File size: 5,295 Bytes
ae9e4fe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 | from .backend import xp, to_device
def _reduce_grad(grad, shape):
while grad.ndim > len(shape):
grad = grad.sum(axis=0)
for i in range(len(shape)):
if shape[i] == 1 and grad.shape[i] != 1:
grad = grad.sum(axis=i, keepdims=True)
return grad.reshape(shape)
class Tensor:
def __init__(self, data, _children=(), _op=""):
if isinstance(data, Tensor):
data = data.data
self.data = to_device(data)
self.grad = xp.zeros_like(self.data)
self._backward = lambda: None
self._prev = set(_children)
self._op = _op
@property
def shape(self):
return self.data.shape
@property
def ndim(self):
return self.data.ndim
def __repr__(self):
return f"Tensor(shape={self.data.shape}, op={self._op or 'leaf'})"
def add(self, other):
other = other if isinstance(other, Tensor) else Tensor(other)
out = Tensor(self.data + other.data, (self, other), "add")
def _backward():
self.grad = self.grad + _reduce_grad(out.grad, self.data.shape)
other.grad = other.grad + _reduce_grad(out.grad, other.data.shape)
out._backward = _backward
return out
def mul(self, other):
other = other if isinstance(other, Tensor) else Tensor(other)
out = Tensor(self.data * other.data, (self, other), "mul")
def _backward():
self.grad = self.grad + _reduce_grad(out.grad * other.data, self.data.shape)
other.grad = other.grad + _reduce_grad(out.grad * self.data, other.data.shape)
out._backward = _backward
return out
def matmul(self, other):
other = other if isinstance(other, Tensor) else Tensor(other)
out = Tensor(self.data @ other.data, (self, other), "matmul")
def _backward():
ga = out.grad @ xp.swapaxes(other.data, -1, -2)
gb = xp.swapaxes(self.data, -1, -2) @ out.grad
self.grad = self.grad + _reduce_grad(ga, self.data.shape)
other.grad = other.grad + _reduce_grad(gb, other.data.shape)
out._backward = _backward
return out
def reshape(self, *shape):
if len(shape) == 1 and isinstance(shape[0], (tuple, list)):
shape = tuple(shape[0])
out = Tensor(self.data.reshape(shape), (self,), "reshape")
def _backward():
self.grad = self.grad + out.grad.reshape(self.data.shape)
out._backward = _backward
return out
def transpose(self, axes=None):
out = Tensor(xp.transpose(self.data, axes), (self,), "transpose")
def _backward():
if axes is None:
self.grad = self.grad + xp.transpose(out.grad)
else:
inv = [0] * len(axes)
for i, a in enumerate(axes):
inv[a] = i
self.grad = self.grad + xp.transpose(out.grad, tuple(inv))
out._backward = _backward
return out
def sum(self, axis=None, keepdims=False):
out = Tensor(self.data.sum(axis=axis, keepdims=keepdims), (self,), "sum")
def _backward():
g = out.grad
if axis is not None and not keepdims:
ax = axis if isinstance(axis, tuple) else (axis,)
for a in sorted(a % self.data.ndim for a in ax):
g = xp.expand_dims(g, a)
self.grad = self.grad + xp.broadcast_to(g, self.data.shape)
out._backward = _backward
return out
def gather(self, index):
idx = index.data if isinstance(index, Tensor) else to_device(index)
idx = idx.astype(xp.int64)
out = Tensor(self.data[idx], (self,), "gather")
def _backward():
grad = xp.zeros_like(self.data)
xp.add.at(grad, idx, out.grad)
self.grad = self.grad + grad
out._backward = _backward
return out
def neg(self):
return self.mul(-1.0)
def sub(self, other):
other = other if isinstance(other, Tensor) else Tensor(other)
return self.add(other.neg())
def __add__(self, other):
return self.add(other)
def __radd__(self, other):
return self.add(other)
def __mul__(self, other):
return self.mul(other)
def __rmul__(self, other):
return self.mul(other)
def __matmul__(self, other):
return self.matmul(other)
def __neg__(self):
return self.neg()
def __sub__(self, other):
return self.sub(other)
def __rsub__(self, other):
return self.neg().add(other)
def backward(self):
topo = []
visited = set()
def build(v):
if v not in visited:
visited.add(v)
for child in v._prev:
build(child)
topo.append(v)
build(self)
self.grad = xp.ones_like(self.data)
for v in reversed(topo):
v._backward()
def zero_grad(self):
visited = set()
def build(v):
if v not in visited:
visited.add(v)
v.grad = xp.zeros_like(v.data)
for child in v._prev:
build(child)
build(self)
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