Update pre-commit config

.pre-commit-config.yaml

@@ -18,7 +18,7 @@ repos:
  )$
  - id: check-merge-conflict
  - repo: https://github.com/psf/black
- rev: 22.12.0
+ rev: 23.1.0
  hooks:
  - id: black
  language_version: python3
@@ -47,7 +47,7 @@ repos:
  )$
  args: ['--in-place', '--remove-all-unused-imports', '--remove-unused-variable']
  - repo: https://github.com/pre-commit/mirrors-mypy
- rev: v0.991
+ rev: v1.1.1
  hooks:
  - id: mypy
  additional_dependencies:

aesara/breakpoint.py

@@ -69,7 +69,6 @@ def __init__(self, name):
  self.name = name
 
  def make_node(self, condition, *monitored_vars):
-
  # Ensure that condition is an Aesara tensor
  if not isinstance(condition, Variable):
  condition = as_tensor_variable(condition)
@@ -150,7 +149,6 @@ def infer_shape(self, fgraph, inputs, input_shapes):
  return input_shapes[1:]
 
  def connection_pattern(self, node):
-
  nb_inp = len(node.inputs)
  nb_out = nb_inp - 1
 

aesara/compile/builders.py

@@ -953,7 +953,6 @@ def connection_pattern(self, node):
  return list(map(list, cpmat_self))
 
  def infer_shape(self, fgraph, node, shapes):
-
  # TODO: Use `fgraph.shape_feature` to do this instead.
  out_shapes = infer_shape(self.inner_outputs, self.inner_inputs, shapes)
 

aesara/compile/debugmode.py

@@ -567,7 +567,6 @@ def _check_viewmap(fgraph, node, storage_map):
  """
 
  for oi, onode in enumerate(node.outputs):
-
  good_alias, bad_alias = {}, {}
  outstorage = storage_map[onode][0]
 
@@ -590,13 +589,11 @@ def _check_viewmap(fgraph, node, storage_map):
  if hasattr(inode.type, "may_share_memory") and inode.type.may_share_memory(
  outstorage, in_storage
  ):
-
  nodeid = id(inode)
  bad_alias[nodeid] = ii
 
  # check that the aliasing was declared in [view|destroy]_map
  if [ii] == view_map.get(oi, None) or [ii] == destroy_map.get(oi, None):
-
  good_alias[nodeid] = bad_alias.pop(nodeid)
 
  # TODO: make sure this is correct
@@ -1010,7 +1007,7 @@ def _check_preallocated_output(
  aliased_inputs.add(r)
 
  _logger.debug("starting preallocated output checking")
- for (name, out_map) in _get_preallocated_maps(
+ for name, out_map in _get_preallocated_maps(
  node,
  thunk,
  prealloc_modes,
@@ -1180,7 +1177,6 @@ class _VariableEquivalenceTracker(Feature):
  """
 
  def on_attach(self, fgraph):
-
  if hasattr(fgraph, "_eq_tracker_equiv"):
  raise AlreadyThere()
 
@@ -1675,7 +1671,6 @@ def f():
  sys.stdout.flush()
 
  if thunk_c:
-
  clobber = True
  if thunk_py:
  dmap = node.op.destroy_map

aesara/compile/function/pfunc.py

@@ -176,7 +176,7 @@ def clone_inputs(i):
  # Fill update_d and update_expr with provided updates
  if updates is None:
  updates = []
- for (store_into, update_val) in iter_over_pairs(updates):
+ for store_into, update_val in iter_over_pairs(updates):
  if not isinstance(store_into, SharedVariable):
  raise TypeError("update target must be a SharedVariable", store_into)
  if store_into in update_d:
@@ -471,7 +471,6 @@ def construct_pfunc_ins_and_outs(
  )
 
  if not fgraph:
-
  # Extend the outputs with the updates on input variables so they are
  # also cloned
  additional_outputs = [i.update for i in inputs if i.update]

aesara/compile/function/types.py

@@ -597,6 +597,7 @@ def copy(
  aesara.Function
  Copied aesara.Function
  """
+
  # helper function
  def checkSV(sv_ori, sv_rpl):
  """
@@ -761,7 +762,6 @@ def checkSV(sv_ori, sv_rpl):
  for in_ori, in_cpy, ori, cpy in zip(
  maker.inputs, f_cpy.maker.inputs, self.input_storage, f_cpy.input_storage
  ):
-
  # Share immutable ShareVariable and constant input's storage
  swapped = swap is not None and in_ori.variable in swap
 
@@ -911,7 +911,6 @@ def restore_defaults():
  if hasattr(i_var.type, "may_share_memory"):
  is_aliased = False
  for j in range(len(args_share_memory)):
-
  group_j = zip(
  [
  self.maker.inputs[k].variable
@@ -929,7 +928,6 @@ def restore_defaults():
  )
  for (var, val) in group_j
  ):
-
  is_aliased = True
  args_share_memory[j].append(i)
  break
@@ -1057,9 +1055,7 @@ def restore_defaults():
  elif self.unpack_single and len(outputs) == 1 and output_subset is None:
  return outputs[0]
  else:
-
  if self.output_keys is not None:
-
  assert len(self.output_keys) == len(outputs)
 
  if output_subset is None:
@@ -1452,7 +1448,6 @@ def prepare_fgraph(
  update = fgraph_outputs[out_idx]
 
  if update.owner and update.owner.op == update_placeholder:
-
  # TODO: Consider removing the corresponding
  # `FunctionGraph` input when it has no other
  # references?
@@ -1479,7 +1474,6 @@ def prepare_fgraph(
  # Add deep copy to respect the memory interface
  insert_deepcopy(fgraph, inputs, outputs + additional_outputs)
  finally:
-
  # If the rewriter got interrupted
  if rewrite_time is None:
  end_rewriter = time.perf_counter()
@@ -1658,7 +1652,6 @@ def create(self, input_storage=None, trustme=False, storage_map=None):
  for i, ((input, indices, subinputs), input_storage_i) in enumerate(
  zip(self.indices, input_storage)
  ):
-
  # Replace any default value given as a variable by its
  # container. Note that this makes sense only in the
  # context of shared variables, but for now we avoid

aesara/compile/profiling.py

@@ -65,7 +65,6 @@ def _atexit_print_fn():
  destination_file = config.profiling__destination
 
  with extended_open(destination_file, mode="w"):
-
  # Reverse sort in the order of compile+exec time
  for ps in sorted(
  _atexit_print_list, key=lambda a: a.compile_time + a.fct_call_time
@@ -358,7 +357,7 @@ def class_impl(self):
  """
  # timing is stored by node, we compute timing by class on demand
  rval = {}
- for (fgraph, node) in self.apply_callcount:
+ for fgraph, node in self.apply_callcount:
  typ = type(node.op)
  if self.apply_cimpl[node]:
  impl = "C "
@@ -401,7 +400,7 @@ def compute_total_times(self):
 
  """
  rval = {}
- for (fgraph, node) in self.apply_time:
+ for fgraph, node in self.apply_time:
  if node not in rval:
  self.fill_node_total_time(fgraph, node, rval)
  return rval
@@ -437,7 +436,7 @@ def op_impl(self):
  """
  # timing is stored by node, we compute timing by Op on demand
  rval = {}
- for (fgraph, node) in self.apply_callcount:
+ for fgraph, node in self.apply_callcount:
  if self.apply_cimpl[node]:
  rval[node.op] = "C "
  else:
@@ -711,7 +710,7 @@ def summary_nodes(self, file=sys.stderr, N=None):
 
  atimes.sort(reverse=True, key=lambda t: (t[1], t[3]))
  tot = 0
- for (f, t, a, nd_id, nb_call) in atimes[:N]:
+ for f, t, a, nd_id, nb_call in atimes[:N]:
  tot += t
  ftot = tot * 100 / local_time
  if nb_call == 0:
@@ -840,7 +839,7 @@ def summary_memory(self, file, N=None):
  var_mem = {} # variable->size in bytes; don't include input variables
  node_mem = {} # (fgraph, node)->total outputs size (only dense outputs)
 
- for (fgraph, node) in self.apply_callcount:
+ for fgraph, node in self.apply_callcount:
  fct_memory.setdefault(fgraph, {})
  fct_memory[fgraph].setdefault(node, [])
  fct_shapes.setdefault(fgraph, {})
@@ -1611,7 +1610,7 @@ def exp_float32_op(op):
  printed_tip = True
 
  # tip 4
- for (fgraph, a) in self.apply_time:
+ for fgraph, a in self.apply_time:
  node = a
  if isinstance(node.op, Dot) and all(
  len(i.type.broadcastable) == 2 for i in node.inputs
@@ -1628,7 +1627,7 @@ def exp_float32_op(op):
  printed_tip = True
 
  # tip 5
- for (fgraph, a) in self.apply_time:
+ for fgraph, a in self.apply_time:
  node = a
  if isinstance(node.op, RandomVariable):
  printed_tip = True
@@ -1642,7 +1641,7 @@ def exp_float32_op(op):
  break
 
  # tip 6
- for (fgraph, a) in self.apply_time:
+ for fgraph, a in self.apply_time:
  node = a
  if isinstance(node.op, Dot) and len({i.dtype for i in node.inputs}) != 1:
  print(

aesara/configdefaults.py

@@ -278,7 +278,6 @@ def short_platform(r=None, p=None):
 
 
 def add_basic_configvars():
-
  config.add(
  "floatX",
  "Default floating-point precision for python casts.\n"
@@ -388,7 +387,6 @@ def _is_greater_or_equal_0(x):
 
 
 def add_compile_configvars():
-
  config.add(
  "mode",
  "Default compilation mode",
@@ -631,7 +629,6 @@ def _is_valid_cmp_sloppy(v):
 
 
 def add_tensor_configvars():
-
  # This flag is used when we import Aesara to initialize global variables.
  # So changing it after import will not modify these global variables.
  # This could be done differently... but for now we simply prevent it from being
@@ -717,7 +714,6 @@ def add_experimental_configvars():
 
 
 def add_error_and_warning_configvars():
-
  ###
  # To disable some warning about old bug that are fixed now.
  ###
@@ -1196,7 +1192,6 @@ def add_vm_configvars():
 
 
 def add_deprecated_configvars():
-
  # TODO: remove this?
  config.add(
  "unittests__rseed",

aesara/gradient.py

@@ -229,7 +229,6 @@ def Rop(
  # Check that each element of wrt corresponds to an element
  # of eval_points with the same dimensionality.
  for i, (wrt_elem, eval_point) in enumerate(zip(_wrt, _eval_points)):
-
  try:
  if wrt_elem.type.ndim != eval_point.type.ndim:
  raise ValueError(
@@ -266,7 +265,6 @@ def _traverse(node):
  # arguments, like for example random states
  local_eval_points.append(None)
  elif inp.owner in seen_nodes:
-
  local_eval_points.append(
  seen_nodes[inp.owner][inp.owner.outputs.index(inp)]
  )
@@ -941,7 +939,6 @@ def account_for(var):
  var_idx = app.outputs.index(var)
 
  for i, ipt in enumerate(app.inputs):
-
  # don't process ipt if it is not a true
  # parent of var
  if not connection_pattern[i][var_idx]:
@@ -1052,7 +1049,6 @@ def access_term_cache(node):
  """Populates term_dict[node] and returns it"""
 
  if node not in term_dict:
-
  inputs = node.inputs
 
  output_grads = [access_grad_cache(var) for var in node.outputs]
@@ -1267,7 +1263,6 @@ def try_to_copy_if_needed(var):
  ]
 
  for i, term in enumerate(input_grads):
-
  # Disallow Nones
  if term is None:
  # We don't know what None means. in the past it has been
@@ -1383,7 +1378,6 @@ def access_grad_cache(var):
  node_to_idx = var_to_app_to_idx[var]
  for node in node_to_idx:
  for idx in node_to_idx[node]:
-
  term = access_term_cache(node)[idx]
 
  if not isinstance(term, Variable):
@@ -1868,7 +1862,6 @@ def random_projection():
  )
 
  if max_abs_err > abs_tol and max_rel_err > rel_tol:
-
  raise GradientError(
  max_arg,
  max_err_pos,
@@ -2052,7 +2045,6 @@ def hessian(cost, wrt, consider_constant=None, disconnected_inputs="raise"):
 
  hessians = []
  for input in wrt:
-
  if not isinstance(input, Variable):
  raise TypeError("hessian expects a (list of) Variable as `wrt`")