
+    def size(self):
+        if hasattr(self.value, "size"):
+            return self.value.size
+        else:
+            return 1
+
+    def backward(self, delta=1, **kwargs):
+        """
+        back-propagate error
+        Parameters
+        ----------
+        delta : array_like
+            derivative with respect to this array
+        """
+        if isinstance(delta, np.ndarray):
+            if delta.shape != self.shape:
+                raise ValueError(
+                    "shapes {} and {} not aligned"
+                    .format(delta.shape, self.shape)
+                )
+        elif isinstance(delta, (int, float, np.number)):
+            if self.shape != ():
+                raise ValueError(
+                    "delta must be np.ndarray"
+                )
+        else:
+            raise TypeError(
+                "unsupported class for delta"
+            )
+        self._backward(delta, **kwargs)
+
+    def _backward(self, delta, **kwargs):
+        if hasattr(self.function, "backward"):
+            self.function.backward(delta, **kwargs)