def process_lines(lines):
results = []
for label, contexts in path_iterator(lines):
masked_contexts = mask_variables_in_contexts(contexts)
masked_contexts = [
",".join(masked_context) for masked_context in masked_contexts
]
contexts_str = " ".join(masked_contexts)
results.append(f"{label} {contexts_str}\n")
return results
def extract_targets_and_subtokens(lines):
subtokens = []
targets = []
for target, contexts in path_iterator(lines):
targets.append(" ".join(target.split("|")))
for start, _, end in contexts:
subtokens.append(" ".join(start.split("|")))
subtokens.append(" ".join(end.split("|")))
return {"subtokens": subtokens, "targets": targets}
def compute_lengths(lines, subtoken_tokenizer, target_tokenizer):
target_lengths = []
subtoken_lengths = []
for label, contexts in path_iterator(lines):
target_lengths.append(len(target_tokenizer.encode(label.split("|"))))
for start, path, end in contexts:
subtoken_lengths.append(
len(subtoken_tokenizer.encode(start.split("|"))))
subtoken_lengths.append(
len(subtoken_tokenizer.encode(end.split("|"))))
return target_lengths, subtoken_lengths
def process_chunk(lines):
target_count = {}
subtoken_count = {}
node_count = {}
for label, contexts in path_iterator(lines):
add_subtokens_to_dict(label, target_count, split_subtokens=True)
for start, path, end in contexts:
add_subtokens_to_dict(start, subtoken_count, split_subtokens=True)
add_subtokens_to_dict(end, subtoken_count, split_subtokens=True)
add_subtokens_to_dict(path, node_count)
return target_count, subtoken_count, node_count
def process_chunk_serial(lines: List[str]):
masked_entries = []
for label, contexts in path_iterator(lines):
variables = get_variables_from_contexts(contexts)
for variable in variables:
new_entries = create_path_for_variable(variable, variables,
contexts)
new_entries = new_entries.strip()
assert "\n" not in new_entries, "Newline found in new_entries"
if len(new_entries) > 0:
masked_entries.append(new_entries)
return masked_entries
def mask_variables_for_method_name(src_folder, out_folder):
raw_src_files = os.listdir(src_folder)
raw_src_files = map(lambda p: os.path.join(src_folder, p), raw_src_files)
for raw_src_file in raw_src_files:
with open(raw_src_file, "r") as f:
lines = map(lambda s: s.strip(), f.readlines())
masked_paths = []
for label, contexts in path_iterator(lines):
masked_contexts = []
masked_contexts = mask_variables_in_contexts(contexts)
masked_contexts = [",".join(masked_context) for masked_context in masked_contexts]
masked_contexts = " ".join(masked_contexts)
masked_paths.append(f"{label} {masked_contexts}")
out_file = os.path.join(out_folder, os.path.basename(raw_src_file))
with open(out_file, "w") as out:
for path in masked_paths:
out.write(f"{path}\n")
def verify_variable_dataset(lines):
for variable, contexts in path_iterator(lines):
# make sure that if variable appears in any context,
# it is not a VDID or a Nm
for context in contexts:
start, path, end = map(lambda x: x.strip(), context)
if start == variable:
start_node = get_start_node(path)
assert not (
is_name_expr(start_node) or is_variable(start_node)
), f"Verification Failed: Variable appears in start node and is not a variable or a name expr:\n{context}"
# print(f"variable name appeared with {start_node}")
if end == variable:
end_node = get_end_node(path)
assert not (
is_name_expr(end_node) or is_variable(end_node)
), f"Verification Failed: Variable appears in start node and is not a variable or a name expr:\n{context}"
def process_variables(lines):
target_count, subtoken_count, node_count = {}, {}, {}
for label, contexts in path_iterator(lines):
variables = get_variables_from_contexts(contexts)
for variable in variables:
add_subtokens_to_dict(variable, target_count)
for start, path, end in contexts:
start_node, end_node = [
f(path) for f in [get_start_node, get_end_node]
]
if should_mask(start, start_node, variables):
add_subtokens_to_dict(start, subtoken_count)
if not should_mask(end, end_node, variables):
add_subtokens_to_dict(end, subtoken_count)
add_subtokens_to_dict(path, node_count)
return target_count, subtoken_count, node_count