code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
values |
|---|---|---|---|---|---|---|---|
def _textual_index_column(
table: Table, text_: Union[str, TextClause, ColumnElement[Any]]
) -> Union[ColumnElement[Any], Column[Any]]:
"""a workaround for the Index construct's severe lack of flexibility"""
if isinstance(text_, str):
c = Column(text_, sqltypes.NULLTYPE)
table.append_column(... | a workaround for the Index construct's severe lack of flexibility | _textual_index_column | python | sqlalchemy/alembic | alembic/util/sqla_compat.py | https://github.com/sqlalchemy/alembic/blob/master/alembic/util/sqla_compat.py | MIT |
def non_native_boolean(self):
"""test will fail if native boolean is provided"""
return exclusions.fails_if(
exclusions.LambdaPredicate(
lambda config: config.db.dialect.supports_native_boolean
)
) | test will fail if native boolean is provided | non_native_boolean | python | sqlalchemy/alembic | tests/requirements.py | https://github.com/sqlalchemy/alembic/blob/master/tests/requirements.py | MIT |
def non_native_boolean_check_constraint(self):
"""backend creates a check constraint for booleans if enabled"""
return exclusions.only_on(
exclusions.LambdaPredicate(
lambda config: not config.db.dialect.supports_native_boolean
and config.db.dialect.non_nativ... | backend creates a check constraint for booleans if enabled | non_native_boolean_check_constraint | python | sqlalchemy/alembic | tests/requirements.py | https://github.com/sqlalchemy/alembic/blob/master/tests/requirements.py | MIT |
def reflects_pk_names(self):
"""Target driver reflects the name of primary key constraints."""
return exclusions.fails_on_everything_except(
"postgresql", "oracle", "mssql", "sybase", "sqlite"
) | Target driver reflects the name of primary key constraints. | reflects_pk_names | python | sqlalchemy/alembic | tests/requirements.py | https://github.com/sqlalchemy/alembic/blob/master/tests/requirements.py | MIT |
def test_render_diffs_batch(self):
"""test a full render in batch mode including indentation"""
template_args = {}
self.context.opts["render_as_batch"] = True
autogenerate._render_migration_diffs(self.context, template_args)
eq_(
template_args["upgrades"],
... | test a full render in batch mode including indentation | test_render_diffs_batch | python | sqlalchemy/alembic | tests/test_autogen_composition.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_autogen_composition.py | MIT |
def test_render_diffs_extras(self):
"""test a full render including indentation (include and schema)"""
template_args = {}
self.context.opts.update(
{
"include_object": _default_include_object,
"include_schemas": True,
}
)
... | test a full render including indentation (include and schema) | test_render_diffs_extras | python | sqlalchemy/alembic | tests/test_autogen_composition.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_autogen_composition.py | MIT |
def test_diffs_order(self):
"""
Added in order to test that child tables(tables with FKs) are
generated before their parent tables
"""
ctx = self.autogen_context
uo = ops.UpgradeOps(ops=[])
autogenerate._produce_net_changes(ctx, uo)
diffs = uo.as_diffs()
... |
Added in order to test that child tables(tables with FKs) are
generated before their parent tables
| test_diffs_order | python | sqlalchemy/alembic | tests/test_autogen_diffs.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_autogen_diffs.py | MIT |
def test_nothing_changed_cols_unsorted(self):
"""test #1240
MySQL doubles unique constraints as indexes, so we need to make
sure we aren't comparing index sigs to unique constraint sigs,
which we were doing previously by mistake. As their signatures
were compatible, things "wo... | test #1240
MySQL doubles unique constraints as indexes, so we need to make
sure we aren't comparing index sigs to unique constraint sigs,
which we were doing previously by mistake. As their signatures
were compatible, things "worked" but once index sigs changed
col name sortin... | test_nothing_changed_cols_unsorted | python | sqlalchemy/alembic | tests/test_autogen_indexes.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_autogen_indexes.py | MIT |
def test_repr_custom_type(self, modname, construct):
"""test #1167 as well as other user defined type variations"""
self.autogen_context.opts["user_module_prefix"] = None
class MyType(UserDefinedType):
pass
if modname == "sqlaname":
MyType.__module__ = mod = "s... | test #1167 as well as other user defined type variations | test_repr_custom_type | python | sqlalchemy/alembic | tests/test_autogen_render.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_autogen_render.py | MIT |
def test_render_check_constraint_renamed(self):
"""test that constraints from autogenerate render with
the naming convention name explicitly. These names should
be frozen into the migration scripts so that they remain
the same if the application's naming convention changes.
How... | test that constraints from autogenerate render with
the naming convention name explicitly. These names should
be frozen into the migration scripts so that they remain
the same if the application's naming convention changes.
However, op.create_table() and others need to be careful that
... | test_render_check_constraint_renamed | python | sqlalchemy/alembic | tests/test_autogen_render.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_autogen_render.py | MIT |
def test_config_file_failure_modes(self):
"""with two config files supported at the same time, test failure
modes with multiple --config directives
"""
c1 = config.CommandLine()
with expect_raises_message(
util.CommandError, "only one ini file may be indicated"
... | with two config files supported at the same time, test failure
modes with multiple --config directives
| test_config_file_failure_modes | python | sqlalchemy/alembic | tests/test_command.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_command.py | MIT |
def test_config_file_resolution(
self, args, expected_toml, expected_conf, pop_alembic_config_env
):
"""with two config files supported at the same time, test resolution
of --config / ALEMBIC_CONFIG to always "do what's expected"
"""
c1 = config.CommandLine()
if "ALE... | with two config files supported at the same time, test resolution
of --config / ALEMBIC_CONFIG to always "do what's expected"
| test_config_file_resolution | python | sqlalchemy/alembic | tests/test_command.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_command.py | MIT |
def test_init_file_relative_version_token(
self,
template,
directory,
toml_file_name,
config_file_name,
expected_toml_location,
expected_ini_location,
clear_staging_dir,
):
"""in 1.16.0 with the advent of pyproject.toml, we are also rendering
... | in 1.16.0 with the advent of pyproject.toml, we are also rendering
the script_location value relative to the ``%(here)s`` token, if
the given path is a relative path. ``%(here)s`` is relative to the
owning config file either alembic.ini or pyproject.toml.
| test_init_file_relative_version_token | python | sqlalchemy/alembic | tests/test_command.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_command.py | MIT |
def test_add_column_schema_type(self):
"""Test that a schema type generates its constraints...."""
context = op_fixture()
op.add_column(
"t1", Column("c1", Boolean(create_constraint=True), nullable=False)
)
context.assert_(
"ALTER TABLE t1 ADD COLUMN c1 BO... | Test that a schema type generates its constraints.... | test_add_column_schema_type | python | sqlalchemy/alembic | tests/test_op.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_op.py | MIT |
def test_add_column_schema_type_checks_rule(self):
"""Test that a schema type doesn't generate a
constraint based on check rule."""
context = op_fixture("postgresql")
op.add_column(
"t1", Column("c1", Boolean(create_constraint=True), nullable=False)
)
context.... | Test that a schema type doesn't generate a
constraint based on check rule. | test_add_column_schema_type_checks_rule | python | sqlalchemy/alembic | tests/test_op.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_op.py | MIT |
def test_add_foreign_key_composite_self_referential(self):
"""test #1215
the same column name is present on both sides.
"""
context = op_fixture()
op.create_foreign_key(
"fk_test", "t1", "t1", ["foo", "bar"], ["bat", "bar"]
)
context.assert_(
... | test #1215
the same column name is present on both sides.
| test_add_foreign_key_composite_self_referential | python | sqlalchemy/alembic | tests/test_op.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_op.py | MIT |
def test_primary_key_skip(self):
"""Test that SERIAL cols are just skipped"""
t1 = Table(
"sometable", self.metadata, Column("id", Integer, primary_key=True)
)
t2 = Table(
"sometable", MetaData(), Column("id", Integer, primary_key=True)
)
assert no... | Test that SERIAL cols are just skipped | test_primary_key_skip | python | sqlalchemy/alembic | tests/test_postgresql.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_postgresql.py | MIT |
def test_inline_exclude_constraint_text(self):
"""test for #1184.
Requires SQLAlchemy 2.0.5 due to issue
https://github.com/sqlalchemy/sqlalchemy/issues/9401
"""
autogen_context = self.autogen_context
m = MetaData()
t = Table(
"TTable",
... | test for #1184.
Requires SQLAlchemy 2.0.5 due to issue
https://github.com/sqlalchemy/sqlalchemy/issues/9401
| test_inline_exclude_constraint_text | python | sqlalchemy/alembic | tests/test_postgresql.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_postgresql.py | MIT |
def test_ignore_for_non_recursive(self, non_recursive_fixture):
"""test traversal is non-recursive when the feature is not enabled
(subdirectories are ignored).
"""
self._setup_revision_files(
[
"r0",
"r1",
("dir_1", ["r2", "r... | test traversal is non-recursive when the feature is not enabled
(subdirectories are ignored).
| test_ignore_for_non_recursive | python | sqlalchemy/alembic | tests/test_script_consumption.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_script_consumption.py | MIT |
def test_downgrade_to_existing(self):
"""test for #838; downgrade to a revision that's already in
current heads, but is not itself a head."""
self._assert_downgrade(
self.a.revision, [self.a.revision], [], {self.a.revision}
) | test for #838; downgrade to a revision that's already in
current heads, but is not itself a head. | test_downgrade_to_existing | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_downgrade_to_existing_head(self):
"""test for #839; downgrade to a revision that's already in current
heads, which *is* itself a head."""
self._assert_downgrade(
self.e.revision, [self.e.revision], [], {self.e.revision}
) | test for #839; downgrade to a revision that's already in current
heads, which *is* itself a head. | test_downgrade_to_existing_head | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_relative_downgrade_baseplus2(self):
"""base+2 points to b, no branch label, drop everything above b."""
self._assert_downgrade(
"base+2",
[self.d2.revision, self.d1.revision],
[
self.down_(self.d1),
self.down_(self.c1),
... | base+2 points to b, no branch label, drop everything above b. | test_relative_downgrade_baseplus2 | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_relative_downgrade_branchplus2(self):
"""
Correct behaviour (per
https://github.com/sqlalchemy/alembic/pull/763#issuecomment-738741297)
Only the c2branch should be downgraded, right back to base+2 = b
"""
self._assert_downgrade(
"c2branch@base+2",
... |
Correct behaviour (per
https://github.com/sqlalchemy/alembic/pull/763#issuecomment-738741297)
Only the c2branch should be downgraded, right back to base+2 = b
| test_relative_downgrade_branchplus2 | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_downgrade_single_branch_c1branch(self):
"""Use branch label to specify the branch to downgrade."""
self._assert_downgrade(
f"c1branch@{self.b.revision}",
(self.c1.revision, self.d2.revision),
[
self.down_(self.c1),
],
{... | Use branch label to specify the branch to downgrade. | test_downgrade_single_branch_c1branch | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_downgrade_single_branch_c1branch_from_d1_head(self):
"""Use branch label to specify the branch (where the branch label is
not on the head revision)."""
self._assert_downgrade(
f"c2branch@{self.b.revision}",
(self.c1.revision, self.d2.revision),
[
... | Use branch label to specify the branch (where the branch label is
not on the head revision). | test_downgrade_single_branch_c1branch_from_d1_head | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_downgrade_single_branch_c2(self):
"""Use a revision on the branch (not head) to specify the branch."""
self._assert_downgrade(
f"{self.c2.revision}@{self.b.revision}",
(self.d1.revision, self.d2.revision),
[
self.down_(self.d2),
... | Use a revision on the branch (not head) to specify the branch. | test_downgrade_single_branch_c2 | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_downgrade_single_branch_d1(self):
"""Use the head revision to specify the branch."""
self._assert_downgrade(
f"{self.d1.revision}@{self.b.revision}",
(self.d1.revision, self.d2.revision),
[
self.down_(self.d1),
self.down_(self.... | Use the head revision to specify the branch. | test_downgrade_single_branch_d1 | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_downgrade_no_effect_branched(self):
"""Added for good measure when there are multiple branches."""
self._assert_downgrade(
self.c2.revision,
[self.d1.revision, self.c2.revision],
[],
{self.d1.revision, self.c2.revision},
)
self._as... | Added for good measure when there are multiple branches. | test_downgrade_no_effect_branched | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def setup_class(cls):
"""
33e21c000cfe -> 178d4e761bbd (head),
2bef33cb3a58, 3904558db1c6, 968330f320d -> 33e21c000cfe (mergepoint)
46c99f866004 -> 18f46b42410d (head),
2bef33cb3a58, 3904558db1c6, 968330f320d -> 46c99f866004 (mergepoint)
f0fa4315825 -> 3904558db1c6 (bran... |
33e21c000cfe -> 178d4e761bbd (head),
2bef33cb3a58, 3904558db1c6, 968330f320d -> 33e21c000cfe (mergepoint)
46c99f866004 -> 18f46b42410d (head),
2bef33cb3a58, 3904558db1c6, 968330f320d -> 46c99f866004 (mergepoint)
f0fa4315825 -> 3904558db1c6 (branchpoint),
--------------... | setup_class | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_downgrade_independent_branch(self):
"""c2branch depends on c1branch so can be taken down on its own.
Current behaviour also takes down the dependency unnecessarily."""
self._assert_downgrade(
f"c2branch@{self.b.revision}",
(self.d1.revision, self.d2.revision),
... | c2branch depends on c1branch so can be taken down on its own.
Current behaviour also takes down the dependency unnecessarily. | test_downgrade_independent_branch | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def test_downgrade_branch_dependency(self):
"""c2branch depends on c1branch so taking down c1branch requires taking
down both"""
destination = f"c1branch@{self.b.revision}"
source = self.d1.revision, self.d2.revision
revs = self.env._downgrade_revs(destination, source)
# ... | c2branch depends on c1branch so taking down c1branch requires taking
down both | test_downgrade_branch_dependency | python | sqlalchemy/alembic | tests/test_version_traversal.py | https://github.com/sqlalchemy/alembic/blob/master/tests/test_version_traversal.py | MIT |
def build_instruction_kwargs(row: dict) -> dict:
"""Builds the list of `kwargs` for each instruction in `instruction_id_list`."""
kwargs = row["kwargs"]
if kwargs is None:
return {"valid_kwargs_json": False}
try:
kwargs = json.loads(row["kwargs"])
except json.JSONDecodeError:
... | Builds the list of `kwargs` for each instruction in `instruction_id_list`. | build_instruction_kwargs | python | huggingface/smollm | text/data/smoltalk/constraints/filter_ifeval_data.py | https://github.com/huggingface/smollm/blob/master/text/data/smoltalk/constraints/filter_ifeval_data.py | Apache-2.0 |
def filter_not_valid_rows(row: dict) -> bool:
"""Filters out rows which their JSON kwargs are not valid or that the instructions
in their `instruction_id_list` conflict each other."""
valid_kwargs_json = row["valid_kwargs_json"]
if not valid_kwargs_json:
return False
instruction_id_list = r... | Filters out rows which their JSON kwargs are not valid or that the instructions
in their `instruction_id_list` conflict each other. | filter_not_valid_rows | python | huggingface/smollm | text/data/smoltalk/constraints/filter_ifeval_data.py | https://github.com/huggingface/smollm/blob/master/text/data/smoltalk/constraints/filter_ifeval_data.py | Apache-2.0 |
def get_ifeval_results(row: dict) -> dict:
"""Checks if the `response` correct is OK using the IFEval benchmark code from `lm-evaluation-harness`."""
results = [row["response"]]
doc = row.copy()
doc["kwargs"] = json.loads(doc["kwargs"])
try:
return process_results(doc, results)
except Ex... | Checks if the `response` correct is OK using the IFEval benchmark code from `lm-evaluation-harness`. | get_ifeval_results | python | huggingface/smollm | text/data/smoltalk/constraints/filter_ifeval_data.py | https://github.com/huggingface/smollm/blob/master/text/data/smoltalk/constraints/filter_ifeval_data.py | Apache-2.0 |
def update_summary_chat(self, chat_display: tk.Text, sender: str, message: str):
"""Update the summary chat display with new message"""
chat_display.config(state='normal')
# Add the message with appropriate styling
chat_display.insert(tk.END, "\n") # Add spacing
chat_di... | Update the summary chat display with new message | update_summary_chat | python | huggingface/smollm | tools/smol_tools/demo_tkinter.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/demo_tkinter.py | Apache-2.0 |
def process_summary_question(self, original_text: str, question: str,
chat_display: tk.Text, chat_input: tk.Text):
"""Process a follow-up question about the summarized text"""
if not question.strip():
return
# Clear input
chat_inpu... | Process a follow-up question about the summarized text | process_summary_question | python | huggingface/smollm | tools/smol_tools/demo_tkinter.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/demo_tkinter.py | Apache-2.0 |
def get_weather(city: str) -> str:
"""
Returns the weather forecast for a given city.
Args:
city: The name of the city.
Returns:
A string with a mock weather forecast.
"""
url = 'https://wttr.in/{}?format=+%C,+%t'.format(city)
res = requests.get(url).text
return f"The ... |
Returns the weather forecast for a given city.
Args:
city: The name of the city.
Returns:
A string with a mock weather forecast.
| get_weather | python | huggingface/smollm | tools/smol_tools/smol_tools/agent.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/smol_tools/agent.py | Apache-2.0 |
def open_webbrowser(url: str) -> str:
"""
This is a tool that opens a web browser to the given website.
If the user asks to open a website or a browser, you should use this tool.
Args:
url: The url to open.
"""
webbrowser.open(url)
return f"I opened {url.replace('https://', '').repl... |
This is a tool that opens a web browser to the given website.
If the user asks to open a website or a browser, you should use this tool.
Args:
url: The url to open.
| open_webbrowser | python | huggingface/smollm | tools/smol_tools/smol_tools/agent.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/smol_tools/agent.py | Apache-2.0 |
def _warm_up(self):
"""Warm up the model with a test prompt"""
print(f"Warming up {self.__class__.__name__}...")
test_text = "This is a test message to warm up the model."
# Consume the generator to complete the warm-up
for _ in self.process(test_text):
pass
p... | Warm up the model with a test prompt | _warm_up | python | huggingface/smollm | tools/smol_tools/smol_tools/base.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/smol_tools/base.py | Apache-2.0 |
def _create_chat_completion(
self,
messages: List[Dict[str, str]],
temperature: float = 0.4,
top_p: float = 0.9,
top_k: int = 50,
repeat_penalty: float = 1.2,
max_tokens: int = 256
) -> Generator[str, None, None]:
"""Helper method to create chat comp... | Helper method to create chat completions with standard parameters | _create_chat_completion | python | huggingface/smollm | tools/smol_tools/smol_tools/base.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/smol_tools/base.py | Apache-2.0 |
def start_new_chat(self):
"""Start a new chat with a unique ID"""
self.current_chat_id = datetime.now().strftime("%Y%m%d_%H%M%S")
self.chat_history = []
self._original_chat_state = None | Start a new chat with a unique ID | start_new_chat | python | huggingface/smollm | tools/smol_tools/smol_tools/chatter.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/smol_tools/chatter.py | Apache-2.0 |
def save_current_chat(self, title: str = None, overwrite: bool = False):
"""Save the current chat to disk if it has any messages"""
if not self.chat_history:
return
if title:
# If overwriting, use existing chat_id if it matches the title
if not ov... | Save the current chat to disk if it has any messages | save_current_chat | python | huggingface/smollm | tools/smol_tools/smol_tools/chatter.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/smol_tools/chatter.py | Apache-2.0 |
def is_chat_modified(self) -> bool:
"""Check if the current chat has been modified since loading"""
if self._original_chat_state is None:
# New chat that hasn't been saved yet
return len(self.chat_history) > 0
current_state = [msg.to_dict() for msg in self.ch... | Check if the current chat has been modified since loading | is_chat_modified | python | huggingface/smollm | tools/smol_tools/smol_tools/chatter.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/smol_tools/chatter.py | Apache-2.0 |
def get_saved_chats(self) -> List[str]:
"""Get list of saved chat IDs"""
chats = []
for filename in os.listdir(self.chats_dir):
if filename.startswith('chat_') and filename.endswith('.json'):
chat_id = filename[5:-5] # Remove 'chat_' prefix and '.json' suffix
... | Get list of saved chat IDs | get_saved_chats | python | huggingface/smollm | tools/smol_tools/smol_tools/chatter.py | https://github.com/huggingface/smollm/blob/master/tools/smol_tools/smol_tools/chatter.py | Apache-2.0 |
def _check_remaining_indices(self) -> List[int]:
"""When taking screenshots of some websites, it often fails for some reasons.
Therefore, we do a try/except and skip the indices of the json where it failed.
We can go through them again to increase our success rate.
This function checks t... | When taking screenshots of some websites, it often fails for some reasons.
Therefore, we do a try/except and skip the indices of the json where it failed.
We can go through them again to increase our success rate.
This function checks the indices of the json files that are yet to be processed.
... | _check_remaining_indices | python | huggingface/smollm | vision/data/datasets_processing_scripts/build_websight_v02/python_scripts/04_screenshot_html_codes.py | https://github.com/huggingface/smollm/blob/master/vision/data/datasets_processing_scripts/build_websight_v02/python_scripts/04_screenshot_html_codes.py | Apache-2.0 |
def _modify_image_urls(self, html_code: str) -> str:
"""When an image URL appears more than once, when the HTML is rendered,
the same image is displayed. The trick is to add a `_` at the end of the
keyword of the URL to generate another image, still corresponding to the
same keyword.
... | When an image URL appears more than once, when the HTML is rendered,
the same image is displayed. The trick is to add a `_` at the end of the
keyword of the URL to generate another image, still corresponding to the
same keyword.
| _modify_image_urls | python | huggingface/smollm | vision/data/datasets_processing_scripts/build_websight_v02/python_scripts/04_screenshot_html_codes.py | https://github.com/huggingface/smollm/blob/master/vision/data/datasets_processing_scripts/build_websight_v02/python_scripts/04_screenshot_html_codes.py | Apache-2.0 |
def create_dict_qbench(split):
"""`split` is "train", "validation" or "test"."""
dict_qbench = {"image": [], "question": [], "label": [], "tested_labels": []}
#
with open(PATHS_JSON_QBENCH[split], "r") as f:
data_qbench = json.load(f)
#
for example in tqdm(data_qbench):
dict_qben... | `split` is "train", "validation" or "test". | create_dict_qbench | python | huggingface/smollm | vision/data/datasets_processing_scripts/integrate_evaluation_benchmarks_chatbot/qbench.py | https://github.com/huggingface/smollm/blob/master/vision/data/datasets_processing_scripts/integrate_evaluation_benchmarks_chatbot/qbench.py | Apache-2.0 |
def require_torch(test_case):
"""
Decorator marking a test that requires PyTorch.
These tests are skipped when PyTorch isn't installed.
"""
if not is_torch_available():
return unittest.skip("test requires PyTorch")(test_case)
else:
return test_case |
Decorator marking a test that requires PyTorch.
These tests are skipped when PyTorch isn't installed.
| require_torch | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_torch_no_gpus(test_case):
"""
Decorator marking a test that requires a setup without GPUs (in PyTorch). These tests are skipped on a machine with GPUs.
To run *only* the no gpu tests, assuming all test names contain no_gpu: $ pytest -sv ./tests -k "no_gpu"
"""
import torch
if is_to... |
Decorator marking a test that requires a setup without GPUs (in PyTorch). These tests are skipped on a machine with GPUs.
To run *only* the no gpu tests, assuming all test names contain no_gpu: $ pytest -sv ./tests -k "no_gpu"
| require_torch_no_gpus | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_torch_multi_gpu(test_case):
"""
Decorator marking a test that requires a multi-GPU setup (in PyTorch). These tests are skipped on a machine without
multiple GPUs.
To run *only* the multi_gpu tests, assuming all test names contain multi_gpu: $ pytest -sv ./tests -k "multi_gpu"
"""
if... |
Decorator marking a test that requires a multi-GPU setup (in PyTorch). These tests are skipped on a machine without
multiple GPUs.
To run *only* the multi_gpu tests, assuming all test names contain multi_gpu: $ pytest -sv ./tests -k "multi_gpu"
| require_torch_multi_gpu | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_torch_non_multi_gpu(test_case):
"""
Decorator marking a test that requires 0 or 1 GPU setup (in PyTorch).
"""
if not is_torch_available():
return unittest.skip("test requires PyTorch")(test_case)
import torch
if torch.cuda.device_count() > 1:
return unittest.skip("t... |
Decorator marking a test that requires 0 or 1 GPU setup (in PyTorch).
| require_torch_non_multi_gpu | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_torch_up_to_2_gpus(test_case):
"""
Decorator marking a test that requires 0 or 1 or 2 GPU setup (in PyTorch).
"""
if not is_torch_available():
return unittest.skip("test requires PyTorch")(test_case)
import torch
if torch.cuda.device_count() > 2:
return unittest.ski... |
Decorator marking a test that requires 0 or 1 or 2 GPU setup (in PyTorch).
| require_torch_up_to_2_gpus | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_torch_gpu(test_case):
"""Decorator marking a test that requires CUDA and PyTorch."""
if torch_device != "cuda":
return unittest.skip("test requires CUDA")(test_case)
else:
return test_case | Decorator marking a test that requires CUDA and PyTorch. | require_torch_gpu | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_deepspeed(test_case):
"""
Decorator marking a test that requires deepspeed
"""
if not is_deepspeed_available():
return unittest.skip("test requires deepspeed")(test_case)
else:
return test_case |
Decorator marking a test that requires deepspeed
| require_deepspeed | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_bnb(test_case):
"""
Decorator marking a test that requires bitsandbytes
"""
if not is_bnb_available():
return unittest.skip("test requires bitsandbytes from https://github.com/facebookresearch/bitsandbytes")(
test_case
)
else:
return test_case |
Decorator marking a test that requires bitsandbytes
| require_bnb | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_bnb_non_decorator():
"""
Non-Decorator function that would skip a test if bitsandbytes is missing
"""
if not is_bnb_available():
raise SkipTest("Test requires bitsandbytes from https://github.com/facebookresearch/bitsandbytes") |
Non-Decorator function that would skip a test if bitsandbytes is missing
| require_bnb_non_decorator | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def set_seed(seed: int = 42):
"""
Helper function for reproducible behavior to set the seed in ``random``, ``numpy``, ``torch``
Args:
seed (:obj:`int`): The seed to set.
"""
random.seed(seed)
np.random.seed(seed)
if is_torch_available():
torch.manual_seed(seed)
torch... |
Helper function for reproducible behavior to set the seed in ``random``, ``numpy``, ``torch``
Args:
seed (:obj:`int`): The seed to set.
| set_seed | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def get_gpu_count():
"""
Return the number of available gpus (regardless of whether torch or tf is used)
"""
if is_torch_available():
import torch
return torch.cuda.device_count()
else:
return 0 |
Return the number of available gpus (regardless of whether torch or tf is used)
| get_gpu_count | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def torch_assert_equal(actual, expected, **kwargs):
"""
compare two tensors or non-tensor numbers for their equality
"""
# assert_close was added around pt-1.9, it does better checks - e.g will check dimensions match
return torch.testing.assert_close(actual, expected, rtol=0.0, atol=0.0, **kwargs) |
compare two tensors or non-tensor numbers for their equality
| torch_assert_equal | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def torch_assert_close(actual, expected, **kwargs):
"""
compare two tensors or non-tensor numbers for their closeness.
"""
# assert_close was added around pt-1.9, it does better checks - e.g will check dimensions match
return torch.testing.assert_close(actual, expected, **kwargs) |
compare two tensors or non-tensor numbers for their closeness.
| torch_assert_close | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def require_torch_bf16(test_case):
"""Decorator marking a test that requires CUDA hardware supporting bf16 and PyTorch >= 1.9."""
if not is_torch_bf16_available():
return unittest.skip("test requires CUDA hardware supporting bf16 and PyTorch >= 1.9")(test_case)
else:
return test_case | Decorator marking a test that requires CUDA hardware supporting bf16 and PyTorch >= 1.9. | require_torch_bf16 | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def get_tests_dir(append_path=None):
"""
Args:
append_path: optional path to append to the tests dir path
Return:
The full path to the `tests` dir, so that the tests can be invoked from anywhere. Optionally `append_path` is
joined after the `tests` dir the former is provided.
"... |
Args:
append_path: optional path to append to the tests dir path
Return:
The full path to the `tests` dir, so that the tests can be invoked from anywhere. Optionally `append_path` is
joined after the `tests` dir the former is provided.
| get_tests_dir | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def ExtendSysPath(path: Union[str, os.PathLike]) -> Iterator[None]:
"""
Temporary add given path to `sys.path`.
Usage ::
with ExtendSysPath('/path/to/dir'):
mymodule = importlib.import_module('mymodule')
"""
path = os.fspath(path)
try:
sys.path.insert(0, path)
... |
Temporary add given path to `sys.path`.
Usage ::
with ExtendSysPath('/path/to/dir'):
mymodule = importlib.import_module('mymodule')
| ExtendSysPath | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def get_env(self):
"""
Return a copy of the ``os.environ`` object that sets up ``PYTHONPATH`` correctly. This is useful
for invoking external programs from the test suite - e.g. distributed training.
It always inserts ``.`` first, then ``./tests`` depending on the test suite type and
... |
Return a copy of the ``os.environ`` object that sets up ``PYTHONPATH`` correctly. This is useful
for invoking external programs from the test suite - e.g. distributed training.
It always inserts ``.`` first, then ``./tests`` depending on the test suite type and
finally the preset ``PYT... | get_env | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def get_auto_remove_tmp_dir(self, tmp_dir=None, before=None, after=None):
"""
Args:
tmp_dir (:obj:`string`, `optional`):
if :obj:`None`:
- a unique temporary path will be created
- sets ``before=True`` if ``before`` is :obj:`None`
... |
Args:
tmp_dir (:obj:`string`, `optional`):
if :obj:`None`:
- a unique temporary path will be created
- sets ``before=True`` if ``before`` is :obj:`None`
- sets ``after=True`` if ``after`` is :obj:`None`
else:
... | get_auto_remove_tmp_dir | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def mockenv_context(*remove, **update):
"""
Temporarily updates the ``os.environ`` dictionary in-place. Similar to mockenv
The ``os.environ`` dictionary is updated in-place so that the modification is sure to work in all situations.
Args:
remove: Environment variables to remove.
update: Di... |
Temporarily updates the ``os.environ`` dictionary in-place. Similar to mockenv
The ``os.environ`` dictionary is updated in-place so that the modification is sure to work in all situations.
Args:
remove: Environment variables to remove.
update: Dictionary of environment variables and values to... | mockenv_context | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def get_xdist_worker_id():
"""
when run under pytest-xdist returns the worker id (int), otherwise returns 0
"""
worker_id_string = os.environ.get("PYTEST_XDIST_WORKER", "gw0")
return int(worker_id_string[2:]) # strip "gw" |
when run under pytest-xdist returns the worker id (int), otherwise returns 0
| get_xdist_worker_id | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def pytest_addoption_shared(parser):
"""
This function is to be called from `conftest.py` via `pytest_addoption` wrapper that has to be defined there.
It allows loading both `conftest.py` files at once without causing a failure due to adding the same `pytest`
option.
"""
option = "--make-repor... |
This function is to be called from `conftest.py` via `pytest_addoption` wrapper that has to be defined there.
It allows loading both `conftest.py` files at once without causing a failure due to adding the same `pytest`
option.
| pytest_addoption_shared | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def pytest_terminal_summary_main(tr, id):
"""
Generate multiple reports at the end of test suite run - each report goes into a dedicated file in the current
directory. The report files are prefixed with the test suite name.
This function emulates --duration and -rA pytest arguments.
This function ... |
Generate multiple reports at the end of test suite run - each report goes into a dedicated file in the current
directory. The report files are prefixed with the test suite name.
This function emulates --duration and -rA pytest arguments.
This function is to be called from `conftest.py` via `pytest_te... | pytest_terminal_summary_main | python | huggingface/smollm | vision/m4/testing_utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/testing_utils.py | Apache-2.0 |
def _compute_relaxed_vqa_accuracy(self, generated_texts_unique, answers_unique, normalize_text_fn):
"""
From https://aclanthology.org/2022.findings-acl.177.pdf
We use a relaxed accuracy measure for the numeric answers to allow a minor inaccuracy that may result from the automatic data extraction... |
From https://aclanthology.org/2022.findings-acl.177.pdf
We use a relaxed accuracy measure for the numeric answers to allow a minor inaccuracy that may result from the automatic data extraction process. We consider an answer to be correct if it is within 5% of the gold answer. For non-numeric answers, w... | _compute_relaxed_vqa_accuracy | python | huggingface/smollm | vision/m4/evaluation/custom_metrics/open_ended_vqa_metrics.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/custom_metrics/open_ended_vqa_metrics.py | Apache-2.0 |
def vqa_normalize_text(text: str) -> str:
"""Process a text
Source: https://github.com/GT-Vision-Lab/VQA/blob/master/PythonEvaluationTools/vqaEvaluation/vqaEval.py
1. Conversion of characters to lower case
2. Replace breaking lines and tabulations by a white space
3. Replace punctuations by a white ... | Process a text
Source: https://github.com/GT-Vision-Lab/VQA/blob/master/PythonEvaluationTools/vqaEvaluation/vqaEval.py
1. Conversion of characters to lower case
2. Replace breaking lines and tabulations by a white space
3. Replace punctuations by a white space
4. Conversion of numbers written in let... | vqa_normalize_text | python | huggingface/smollm | vision/m4/evaluation/custom_metrics/utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/custom_metrics/utils.py | Apache-2.0 |
def check_is_number(string):
"""
Check if the given string is a number
"""
try:
_ = convert_to_number(string)
return True
except ValueError:
return False |
Check if the given string is a number
| check_is_number | python | huggingface/smollm | vision/m4/evaluation/custom_metrics/utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/custom_metrics/utils.py | Apache-2.0 |
def normalize_str_mmmu(string):
"""
Normalize the str to lower case and make them float numbers if possible.
"""
# check if characters in the string
# if number, numerize it.
string = string.strip()
if string.startswith("Answer: "):
string = string.replace("Answer: ", "")
is_nu... |
Normalize the str to lower case and make them float numbers if possible.
| normalize_str_mmmu | python | huggingface/smollm | vision/m4/evaluation/custom_metrics/utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/custom_metrics/utils.py | Apache-2.0 |
def extract_numbers_mmmu(string):
"""
Exact all forms of numbers from a string with regex.
"""
# Pattern for numbers with commas
pattern_commas = r"-?\b\d{1,3}(?:,\d{3})+\b"
# Pattern for scientific notation
pattern_scientific = r"-?\d+(?:\.\d+)?[eE][+-]?\d+"
# Pattern for simple numbers... |
Exact all forms of numbers from a string with regex.
| extract_numbers_mmmu | python | huggingface/smollm | vision/m4/evaluation/custom_metrics/utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/custom_metrics/utils.py | Apache-2.0 |
def parse_open_response_mmmu(response, normalize_text_fn):
"""
Parse the prediction from the generated response.
Return a list of predicted strings or numbers
"""
def get_key_subresponses(response):
key_responses = []
response = response.strip().strip(".").lower()
sub_respon... |
Parse the prediction from the generated response.
Return a list of predicted strings or numbers
| parse_open_response_mmmu | python | huggingface/smollm | vision/m4/evaluation/custom_metrics/utils.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/custom_metrics/utils.py | Apache-2.0 |
def _split_to_single_caption(caption):
"""This function is mainly used in Localized Narratives where a paragraph can contain
multiple relevant captions to a single image. We split the paragraph into multiple
captions and then return each as an individual sample.
"""
extended = []
captions = capt... | This function is mainly used in Localized Narratives where a paragraph can contain
multiple relevant captions to a single image. We split the paragraph into multiple
captions and then return each as an individual sample.
| _split_to_single_caption | python | huggingface/smollm | vision/m4/evaluation/scripts/create_sample_evaluation_datasets_simplified.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/scripts/create_sample_evaluation_datasets_simplified.py | Apache-2.0 |
def fetch_training_run(training_run_name):
"""
Fetch training run. There can only be one corresponding training run.
If not, double check the tags (killed, failed, etc.)
"""
matching_runs = []
runs = api.runs(f"{args.wandb_entity}/{args.wandb_training_project}")
... |
Fetch training run. There can only be one corresponding training run.
If not, double check the tags (killed, failed, etc.)
| fetch_training_run | python | huggingface/smollm | vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | Apache-2.0 |
def fetch_evaluation_run(evaluation_run_name):
"""
Fetch evaluation run. There can only be one corresponding evaluation run at most.
If not, double check the tags (killed, failed, etc.)
"""
matching_runs = []
runs = api.runs(f"{args.wandb_entity}/{args.wandb_eval_project... |
Fetch evaluation run. There can only be one corresponding evaluation run at most.
If not, double check the tags (killed, failed, etc.)
| fetch_evaluation_run | python | huggingface/smollm | vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | Apache-2.0 |
def get_logged_eval_values(evaluation_run):
"""
If `evaluation_run` already exists, get the already logged values into a dictionary.
"""
logged_evaluation_values = defaultdict()
if evaluation_run is not None:
for row in evaluation_run.scan_history():
... |
If `evaluation_run` already exists, get the already logged values into a dictionary.
| get_logged_eval_values | python | huggingface/smollm | vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | Apache-2.0 |
def get_evaluations_values_from_json():
"""
Load all values from the json file
"""
evaluation_values = defaultdict(lambda: defaultdict())
for evaluation_jsonl_file in args.evaluation_jsonl_files:
with open(evaluation_jsonl_file, "r") as f:
for line in ... |
Load all values from the json file
| get_evaluations_values_from_json | python | huggingface/smollm | vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | Apache-2.0 |
def convert_training_run_to_dict(training_run):
"""
Get all the logged values from the training into a dictionary.
"""
training_history = training_run.scan_history()
d = defaultdict(dict)
for row in training_history:
if "num_opt_steps" not in row:
... |
Get all the logged values from the training into a dictionary.
| convert_training_run_to_dict | python | huggingface/smollm | vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | https://github.com/huggingface/smollm/blob/master/vision/m4/evaluation/scripts/sync_evaluations_on_wandb.py | Apache-2.0 |
def from_pretrained(cls, *model_args, is_resume=False, new_model=False, **kwargs):
"""
Use this method when loading an already pretrained vloom model - either from a checkpoint or from hub.
For creating an untrained model use `pretrained_models` instead.
"""
# config is:
... |
Use this method when loading an already pretrained vloom model - either from a checkpoint or from hub.
For creating an untrained model use `pretrained_models` instead.
| from_pretrained | python | huggingface/smollm | vision/m4/models/custom_modules.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/custom_modules.py | Apache-2.0 |
def __init__(
self,
num_embeddings,
num_additional_embeddings,
embedding_dim,
partially_freeze=False,
device=None,
dtype=None,
padding_idx=None,
**kwargs,
) -> None:
"""
num_additional_embeddings: int. Number of additional embed... |
num_additional_embeddings: int. Number of additional embeddings. Only useful when you `partially_freeze=True`.
partially_freeze: bool. If True, the regular `weight` will be frozen. `additional_weight` is never frozen.
Note: there are a lot of other parameters to initialize a standard `nn.Embed... | __init__ | python | huggingface/smollm | vision/m4/models/custom_modules.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/custom_modules.py | Apache-2.0 |
def forward(self, input_ids):
"""
we have 2 embeddings, with different indices - one pretrained self.weight and another
self.additional_embedding.weight that is being trained.
in order to make a lookup of the input ids, we:
1. find out the indices of the entries belonging to the... |
we have 2 embeddings, with different indices - one pretrained self.weight and another
self.additional_embedding.weight that is being trained.
in order to make a lookup of the input ids, we:
1. find out the indices of the entries belonging to the 2nd embedding
2. extract those v... | forward | python | huggingface/smollm | vision/m4/models/custom_modules.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/custom_modules.py | Apache-2.0 |
def __init__(
self,
in_features: int,
out_features: int,
out_additional_features: int = 0,
bias: bool = True,
partially_freeze: bool = True,
device=None,
dtype=None,
) -> None:
"""
out_additional_features: int. Number of additional trai... |
out_additional_features: int. Number of additional trainable dimensions. Only makes sense when `partially_freeze=True`.
partially_freeze: bool. If True, the regular `weight` will be frozen and extra parameters (if any) will be trainable. If False, default to the regular behavior of nn.Linear.
| __init__ | python | huggingface/smollm | vision/m4/models/custom_modules.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/custom_modules.py | Apache-2.0 |
def extra_repr(self) -> str:
"""Overwriting `nn.Linear.extra_repr` to include new parameters."""
return "in_features={}, out_features={}, out_additional_features={}, bias={}, partially_freeze={}".format(
self.in_features,
self.out_features,
self.out_additional_feature... | Overwriting `nn.Linear.extra_repr` to include new parameters. | extra_repr | python | huggingface/smollm | vision/m4/models/custom_modules.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/custom_modules.py | Apache-2.0 |
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
... |
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
| to_dict | python | huggingface/smollm | vision/m4/models/idefics/configuration_idefics.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/idefics/configuration_idefics.py | Apache-2.0 |
def _make_causal_mask(input_ids_shape: torch.Size, dtype: torch.dtype, past_key_values_length: int = 0):
"""
Make causal mask used for bi-directional self-attention.
"""
bsz, tgt_len = input_ids_shape
mask = torch.full((tgt_len, tgt_len), torch.tensor(torch.finfo(dtype).min))
mask_cond = torch.a... |
Make causal mask used for bi-directional self-attention.
| _make_causal_mask | python | huggingface/smollm | vision/m4/models/idefics/modeling_idefics.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/idefics/modeling_idefics.py | Apache-2.0 |
def rotate_half(x):
"""Rotates half the hidden dims of the input."""
x1 = x[..., : x.shape[-1] // 2]
x2 = x[..., x.shape[-1] // 2 :]
return torch.cat((-x2, x1), dim=-1) | Rotates half the hidden dims of the input. | rotate_half | python | huggingface/smollm | vision/m4/models/idefics/modeling_idefics.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/idefics/modeling_idefics.py | Apache-2.0 |
def forward(
self,
hidden_states: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
position_ids: Optional[torch.LongTensor] = None,
past_key_value: Optional[Tuple[torch.Tensor]] = None,
output_attentions: Optional[bool] = False,
use_cache: Optional[boo... |
Args:
hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`
attention_mask (`torch.FloatTensor`, *optional*): attention mask of size
`(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values... | forward | python | huggingface/smollm | vision/m4/models/idefics/modeling_idefics.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/idefics/modeling_idefics.py | Apache-2.0 |
def tie_weights(self):
"""
Overwrite `transformers.modeling_utils.PreTrainedModel.tie_weights` to handle the case of DecoupledLinear and DecoupledEmbedding.
"""
output_embeddings = self.get_output_embeddings()
input_embeddings = self.get_input_embeddings()
if getattr(sel... |
Overwrite `transformers.modeling_utils.PreTrainedModel.tie_weights` to handle the case of DecoupledLinear and DecoupledEmbedding.
| tie_weights | python | huggingface/smollm | vision/m4/models/idefics/modeling_idefics.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/idefics/modeling_idefics.py | Apache-2.0 |
def forward(
self,
input_ids: torch.LongTensor = None,
attention_mask: Optional[torch.Tensor] = None,
position_ids: Optional[torch.LongTensor] = None,
past_key_values: Optional[List[torch.FloatTensor]] = None,
inputs_embeds: Optional[torch.FloatTensor] = None,
pix... |
Args:
labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
Labels for computing the masked language modeling loss. Indices should either be in `[0, ...,
config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `... | forward | python | huggingface/smollm | vision/m4/models/idefics/modeling_idefics.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/idefics/modeling_idefics.py | Apache-2.0 |
def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
"""
This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch,
num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim)
"""
batch, num_key_value_... |
This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch,
num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim)
| repeat_kv | python | huggingface/smollm | vision/m4/models/perceiver/perceiver.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/perceiver/perceiver.py | Apache-2.0 |
def __init__(self, config) -> None:
"""Perceiver Cross-Attention Module --> let long-form inputs be `context`, resampled embeddings be `latents`"""
super().__init__()
self.config = config
self.hidden_size = config.hidden_size
self.num_heads = config.perceiver_config.resampler_n... | Perceiver Cross-Attention Module --> let long-form inputs be `context`, resampled embeddings be `latents` | __init__ | python | huggingface/smollm | vision/m4/models/perceiver/perceiver.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/perceiver/perceiver.py | Apache-2.0 |
def forward(
self,
latents: torch.Tensor,
context: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
position_ids: Optional[torch.LongTensor] = None,
past_key_value: Optional[Tuple[torch.Tensor]] = None,
output_attentions: bool = False,
use_cach... |
Runs Perceiver Self-Attention, with special (context, latents) appended along the `seq` dimension!
:param context: Tensor of shape [bsz, seq, embed_dim] representing long-form context to resample.
:param latents: Tensor of shape [bsz, n_latents, embed_dim] representing fixed length latents to c... | forward | python | huggingface/smollm | vision/m4/models/perceiver/perceiver.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/perceiver/perceiver.py | Apache-2.0 |
def _flash_attention_forward(
self,
query_states,
key_states,
value_states,
attention_mask,
query_length,
dropout=0.0,
softmax_scale=None,
use_sliding_windows=False,
):
"""
Calls the forward method of Flash Attention - if the in... |
Calls the forward method of Flash Attention - if the input hidden states contain at least one padding token
first unpad the input, then computes the attention scores and pad the final attention scores.
Args:
query_states (`torch.Tensor`):
Input query states to be pa... | _flash_attention_forward | python | huggingface/smollm | vision/m4/models/perceiver/perceiver.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/perceiver/perceiver.py | Apache-2.0 |
def forward(
self,
latents: torch.Tensor,
context: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
position_ids: Optional[torch.LongTensor] = None,
past_key_value: Optional[Tuple[torch.Tensor]] = None,
output_attentions: Optional[bool] = False,
... |
Args:
latents (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`
context (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`
attention_mask (`torch.FloatTensor`, *optional*): attention mask of size
`(... | forward | python | huggingface/smollm | vision/m4/models/perceiver/perceiver.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/perceiver/perceiver.py | Apache-2.0 |
def __init__(
self,
config,
) -> None:
"""
Instantiates a Perceiver Resampler that operates over a sequence of embeddings (say from a ResNet or ViT or
MAE) of a given dimension, performs `depth` blocks of cross-attention with a fixed `n_latents` inputs, then
returns a... |
Instantiates a Perceiver Resampler that operates over a sequence of embeddings (say from a ResNet or ViT or
MAE) of a given dimension, performs `depth` blocks of cross-attention with a fixed `n_latents` inputs, then
returns a Tensor of shape [bsz, n_latents, embed_dim].
:param embed_dim... | __init__ | python | huggingface/smollm | vision/m4/models/perceiver/perceiver.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/perceiver/perceiver.py | Apache-2.0 |
def retrieve_idx_closest_examples(ref_embedding, embeddings_to_compare, num_examples):
"Returns the indices of the `num_examples` closest embeddings in ascending order"
sim = np.dot(embeddings_to_compare, ref_embedding)
# We can achieve linear complexity because we don't need to sort... | Returns the indices of the `num_examples` closest embeddings in ascending order | retrieve_idx_closest_examples | python | huggingface/smollm | vision/m4/models/vgpt2/evaluation_captioning_in_context_vgpt2.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/vgpt2/evaluation_captioning_in_context_vgpt2.py | Apache-2.0 |
def prepare_dataset(self, exs: Dict, **kwargs) -> Dict:
"""
Prepare batch of examples.
Each example (X, y) where y is among (y1, y2, ..., yN) - the labels options -
is turned into [(X, y1), (X, y2), ... (X, yN)].
"""
support_dataset: Dataset = kwargs["support_dataset"]
... |
Prepare batch of examples.
Each example (X, y) where y is among (y1, y2, ..., yN) - the labels options -
is turned into [(X, y1), (X, y2), ... (X, yN)].
| prepare_dataset | python | huggingface/smollm | vision/m4/models/vgpt2/evaluation_classification_in_context_vgpt2.py | https://github.com/huggingface/smollm/blob/master/vision/m4/models/vgpt2/evaluation_classification_in_context_vgpt2.py | Apache-2.0 |
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