def visit_AugAssign(self, node):
read_target = deepcopy(node.target)
existing_node = self.generic_visit(node)
line_numbers = set()
self._find_line_numbers(existing_node, line_numbers)
first_line_number = min(line_numbers)
last_line_number = max(line_numbers)
new_nodes = []
format_string = (self._wrap_assignment_target(existing_node.target) +
' = {!r}')
new_nodes.append(self._create_context_call('start_assignment'))
self._wrap_assignment_target(read_target, index_to_get=-1)
read_target.ctx = Load()
set_assignment_value = self._create_context_call(
'set_assignment_value',
[read_target])
report_assignment = self._create_context_call(
'report_assignment',
[Str(s=format_string), Num(n=existing_node.lineno)])
end_assignment = self._create_context_call('end_assignment')
try_body = [existing_node, set_assignment_value, report_assignment]
finally_body = [end_assignment]
new_nodes.append(TryFinally(body=try_body,
finalbody=finally_body,
handlers=[],
orelse=[],
lineno=first_line_number))
self._set_statement_line_numbers(try_body, first_line_number)
self._set_statement_line_numbers(finally_body, last_line_number)
return new_nodes
def rewrite_with_to_binds(body, monad):
new_body = []
# Construct a transformer for this specific monad's mreturn
rdb = RewriteDoBody(monad)
# This is the body of the lambda we're about to construct
last_part = body[-1].value
# Rewrite mreturn
rdb.visit(last_part)
# Iterate in reverse, making each line the into a lambda whose body is the
# rest of the lines (which are each lambdas), and whose names are the
# bind assignments.
for b in reversed(body[:-1]):
rdb.visit(b)
if isinstance(b, Assign):
name = b.targets[0].id
value = b.value
else:
# If there was no assignment to the bind, just use a random name, eek
name = '__DO_NOT_NAME_A_VARIABLE_THIS_STRING__'
value = b.value
# last part = value.bind(lambda name: last_part)
last_part = Call(func=Attribute(value=value, attr='bind', ctx=Load()),
args=[
Lambda(args=arguments(args=[
Name(id=name, ctx=Param()),
],
vararg=None,
kwarg=None,
defaults=[]),
body=last_part),
],
keywords=[],
starargs=None,
kwargs=None)
return last_part
def visit_AugAssign(self, node):
read_target = deepcopy(node.target)
existing_node = self.generic_visit(node)
line_numbers = set()
find_line_numbers(existing_node, line_numbers)
first_line_number = min(line_numbers)
last_line_number = max(line_numbers)
new_nodes = []
try_body = [existing_node]
new_nodes.append(self._create_context_call('start_assignment'))
format_string = self._wrap_assignment_target(existing_node.target)
if format_string is not None:
if ':' in format_string:
existing_node.value = self._create_bare_context_call(
'set_assignment_value', [existing_node.value])
operator_char = OPERATOR_CHARS.get(type(existing_node.op), '?')
format_string += ' {}= {{}} '.format(operator_char)
else:
self._wrap_assignment_target(read_target, index_to_get=-1)
read_target.ctx = Load()
set_assignment_value = self._create_context_call(
'set_assignment_value', [read_target])
try_body.append(set_assignment_value)
format_string += ' = {}'
try_body.append(
self._create_context_call(
'report_assignment',
[Str(s=format_string),
Num(n=existing_node.lineno)]))
self._create_end_assignment(new_nodes, try_body, first_line_number,
last_line_number)
return new_nodes
def __init__(self, *, elts: tp.List[expr], ctx: expr_context = Load()):
super().__init__(
**{
key: value
for key, value in locals().items()
if key not in ('self', '__class__')
})
def visit_Name(self, node):
name = node.id
if name in self.variables:
return Name(id=std_tsymbol((name, 0)), ctx=Load())
else:
return node
def visit_Call(self, node):
name = node.func.id
args = node.args[0]
if name in self.variables:
if isinstance(args, UnaryOp):
# we have s(+1)
if (isinstance(args.op, UAdd)):
args = args.operand
date = args.n
elif (isinstance(args.op, USub)):
args = args.operand
date = -args.n
else:
raise Exception("Unrecognized subscript.")
else:
date = args.n
newname = std_tsymbol((name, date))
if newname is not None:
return Name(newname, Load())
else:
# , keywords=node.keywords, starargs=node.starargs, kwargs=node.kwargs)
return Call(func=node.func,
args=[self.visit(e) for e in node.args],
keywords=[])
def getTracer(file_name, arg_name, id):
return Expr(
value=Call(
func=Attribute(
value=Name(id='Tracer', ctx=Load()),
attr='trace', ctx=Load()),
args=[
Constant(value=str(file_name), kind=None),
Constant(value=str(id), kind=None),
Constant(value=str(arg_name), kind=None),
Name(id=arg_name, ctx=Load()),
],
keywords=[]
)
)
def AugAssignToAssign(node):
store_var = node.target
load_var = Name(id=store_var.id, ctx=Load())
return Assign(targets=[store_var],
value=BinOp(left=load_var,
op=node.op,
right=node.value))
def visit_Name(self, node):
try:
replacement = self.replacements[node.id]
except (KeyError, AttributeError):
return node
else:
return Name(id=replacement.name, ctx=Load())
def visit_UnaryOp(self, node):
self.generic_visit(node)
if isinstance(node.op, Not):
return Call(Name('logical_not', Load()), [node.operand],
[], None, None)
else:
raise NotImplementedError('%s not implemented' % (node.op, ))
def test_param2argparse_param_default_ast_expr_with_list(self) -> None:
"""
Tests that param2argparse_param works to change the type based on the default
whence said default is an ast.List inside an ast.Expr
"""
run_ast_test(
gen_ast=param2argparse_param(
(
"byo",
{
"default": Expr(
List(
elts=[],
ctx=Load(),
expr=None,
),
expr_value=None,
),
"typ": "str",
},
),
),
gold=argparse_add_argument_expr,
test_case_instance=self,
)
def visit_let(self, letexp: Expr):
# To properly account for scoping and ensure that the entire node produces an expression,
# we translate the let binding as a function that we call with the value we intend to bind.
# Yes, this is somewhat ugly.
"""
let var = value in body
=======================
def let_thunk(var):
return body
let_thunk(value)
"""
bind_body, bind_defs = self.visit(letexp.body)
func_name = self.generate_function_name("_let_func")
binding_func = self.create_def(func_name,
[self.get_var_name(letexp.var)],
bind_defs + [Return(bind_body)])
# we call the binding func with the intended value for the bound variable
# special case: if the value is a function literal, we must ensure it can be
# recursive by naming it after the var
if isinstance(letexp.value, Function):
value_def, value_name = self.convert_func_node(
letexp.value, letexp.var)
return (
self.create_call(func_name, [Name(value_name, Load())]),
[value_def, binding_func],
)
value_body, value_defs = self.visit(letexp.value)
value_defs.append(binding_func)
binding_call = self.create_call(func_name, [value_body])
return (binding_call, value_defs)
def test_replace_in_ast_with_val_on_non_function(self) -> None:
"""
Tests that `RewriteAtQuery` can actually replace a node at given location
"""
parsed_ast = ast_parse(class_str)
rewrite_at_query = RewriteAtQuery(
search="ConfigClass.dataset_name".split("."),
replacement_node=AnnAssign(
annotation=Name("int", Load()),
simple=1,
target=Name("dataset_name", Store()),
value=set_value(15),
expr=None,
expr_target=None,
expr_annotation=None,
),
)
gen_ast = rewrite_at_query.visit(parsed_ast)
self.assertTrue(rewrite_at_query.replaced, True)
run_ast_test(
self,
gen_ast,
ast.parse(
class_str.replace(
'dataset_name: str = "mnist"', "dataset_name: int = 15"
)
),
)
def test_annotate_ancestry(self) -> None:
"""Tests that `annotate_ancestry` properly decorates"""
node = Module(
body=[
AnnAssign(
annotation=Name(
"str",
Load(),
),
simple=1,
target=Name("dataset_name", Store()),
value=set_value("~/tensorflow_datasets"),
expr=None,
expr_target=None,
expr_annotation=None,
),
Assign(
annotation=None,
simple=1,
targets=[Name("epochs", Store())],
value=set_value("333"),
expr=None,
expr_target=None,
expr_annotation=None,
**maybe_type_comment
),
],
stmt=None,
)
self.assertFalse(hasattr(node.body[0], "_location"))
self.assertFalse(hasattr(node.body[1], "_location"))
annotate_ancestry(node)
self.assertEqual(node.body[0]._location, ["dataset_name"])
self.assertEqual(node.body[1]._location, ["epochs"])
def test_emit_ann_assign(self) -> None:
"""Tests that AnnAssign is emitted from `emit_ann_assign`"""
self.assertIsInstance(class_ast.body[1], AnnAssign)
self.assertIsInstance(emit_ann_assign(class_ast.body[1]), AnnAssign)
self.assertIsInstance(emit_ann_assign(class_ast.body[1]), AnnAssign)
gen_ast = emit_ann_assign(
find_in_ast(
"C.function_name.dataset_name".split("."),
class_with_method_and_body_types_ast,
)
)
self.assertIsInstance(gen_ast, AnnAssign)
run_ast_test(
self,
gen_ast,
AnnAssign(
annotation=Name(
"str",
Load(),
),
simple=1,
target=Name("dataset_name", Store()),
value=set_value("~/tensorflow_datasets"),
expr=None,
expr_target=None,
expr_annotation=None,
),
)
def test_parse_to_scalar(self) -> None:
"""Test various inputs and outputs for `parse_to_scalar`"""
for fst, snd in (
(5, 5),
("5", "5"),
(set_value(5), 5),
(ast.Expr(None), NoneStr),
):
self.assertEqual(parse_to_scalar(fst), snd)
self.assertEqual(
get_value(parse_to_scalar(ast.parse("[5]").body[0]).elts[0]), 5
)
self.assertTrue(
cmp_ast(
parse_to_scalar(ast.parse("[5]").body[0]),
List([set_value(5)], Load()),
)
)
self.assertEqual(parse_to_scalar(ast.parse("[5]")), "[5]")
parse_to_scalar(ast.parse("[5]").body[0])
self.assertRaises(NotImplementedError, parse_to_scalar, memoryview(b""))
self.assertRaises(NotImplementedError, parse_to_scalar, memoryview(b""))
def visit_BoolOp(self, node: BoolOp) -> Union[UnaryOp, Call]:
self.generic_visit(node)
if isinstance(node.op, And):
runtime = '__lazybooland__'
elif isinstance(node.op, Or):
runtime = '__lazyboolor__'
else:
return node
lhs, rhs = node.values
delegate = Call(
func=Name(id=runtime, ctx=Load()),
args=[
lhs,
# Make the rhs a deferred computation by wrapping with a lambda
Lambda(args=arguments(args=[],
kwonlyargs=[],
kw_defaults=[],
defaults=[]),
body=rhs)
],
keywords=[])
copy_location(delegate, node)
fix_missing_locations(delegate)
return delegate
def visit_call(self, call: Expr):
"""For calls, we must distinguish between ordinary functions,
operators, and constructor calls."""
func = call.op
fields, field_defs = self.convert_fields(call.args)
if isinstance(func, tvm.ir.Op):
raise Exception(
'Operators should have been lowered and eliminated')
if isinstance(func, relay.Constructor):
# produce a constructor value
return (self.create_call('ConstructorValue', [
ast.Num(func.tag),
ast.List(fields, Load()),
NameConstant(None)
]), field_defs)
# lowered operator: generate a call to a function that gets the PackedFunc
# from TVM's registry
if isinstance(
func,
Function) and func.attrs and func.attrs.Primitive.value == 1:
op_call_def, op_call = self.create_op_call(func, call.args, fields)
return (op_call, field_defs + [op_call_def])
# ordinary function
converted_func, defs = self.visit(func)
defs += field_defs
return (ast.Call(converted_func, fields, []), defs)
def convert_input(py_input, arg_type):
"""Use the types of the function arguments to determine whether we expect
a tensor or tuple (returns list of inputs to the lowered op call)"""
# equivalent: input.data
if isinstance(arg_type, relay.TensorType):
return [py_input]
assert isinstance(arg_type, relay.TupleType)
# convert each input.fields[i]
ret = []
for i in range(len(arg_type.fields)):
ret += convert_input(
ast.Subscript(
ast.Attribute(py_input, 'fields', Load()),
ast.Index(Num(i)), Load()),
arg_type.fields[i])
return ret
def _getblockattr(name, lineno, col):
"""calls getattr(name, '__xonsh_block__', False)."""
return xonsh_call('getattr', args=[
Name(id=name, ctx=Load(), lineno=lineno, col_offset=col),
Str(s='__xonsh_block__', lineno=lineno, col_offset=col),
NameConstant(value=False, lineno=lineno, col_offset=col)],
lineno=lineno, col=col)
def _split_set_elts(elts): # pylint: disable=C0111
collapsed = []
for element in elts:
if isinstance(element, BinOp) and isinstance(element.op, BitOr):
collapsed.extend(NotationASTTransformer._collapse(element))
else:
collapsed.append(element)
last_choice = []
choices = [last_choice]
for element in collapsed:
if isinstance(element, BitOr):
last_choice = []
choices.append(last_choice)
else:
last_choice.append(element)
splitted = []
for choice in choices:
if len(choice) > 1:
splitted.append(Tuple(choice, Load()))
else:
splitted.append(choice[0])
return splitted
def test_ast_equal() -> None:
a = Name(id="print", ctx=Load())
b = Name(id="print", ctx=Load())
assert ast_deep_equal(a, b)
a = Expr(value=Call(
func=Name(id="print", ctx=Load()),
args=[Constant(value="hello, world")],
keywords=[],
))
b = Expr(value=Call(
func=Name(id="print", ctx=Load()),
args=[Constant(value="hello, world")],
keywords=[],
))
assert ast_deep_equal(a, b)
def visit_Tuple(self, node):
if len(node.elts) != 2:
raise self.parseError(node,
'interval must have exactly two endpoints')
newElts = [self.visit(elt) for elt in node.elts]
return copy_location(Call(Name(rangeConstructor, Load()), newElts, []),
node)
def boolOpBreaker(self, values, func):
if len(values) == 1:
return values[0]
else:
return Call(Name(func, Load()),
[values[0], self.boolOpBreaker(values[1:], func)],
[], None, None)
def compile(self, im_root):
"""
Compile a :class:`piglet.intermediate.RootNode` to an
:class:`ast.Module` object
"""
assert self.src_root is None, \
"{!r}.compile called more than once".format(self)
try:
self.src_root = im_root
fn = self._compile_function(im_root,
self.module,
'__piglet_root__')
add_arg_default(fn, make_arg('__piglet_bases'),
List(elts=[], ctx=Load()))
fn.args.kwarg = make_kwarg('__piglet_extra_blocks')
module = self.module
module = _hoist_variables_to_piglet_context(module)
module = _ensure_all_functions_yield(module)
module = _deduplicate_exception_annotations(module)
module = add_locations(module)
except PigletParseError as e:
e.filename = self.filename
raise
return module
def visit_Call(self, node):
name = node.func.id
args = node.args[0]
if name in self.variables:
if isinstance(args, UnaryOp):
# we have s(+1)
assert (isinstance(args.op, UAdd))
args = args.operand
date = args.n
key = (name, date)
newname = self.table_symbols.get(key)
if newname is not None:
return Name(newname, Load())
else:
raise Exception(
"Symbol {} incorrectly subscripted with date {}.".format(
name, date))
else:
return Call(func=node.func,
args=[self.visit(e) for e in node.args],
keywords=node.keywords,
starargs=node.starargs,
kwargs=node.kwargs)
def test_param2argparse_param_default_torch(self) -> None:
"""
Tests that param2argparse_param works to change the type based on the default
whence said default is a proxy for an internal PyTorch type
"""
class FakeTorch(object):
""" Not a real torch """
def __str__(self):
"""But a real str
:return: An actual str
:rtype: ```Literal['<required parameter>']```
"""
return "<required parameter>"
# type("FakeTorch", tuple(), {"__str__": lambda _: "<required parameter>"})
run_ast_test(
gen_ast=param2argparse_param((
"byo",
{
"default": FakeTorch(),
},
), ),
gold=Expr(
Call(
args=[set_value("--byo")],
func=Attribute(
Name("argument_parser", Load()),
"add_argument",
Load(),
),
keywords=[
keyword(
arg="type",
value=Name(FakeTorch.__name__, Load()),
identifier=None,
),
keyword(arg="required",
value=set_value(True),
identifier=None),
],
expr=None,
expr_func=None,
)),
test_case_instance=self,
)
def compile_translationnode(self, srcnode, parent):
translated = Call(func=LoadName('_'),
args=[Str(srcnode.get_msgstr())],
starargs=None,
kwargs=None,
keywords=[])
named_children = [(name, node)
for name, node in srcnode.named_children()
if name is not None]
if not named_children:
# Simple case - no dynamic children for placeholder replacement
parent.body.append(Expr(value=Yield(translated)))
return
parent.body.append(
Assign(targets=[StoreName('__piglet_places')],
value=Dict([], []))
)
for name, node in named_children:
with self.collect_output(parent) as ACC:
self._compile(node, parent)
parent.body.append(
Assign(targets=[Subscript(value=LoadName('__piglet_places'),
slice=Index(value=Str(name)),
ctx=Store())],
value=Call(func=Attribute(value=Str(s=''), attr='join', ctx=Load()),
args=[LoadName(ACC)],
starargs=None,
kwargs=None,
keywords=[]))
)
for name, node in named_children:
translated = Call(
func=Attribute(value=translated, attr='replace', ctx=Load()),
args=[Str('${{{}}}'.format(name)),
Subscript(value=LoadName('__piglet_places'),
slice=Index(value=Str(name)),
ctx=Load())],
starargs=None,
kwargs=None,
keywords=[])
set_pos(translated, srcnode)
parent.body.append(Expr(value=Yield(translated)))
def visit_ClassDef(self, node):
"""Process property defaults for Scenic classes."""
if node.name in self.constructors: # Scenic class definition
newBody = []
for child in node.body:
child = self.visit(child)
if isinstance(child, AnnAssign): # default value for property
origValue = child.annotation
target = child.target
# extract any attributes for this property
metaAttrs = []
if isinstance(target, Subscript):
sl = target.slice
if not isinstance(sl, Index):
self.parseError(sl, 'malformed attributes for property default')
sl = sl.value
if isinstance(sl, Name):
metaAttrs.append(sl.id)
elif isinstance(sl, Tuple):
for elt in sl.elts:
if not isinstance(elt, Name):
self.parseError(elt,
'malformed attributes for property default')
metaAttrs.append(elt.id)
else:
self.parseError(sl, 'malformed attributes for property default')
newTarget = Name(target.value.id, Store())
copy_location(newTarget, target)
target = newTarget
# find dependencies of the default value
properties = AttributeFinder.find('self', origValue)
# create default value object
args = [
Set([Str(prop) for prop in properties]),
Set([Str(attr) for attr in metaAttrs]),
Lambda(self.self_args, origValue)
]
value = Call(Name(createDefault, Load()), args, [])
copy_location(value, origValue)
newChild = AnnAssign(
target=target, annotation=value,
value=None, simple=True)
child = copy_location(newChild, child)
newBody.append(child)
node.body = newBody
return node
else: # ordinary Python class
# it's impossible at the moment to define a Python class in a Scenic file,
# but we'll leave this check here for future-proofing
for base in node.bases:
name = None
if isinstance(base, Call):
name = base.func.id
elif isinstance(base, Name):
name = base.id
if name is not None and name in self.constructors:
self.parseError(node,
f'Python class {node.name} derives from PRS class {name}')
return self.generic_visit(node)
def visit_Yield(self, node):
existing_node = self.generic_visit(node)
value = existing_node.value
if value is None:
value = Name(id='None', ctx=Load())
return Yield(value=self._create_bare_context_call(
'yield_value', [value, Num(n=existing_node.lineno)]))
