Since we don't implement any integer-like operations for TBool
(addition, bitwise not, etc.), TBool is currently neither
strictly equivalent to builtin bool nor numpy.bool_, but through
very obvious compiler errors (operation not supported) rather than
silently different runtime behaviour.
Just mapping both to TBool thus is a huge improvement over the
current behaviour (where numpy.False_ is a true-like object). In
the future, we could still implement more operations for TBool,
presumably following numpy.bool_ rather than the builtin type,
just like builtin integers get translated to the numpy-like
TInt{32,64}.
GitHub: Fixes#1275.
Previously, any type would be accepted for the test expression,
leading to internal errors in the code generator if the passed
value wasn't in fact a bool.
array([...]), the constructor for NumPy arrays, currently has the
status of some weird kind of macro in ARTIQ Python, as it needs
to determine the number of dimensions in the resulting array
type, which is a fixed type parameter on which inference cannot
be performed.
This leads to an ambiguity for empty lists, which could contain
elements of arbitrary type, including other lists (which would
add to the number of dimensions).
Previously, I had chosen to make array([]) to be of completely
indeterminate type for this reason. However, this is different
to how the call behaves in host NumPy, where this is a well-formed
call creating an empty 1D array (or 2D for array([[], []]), etc.).
This commit adds special matching for (recursive lists of) empty
ListT AST nodes to treat them as scalar dimensions, with the
element type still unknown.
This also happens to fix type inference for embedding empty 1D
NumPy arrays from host object attributes, although multi-dimensional
arrays will still require work (see GitHub #1633).
GitHub: Fixes#1626.
Strided slicing of one-dimensional arrays (i.e. with non-trivial
steps) might have previously been working, but would have had
different semantics, as all slices were copies rather than a view
into the original data.
Fixing this in the future will require adding support for an index
stride field/tuple to our array representation (and all the
associated indexing logic).
GitHub: Fixes#1627.
This was a long-standing issue affecting both lists and
the new NumPy array implementation, just caused by the
generic inference passes not being run on the slice
subexpressions (and thus e.g. ints not being monomorphized).
GitHub: Fixes#1632.
Resolves error message shown.
The following error message is shown when worker_impl.py:199 is run:
```
WARNING:worker(RID,EXPERIMENT):py.warnings:/nix/store/77sw4p03cb7rdayx86agi4yqxh5wq46b-python3.7-artiq-5.7141.1b68906/lib/python3.7/site-packages/artiq/master/worker_impl.py:199: DeprecationWarning: The 'warn' function is deprecated, use 'warning' instead
logging.warn(message)
```
recv() returns 0 instead of data if the socket has already
been closed. This is translated into a zero-length list on
the Python layer. Previously, the code would enter an
infinite loop if the socket was closed while attempting
to receive data.
This partially reverts commit b5e1bd3fa2,
which had removed keepalive. This, however, led to experiments
hanging forever if the core device had dropped the connection
(e.g. to a kernel CPU panic, or the device being rebooted).
The chosen keepalive settings are fairly conservative (with the
10 s timeout) to avoid any possible interaction with smoltcp's
3 s ARP try interval (see GitHub issue #1150), even though this
should be a non-issue now due to the larger ARP cache.
David Nadlinger
Sebastien Bourdeauducq
Etienne Wodey
Astro
Drew
Robert Jördens
Ilia Sergachev
pca006132