FYS-STK4155/doc/LectureNotes/_build/html/reports/chapter4.log

Traceback (most recent call last):
  File "/Users/mhjensen/opt/anaconda3/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 51, in single_nb_execution
    executenb(
  File "/Users/mhjensen/opt/anaconda3/lib/python3.8/site-packages/nbclient/client.py", line 1087, in execute
    return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute()
  File "/Users/mhjensen/opt/anaconda3/lib/python3.8/site-packages/nbclient/util.py", line 74, in wrapped
    return just_run(coro(*args, **kwargs))
  File "/Users/mhjensen/opt/anaconda3/lib/python3.8/site-packages/nbclient/util.py", line 53, in just_run
    return loop.run_until_complete(coro)
  File "/Users/mhjensen/opt/anaconda3/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete
    return future.result()
  File "/Users/mhjensen/opt/anaconda3/lib/python3.8/site-packages/nbclient/client.py", line 540, in async_execute
    await self.async_execute_cell(
  File "/Users/mhjensen/opt/anaconda3/lib/python3.8/site-packages/nbclient/client.py", line 832, in async_execute_cell
    self._check_raise_for_error(cell, exec_reply)
  File "/Users/mhjensen/opt/anaconda3/lib/python3.8/site-packages/nbclient/client.py", line 740, in _check_raise_for_error
    raise CellExecutionError.from_cell_and_msg(cell, exec_reply['content'])
nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
------------------
import autograd.numpy as np
from autograd import grad
def f8(x): # Assume x is an array
    x[2] = 3
    return x*2

f8_grad = grad(f8)

x = 8.4

print("The derivative of f8 is:",f8_grad(x))
------------------

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-29-cabc613b8702> in <module>
      9 x = 8.4
     10 
---> 11 print("The derivative of f8 is:",f8_grad(x))

~/opt/anaconda3/lib/python3.8/site-packages/autograd/wrap_util.py in nary_f(*args, **kwargs)
     18             else:
     19                 x = tuple(args[i] for i in argnum)
---> 20             return unary_operator(unary_f, x, *nary_op_args, **nary_op_kwargs)
     21         return nary_f
     22     return nary_operator

~/opt/anaconda3/lib/python3.8/site-packages/autograd/differential_operators.py in grad(fun, x)
     23     arguments as `fun`, but returns the gradient instead. The function `fun`
     24     should be scalar-valued. The gradient has the same type as the argument."""
---> 25     vjp, ans = _make_vjp(fun, x)
     26     if not vspace(ans).size == 1:
     27         raise TypeError("Grad only applies to real scalar-output functions. "

~/opt/anaconda3/lib/python3.8/site-packages/autograd/core.py in make_vjp(fun, x)
      8 def make_vjp(fun, x):
      9     start_node = VJPNode.new_root()
---> 10     end_value, end_node =  trace(start_node, fun, x)
     11     if end_node is None:
     12         def vjp(g): return vspace(x).zeros()

~/opt/anaconda3/lib/python3.8/site-packages/autograd/tracer.py in trace(start_node, fun, x)
      8     with trace_stack.new_trace() as t:
      9         start_box = new_box(x, t, start_node)
---> 10         end_box = fun(start_box)
     11         if isbox(end_box) and end_box._trace == start_box._trace:
     12             return end_box._value, end_box._node

~/opt/anaconda3/lib/python3.8/site-packages/autograd/wrap_util.py in unary_f(x)
     13                 else:
     14                     subargs = subvals(args, zip(argnum, x))
---> 15                 return fun(*subargs, **kwargs)
     16             if isinstance(argnum, int):
     17                 x = args[argnum]

<ipython-input-29-cabc613b8702> in f8(x)
      2 from autograd import grad
      3 def f8(x): # Assume x is an array
----> 4     x[2] = 3
      5     return x*2
      6 

TypeError: 'ArrayBox' object does not support item assignment
TypeError: 'ArrayBox' object does not support item assignment