def tensors(
draw,
numbers=floats(allow_nan=False, min_value=-100, max_value=100),
backend=minitorch.TensorFunctions,
shape=None,
):
td = draw(tensor_data(numbers, shape=shape))
return minitorch.Tensor(td, backend=backend)
def matmul_tensors(
draw, numbers=floats(allow_nan=False, min_value=-100, max_value=100)
):
i, j, k = [draw(integers(min_value=1, max_value=10)) for _ in range(3)]
l1 = (i, j)
l2 = (j, k)
values = []
for shape in [l1, l2]:
size = int(minitorch.prod(shape))
data = draw(lists(numbers, min_size=size, max_size=size))
values.append(minitorch.Tensor(minitorch.TensorData(data, shape)))
return values
def shaped_tensors(
draw,
n,
numbers=floats(allow_nan=False, min_value=-100, max_value=100),
backend=minitorch.TensorFunctions,
):
td = draw(tensor_data(numbers))
values = []
for i in range(n):
data = draw(lists(numbers, min_size=td.size, max_size=td.size))
values.append(
minitorch.Tensor(minitorch.TensorData(data, td.shape),
backend=backend))
return values
