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1 | test_update_realm_allow_message_editing | def test_update_realm_allow_message_editing(self) -> None:
self.set_up_db("allow_message_editing", False)
self.set_up_db("message_content_edit_limit_seconds", None)
self.set_up_db("edit_topic_policy", Realm.POLICY_ADMINS_ONLY)
realm = self.update_with_api("allow_message_editing", True)
realm = self.update_with_api("message_content_edit_limit_seconds", 100)
realm = self.update_with_api("edit_topic_policy", Realm.POLICY_EVERYONE)
self.assertEqual(realm.allow_message_editing, True)
self.assertEqual(realm.message_content_edit_limit_seconds, 100)
self.assertEqual(realm.edit_topic_policy, Realm.POLICY_EVERYONE)
realm = self.update_with_api("allow_message_editing", False)
self.assertEqual(realm.allow_message_editing, False)
self.assertEqual(realm.message_content_edit_limit_seconds, 100)
self.assertEqual(realm.edit_topic_policy, Realm.POLICY_EVERYONE)
realm = self.update_with_api("message_content_edit_limit_seconds", 200)
self.assertEqual(realm.allow_message_editing, False)
self.assertEqual(realm.message_content_edit_limit_seconds, 200)
self.assertEqual(realm.edit_topic_policy, Realm.POLICY_EVERYONE)
realm = self.update_with_api("edit_topic_policy", Realm.POLICY_ADMINS_ONLY)
self.assertEqual(realm.allow_message_editing, False)
self.assertEqual(realm.message_content_edit_limit_seconds, 200)
self.assertEqual(realm.edit_topic_policy, Realm.POLICY_ADMINS_ONLY)
realm = self.update_with_api("edit_topic_policy", Realm.POLICY_MODERATORS_ONLY)
self.assertEqual(realm.allow_message_editing, False)
self.assertEqual(realm.message_content_edit_limit_seconds, 200)
self.assertEqual(realm.edit_topic_policy, Realm.POLICY_MODERATORS_ONLY)
realm = self.update_with_api("edit_topic_policy", Realm.POLICY_FULL_MEMBERS_ONLY)
self.assertEqual(realm.allow_message_editing, False)
self.assertEqual(realm.message_content_edit_limit_seconds, 200)
self.assertEqual(realm.edit_topic_policy, Realm.POLICY_FULL_MEMBERS_ONLY)
realm = self.update_with_api("edit_topic_policy", Realm.POLICY_MEMBERS_ONLY)
self.assertEqual(realm.allow_message_editing, False)
self.assertEqual(realm.message_content_edit_limit_seconds, 200)
self.assertEqual(realm.edit_topic_policy, Realm.POLICY_MEMBERS_ONLY)
# Test an invalid value for edit_topic_policy
invalid_edit_topic_policy_value = 10
req = {"edit_topic_policy": orjson.dumps(invalid_edit_topic_policy_value).decode()}
result = self.client_patch("/json/realm", req)
self.assert_json_error(result, "Invalid edit_topic_policy")
# Test 0 is invalid value of message_content_edit_limit_seconds
invalid_message_content_edit_limit_seconds_value = 0
req = {
"message_content_edit_limit_seconds": orjson.dumps(
invalid_message_content_edit_limit_seconds_value
).decode()
}
result = self.client_patch("/json/realm", req)
self.assert_json_error(result, "Bad value for 'message_content_edit_limit_seconds': 0")
| a1f40ccda5d9bbf91122d755f88e8f03f426fc9a | 12 | test_realm.py | 695 | message_edit: Make zero invalid value for message_content_edit_time_limit_seconds.
This commit changes the code to consider zero as an invalid value for
message_content_edit_time_limit_seconds. Now to represent the setting that
user can edit the message anytime, the setting value will be "None" in
database and "unlimited" will be passed to API from clients. | 17,846 | 0 | 490 | 432 | 56 | 84,571 | 138 | zulip | 24 | zerver/tests/test_realm.py | Python | 47 | {
"docstring": "Tests updating the realm property 'allow_message_editing'.",
"language": "en",
"n_whitespaces": 5,
"n_words": 6,
"vocab_size": 6
} | https://github.com/zulip/zulip.git |
|
1 | engine | def engine(self):
raise NotImplementedError
# TODO: make this cache_readonly after docstring inheritance is fixed. | b240370bf83c88589d293b76b4a2409294e06f90 | 6 | parquet_dispatcher.py | 17 | FEAT-#4733: Support fastparquet as engine for `read_parquet` (#4807)
Signed-off-by: Karthik Velayutham <[email protected]> | 35,890 | 0 | 31 | 8 | 14 | 154,270 | 14 | modin | 3 | modin/core/io/column_stores/parquet_dispatcher.py | Python | 2 | {
"docstring": "Return string representing what engine is being used.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/modin-project/modin.git |
|
2 | __truediv__ | def __truediv__(self, other):
if self._delegate_binop(other):
return NotImplemented
return np.true_divide(self, other)
| 6d77c591c59b5678f14ae5af2127eebb7d2415bc | 7 | core.py | 44 | ENH: Adding __array_ufunc__ capability to MaskedArrays.
This enables any ufunc numpy operations that are called on a
MaskedArray to use the masked version of that function automatically
without needing to resort to np.ma.func() calls. | 38,769 | 0 | 42 | 27 | 9 | 160,869 | 10 | numpy | 7 | numpy/ma/core.py | Python | 4 | {
"docstring": "\n Divide other into self, and return a new masked array.\n\n ",
"language": "en",
"n_whitespaces": 25,
"n_words": 10,
"vocab_size": 10
} | https://github.com/numpy/numpy.git |
|
2 | __call__ | def __call__(self, y_true, y_pred, sample_weight=None):
# If we are wrapping a lambda function strip '<>' from the name as it is not
# accepted in scope name.
graph_ctx = tf_utils.graph_context_for_symbolic_tensors(
y_true, y_pred, sample_weight
)
with backend.name_scope(self._name_scope), graph_ctx:
if tf.executing_eagerly():
call_fn = self.call
else:
call_fn = tf.__internal__.autograph.tf_convert(
self.call, tf.__internal__.autograph.control_status_ctx()
)
losses = call_fn(y_true, y_pred)
return losses_utils.compute_weighted_loss(
losses, sample_weight, reduction=self._get_reduction()
)
| 84afc5193d38057e2e2badf9c889ea87d80d8fbf | 17 | losses.py | 160 | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | 81,211 | 0 | 246 | 101 | 50 | 274,533 | 59 | keras | 24 | keras/losses.py | Python | 15 | {
"docstring": "Invokes the `Loss` instance.\n\n Args:\n y_true: Ground truth values. shape = `[batch_size, d0, .. dN]`, except\n sparse loss functions such as sparse categorical crossentropy where\n shape = `[batch_size, d0, .. dN-1]`\n y_pred: The predicted values. shape = `[batch_size, d0, .. dN]`\n sample_weight: Optional `sample_weight` acts as a coefficient for the\n loss. If a scalar is provided, then the loss is simply scaled by the\n given value. If `sample_weight` is a tensor of size `[batch_size]`, then\n the total loss for each sample of the batch is rescaled by the\n corresponding element in the `sample_weight` vector. If the shape of\n `sample_weight` is `[batch_size, d0, .. dN-1]` (or can be broadcasted to\n this shape), then each loss element of `y_pred` is scaled\n by the corresponding value of `sample_weight`. (Note on`dN-1`: all loss\n functions reduce by 1 dimension, usually axis=-1.)\n\n Returns:\n Weighted loss float `Tensor`. If `reduction` is `NONE`, this has\n shape `[batch_size, d0, .. dN-1]`; otherwise, it is scalar. (Note `dN-1`\n because all loss functions reduce by 1 dimension, usually axis=-1.)\n\n Raises:\n ValueError: If the shape of `sample_weight` is invalid.\n ",
"language": "en",
"n_whitespaces": 384,
"n_words": 177,
"vocab_size": 94
} | https://github.com/keras-team/keras.git |
|
1 | test_block_render_result_is_safe | def test_block_render_result_is_safe(self):
stream_block = blocks.StreamBlock(
[("paragraph", blocks.CharBlock(template="tests/jinja2/paragraph.html"))]
)
stream_value = stream_block.to_python(
[
{"type": "paragraph", "value": "hello world"},
]
)
result = render_to_string(
"tests/jinja2/stream.html",
{
"value": stream_value,
},
)
self.assertIn("<p>hello world</p>", result)
| d10f15e55806c6944827d801cd9c2d53f5da4186 | 14 | test_jinja2.py | 123 | Reformat with black | 16,230 | 0 | 183 | 68 | 26 | 74,199 | 31 | wagtail | 12 | wagtail/core/tests/test_jinja2.py | Python | 16 | {
"docstring": "\n Ensure that any results of template rendering in block.render are marked safe\n so that they don't get double-escaped when inserted into a parent template (#2541)\n ",
"language": "en",
"n_whitespaces": 47,
"n_words": 25,
"vocab_size": 23
} | https://github.com/wagtail/wagtail.git |
|
8 | get_matching_frame_actions | def get_matching_frame_actions(self, frames, platform, exception_data=None, cache=None):
if not self.matchers:
return []
# 1 - Check if exception matchers match
for m in self._exception_matchers:
if not m.matches_frame(frames, None, platform, exception_data, cache):
return []
rv = []
# 2 - Check if frame matchers match
for idx, frame in enumerate(frames):
if all(
m.matches_frame(frames, idx, platform, exception_data, cache)
for m in self._other_matchers
):
for action in self.actions:
rv.append((idx, action))
return rv
| 686675f81bf9402bc9b671e61ea0481b0c5c3468 | 14 | __init__.py | 166 | fix(grouping): Exception matcher with no frames (#38994)
We used to pass `-1` as a frame index for exception matchers, which
worked by accident because `-1` is a valid list index in Python, except
when the list of frames was empty.
Replace `-1` by `None` and make sure we do not attempt to access the
list of frames in the exception matcher, by giving it its own
`matches_frame` override.
Fixes SENTRY-VWW | 18,062 | 0 | 247 | 112 | 40 | 85,913 | 68 | sentry | 19 | src/sentry/grouping/enhancer/__init__.py | Python | 15 | {
"docstring": "Given a frame returns all the matching actions based on this rule.\n If the rule does not match `None` is returned.\n ",
"language": "en",
"n_whitespaces": 35,
"n_words": 21,
"vocab_size": 20
} | https://github.com/getsentry/sentry.git |
|
3 | update | def update(self):
x, y = pygame.mouse.get_pos()
if x >= 0 and x <= (self.__W - self._width):
self._xLoc = x
| f0af0c43340763724f139fa68aa1e5a9ffe458b4 | 10 | brickout-game.py | 69 | refactor: clean code
Signed-off-by: slowy07 <[email protected]> | 4,369 | 0 | 51 | 39 | 16 | 22,589 | 19 | Python | 10 | brickout-game/brickout-game.py | Python | 4 | {
"docstring": "\n moves the paddle at the screen via mouse\n \n This class represents a simple Brick class.\n For representing bricks onto screen.\n",
"language": "en",
"n_whitespaces": 41,
"n_words": 20,
"vocab_size": 19
} | https://github.com/geekcomputers/Python.git |
|
3 | _create_placement_group | def _create_placement_group(self, num_workers):
pg = get_current_placement_group()
if pg is None:
bundle = {"CPU": self._num_cpus_per_worker, "GPU": int(self._use_gpu)}
bundles = [bundle] * num_workers
pg = ray.util.placement_group(bundles, strategy="SPREAD")
logger.debug("Waiting for placement group to start.")
ready, _ = ray.wait([pg.ready()], timeout=SGD_PLACEMENT_GROUP_TIMEOUT_S)
if ready:
logger.debug("Placement group has started.")
else:
raise TimeoutError(
"Placement group creation timed out. Make sure "
"your cluster either has enough resources or use "
"an autoscaling cluster. Current resources "
"available: {}, resources requested by the "
"placement group: {}".format(
ray.available_resources(), pg.bundle_specs
)
)
self._worker_placement_group = pg
| 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | 16 | worker_group.py | 212 | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | 30,006 | 0 | 376 | 121 | 67 | 133,393 | 85 | ray | 26 | python/ray/util/sgd/torch/worker_group.py | Python | 21 | {
"docstring": "Creates a placement group for the workers.\n\n If this worker is already in a placement group then a new one will\n not be created. This is primarily for when Tune is the upstream and\n will allocate resources for SGD workers.\n\n If this worker is not in a placement group, a new one will be created\n and set. The placement group will have a single bundle for each worker\n and use the SPREAD strategy for an even distribution.\n ",
"language": "en",
"n_whitespaces": 126,
"n_words": 77,
"vocab_size": 43
} | https://github.com/ray-project/ray.git |
|
3 | print_help | def print_help(self):
id_string = ""
for s_id, sub_dict in self.current_series.items():
id_string += (
f" {s_id.upper()}{(self.long_id-len(s_id)) * ' '} :"
f" [italic]{sub_dict['title']}[/italic]\n"
)
if not id_string:
id_string += " [bold][red]None[/red][/bold]\n"
help_text = f
console.print(text=help_text, menu="Economy - Federal Reserve Economic Data")
| 82747072c511beb1b2672846ae2ee4aec53eb562 | 17 | fred_controller.py | 243 | Terminal Wide Rich (#1161)
* My idea for how we handle Rich moving forward
* remove independent consoles
* FIxed pylint issues
* add a few vars
* Switched print to console
* More transitions
* Changed more prints
* Replaced all prints
* Fixing tabulate
* Finished replace tabulate
* Finished removing rich from Tabulate
* add Panel around menu
* add GST watermark under feature flag
* Fixed 46 tests
* Delete test_screener[False].yaml
* Delete test_screener[True].yaml
* Fixed the rest of the tests
* add help and source color vars and use rgb
* rich on stocks/options
* update rich on disc, dps, sia
* rich in gov, ins and scr menus
* ba and ca menus with rich
* Fixed import issue
* Fixed some tests
* removed termcolor
* Removed prettytable
* add rich to remaining stocks menus
* FIxed linting issue
* Added James' changes
* Updated dependencies
* Add rich to cryptocurrency menu
* refactor economy and forex
* refactor etf with rich
* refactor mfunds
* refactor rich rest
* not specify style so default color works well on any background
* Fixing mypy issues
* Updated tests
* More test fixes
* James' test fixes
* Updating tests : stocks/screener - fix cassettes using BR
* Updating tests : crypto
* Updating tests : disable DEBUG_MODE
* Updating tests : stocks/fa/yfinance
* minor fixes that escape
* Improve the rich table function (that replaces tabulate :D )
* Fixed bad code
* delete rogue file + dcf fix + NoConsole
* sia mypy
* fuck you linter
* fuck you linter pt 2
* skip hehe
* i hate the black linter
* ubuntu mypy attempt
* Update : rich_config + gtff
* Updating tests : conftest
* Updating tests : stocks
* Update : rich_config
* Updating : rich_config
* make panel configurable for Theodore :b
* colors update
* Merged
* Updating : rich_config + feature_flags
* Updating : rich_config
* Updating tests : stocks
* Updating : feature_flags
Co-authored-by: DidierRLopes <[email protected]>
Co-authored-by: Chavithra PARANA <[email protected]>
Co-authored-by: james <[email protected]>
Co-authored-by: jose-donato <[email protected]> | 83,791 | 0 | 150 | 53 | 34 | 281,474 | 39 | OpenBBTerminal | 16 | gamestonk_terminal/economy/fred/fred_controller.py | Python | 21 | {
"docstring": "Print help[cmds]\n search search FRED series notes\n add add series ID to list\n rmv remove series ID from list[/cmds]\n\n[param]Current Series IDs:[/param]\n{id_string}{'[dim]'if not self.current_series else \"\"}[cmds]\n plot plot selected series [/cmds]{'[/dim]'if not self.current_series else \"\"}\n{'[dim]'if len(self.current_series.keys())!=1 else \"\"}[menu]\n> pred prediction techniques (single SeriesID)[/menu]{'[/dim]'if len(self.current_series.keys())!=1 else \"\"}\n ",
"language": "en",
"n_whitespaces": 111,
"n_words": 49,
"vocab_size": 35
} | https://github.com/OpenBB-finance/OpenBBTerminal.git |
|
8 | deserialize | def deserialize(obj):
if isinstance(obj, ObjectIDType):
return ray.get(obj)
elif isinstance(obj, (tuple, list)) and any(
isinstance(o, ObjectIDType) for o in obj
):
return ray.get(list(obj))
elif isinstance(obj, dict) and any(
isinstance(val, ObjectIDType) for val in obj.values()
):
return dict(zip(obj.keys(), ray.get(list(obj.values()))))
else:
return obj
| b22b93df20ad25ae7a11f0c89d32fb2f234d4641 | 18 | utils.py | 177 | FIX-#4464: Refactor Ray utils and quick fix groupby.count failing on virtual partitions (#4490)
Co-authored-by: Devin Petersohn <[email protected]>
Signed-off-by: jeffreykennethli <[email protected]> | 35,654 | 0 | 103 | 113 | 27 | 153,841 | 40 | modin | 15 | modin/core/execution/ray/common/utils.py | Python | 13 | {
"docstring": "\n Deserialize a Ray object.\n\n Parameters\n ----------\n obj : ObjectIDType, iterable of ObjectIDType, or mapping of keys to ObjectIDTypes\n Object(s) to deserialize.\n\n Returns\n -------\n obj\n The deserialized object.\n ",
"language": "en",
"n_whitespaces": 66,
"n_words": 27,
"vocab_size": 22
} | https://github.com/modin-project/modin.git |
|
1 | test_metadata | def test_metadata(self):
checkpoint = self._prepare_fs_checkpoint()
# Convert into dict checkpoint
data_dict = checkpoint.to_dict()
self.assertIsInstance(data_dict, dict)
data_dict["my_marker"] = "marked"
# Create from dict
checkpoint = Checkpoint.from_dict(data_dict)
self.assertTrue(checkpoint._data_dict)
self._assert_fs_checkpoint(checkpoint)
# Convert back to dict
data_dict_2 = Checkpoint.from_directory(checkpoint.to_directory()).to_dict()
assert data_dict_2["my_marker"] == "marked"
| cc53a1e28bdb0dc7121f4378c651e6290b7bc84d | 12 | test_checkpoints.py | 142 | [air] update checkpoint.py to deal with metadata in conversion. (#25727)
This is carved out from https://github.com/ray-project/ray/pull/25558.
tlrd: checkpoint.py current doesn't support the following
```
a. from fs to dict checkpoint;
b. drop some marker to dict checkpoint;
c. convert back to fs checkpoint;
d. convert back to dict checkpoint.
Assert that the marker should still be there
``` | 32,525 | 0 | 130 | 79 | 27 | 141,909 | 39 | ray | 16 | python/ray/air/tests/test_checkpoints.py | Python | 10 | {
"docstring": "Test conversion with metadata involved.\n\n a. from fs to dict checkpoint;\n b. drop some marker to dict checkpoint;\n c. convert back to fs checkpoint;\n d. convert back to dict checkpoint.\n\n Assert that the marker should still be there.",
"language": "en",
"n_whitespaces": 72,
"n_words": 38,
"vocab_size": 27
} | https://github.com/ray-project/ray.git |
|
3 | get | def get(self, request, *args, **kwargs):
(
self.term,
self.model_admin,
self.source_field,
to_field_name,
) = self.process_request(request)
if not self.has_perm(request):
raise PermissionDenied
self.object_list = self.get_queryset()
context = self.get_context_data()
return JsonResponse(
{
"results": [
self.serialize_result(obj, to_field_name)
for obj in context["object_list"]
],
"pagination": {"more": context["page_obj"].has_next()},
}
)
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 15 | autocomplete.py | 169 | Refs #33476 -- Reformatted code with Black. | 50,440 | 0 | 257 | 105 | 38 | 203,544 | 41 | django | 20 | django/contrib/admin/views/autocomplete.py | Python | 20 | {
"docstring": "\n Return a JsonResponse with search results as defined in\n serialize_result(), by default:\n {\n results: [{id: \"123\" text: \"foo\"}],\n pagination: {more: true}\n }\n ",
"language": "en",
"n_whitespaces": 80,
"n_words": 22,
"vocab_size": 22
} | https://github.com/django/django.git |
|
4 | get_users_from_dialog | def get_users_from_dialog(old_data, dialog, logger):
try:
user_blocks = dialog.find_elements(By.TAG_NAME, "a")
loaded_users = [
extract_text_from_element(u)
for u in user_blocks
if extract_text_from_element(u)
]
new_data = old_data + loaded_users
new_data = remove_duplicates(new_data, True, None)
return new_data
except (NoSuchElementException, StaleElementReferenceException) as exc:
# Catch stale elements if any
logger.error(
"Error occurred while retrieving data.\n\t{}".format(
str(exc).encode("utf-8")
)
)
return old_data
| 2a157d452611d37cf50ccb7d56ff1a06e9790ecb | 16 | util.py | 147 | PR - Fix `extract_text_from_element()`and `find_element*()` to `find_element()` (#6438)
* Updated getUserData() and find_element*
Signed-off-by: elulcao <[email protected]>
Thanks @breuerfelix for reviewing, 🚀
People in this thread please let me know if something is not OK, IG changed a lot these days. 🤗 @her | 846 | 0 | 203 | 88 | 42 | 5,824 | 54 | InstaPy | 20 | instapy/util.py | Python | 18 | {
"docstring": "\n Prepared to work specially with the dynamic data load in the 'Likes'\n dialog box\n ",
"language": "en",
"n_whitespaces": 24,
"n_words": 14,
"vocab_size": 13
} | https://github.com/InstaPy/InstaPy.git |
|
4 | test_log_redirect_to_stderr | def test_log_redirect_to_stderr(shutdown_only, capfd):
log_components = {
ray_constants.PROCESS_TYPE_DASHBOARD: "Dashboard head grpc address",
ray_constants.PROCESS_TYPE_DASHBOARD_AGENT: "Dashboard agent grpc address",
ray_constants.PROCESS_TYPE_GCS_SERVER: "Loading job table data",
# No log monitor output if all components are writing to stderr.
ray_constants.PROCESS_TYPE_LOG_MONITOR: "",
ray_constants.PROCESS_TYPE_MONITOR: "Starting monitor using ray installation",
ray_constants.PROCESS_TYPE_PYTHON_CORE_WORKER: "worker server started",
ray_constants.PROCESS_TYPE_PYTHON_CORE_WORKER_DRIVER: "driver server started",
# TODO(Clark): Add coverage for Ray Client.
# ray_constants.PROCESS_TYPE_RAY_CLIENT_SERVER: "Starting Ray Client server",
ray_constants.PROCESS_TYPE_RAY_CLIENT_SERVER: "",
ray_constants.PROCESS_TYPE_RAYLET: "Starting object store with directory",
# No reaper process run (kernel fate-sharing).
ray_constants.PROCESS_TYPE_REAPER: "",
# No reporter process run.
ray_constants.PROCESS_TYPE_REPORTER: "",
# No web UI process run.
ray_constants.PROCESS_TYPE_WEB_UI: "",
# Unused.
ray_constants.PROCESS_TYPE_WORKER: "",
}
script = | 43aa2299e6623c8f8c7c4a1b80133459d0aa68b0 | script = """
import os
from pathlib import Path
import ray
os.environ["RAY_LOG_TO_STDERR"] = "1"
ray.init()
session_dir = ray._private.worker.global_worker.node.address_info["session_dir"]
session_path = Path(session_dir)
log_dir_path = session_path / "logs"@ray.remote | 9 | test_logging.py | 167 | [api] Annotate as public / move ray-core APIs to _private and add enforcement rule (#25695)
Enable checking of the ray core module, excluding serve, workflows, and tune, in ./ci/lint/check_api_annotations.py. This required moving many files to ray._private and associated fixes. | 32,740 | 2 | 250 | 150 | 73 | 142,603 | 101 | ray | 21 | python/ray/tests/test_logging.py | Python | 53 | {
"docstring": "\nimport os\nfrom pathlib import Path\n\nimport ray\n\nos.environ[\"RAY_LOG_TO_STDERR\"] = \"1\"\nray.init()\n\nsession_dir = ray._private.worker.global_worker.node.address_info[\"session_dir\"]\nsession_path = Path(session_dir)\nlog_dir_path = session_path / \"logs\"\n\n# Run the basic workload.\[email protected]",
"language": "en",
"n_whitespaces": 19,
"n_words": 29,
"vocab_size": 23
} | https://github.com/ray-project/ray.git |
1 | _set_rounding | def _set_rounding(self, type):
rounding = self.rounding
self.rounding = type
return rounding
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 7 | _pydecimal.py | 34 | add python 3.10.4 for windows | 55,717 | 0 | 39 | 20 | 8 | 219,692 | 11 | XX-Net | 4 | python3.10.4/Lib/_pydecimal.py | Python | 4 | {
"docstring": "Sets the rounding type.\n\n Sets the rounding type, and returns the current (previous)\n rounding type. Often used like:\n\n context = context.copy()\n # so you don't change the calling context\n # if an error occurs in the middle.\n rounding = context._set_rounding(ROUND_UP)\n val = self.__sub__(other, context=context)\n context._set_rounding(rounding)\n\n This will make it round up for that operation.\n ",
"language": "en",
"n_whitespaces": 125,
"n_words": 54,
"vocab_size": 41
} | https://github.com/XX-net/XX-Net.git |
|
7 | add_edge | def add_edge(self, u_for_edge, v_for_edge, key=None, **attr):
u, v = u_for_edge, v_for_edge
# add nodes
if u not in self._adj:
if u is None:
raise ValueError("None cannot be a node")
self._adj[u] = self.adjlist_inner_dict_factory()
self._node[u] = self.node_attr_dict_factory()
if v not in self._adj:
if v is None:
raise ValueError("None cannot be a node")
self._adj[v] = self.adjlist_inner_dict_factory()
self._node[v] = self.node_attr_dict_factory()
if key is None:
key = self.new_edge_key(u, v)
if v in self._adj[u]:
keydict = self._adj[u][v]
datadict = keydict.get(key, self.edge_attr_dict_factory())
datadict.update(attr)
keydict[key] = datadict
else:
# selfloops work this way without special treatment
datadict = self.edge_attr_dict_factory()
datadict.update(attr)
keydict = self.edge_key_dict_factory()
keydict[key] = datadict
self._adj[u][v] = keydict
self._adj[v][u] = keydict
return key
| 8f4c99debc9440728c5e85f8bffa5d26b232eb6f | 12 | multigraph.py | 352 | Multigraph docs update (#5389)
* Updated MultiDiGraph documentation to include more examples of actually
using parallel edges, and fixed references to things like G[u, v] where
G[u, v, k] is required for a MultiDigraph. Have not made parallel
changes in MultiGraph which should maybe also be made?
Docs tests pass on my end; no code outside of comments was changed.
-Peter Mawhorter
* Updated docs for MultiGraph to add more multigraph-specific examples and
fix a few places where untested examples were wrong.
-Peter Mawhorter
* [DOC] fix typo
* add the right amount of separators
Co-authored-by: Mridul Seth <[email protected]> | 41,876 | 0 | 397 | 222 | 55 | 176,411 | 106 | networkx | 20 | networkx/classes/multigraph.py | Python | 27 | {
"docstring": "Add an edge between u and v.\n\n The nodes u and v will be automatically added if they are\n not already in the graph.\n\n Edge attributes can be specified with keywords or by directly\n accessing the edge's attribute dictionary. See examples below.\n\n Parameters\n ----------\n u_for_edge, v_for_edge : nodes\n Nodes can be, for example, strings or numbers.\n Nodes must be hashable (and not None) Python objects.\n key : hashable identifier, optional (default=lowest unused integer)\n Used to distinguish multiedges between a pair of nodes.\n attr : keyword arguments, optional\n Edge data (or labels or objects) can be assigned using\n keyword arguments.\n\n Returns\n -------\n The edge key assigned to the edge.\n\n See Also\n --------\n add_edges_from : add a collection of edges\n\n Notes\n -----\n To replace/update edge data, use the optional key argument\n to identify a unique edge. Otherwise a new edge will be created.\n\n NetworkX algorithms designed for weighted graphs cannot use\n multigraphs directly because it is not clear how to handle\n multiedge weights. Convert to Graph using edge attribute\n 'weight' to enable weighted graph algorithms.\n\n Default keys are generated using the method `new_edge_key()`.\n This method can be overridden by subclassing the base class and\n providing a custom `new_edge_key()` method.\n\n Examples\n --------\n The following each add an additional edge e=(1, 2) to graph G:\n\n >>> G = nx.MultiGraph()\n >>> e = (1, 2)\n >>> ekey = G.add_edge(1, 2) # explicit two-node form\n >>> G.add_edge(*e) # single edge as tuple of two nodes\n 1\n >>> G.add_edges_from([(1, 2)]) # add edges from iterable container\n [2]\n\n Associate data to edges using keywords:\n\n >>> ekey = G.add_edge(1, 2, weight=3)\n >>> ekey = G.add_edge(1, 2, key=0, weight=4) # update data for key=0\n >>> ekey = G.add_edge(1, 3, weight=7, capacity=15, length=342.7)\n\n For non-string attribute keys, use subscript notation.\n\n >>> ekey = G.add_edge(1, 2)\n >>> G[1][2][0].update({0: 5})\n >>> G.edges[1, 2, 0].update({0: 5})\n ",
"language": "en",
"n_whitespaces": 678,
"n_words": 302,
"vocab_size": 187
} | https://github.com/networkx/networkx.git |
|
1 | set_logdir | def set_logdir(self, logdir):
self.logfile = tempfile.NamedTemporaryFile(
prefix="log_sync_out", dir=logdir, suffix=".log", delete=False
)
self._closed = False
| 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | 10 | sync_client.py | 61 | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | 29,741 | 0 | 53 | 37 | 13 | 132,332 | 14 | ray | 11 | python/ray/tune/sync_client.py | Python | 5 | {
"docstring": "Sets the directory to log sync execution output in.\n\n Args:\n logdir (str): Log directory.\n ",
"language": "en",
"n_whitespaces": 39,
"n_words": 14,
"vocab_size": 14
} | https://github.com/ray-project/ray.git |
|
1 | setUp | def setUp(self):
data_prefix = osp.join(osp.dirname(__file__), '../../data')
img_path = osp.join(data_prefix, 'color.jpg')
rng = np.random.RandomState(0)
self.results1 = {
'img_id': 1,
'img_path': img_path,
'ori_height': 300,
'ori_width': 400,
'height': 600,
'width': 800,
'scale_factor': 2.0,
'flip': False,
'img': rng.rand(300, 400),
'gt_seg_map': rng.rand(300, 400),
'gt_masks':
BitmapMasks(rng.rand(3, 300, 400), height=300, width=400),
'gt_bboxes_labels': rng.rand(3, ),
'gt_ignore_flags': np.array([0, 0, 1], dtype=np.bool)
}
self.results2 = {
'img_id': 1,
'img_path': img_path,
'ori_height': 300,
'ori_width': 400,
'height': 600,
'width': 800,
'scale_factor': 2.0,
'flip': False,
'img': rng.rand(300, 400),
'gt_seg_map': rng.rand(300, 400),
'gt_masks':
BitmapMasks(rng.rand(3, 300, 400), height=300, width=400),
'gt_bboxes_labels': rng.rand(3, )
}
self.meta_keys = ('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor', 'flip')
| 2cc631f7656258dec0d12bcce459f5fe3f781b68 | 12 | test_formatting.py | 432 | Add Transforms | 70,384 | 0 | 481 | 269 | 55 | 244,450 | 96 | mmdetection | 22 | tests/test_datasets/test_pipelines/test_formatting.py | Python | 37 | {
"docstring": "Setup the model and optimizer which are used in every test method.\n\n TestCase calls functions in this order: setUp() -> testMethod() ->\n tearDown() -> cleanUp()\n ",
"language": "en",
"n_whitespaces": 46,
"n_words": 25,
"vocab_size": 22
} | https://github.com/open-mmlab/mmdetection.git |
|
5 | _no_global_under_venv | def _no_global_under_venv() -> bool:
cfg_lines = _get_pyvenv_cfg_lines()
if cfg_lines is None:
# We're not in a "sane" venv, so assume there is no system
# site-packages access (since that's PEP 405's default state).
logger.warning(
"Could not access 'pyvenv.cfg' despite a virtual environment "
"being active. Assuming global site-packages is not accessible "
"in this environment."
)
return True
for line in cfg_lines:
match = _INCLUDE_SYSTEM_SITE_PACKAGES_REGEX.match(line)
if match is not None and match.group("value") == "false":
return True
return False
| f3166e673fe8d40277b804d35d77dcdb760fc3b3 | 12 | virtualenv.py | 109 | check point progress on only bringing in pip==22.0.4 (#4966)
* vendor in pip==22.0.4
* updating vendor packaging version
* update pipdeptree to fix pipenv graph with new version of pip.
* Vendoring of pip-shims 0.7.0
* Vendoring of requirementslib 1.6.3
* Update pip index safety restrictions patch for pip==22.0.4
* Update patches
* exclude pyptoject.toml from black to see if that helps.
* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4 | 3,177 | 0 | 186 | 59 | 59 | 20,009 | 78 | pipenv | 10 | pipenv/patched/notpip/_internal/utils/virtualenv.py | Python | 24 | {
"docstring": "Check `{sys.prefix}/pyvenv.cfg` for system site-packages inclusion\n\n PEP 405 specifies that when system site-packages are not supposed to be\n visible from a virtual environment, `pyvenv.cfg` must contain the following\n line:\n\n include-system-site-packages = false\n\n Additionally, log a warning if accessing the file fails.\n ",
"language": "en",
"n_whitespaces": 63,
"n_words": 41,
"vocab_size": 37
} | https://github.com/pypa/pipenv.git |
|
2 | close | def close(self) -> None:
if self.handles is not None:
self.handles.close()
| 734db4f1fde2566a02b3c7ff661a479b0a71633c | 10 | _json.py | 40 | TYP: Return annotations for io/{formats,json} (#47516)
* TYP: Return annotations for io/{formats,json}
* flake8
* explicitly check whether width is None | 40,007 | 0 | 35 | 23 | 9 | 167,423 | 10 | pandas | 3 | pandas/io/json/_json.py | Python | 9 | {
"docstring": "\n If we opened a stream earlier, in _get_data_from_filepath, we should\n close it.\n\n If an open stream or file was passed, we leave it open.\n ",
"language": "en",
"n_whitespaces": 53,
"n_words": 24,
"vocab_size": 20
} | https://github.com/pandas-dev/pandas.git |
|
4 | _laplace_deep_collect | def _laplace_deep_collect(f, t):
func = f.func
args = list(f.args)
if len(f.args) == 0:
return f
else:
args = [_laplace_deep_collect(arg, t) for arg in args]
if func.is_Add:
return func(*args).collect(t)
else:
return func(*args)
| 7d773eb18daaef3c54f34d1ac6cbc5b83a5bb16c | 15 | transforms.py | 119 | Cleanup loops and ranges | 48,899 | 0 | 96 | 73 | 24 | 198,387 | 31 | sympy | 10 | sympy/integrals/transforms.py | Python | 11 | {
"docstring": "\n This is an internal helper function that traverses through the epression\n tree of `f(t)` and collects arguments. The purpose of it is that\n anything like `f(w*t-1*t-c)` will be written as `f((w-1)*t-c)` such that\n it can match `f(a*t+b)`.\n ",
"language": "en",
"n_whitespaces": 53,
"n_words": 37,
"vocab_size": 32
} | https://github.com/sympy/sympy.git |
|
1 | test_from_yaml_string | def test_from_yaml_string(self):
valid_yaml_string = _dedent(
)
assert DatasetMetadata.from_yaml_string(valid_yaml_string)
duplicate_yaml_keys = _dedent(
)
with self.assertRaises(TypeError):
DatasetMetadata.from_yaml_string(duplicate_yaml_keys)
valid_yaml_with_optional_keys = _dedent(
)
assert DatasetMetadata.from_yaml_string(valid_yaml_with_optional_keys)
| 67e65c90e9490810b89ee140da11fdd13c356c9c | 9 | test_metadata_util.py | 95 | Dataset infos in yaml (#4926)
* wip
* fix Features yaml
* splits to yaml
* add _to_yaml_list
* style
* example: conll2000
* example: crime_and_punish
* add pyyaml dependency
* remove unused imports
* remove validation tests
* style
* allow dataset_infos to be struct or list in YAML
* fix test
* style
* update "datasets-cli test" + remove "version"
* remove config definitions in conll2000 and crime_and_punish
* remove versions for conll2000 and crime_and_punish
* move conll2000 and cap dummy data
* fix test
* add tests
* comments and tests
* more test
* don't mention the dataset_infos.json file in docs
* nit in docs
* docs
* dataset_infos -> dataset_info
* again
* use id2label in class_label
* update conll2000
* fix utf-8 yaml dump
* --save_infos -> --save_info
* Apply suggestions from code review
Co-authored-by: Polina Kazakova <[email protected]>
* style
* fix reloading a single dataset_info
* push info to README.md in push_to_hub
* update test
Co-authored-by: Polina Kazakova <[email protected]> | 22,202 | 0 | 130 | 51 | 14 | 105,744 | 21 | datasets | 10 | tests/test_metadata_util.py | Python | 99 | {
"docstring": "\\\n annotations_creators:\n - found\n language_creators:\n - found\n language:\n - en\n license:\n - unknown\n multilinguality:\n - monolingual\n pretty_name: Test Dataset\n size_categories:\n - 10K<n<100K\n source_datasets:\n - extended|other-yahoo-webscope-l6\n task_categories:\n - question-answering\n task_ids:\n - open-domain-qa\n \\\n annotations_creators:\n - found\n language:\n - en\n license:\n - unknown\n multilinguality:\n - monolingual\n pretty_name: Test Dataset\n size_categories:\n - 10K<n<100K\n source_datasets:\n - extended|other-yahoo-webscope-l6\n task_categories:\n - question-answering\n task_ids:\n - open-domain-qa\n task_ids:\n - open-domain-qa\n \\\n annotations_creators:\n - found\n language_creators:\n - found\n language:\n - en\n license:\n - unknown\n multilinguality:\n - monolingual\n pretty_name: Test Dataset\n size_categories:\n - 10K<n<100K\n source_datasets:\n - extended|other-yahoo-webscope-l6\n task_categories:\n - text-classification\n task_ids:\n - multi-class-classification\n paperswithcode_id:\n - squad\n configs:\n - en\n train-eval-index:\n - config: en\n task: text-classification\n task_id: multi_class_classification\n splits:\n train_split: train\n eval_split: test\n col_mapping:\n text: text\n label: target\n metrics:\n - type: accuracy\n name: Accuracy\n extra_gated_prompt: |\n By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n [RESEARCHER_FULLNAME] (the \"Researcher\") has requested permission to use the ImageNet database (the \"Database\") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n 1. Researcher shall use the Database only for non-commercial research and educational purposes.\n extra_gated_fields:\n Company: text\n Country: text\n I agree to use this model for non-commerical use ONLY: checkbox\n ",
"language": "en",
"n_whitespaces": 1184,
"n_words": 201,
"vocab_size": 107
} | https://github.com/huggingface/datasets.git |
|
1 | test_playlist_from_string | def test_playlist_from_string():
playlist = Playlist.from_search_term("playlist:this is gorillaz")
assert playlist.name == "This Is Gorillaz"
assert playlist.url == "http://open.spotify.com/playlist/37i9dQZF1DZ06evO25rXbO"
assert len(playlist.urls) > 1
@pytest.mark.vcr() | 57ce5c09ee1ac101f79962e59bd44a0396dfb76c | @pytest.mark.vcr() | 9 | test_playlist.py | 77 | Search album by string enhancement (#1663) | 5,605 | 1 | 36 | 34 | 19 | 30,466 | 22 | spotify-downloader | 11 | tests/types/test_playlist.py | Python | 5 | {
"docstring": "\n Test if Playlist class can be initialized from string.\n ",
"language": "en",
"n_whitespaces": 16,
"n_words": 9,
"vocab_size": 9
} | https://github.com/spotDL/spotify-downloader.git |
16 | untar_file | def untar_file(filename, location):
# type: (str, str) -> None
ensure_dir(location)
if filename.lower().endswith(".gz") or filename.lower().endswith(".tgz"):
mode = "r:gz"
elif filename.lower().endswith(BZ2_EXTENSIONS):
mode = "r:bz2"
elif filename.lower().endswith(XZ_EXTENSIONS):
mode = "r:xz"
elif filename.lower().endswith(".tar"):
mode = "r"
else:
logger.warning(
"Cannot determine compression type for file %s",
filename,
)
mode = "r:*"
tar = tarfile.open(filename, mode)
try:
leading = has_leading_dir([member.name for member in tar.getmembers()])
for member in tar.getmembers():
fn = member.name
if leading:
fn = split_leading_dir(fn)[1]
path = os.path.join(location, fn)
if not is_within_directory(location, path):
message = (
"The tar file ({}) has a file ({}) trying to install "
"outside target directory ({})"
)
raise InstallationError(message.format(filename, path, location))
if member.isdir():
ensure_dir(path)
elif member.issym():
try:
# https://github.com/python/typeshed/issues/2673
tar._extract_member(member, path) # type: ignore
except Exception as exc:
# Some corrupt tar files seem to produce this
# (specifically bad symlinks)
logger.warning(
"In the tar file %s the member %s is invalid: %s",
filename,
member.name,
exc,
)
continue
else:
try:
fp = tar.extractfile(member)
except (KeyError, AttributeError) as exc:
# Some corrupt tar files seem to produce this
# (specifically bad symlinks)
logger.warning(
"In the tar file %s the member %s is invalid: %s",
filename,
member.name,
exc,
)
continue
ensure_dir(os.path.dirname(path))
assert fp is not None
with open(path, "wb") as destfp:
shutil.copyfileobj(fp, destfp)
fp.close()
# Update the timestamp (useful for cython compiled files)
tar.utime(member, path)
# member have any execute permissions for user/group/world?
if member.mode & 0o111:
set_extracted_file_to_default_mode_plus_executable(path)
finally:
tar.close()
| f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | 18 | unpacking.py | 591 | upd; format | 12,505 | 0 | 1,194 | 345 | 133 | 61,319 | 229 | transferlearning | 44 | .venv/lib/python3.8/site-packages/pip/_internal/utils/unpacking.py | Python | 64 | {
"docstring": "\n Untar the file (with path `filename`) to the destination `location`.\n All files are written based on system defaults and umask (i.e. permissions\n are not preserved), except that regular file members with any execute\n permissions (user, group, or world) have \"chmod +x\" applied after being\n written. Note that for windows, any execute changes using os.chmod are\n no-ops per the python docs.\n ",
"language": "en",
"n_whitespaces": 83,
"n_words": 60,
"vocab_size": 51
} | https://github.com/jindongwang/transferlearning.git |
|
2 | parent | def parent(self) -> DOMNode:
if self._parent is None:
raise NoParent(f"{self} has no parent")
assert isinstance(self._parent, DOMNode)
return self._parent
| 2635f58e7c3d10b161ee69a15ebfe6499ac26daa | 11 | dom.py | 60 | docstrings and tidy | 43,685 | 0 | 57 | 34 | 17 | 181,946 | 18 | textual | 6 | src/textual/dom.py | Python | 13 | {
"docstring": "Get the parent node.\n\n Raises:\n NoParent: If this is the root node.\n\n Returns:\n DOMNode: The node which is the direct parent of this node.\n ",
"language": "en",
"n_whitespaces": 67,
"n_words": 24,
"vocab_size": 17
} | https://github.com/Textualize/textual.git |
|
2 | merge_subcluster | def merge_subcluster(self, nominee_cluster, threshold):
new_ss = self.squared_sum_ + nominee_cluster.squared_sum_
new_ls = self.linear_sum_ + nominee_cluster.linear_sum_
new_n = self.n_samples_ + nominee_cluster.n_samples_
new_centroid = (1 / new_n) * new_ls
new_sq_norm = np.dot(new_centroid, new_centroid)
# The squared radius of the cluster is defined:
# r^2 = sum_i ||x_i - c||^2 / n
# with x_i the n points assigned to the cluster and c its centroid:
# c = sum_i x_i / n
# This can be expanded to:
# r^2 = sum_i ||x_i||^2 / n - 2 < sum_i x_i / n, c> + n ||c||^2 / n
# and therefore simplifies to:
# r^2 = sum_i ||x_i||^2 / n - ||c||^2
sq_radius = new_ss / new_n - new_sq_norm
if sq_radius <= threshold**2:
(
self.n_samples_,
self.linear_sum_,
self.squared_sum_,
self.centroid_,
self.sq_norm_,
) = (new_n, new_ls, new_ss, new_centroid, new_sq_norm)
return True
return False
| 1fc86b6aacd89da44a3b4e8abf7c3e2ba4336ffe | 10 | _birch.py | 167 | MNT Update black to stable version (#22474) | 75,440 | 0 | 373 | 108 | 79 | 258,813 | 137 | scikit-learn | 17 | sklearn/cluster/_birch.py | Python | 17 | {
"docstring": "Check if a cluster is worthy enough to be merged. If\n yes then merge.\n ",
"language": "en",
"n_whitespaces": 28,
"n_words": 14,
"vocab_size": 14
} | https://github.com/scikit-learn/scikit-learn.git |
|
1 | test_lda_numerical_consistency | def test_lda_numerical_consistency(learning_method, global_random_seed):
rng = np.random.RandomState(global_random_seed)
X64 = rng.uniform(size=(20, 10))
X32 = X64.astype(np.float32)
lda_64 = LatentDirichletAllocation(
n_components=5, random_state=global_random_seed, learning_method=learning_method
).fit(X64)
lda_32 = LatentDirichletAllocation(
n_components=5, random_state=global_random_seed, learning_method=learning_method
).fit(X32)
assert_allclose(lda_32.components_, lda_64.components_)
assert_allclose(lda_32.transform(X32), lda_64.transform(X64))
| 703bee65e2122ad273cf0b42460c5c28ca638af8 | 11 | test_online_lda.py | 170 | ENH Preserving dtype for np.float32 in LatentDirichletAllocation (#24528)
Co-authored-by: Thomas J. Fan <[email protected]>
Co-authored-by: Julien Jerphanion <[email protected]>
Co-authored-by: takoika <>
Co-authored-by: Takeshi Oura <[email protected]> | 76,684 | 0 | 75 | 110 | 23 | 261,187 | 31 | scikit-learn | 22 | sklearn/decomposition/tests/test_online_lda.py | Python | 12 | {
"docstring": "Check numerical consistency between np.float32 and np.float64.",
"language": "en",
"n_whitespaces": 6,
"n_words": 7,
"vocab_size": 7
} | https://github.com/scikit-learn/scikit-learn.git |
|
1 | current_columns | def current_columns(self):
return copy.deepcopy(self.custcols) #deepcopy to prevent users from changing it
| 7b9bb6e62424e4b3c960e9e25c45a6946988959c | 8 | create_custom_column.py | 28 | Yet another version of CreateNewCustomColumn.
My apologies for the multiple commits. I have been working with @davidfor and we cycled a few times. I hope this is the last, barring bugs. | 45,933 | 0 | 25 | 15 | 11 | 188,795 | 11 | calibre | 5 | src/calibre/gui2/preferences/create_custom_column.py | Python | 2 | {
"docstring": "\n Return the currently defined custom columns\n\n Return the currently defined custom columns including the ones that haven't\n yet been created. It is a dict of dicts defined as follows:\n custcols[lookup_name] = {\n 'label': lookup_name,\n 'name': column_heading,\n 'datatype': datatype,\n 'display': display,\n 'normalized': None,\n 'colnum': an integer used internally,\n 'is_multiple': is_multiple,\n }\n Columns that already exist will have additional attributes that this class\n doesn't use. See calibre.library.field_metadata.add_custom_field() for the\n complete list.\n ",
"language": "en",
"n_whitespaces": 278,
"n_words": 69,
"vocab_size": 58
} | https://github.com/kovidgoyal/calibre.git |
|
1 | get_tables | def get_tables(self) -> Response:
q = 'SHOW TABLES;'
return self.native_query(q)
| 257dfe6bac18d28088c7bfc79ca22cde682f9cd6 | 7 | tdengine_handler.py | 34 | Added TDENgine Handler | 25,874 | 0 | 40 | 18 | 10 | 116,966 | 10 | mindsdb | 5 | mindsdb/integrations/handlers/tdengine_handler/tdengine_handler.py | Python | 6 | {
"docstring": "\n Get a list with all of the tabels in TDEngine\n ",
"language": "en",
"n_whitespaces": 25,
"n_words": 10,
"vocab_size": 10
} | https://github.com/mindsdb/mindsdb.git |
|
2 | set_immutable | def set_immutable(self, immutable):
for task in self.tasks:
task.set_immutable(immutable)
| 577eee60d51bdd75d3658699effdf6f78a3e604d | 9 | canvas.py | 35 | Canvas.py doc enhancement (#7907)
* Enhanced doc for canvas._chord.set_immutable()
* Enhanced doc for canvas._chord.link()
* Enhanced doc for canvas._chord.link_error()
* Enhanced doc for canvas._chord.__length_hint__()
* Enhanced doc for canvas._chord._descend()
* Enhanced doc for canvas._chord.from_dict()
* Enhanced doc for canvas._chord.run() | 52,289 | 0 | 33 | 21 | 8 | 208,353 | 8 | celery | 5 | celery/canvas.py | Python | 3 | {
"docstring": "Sets the immutable flag on the chord header only.\n\n Note:\n Does not affect the chord body.\n\n Arguments:\n immutable (bool): The new mutability value for chord header.\n ",
"language": "en",
"n_whitespaces": 69,
"n_words": 26,
"vocab_size": 21
} | https://github.com/celery/celery.git |
|
1 | test_model_admin_no_delete_permission_externalsubscriber | def test_model_admin_no_delete_permission_externalsubscriber(self):
permission = Permission.objects.get(codename="delete_subscriber")
self.user.user_permissions.add(permission)
delete_confirmation_data = {
ACTION_CHECKBOX_NAME: [self.s1.pk, self.s2.pk],
"action": "delete_selected",
"post": "yes",
}
response = self.client.post(
reverse("admin:admin_views_subscriber_changelist"), delete_confirmation_data
)
self.assertEqual(response.status_code, 403)
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 11 | test_actions.py | 137 | Refs #33476 -- Reformatted code with Black. | 51,987 | 0 | 125 | 81 | 22 | 207,497 | 25 | django | 21 | tests/admin_views/test_actions.py | Python | 12 | {
"docstring": "\n Permission is denied if the user doesn't have delete permission for a\n related model (ExternalSubscriber).\n ",
"language": "en",
"n_whitespaces": 37,
"n_words": 15,
"vocab_size": 15
} | https://github.com/django/django.git |
|
1 | test_download_info_vcs | def test_download_info_vcs(self) -> None:
finder = make_test_finder()
with self._basic_resolver(finder) as resolver:
ireq = get_processed_req_from_line(
"pip-test-package @ git+https://github.com/pypa/pip-test-package"
)
reqset = resolver.resolve([ireq], True)
assert len(reqset.all_requirements) == 1
req = reqset.all_requirements[0]
assert req.download_info
assert isinstance(req.download_info.info, VcsInfo)
assert req.download_info.url == "https://github.com/pypa/pip-test-package"
assert req.download_info.info.vcs == "git"
| c6baa7514ab87426780a004e34386c3b104a7f56 | 11 | test_req.py | 153 | Add download_info to InstallRequirement | 41,327 | 0 | 177 | 91 | 33 | 174,533 | 42 | pip | 19 | tests/unit/test_req.py | Python | 14 | {
"docstring": "Test that download_info is set for requirements from git.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 9
} | https://github.com/pypa/pip.git |
|
2 | get_formatted_field_choices | def get_formatted_field_choices(self, field):
if "\n" in field.choices:
choices = map(
lambda x: (
x.strip().rstrip(",").strip(),
x.strip().rstrip(",").strip(),
),
field.choices.split("\r\n"),
)
else:
choices = map(lambda x: (x.strip(), x.strip()), field.choices.split(","))
return choices
| 134bd19bef529f0c205a48cedb8574ee0c52d436 | 18 | forms.py | 172 | add ability for form builder to split choices by newline
- fixes #3001
- keep support for comma separated lists if supplied | 16,608 | 0 | 172 | 99 | 23 | 76,983 | 28 | wagtail | 9 | wagtail/contrib/forms/forms.py | Python | 12 | {
"docstring": "\n Returns a list of choices [(string, string),] for the field.\n Split the provided choices into a list, separated by new lines.\n If no new lines in the provided choices, split by commas.\n ",
"language": "en",
"n_whitespaces": 61,
"n_words": 32,
"vocab_size": 25
} | https://github.com/wagtail/wagtail.git |
|
1 | test_400_missing_param_without_id_access_token | def test_400_missing_param_without_id_access_token(self) -> None:
channel = self.make_request(
method="POST",
path="/rooms/" + self.room_id + "/invite",
content={
"id_server": "example.com",
"medium": "email",
"address": "[email protected]",
},
access_token=self.tok,
)
self.assertEqual(channel.code, 400)
self.assertEqual(channel.json_body["errcode"], "M_MISSING_PARAM")
| 84ddcd7bbfe4100101741a408a91f283a8f742c7 | 12 | test_rooms.py | 133 | Drop support for calling `/_matrix/client/v3/rooms/{roomId}/invite` without an `id_access_token` (#13241)
Fixes #13206
Signed-off-by: Jacek Kusnierz [email protected] | 72,915 | 0 | 162 | 75 | 26 | 249,435 | 27 | synapse | 13 | tests/rest/client/test_rooms.py | Python | 17 | {
"docstring": "\n Test that a 3pid invite request returns 400 M_MISSING_PARAM\n if we do not include id_access_token.\n ",
"language": "en",
"n_whitespaces": 37,
"n_words": 15,
"vocab_size": 15
} | https://github.com/matrix-org/synapse.git |
|
1 | test_multiple_server_connections | def test_multiple_server_connections(tctx):
server1 = Placeholder(Server)
server2 = Placeholder(Server)
playbook = Playbook(http.HttpLayer(tctx, HTTPMode.regular), hooks=False)
| b3587b52b25077f68116b9852b041d33e7fc6601 | 11 | test_http.py | 61 | make it black! | 73,835 | 0 | 25 | 219 | 10 | 251,831 | 13 | mitmproxy | 13 | test/mitmproxy/proxy/layers/http/test_http.py | Python | 35 | {
"docstring": "Test multiple requests being rewritten to different targets.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/mitmproxy/mitmproxy.git |
|
2 | parse | def parse(version):
# type: (str) -> Union[LegacyVersion, Version]
try:
return Version(version)
except InvalidVersion:
return LegacyVersion(version)
| f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | 10 | version.py | 39 | upd; format | 13,074 | 0 | 41 | 21 | 14 | 62,933 | 15 | transferlearning | 5 | .venv/lib/python3.8/site-packages/pip/_vendor/packaging/version.py | Python | 5 | {
"docstring": "\n Parse the given version string and return either a :class:`Version` object\n or a :class:`LegacyVersion` object depending on if the given version is\n a valid PEP 440 version or a legacy version.\n ",
"language": "en",
"n_whitespaces": 44,
"n_words": 31,
"vocab_size": 22
} | https://github.com/jindongwang/transferlearning.git |
|
8 | test_promote_types_metadata | def test_promote_types_metadata(self, dtype1, dtype2):
metadata1 = {1: 1}
metadata2 = {2: 2}
dtype1 = np.dtype(dtype1, metadata=metadata1)
dtype2 = np.dtype(dtype2, metadata=metadata2)
try:
res = np.promote_types(dtype1, dtype2)
except TypeError:
# Promotion failed, this test only checks metadata
return
if res.char not in "USV" or res.names is not None or res.shape != ():
# All except string dtypes (and unstructured void) lose metadata
# on promotion (unless both dtypes are identical).
# At some point structured ones did not, but were restrictive.
assert res.metadata is None
elif res == dtype1:
# If one result is the result, it is usually returned unchanged:
assert res is dtype1
elif res == dtype2:
# dtype1 may have been cast to the same type/kind as dtype2.
# If the resulting dtype is identical we currently pick the cast
# version of dtype1, which lost the metadata:
if np.promote_types(dtype1, dtype2.kind) == dtype2:
res.metadata is None
else:
res.metadata == metadata2
else:
assert res.metadata is None
# Try again for byteswapped version
dtype1 = dtype1.newbyteorder()
assert dtype1.metadata == metadata1
res_bs = np.promote_types(dtype1, dtype2)
assert res_bs == res
assert res_bs.metadata == res.metadata
| 1b9a98af861441899b882e2ceb40770b4a96b584 | 13 | test_numeric.py | 284 | TST: Fixup slow metadata promotion tests to match new behaviour | 38,594 | 0 | 495 | 175 | 112 | 160,301 | 181 | numpy | 18 | numpy/core/tests/test_numeric.py | Python | 25 | {
"docstring": "Metadata handling in promotion does not appear formalized\n right now in NumPy. This test should thus be considered to\n document behaviour, rather than test the correct definition of it.\n\n This test is very ugly, it was useful for rewriting part of the\n promotion, but probably should eventually be replaced/deleted\n (i.e. when metadata handling in promotion is better defined).\n ",
"language": "en",
"n_whitespaces": 100,
"n_words": 58,
"vocab_size": 46
} | https://github.com/numpy/numpy.git |
|
7 | equals | def equals(self, other):
if not isinstance(other, PermutationGroup):
return False
set_self_gens = set(self.generators)
set_other_gens = set(other.generators)
# before reaching the general case there are also certain
# optimisation and obvious cases requiring less or no actual
# computation.
if set_self_gens == set_other_gens:
return True
# in the most general case it will check that each generator of
# one group belongs to the other PermutationGroup and vice-versa
for gen1 in set_self_gens:
if not other.contains(gen1):
return False
for gen2 in set_other_gens:
if not self.contains(gen2):
return False
return True
| 3e167a67bde4b4817666de48bf98d247bed86e2d | 10 | perm_groups.py | 127 | Update sympy/combinatorics/perm_groups.py | 47,843 | 0 | 251 | 76 | 59 | 196,343 | 86 | sympy | 12 | sympy/combinatorics/perm_groups.py | Python | 14 | {
"docstring": "Return ``True`` if PermutationGroup generated by elements in the\n group are same i.e they represent the same PermutationGroup.\n\n Examples\n ========\n\n >>> from sympy.combinatorics import Permutation, PermutationGroup\n >>> p = Permutation(0, 1, 2, 3, 4, 5)\n >>> G = PermutationGroup([p, p**2])\n >>> H = PermutationGroup([p**2, p])\n >>> G.generators == H.generators\n False\n >>> G.equals(H)\n True\n\n ",
"language": "en",
"n_whitespaces": 137,
"n_words": 53,
"vocab_size": 43
} | https://github.com/sympy/sympy.git |
|
2 | check_libraries | def check_libraries():
modules = {
'jinja2': _missing_str("jinja2"),
'yaml': _missing_str("PyYAML"),
'PyQt5.QtQml': _missing_str("PyQt5.QtQml"),
'PyQt5.QtSql': _missing_str("PyQt5.QtSql"),
'PyQt5.QtOpenGL': _missing_str("PyQt5.QtOpenGL"),
'PyQt5.QtDBus': _missing_str("PyQt5.QtDBus"),
}
if sys.version_info < (3, 9):
# Backport required
modules['importlib_resources'] = _missing_str("importlib_resources")
_check_modules(modules)
| cd4429db25746acbec3ef434935959d0f5f66224 | 11 | earlyinit.py | 145 | Remove 3.6 pins from requirements files.
Then regenerate the relevant files.
Also drop dataclasses from requirements files.
TODO: should we drop the dataclasses-types requirement for mypy too? | 117,285 | 0 | 101 | 82 | 29 | 320,692 | 30 | qutebrowser | 6 | qutebrowser/misc/earlyinit.py | Python | 13 | {
"docstring": "Check if all needed Python libraries are installed.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/qutebrowser/qutebrowser.git |
|
9 | alpha_composite | def alpha_composite(self, im, dest=(0, 0), source=(0, 0)):
if not isinstance(source, (list, tuple)):
msg = "Source must be a tuple"
raise ValueError(msg)
if not isinstance(dest, (list, tuple)):
msg = "Destination must be a tuple"
raise ValueError(msg)
if not len(source) in (2, 4):
msg = "Source must be a 2 or 4-tuple"
raise ValueError(msg)
if not len(dest) == 2:
msg = "Destination must be a 2-tuple"
raise ValueError(msg)
if min(source) < 0:
msg = "Source must be non-negative"
raise ValueError(msg)
if len(source) == 2:
source = source + im.size
# over image, crop if it's not the whole thing.
if source == (0, 0) + im.size:
overlay = im
else:
overlay = im.crop(source)
# target for the paste
box = dest + (dest[0] + overlay.width, dest[1] + overlay.height)
# destination image. don't copy if we're using the whole image.
if box == (0, 0) + self.size:
background = self
else:
background = self.crop(box)
result = alpha_composite(background, overlay)
self.paste(result, box)
| 2ae55ccbdad9c842929fb238ea1eb81d1f999024 | 11 | Image.py | 362 | Improve exception traceback readability | 70,092 | 0 | 441 | 226 | 80 | 243,723 | 157 | Pillow | 21 | src/PIL/Image.py | Python | 41 | {
"docstring": "'In-place' analog of Image.alpha_composite. Composites an image\n onto this image.\n\n :param im: image to composite over this one\n :param dest: Optional 2 tuple (left, top) specifying the upper\n left corner in this (destination) image.\n :param source: Optional 2 (left, top) tuple for the upper left\n corner in the overlay source image, or 4 tuple (left, top, right,\n bottom) for the bounds of the source rectangle\n\n Performance Note: Not currently implemented in-place in the core layer.\n ",
"language": "en",
"n_whitespaces": 144,
"n_words": 75,
"vocab_size": 49
} | https://github.com/python-pillow/Pillow.git |
|
7 | override_recursive | def override_recursive(a, b):
for key in b:
if isinstance(b[key], dict) is False:
a[key] = b[key]
elif key not in a or isinstance(a[key], dict) is False:
a[key] = b[key]
# make config section empty by demand
elif isinstance(b[key], dict) is True and b[key] == {}:
a[key] = b[key]
else:
override_recursive(a[key], b[key])
@pytest.fixture(scope="module") | ae4fa77a2c0a9fa57cc9c8bc7e8961dd01e4067e | @pytest.fixture(scope="module") | 13 | conftest.py | 176 | It mysql api test pytest (#3694)
* migration to pytest
* Tests start passing
* Fully working tests
* Increase timeout for mindsdb start
* reduce amount of logs
* show logs only for failed tests | 25,896 | 1 | 135 | 106 | 35 | 117,084 | 51 | mindsdb | 9 | tests/integration_tests/flows/conftest.py | Python | 10 | {
"docstring": "Overrides some elements in json 'a' by elements in json 'b'",
"language": "en",
"n_whitespaces": 10,
"n_words": 11,
"vocab_size": 8
} | https://github.com/mindsdb/mindsdb.git |
1 | get_all_applicant | def get_all_applicant(self) -> List[NoSQLUserApplication]:
return self.user_application_manager.all()
| 58da94aae4e66576a7f40b55f2de2d69693bfe20 | 8 | user_manager.py | 33 | added user application manager,
reverted default signup on user creation | 286 | 0 | 20 | 19 | 6 | 2,395 | 6 | PySyft | 6 | packages/syft/src/syft/core/node/common/node_manager/user_manager.py | Python | 7 | {
"docstring": "Returns the application data of all the applicants in the database.\n\n Returns:\n List[NoSQLUserApplication]: All user applications.\n ",
"language": "en",
"n_whitespaces": 41,
"n_words": 16,
"vocab_size": 14
} | https://github.com/OpenMined/PySyft.git |
|
3 | test_gumbel_softmax | def test_gumbel_softmax(self):
for fw, sess in framework_iterator(frameworks=("tf2", "tf"), session=True):
batch_size = 1000
num_categories = 5
input_space = Box(-1.0, 1.0, shape=(batch_size, num_categories))
input_space.seed(42)
# Batch of size=n and deterministic.
inputs = input_space.sample()
gumbel_softmax = GumbelSoftmax(inputs, {}, temperature=1.0)
expected = softmax(inputs)
# Sample n times, expect always mean value (deterministic draw).
out = gumbel_softmax.deterministic_sample()
check(out, expected)
# Batch of size=n and non-deterministic -> expect roughly that
# the max-likelihood (argmax) ints are output (most of the time).
inputs = input_space.sample()
gumbel_softmax = GumbelSoftmax(inputs, {}, temperature=1.0)
expected_mean = np.mean(np.argmax(inputs, -1)).astype(np.float32)
outs = gumbel_softmax.sample()
if sess:
outs = sess.run(outs)
check(np.mean(np.argmax(outs, -1)), expected_mean, rtol=0.08)
| 432f023642731bf53aac9b6c778f9dd7b1d82a57 | 15 | test_distributions.py | 286 | [RLlib] Deprecate `AlgorithmConfig.framework("tfe")`: Use `tf2` instead. (#29755) | 30,547 | 0 | 337 | 188 | 71 | 135,117 | 99 | ray | 32 | rllib/models/tests/test_distributions.py | Python | 18 | {
"docstring": "Tests the GumbelSoftmax ActionDistribution (tf + eager only).",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/ray-project/ray.git |
|
7 | _render_cmd | def _render_cmd(cmd, cwd, template, saltenv=None, pillarenv=None, pillar_override=None):
if saltenv is None:
saltenv = __opts__.get("saltenv", "base")
if not template:
return (cmd, cwd)
# render the path as a template using path_template_engine as the engine
if template not in salt.utils.templates.TEMPLATE_REGISTRY:
raise CommandExecutionError(
"Attempted to render file paths with unavailable engine {}".format(template)
)
kwargs = {}
kwargs["salt"] = __salt__
if pillarenv is not None or pillar_override is not None:
pillarenv = pillarenv or __opts__["pillarenv"]
kwargs["pillar"] = _gather_pillar(pillarenv, pillar_override)
else:
kwargs["pillar"] = __pillar__
kwargs["grains"] = __grains__
kwargs["opts"] = __opts__
kwargs["saltenv"] = saltenv
| 21d3f4bc9eb7b9fb1118c59073595a9e9ee836bd | 12 | cmdmod.py | 225 | fixes salt bug 61507 | 54,474 | 0 | 184 | 155 | 60 | 216,231 | 88 | salt | 20 | salt/modules/cmdmod.py | Python | 23 | {
"docstring": "\n If template is a valid template engine, process the cmd and cwd through\n that engine.\n ",
"language": "en",
"n_whitespaces": 25,
"n_words": 15,
"vocab_size": 14
} | https://github.com/saltstack/salt.git |
|
2 | _compile_output | def _compile_output(self) -> Union[List[str], List[Tuple[str, int]]]:
action = self._job.replace("-", "_")
processor = getattr(self, f"_get_{action}")
logger.debug("Processor: %s", processor)
return [item for item in processor()] # pylint:disable=unnecessary-comprehension
| e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1 | 10 | jobs.py | 106 | Alignments Tool - Typing, Documentation + Re-org | 21,118 | 0 | 61 | 63 | 24 | 101,714 | 25 | faceswap | 15 | tools/alignments/jobs.py | Python | 12 | {
"docstring": " Compile list of frames that meet criteria\n\n Returns\n -------\n list\n List of filenames or filenames and face indices for the selected criteria\n ",
"language": "en",
"n_whitespaces": 62,
"n_words": 22,
"vocab_size": 18
} | https://github.com/deepfakes/faceswap.git |
|
1 | test_layout_change_warning | def test_layout_change_warning(layout):
fig, ax = plt.subplots(layout=layout)
with pytest.warns(UserWarning, match='The figure layout has changed to'):
plt.tight_layout()
@check_figures_equal(extensions=["png", "pdf"]) | 94397f4949511881dfc35fbab76cb237f6911424 | @check_figures_equal(extensions=["png", "pdf"]) | 11 | test_figure.py | 84 | BUG: Warn when an existing layout manager changes to tight layout | 24,198 | 1 | 32 | 35 | 17 | 110,522 | 17 | matplotlib | 13 | lib/matplotlib/tests/test_figure.py | Python | 4 | {
"docstring": "\n Raise a warning when a previously assigned layout changes to tight using\n plt.tight_layout().\n ",
"language": "en",
"n_whitespaces": 23,
"n_words": 13,
"vocab_size": 12
} | https://github.com/matplotlib/matplotlib.git |
2 | move_cursor_forward | def move_cursor_forward(self) -> None:
row, col = self.cursor_position
if col == self.screen_size.col - 1:
row += 1
col = 0
else:
col += 1
SetConsoleCursorPosition(
self._handle, coords=WindowsCoordinates(row=row, col=col)
)
| c69d55f7c82d5ae2cce542bcfb98d043ca4836a0 | 11 | _win32_console.py | 91 | Vendor in pip 22.1.2 | 3,923 | 0 | 115 | 56 | 23 | 21,553 | 29 | pipenv | 10 | pipenv/patched/notpip/_vendor/rich/_win32_console.py | Python | 11 | {
"docstring": "Move the cursor forward a single cell. Wrap to the next line if required.",
"language": "en",
"n_whitespaces": 13,
"n_words": 14,
"vocab_size": 13
} | https://github.com/pypa/pipenv.git |
|
2 | get_item_info | def get_item_info(filters):
from erpnext.stock.report.stock_ledger.stock_ledger import get_item_group_condition
conditions = [get_item_group_condition(filters.get("item_group"))]
if filters.get("brand"):
conditions.append("item.brand=%(brand)s")
conditions.append("is_stock_item = 1")
return frappe.db.sql(
.format(
" and ".join(conditions)
),
filters,
as_dict=1,
)
| 494bd9ef78313436f0424b918f200dab8fc7c20b | 12 | itemwise_recommended_reorder_level.py | 128 | style: format code with black | 14,656 | 0 | 12 | 76 | 24 | 67,893 | 25 | erpnext | 16 | erpnext/stock/report/itemwise_recommended_reorder_level/itemwise_recommended_reorder_level.py | Python | 14 | {
"docstring": "select name, item_name, description, brand, item_group,\n\t\tsafety_stock, lead_time_days from `tabItem` item where {}",
"language": "en",
"n_whitespaces": 11,
"n_words": 13,
"vocab_size": 13
} | https://github.com/frappe/erpnext.git |
|
5 | parse_content_disposition | def parse_content_disposition(reply):
is_inline = True
filename = None
content_disposition_header = b'Content-Disposition'
# First check if the Content-Disposition header has a filename
# attribute.
if reply.hasRawHeader(content_disposition_header):
# We use the unsafe variant of the filename as we sanitize it via
# os.path.basename later.
try:
value = bytes(reply.rawHeader(content_disposition_header))
log.network.debug("Parsing Content-Disposition: {value!r}")
content_disposition = ContentDisposition.parse(value)
filename = content_disposition.filename()
except ContentDispositionError as e:
log.network.error(f"Error while parsing filename: {e}")
else:
is_inline = content_disposition.is_inline()
# Then try to get filename from url
if not filename:
filename = reply.url().path().rstrip('/')
# If that fails as well, use a fallback
if not filename:
filename = 'qutebrowser-download'
return is_inline, os.path.basename(filename)
| bd8c940320b7d8476b422edd9c417703db64f603 | 14 | http.py | 222 | Simplify some syntax
Found via pyupgrade | 117,279 | 0 | 251 | 121 | 68 | 320,685 | 100 | qutebrowser | 23 | qutebrowser/browser/webkit/http.py | Python | 19 | {
"docstring": "Parse a content_disposition header.\n\n Args:\n reply: The QNetworkReply to get a filename for.\n\n Return:\n A (is_inline, filename) tuple.\n ",
"language": "en",
"n_whitespaces": 41,
"n_words": 18,
"vocab_size": 17
} | https://github.com/qutebrowser/qutebrowser.git |
|
1 | get_protobuf_schema | def get_protobuf_schema() -> GeneratedProtocolMessageType:
return GetAllRequestsMessage_PB
@serializable() | 05edf746cf5742b562996cf1a319b404152960e5 | @serializable() | 6 | object_request_messages.py | 26 | MOVE GetAllRequestsMessage and GetAllRequestsResponseMessage to the proper message file | 12 | 1 | 20 | 9 | 7 | 20 | 7 | PySyft | 4 | packages/syft/src/syft/core/node/common/node_service/object_request/object_request_messages.py | Python | 17 | {
"docstring": "Return the type of protobuf object which stores a class of this type\n\n As a part of serialization and deserialization, we need the ability to\n lookup the protobuf object type directly from the object type. This\n static method allows us to do this.\n\n Importantly, this method is also used to create the reverse lookup ability within\n the metaclass of Serializable. In the metaclass, it calls this method and then\n it takes whatever type is returned from this method and adds an attribute to it\n with the type of this class attached to it. See the MetaSerializable class for details.\n\n :return: the type of protobuf object which corresponds to this class.\n :rtype: GeneratedProtocolMessageType\n\n ",
"language": "en",
"n_whitespaces": 182,
"n_words": 112,
"vocab_size": 63
} | https://github.com/OpenMined/PySyft.git |
1 | _get_server | def _get_server(self):
live_run = self._get_live_run()
return live_run.architect.server
| c946fb395d52e0f7ad67646a1c01b8327c232027 | 8 | tests.py | 34 | Updating to Mephisto 1.0 (#4426)
* Version bumps
* Correct version
* Correct beta release
* Tests should _run_, but fail
* Temporarily force run all crowdsourcing tests
* Forcerun crowdsourcing checks
* Typo
* Update config.yml
* Minor
* Update acute_eval_runner.py
* Simple fix, more tests run
* Force cleanup of the server.
* Correct AcuteEvalRunner.run_unit
* using v1.0.0 from Mephisto github
* Rolling back temp solution
* Fix model chat test?
* chat demo fix
* QA fix
* model image chat
* Only add sleep time to model image chat
* Remove agent retry loop
* Remove 2 lines
* Lengthen time
* Fixing model chat onboarding and task frontend
* fix acute eval test
* Remove TODOs
Co-authored-by: Eric Smith <[email protected]>
Co-authored-by: Stephen Roller <[email protected]>
Co-authored-by: EricMichaelSmith <[email protected]>
Co-authored-by: Dexter Ju <[email protected]> | 47,139 | 0 | 28 | 19 | 7 | 194,984 | 7 | ParlAI | 6 | parlai/crowdsourcing/utils/tests.py | Python | 3 | {
"docstring": "\n Return the MockArchitect's server associated with this run\n ",
"language": "en",
"n_whitespaces": 23,
"n_words": 8,
"vocab_size": 8
} | https://github.com/facebookresearch/ParlAI.git |
|
1 | _installed_pip | def _installed_pip(self):
with Popen(f"{sys.executable} -m pip freeze", shell=True, stdout=PIPE) as pip:
installed = pip.communicate()[0].decode(self._encoding, errors="replace").splitlines()
return "\n".join(installed)
| 48c886b3dce3d3117ad16edaf35c8abd28dc51f5 | 15 | sysinfo.py | 103 | Allow decoding errors | 21,435 | 0 | 49 | 55 | 17 | 102,070 | 17 | faceswap | 16 | lib/sysinfo.py | Python | 4 | {
"docstring": " str: The list of installed pip packages within Faceswap's scope. ",
"language": "en",
"n_whitespaces": 11,
"n_words": 10,
"vocab_size": 10
} | https://github.com/deepfakes/faceswap.git |
|
2 | copy2 | def copy2(src, dst):
if os.path.isdir(dst):
dst = os.path.join(dst, os.path.basename(src))
copyfile(src, dst)
copystat(src, dst)
| c69d55f7c82d5ae2cce542bcfb98d043ca4836a0 | 13 | shutil.py | 78 | Vendor in pip 22.1.2 | 3,771 | 0 | 32 | 49 | 12 | 21,340 | 13 | pipenv | 10 | pipenv/patched/notpip/_vendor/distlib/_backport/shutil.py | Python | 5 | {
"docstring": "Copy data and all stat info (\"cp -p src dst\").\n\n The destination may be a directory.\n\n ",
"language": "en",
"n_whitespaces": 22,
"n_words": 16,
"vocab_size": 16
} | https://github.com/pypa/pipenv.git |
|
1 | _merge_batch_beams | def _merge_batch_beams(self, x):
r
check_type(x, 'x', (Variable), 'BeamSearchDecoder._merge_batch_beams')
# TODO: avoid fake shape in compile-time like tile_beam_merge_with_batch
return nn.reshape(x, shape=[-1] + list(x.shape[2:]))
| ffcde21305c61d950a9f93e57e6180c9a9665b87 | 13 | beam.py | 74 | add disco_diffusion_ernievil_base | 10,041 | 0 | 49 | 46 | 22 | 50,183 | 22 | PaddleHub | 9 | modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/beam.py | Python | 15 | {
"docstring": "\n Reshape a tensor with shape `[batch_size, beam_size, ...]` to a new\n tensor with shape `[batch_size * beam_size, ...]`.\n\n Parameters:\n x(Variable): A tensor with shape `[batch_size, beam_size, ...]`. The\n data type should be float32, float64, int32, int64 or bool.\n\n Returns:\n Variable: A tensor with shape `[batch_size * beam_size, ...]`, whose \\\n data type is same as `x`.\n ",
"language": "en",
"n_whitespaces": 144,
"n_words": 56,
"vocab_size": 36
} | https://github.com/PaddlePaddle/PaddleHub.git |
|
1 | _median_bias | def _median_bias(n):
ii_2 = jnp.arange(2., n, 2)
return 1 + jnp.sum(1. / (ii_2 + 1) - 1. / ii_2)
| e085370ec4137cf0f73c5163cb664bc4e1c46082 | 12 | signal_helper.py | 59 | Add some functions for spectral analysis.
This commit adds "stft", "csd", and "welch" functions in scipy.signal. | 26,584 | 0 | 22 | 40 | 17 | 119,313 | 19 | jax | 6 | jax/_src/third_party/scipy/signal_helper.py | Python | 3 | {
"docstring": "\n Returns the bias of the median of a set of periodograms relative to\n the mean.\n See Appendix B from [1]_ for details.\n Parameters\n ----------\n n : int\n Numbers of periodograms being averaged.\n Returns\n -------\n bias : float\n Calculated bias.\n References\n ----------\n .. [1] B. Allen, W.G. Anderson, P.R. Brady, D.A. Brown, J.D.E. Creighton.\n \"FINDCHIRP: an algorithm for detection of gravitational waves from\n inspiraling compact binaries\", Physical Review D 85, 2012,\n :arxiv:`gr-qc/0509116`\n ",
"language": "en",
"n_whitespaces": 122,
"n_words": 71,
"vocab_size": 58
} | https://github.com/google/jax.git |
|
2 | parseaddr | def parseaddr(addr):
addrs = _AddressList(addr).addresslist
if not addrs:
return '', ''
return addrs[0]
# rfc822.unquote() doesn't properly de-backslash-ify in Python pre-2.3. | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 9 | utils.py | 51 | add python 3.10.4 for windows | 57,132 | 0 | 39 | 27 | 20 | 223,882 | 21 | XX-Net | 5 | python3.10.4/Lib/email/utils.py | Python | 5 | {
"docstring": "\n Parse addr into its constituent realname and email address parts.\n\n Return a tuple of realname and email address, unless the parse fails, in\n which case return a 2-tuple of ('', '').\n ",
"language": "en",
"n_whitespaces": 44,
"n_words": 31,
"vocab_size": 26
} | https://github.com/XX-net/XX-Net.git |
|
2 | handle_defect | def handle_defect(self, obj, defect):
if self.raise_on_defect:
raise defect
self.register_defect(obj, defect)
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 7 | _policybase.py | 40 | add python 3.10.4 for windows | 57,022 | 0 | 42 | 25 | 10 | 223,636 | 10 | XX-Net | 6 | python3.10.4/Lib/email/_policybase.py | Python | 4 | {
"docstring": "Based on policy, either raise defect or call register_defect.\n\n handle_defect(obj, defect)\n\n defect should be a Defect subclass, but in any case must be an\n Exception subclass. obj is the object on which the defect should be\n registered if it is not raised. If the raise_on_defect is True, the\n defect is raised as an error, otherwise the object and the defect are\n passed to register_defect.\n\n This method is intended to be called by parsers that discover defects.\n The email package parsers always call it with Defect instances.\n\n ",
"language": "en",
"n_whitespaces": 155,
"n_words": 86,
"vocab_size": 60
} | https://github.com/XX-net/XX-Net.git |
|
10 | output_difference | def output_difference(self, example, got, optionflags):
want = example.want
# If <BLANKLINE>s are being used, then replace blank lines
# with <BLANKLINE> in the actual output string.
if not (optionflags & DONT_ACCEPT_BLANKLINE):
got = re.sub('(?m)^[ ]*(?=\n)', BLANKLINE_MARKER, got)
# Check if we should use diff.
if self._do_a_fancy_diff(want, got, optionflags):
# Split want & got into lines.
want_lines = want.splitlines(keepends=True)
got_lines = got.splitlines(keepends=True)
# Use difflib to find their differences.
if optionflags & REPORT_UDIFF:
diff = difflib.unified_diff(want_lines, got_lines, n=2)
diff = list(diff)[2:] # strip the diff header
kind = 'unified diff with -expected +actual'
elif optionflags & REPORT_CDIFF:
diff = difflib.context_diff(want_lines, got_lines, n=2)
diff = list(diff)[2:] # strip the diff header
kind = 'context diff with expected followed by actual'
elif optionflags & REPORT_NDIFF:
engine = difflib.Differ(charjunk=difflib.IS_CHARACTER_JUNK)
diff = list(engine.compare(want_lines, got_lines))
kind = 'ndiff with -expected +actual'
else:
assert 0, 'Bad diff option'
return 'Differences (%s):\n' % kind + _indent(''.join(diff))
# If we're not using diff, then simply list the expected
# output followed by the actual output.
if want and got:
return 'Expected:\n%sGot:\n%s' % (_indent(want), _indent(got))
elif want:
return 'Expected:\n%sGot nothing\n' % _indent(want)
elif got:
return 'Expected nothing\nGot:\n%s' % _indent(got)
else:
return 'Expected nothing\nGot nothing\n'
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 15 | doctest.py | 396 | add python 3.10.4 for windows | 56,917 | 0 | 589 | 229 | 111 | 223,462 | 194 | XX-Net | 32 | python3.10.4/Lib/doctest.py | Python | 30 | {
"docstring": "\n Return a string describing the differences between the\n expected output for a given example (`example`) and the actual\n output (`got`). `optionflags` is the set of option flags used\n to compare `want` and `got`.\n ",
"language": "en",
"n_whitespaces": 70,
"n_words": 33,
"vocab_size": 27
} | https://github.com/XX-net/XX-Net.git |
|
1 | subclass_exception | def subclass_exception(name, bases, module, attached_to):
return type(
name,
bases,
{
"__module__": module,
"__qualname__": "%s.%s" % (attached_to.__qualname__, name),
},
)
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 12 | base.py | 61 | Refs #33476 -- Reformatted code with Black. | 51,117 | 0 | 78 | 39 | 17 | 205,408 | 19 | django | 7 | django/db/models/base.py | Python | 9 | {
"docstring": "\n Create exception subclass. Used by ModelBase below.\n\n The exception is created in a way that allows it to be pickled, assuming\n that the returned exception class will be added as an attribute to the\n 'attached_to' class.\n ",
"language": "en",
"n_whitespaces": 52,
"n_words": 36,
"vocab_size": 30
} | https://github.com/django/django.git |
|
12 | _make_zipfile | def _make_zipfile(base_name, base_dir, verbose=0, dry_run=0, logger=None):
zip_filename = base_name + ".zip"
archive_dir = os.path.dirname(base_name)
if not os.path.exists(archive_dir):
if logger is not None:
logger.info("creating %s", archive_dir)
if not dry_run:
os.makedirs(archive_dir)
# If zipfile module is not available, try spawning an external 'zip'
# command.
try:
import zipfile
except ImportError:
zipfile = None
if zipfile is None:
_call_external_zip(base_dir, zip_filename, verbose, dry_run)
else:
if logger is not None:
logger.info("creating '%s' and adding '%s' to it",
zip_filename, base_dir)
if not dry_run:
zip = zipfile.ZipFile(zip_filename, "w",
compression=zipfile.ZIP_DEFLATED)
for dirpath, dirnames, filenames in os.walk(base_dir):
for name in filenames:
path = os.path.normpath(os.path.join(dirpath, name))
if os.path.isfile(path):
zip.write(path, path)
if logger is not None:
logger.info("adding '%s'", path)
zip.close()
return zip_filename
_ARCHIVE_FORMATS = {
'gztar': (_make_tarball, [('compress', 'gzip')], "gzip'ed tar-file"),
'bztar': (_make_tarball, [('compress', 'bzip2')], "bzip2'ed tar-file"),
'tar': (_make_tarball, [('compress', None)], "uncompressed tar file"),
'zip': (_make_zipfile, [], "ZIP file"),
}
if _BZ2_SUPPORTED:
_ARCHIVE_FORMATS['bztar'] = (_make_tarball, [('compress', 'bzip2')],
"bzip2'ed tar-file")
| c69d55f7c82d5ae2cce542bcfb98d043ca4836a0 | 21 | shutil.py | 479 | Vendor in pip 22.1.2 | 3,780 | 0 | 529 | 210 | 97 | 21,352 | 148 | pipenv | 34 | pipenv/patched/notpip/_vendor/distlib/_backport/shutil.py | Python | 30 | {
"docstring": "Create a zip file from all the files under 'base_dir'.\n\n The output zip file will be named 'base_name' + \".zip\". Uses either the\n \"zipfile\" Python module (if available) or the InfoZIP \"zip\" utility\n (if installed and found on the default search path). If neither tool is\n available, raises ExecError. Returns the name of the output zip\n file.\n ",
"language": "en",
"n_whitespaces": 78,
"n_words": 57,
"vocab_size": 47
} | https://github.com/pypa/pipenv.git |
|
3 | needs_document_end_workaround | def needs_document_end_workaround(self):
if objects.backend == usertypes.Backend.QtWebKit:
return False
assert objects.backend == usertypes.Backend.QtWebEngine, objects.backend
broken_scripts = [
('http://userstyles.org', None),
('https://github.com/ParticleCore', 'Iridium'),
]
return any(self._matches_id(namespace=namespace, name=name)
for namespace, name in broken_scripts)
| c5a51eb0bcbab0b68cdfbf3eba2e681cff2adf7a | 10 | greasemonkey.py | 112 | Drop Qt < 5.15
Fixes #7091
TODO: Add changelog | 117,818 | 0 | 122 | 71 | 25 | 321,601 | 29 | qutebrowser | 13 | qutebrowser/browser/greasemonkey.py | Python | 10 | {
"docstring": "Check whether to force @run-at document-end.\n\n This needs to be done on QtWebEngine for known-broken scripts.\n\n On Qt 5.12, accessing the DOM isn't possible with \"@run-at\n document-start\". It was documented to be impossible before, but seems\n to work fine.\n\n However, some scripts do DOM access with \"@run-at document-start\". Fix\n those by forcing them to use document-end instead.\n ",
"language": "en",
"n_whitespaces": 106,
"n_words": 57,
"vocab_size": 48
} | https://github.com/qutebrowser/qutebrowser.git |
|
1 | test_explorer_list_private | def test_explorer_list_private(self):
response = self.client.get(
reverse("wagtailadmin_explore", args=(self.private_page.id,))
)
# Check the response
self.assertEqual(response.status_code, 200)
# Must have one privacy icon (next to the private child page)
self.assertContains(
response,
'<span class="indicator privacy-indicator icon icon-no-view"',
count=1,
)
| d10f15e55806c6944827d801cd9c2d53f5da4186 | 14 | test_privacy.py | 88 | Reformat with black | 15,840 | 0 | 135 | 53 | 30 | 72,114 | 35 | wagtail | 13 | wagtail/admin/tests/test_privacy.py | Python | 10 | {
"docstring": "\n This tests that there is a padlock displayed\n next to the private child page in the private pages explorer listing\n ",
"language": "en",
"n_whitespaces": 42,
"n_words": 20,
"vocab_size": 18
} | https://github.com/wagtail/wagtail.git |
|
1 | test_order_query_customer | def test_order_query_customer(api_client):
query =
response = api_client.post_graphql(query)
assert_no_permission(response)
@pytest.mark.parametrize(
"total_authorized, total_charged, expected_status",
[
(Decimal("98.40"), Decimal("0"), OrderAuthorizeStatusEnum.FULL.name),
(Decimal("0"), Decimal("98.40"), OrderAuthorizeStatusEnum.FULL.name),
(Decimal("10"), Decimal("88.40"), OrderAuthorizeStatusEnum.FULL.name),
(Decimal("0"), Decimal("0"), OrderAuthorizeStatusEnum.NONE.name),
(Decimal("11"), Decimal("0"), OrderAuthorizeStatusEnum.PARTIAL.name),
(Decimal("0"), Decimal("50.00"), OrderAuthorizeStatusEnum.PARTIAL.name),
(Decimal("10"), Decimal("40.40"), OrderAuthorizeStatusEnum.PARTIAL.name),
],
) | 9effd5aec81acbdd2a1076c1d72bbee1afcc65a1 | @pytest.mark.parametrize(
"total_authorized, total_charged, expected_status",
[
(Decimal("98.40"), Decimal("0"), OrderAuthorizeStatusEnum.FULL.name),
(Decimal("0"), Decimal("98.40"), OrderAuthorizeStatusEnum.FULL.name),
(Decimal("10"), Decimal("88.40"), OrderAuthorizeStatusEnum.FULL.name),
(Decimal("0"), Decimal("0"), OrderAuthorizeStatusEnum.NONE.name),
(Decimal("11"), Decimal("0"), OrderAuthorizeStatusEnum.PARTIAL.name),
(Decimal("0"), Decimal("50.00"), OrderAuthorizeStatusEnum.PARTIAL.name),
(Decimal("10"), Decimal("40.40"), OrderAuthorizeStatusEnum.PARTIAL.name),
],
) | 11 | test_order.py | 261 | restructure order app tests (#11226) | 5,251 | 1 | 101 | 20 | 26 | 29,667 | 36 | saleor | 15 | saleor/graphql/order/tests/queries/test_order.py | Python | 14 | {
"docstring": "\n query OrdersQuery {\n orders(first: 1) {\n edges {\n node {\n id\n }\n }\n }\n }\n ",
"language": "en",
"n_whitespaces": 146,
"n_words": 15,
"vocab_size": 9
} | https://github.com/saleor/saleor.git |
1 | test_numeric_repl | def test_numeric_repl(file, multiline_file):
file.replace(multiline_file, r"Etiam", 123)
assert "123" in multiline_file.read_text()
| a35b29b2651bf33c5d5b45e64bc7765ffde4aff4 | 8 | test_replace.py | 46 | Add some funtional tests
Add functional tests for the following:
- file.readlink
- file.replace
- file.symlink
Remove unit tests for file.replace as they are duplicated in the added
functional test | 54,182 | 0 | 19 | 27 | 10 | 215,808 | 10 | salt | 5 | tests/pytests/functional/modules/file/test_replace.py | Python | 3 | {
"docstring": "\n This test covers cases where the replacement string is numeric. The CLI\n parser yaml-fies it into a numeric type. If not converted back to a string\n type in file.replace, a TypeError occurs when the replace is attempted. See\n https://github.com/saltstack/salt/issues/9097 for more information.\n ",
"language": "en",
"n_whitespaces": 58,
"n_words": 42,
"vocab_size": 37
} | https://github.com/saltstack/salt.git |
|
2 | PreStem | def PreStem(name=None):
if name is None:
name = "prestem" + str(backend.get_uid("prestem"))
| 2d1086447a25d281f9428832d046c473d80ad761 | 14 | convnext.py | 49 | Corrected preprocess_input docstring in regnet.py and convnext.py | 80,000 | 0 | 24 | 30 | 10 | 269,281 | 11 | keras | 5 | keras/applications/convnext.py | Python | 5 | {
"docstring": "Normalizes inputs with ImageNet-1k mean and std.\n\n Args:\n name (str): Name prefix.\n\n Returns:\n A presemt function.\n ",
"language": "en",
"n_whitespaces": 25,
"n_words": 16,
"vocab_size": 16
} | https://github.com/keras-team/keras.git |
|
23 | model_fn | def model_fn(features, labels, mode, params, config):
del config
hparams = params
length = features.length
spec = features.spec
is_training = mode == tf_estimator.ModeKeys.TRAIN
if is_training:
onset_labels = labels.onsets
offset_labels = labels.offsets
velocity_labels = labels.velocities
frame_labels = labels.labels
frame_label_weights = labels.label_weights
if hparams.stop_activation_gradient and not hparams.activation_loss:
raise ValueError(
'If stop_activation_gradient is true, activation_loss must be true.')
losses = {}
with slim.arg_scope([slim.batch_norm, slim.dropout], is_training=is_training):
with tf.variable_scope('onsets'):
onset_outputs = acoustic_model(
spec,
hparams,
lstm_units=hparams.onset_lstm_units,
lengths=length)
onset_probs = slim.fully_connected(
onset_outputs,
constants.MIDI_PITCHES,
activation_fn=tf.sigmoid,
scope='onset_probs')
# onset_probs_flat is used during inference.
onset_probs_flat = flatten_maybe_padded_sequences(onset_probs, length)
if is_training:
onset_labels_flat = flatten_maybe_padded_sequences(onset_labels, length)
onset_losses = tf_utils.log_loss(onset_labels_flat, onset_probs_flat)
tf.losses.add_loss(tf.reduce_mean(onset_losses))
losses['onset'] = onset_losses
with tf.variable_scope('offsets'):
offset_outputs = acoustic_model(
spec,
hparams,
lstm_units=hparams.offset_lstm_units,
lengths=length)
offset_probs = slim.fully_connected(
offset_outputs,
constants.MIDI_PITCHES,
activation_fn=tf.sigmoid,
scope='offset_probs')
# offset_probs_flat is used during inference.
offset_probs_flat = flatten_maybe_padded_sequences(offset_probs, length)
if is_training:
offset_labels_flat = flatten_maybe_padded_sequences(
offset_labels, length)
offset_losses = tf_utils.log_loss(offset_labels_flat, offset_probs_flat)
tf.losses.add_loss(tf.reduce_mean(offset_losses))
losses['offset'] = offset_losses
with tf.variable_scope('velocity'):
velocity_outputs = acoustic_model(
spec,
hparams,
lstm_units=hparams.velocity_lstm_units,
lengths=length)
velocity_values = slim.fully_connected(
velocity_outputs,
constants.MIDI_PITCHES,
activation_fn=None,
scope='onset_velocities')
velocity_values_flat = flatten_maybe_padded_sequences(
velocity_values, length)
if is_training:
velocity_labels_flat = flatten_maybe_padded_sequences(
velocity_labels, length)
velocity_loss = tf.reduce_sum(
onset_labels_flat *
tf.square(velocity_labels_flat - velocity_values_flat),
axis=1)
tf.losses.add_loss(tf.reduce_mean(velocity_loss))
losses['velocity'] = velocity_loss
with tf.variable_scope('frame'):
if not hparams.share_conv_features:
# TODO(eriche): this is broken when hparams.frame_lstm_units > 0
activation_outputs = acoustic_model(
spec,
hparams,
lstm_units=hparams.frame_lstm_units,
lengths=length)
activation_probs = slim.fully_connected(
activation_outputs,
constants.MIDI_PITCHES,
activation_fn=tf.sigmoid,
scope='activation_probs')
else:
activation_probs = slim.fully_connected(
onset_outputs,
constants.MIDI_PITCHES,
activation_fn=tf.sigmoid,
scope='activation_probs')
probs = []
if hparams.stop_onset_gradient:
probs.append(tf.stop_gradient(onset_probs))
else:
probs.append(onset_probs)
if hparams.stop_activation_gradient:
probs.append(tf.stop_gradient(activation_probs))
else:
probs.append(activation_probs)
if hparams.stop_offset_gradient:
probs.append(tf.stop_gradient(offset_probs))
else:
probs.append(offset_probs)
combined_probs = tf.concat(probs, 2)
if hparams.combined_lstm_units > 0:
outputs = lstm_layer(
combined_probs,
hparams.combined_lstm_units,
lengths=length if hparams.use_lengths else None,
stack_size=hparams.combined_rnn_stack_size,
use_cudnn=hparams.use_cudnn,
bidirectional=hparams.bidirectional)
else:
outputs = combined_probs
frame_probs = slim.fully_connected(
outputs,
constants.MIDI_PITCHES,
activation_fn=tf.sigmoid,
scope='frame_probs')
frame_probs_flat = flatten_maybe_padded_sequences(frame_probs, length)
if is_training:
frame_labels_flat = flatten_maybe_padded_sequences(frame_labels, length)
frame_label_weights_flat = flatten_maybe_padded_sequences(
frame_label_weights, length)
if hparams.weight_frame_and_activation_loss:
frame_loss_weights = frame_label_weights_flat
else:
frame_loss_weights = None
frame_losses = tf_utils.log_loss(
frame_labels_flat, frame_probs_flat, weights=frame_loss_weights)
tf.losses.add_loss(tf.reduce_mean(frame_losses))
losses['frame'] = frame_losses
if hparams.activation_loss:
if hparams.weight_frame_and_activation_loss:
activation_loss_weights = frame_label_weights
else:
activation_loss_weights = None
activation_losses = tf_utils.log_loss(
frame_labels_flat,
flatten_maybe_padded_sequences(activation_probs, length),
weights=activation_loss_weights)
tf.losses.add_loss(tf.reduce_mean(activation_losses))
losses['activation'] = activation_losses
frame_predictions = frame_probs_flat > hparams.predict_frame_threshold
onset_predictions = onset_probs_flat > hparams.predict_onset_threshold
offset_predictions = offset_probs_flat > hparams.predict_offset_threshold
frame_predictions = tf.expand_dims(frame_predictions, axis=0)
onset_predictions = tf.expand_dims(onset_predictions, axis=0)
offset_predictions = tf.expand_dims(offset_predictions, axis=0)
velocity_values = tf.expand_dims(velocity_values_flat, axis=0)
metrics_values = metrics.define_metrics(
frame_probs=frame_probs,
onset_probs=onset_probs,
frame_predictions=frame_predictions,
onset_predictions=onset_predictions,
offset_predictions=offset_predictions,
velocity_values=velocity_values,
length=features.length,
sequence_label=labels.note_sequence,
frame_labels=labels.labels,
sequence_id=features.sequence_id,
hparams=hparams)
for label, loss_collection in losses.items():
loss_label = 'losses/' + label
metrics_values[loss_label] = loss_collection
def predict_sequence():
| f73ff0c91f0159a925fb6547612199bb7c915248 | 18 | model.py | 1,442 | Explicitly import estimator from tensorflow as a separate import instead of accessing it via tf.estimator and depend on the tensorflow estimator target.
PiperOrigin-RevId: 436568278 | 40,851 | 0 | 1,488 | 1,401 | 217 | 173,538 | 385 | magenta | 114 | magenta/models/onsets_frames_transcription/model.py | Python | 228 | {
"docstring": "Builds the acoustic model.Convert frame predictions into a sequence (TF).",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | https://github.com/magenta/magenta.git |
|
1 | test_title_present | def test_title_present(self):
response = self.get(4)
self.assertContains(response, "Christmas", 3)
| d10f15e55806c6944827d801cd9c2d53f5da4186 | 8 | test_page_modeladmin.py | 42 | Reformat with black | 15,993 | 0 | 29 | 24 | 8 | 73,217 | 8 | wagtail | 5 | wagtail/contrib/modeladmin/tests/test_page_modeladmin.py | Python | 3 | {
"docstring": "\n The page title should appear three times. Once in the header, and two times\n in the field listing (as the actual title and as the draft title)\n ",
"language": "en",
"n_whitespaces": 49,
"n_words": 27,
"vocab_size": 21
} | https://github.com/wagtail/wagtail.git |
|
2 | all_triads | def all_triads(G):
triplets = combinations(G.nodes(), 3)
for triplet in triplets:
yield G.subgraph(triplet).copy()
@not_implemented_for("undirected") | db35812af218482b0ddf9ca47e4792e47e4d4666 | @not_implemented_for("undirected") | 12 | triads.py | 69 | Add docstring examples for triads functions (#5522)
Adds docstring examples to the functions in the triads module as well as
some additional explanatory text + links to other examples.
Co-authored-by: Ross Barnowski <[email protected]>
Co-authored-by: Mridul Seth <[email protected]> | 42,209 | 1 | 28 | 34 | 13 | 176,981 | 13 | networkx | 9 | networkx/algorithms/triads.py | Python | 4 | {
"docstring": "A generator of all possible triads in G.\n\n Parameters\n ----------\n G : digraph\n A NetworkX DiGraph\n\n Returns\n -------\n all_triads : generator of DiGraphs\n Generator of triads (order-3 DiGraphs)\n\n Examples\n --------\n >>> G = nx.DiGraph([(1, 2), (2, 3), (3, 1), (3, 4), (4, 1), (4, 2)])\n >>> for triad in nx.all_triads(G):\n ... print(triad.edges)\n [(1, 2), (2, 3), (3, 1)]\n [(1, 2), (4, 1), (4, 2)]\n [(3, 1), (3, 4), (4, 1)]\n [(2, 3), (3, 4), (4, 2)]\n\n ",
"language": "en",
"n_whitespaces": 140,
"n_words": 76,
"vocab_size": 45
} | https://github.com/networkx/networkx.git |
10 | totientrange | def totientrange(self, a, b):
a = max(1, _as_int_ceiling(a))
b = _as_int_ceiling(b)
n = len(self._tlist)
if a >= b:
return
elif b <= n:
for i in range(a, b):
yield self._tlist[i]
else:
self._tlist += _arange(n, b)
for i in range(1, n):
ti = self._tlist[i]
startindex = (n + i - 1) // i * i
for j in range(startindex, b, i):
self._tlist[j] -= ti
if i >= a:
yield ti
for i in range(n, b):
ti = self._tlist[i]
for j in range(2 * i, b, i):
self._tlist[j] -= ti
if i >= a:
yield ti
| e0dc14eca132f37c5f49369eb4051eae37c9b119 | 16 | generate.py | 274 | Refactored import ordering in functions | 48,298 | 0 | 394 | 177 | 50 | 197,041 | 94 | sympy | 15 | sympy/ntheory/generate.py | Python | 24 | {
"docstring": "Generate all totient numbers for the range [a, b).\n\n Examples\n ========\n\n >>> from sympy import sieve\n >>> print([i for i in sieve.totientrange(7, 18)])\n [6, 4, 6, 4, 10, 4, 12, 6, 8, 8, 16]\n ",
"language": "en",
"n_whitespaces": 76,
"n_words": 34,
"vocab_size": 28
} | https://github.com/sympy/sympy.git |
|
2 | get_deps | def get_deps(self, candidate):
key = format_requirement(candidate)
if key not in self.dep_dict:
from .requirements import Requirement
req = Requirement.from_line(key)
req = req.merge_markers(self.markers)
self.dep_dict[key] = req.get_abstract_dependencies()
return self.dep_dict[key]
| cd5a9683be69c86c8f3adcd13385a9bc5db198ec | 11 | dependencies.py | 105 | Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir. | 4,272 | 0 | 98 | 64 | 20 | 22,228 | 26 | pipenv | 13 | pipenv/vendor/requirementslib/models/dependencies.py | Python | 8 | {
"docstring": "Get the dependencies of the supplied candidate.\n\n :param candidate: An installrequirement\n :type candidate: :class:`~pipenv.patched.pip._internal.req.req_install.InstallRequirement`\n :return: A list of abstract dependencies\n :rtype: list[:class:`~requirementslib.models.dependency.AbstractDependency`]\n ",
"language": "en",
"n_whitespaces": 57,
"n_words": 22,
"vocab_size": 18
} | https://github.com/pypa/pipenv.git |
|
1 | test_all | def test_all(self):
self.write_settings("settings_to_diff.py", sdict={"STATIC_URL": "None"})
args = ["diffsettings", "--settings=settings_to_diff", "--all"]
out, err = self.run_manage(args)
self.assertNoOutput(err)
self.assertOutput(out, "### STATIC_URL = None")
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 11 | tests.py | 98 | Refs #33476 -- Reformatted code with Black. | 51,934 | 0 | 62 | 53 | 18 | 207,354 | 20 | django | 10 | tests/admin_scripts/tests.py | Python | 6 | {
"docstring": "The all option also shows settings with the default value.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | https://github.com/django/django.git |
|
15 | _validate | def _validate(self) -> None:
if (self._args.writer == "ffmpeg" and
not self._images.is_video and
self._args.reference_video is None):
raise FaceswapError("Output as video selected, but using frames as input. You must "
"provide a reference video ('-ref', '--reference-video').")
if (self._args.on_the_fly and
self._args.mask_type not in ("none", "extended", "components")):
logger.warning("You have selected an incompatible mask type ('%s') for On-The-Fly "
"conversion. Switching to 'extended'", self._args.mask_type)
self._args.mask_type = "extended"
if (not self._args.on_the_fly and
self._args.mask_type not in ("none", "predicted") and
not self._alignments.mask_is_valid(self._args.mask_type)):
msg = (f"You have selected the Mask Type `{self._args.mask_type}` but at least one "
"face does not have this mask stored in the Alignments File.\nYou should "
"generate the required masks with the Mask Tool or set the Mask Type option to "
"an existing Mask Type.\nA summary of existing masks is as follows:\nTotal "
f"faces: {self._alignments.faces_count}, "
f"Masks: {self._alignments.mask_summary}")
raise FaceswapError(msg)
if self._args.mask_type == "predicted" and not self._predictor.has_predicted_mask:
available_masks = [k for k, v in self._alignments.mask_summary.items()
if k != "none" and v == self._alignments.faces_count]
if not available_masks:
msg = ("Predicted Mask selected, but the model was not trained with a mask and no "
"masks are stored in the Alignments File.\nYou should generate the "
"required masks with the Mask Tool or set the Mask Type to `none`.")
raise FaceswapError(msg)
mask_type = available_masks[0]
logger.warning("Predicted Mask selected, but the model was not trained with a "
"mask. Selecting first available mask: '%s'", mask_type)
self._args.mask_type = mask_type
| 1022651eb8a7741014f5d2ec7cbfe882120dfa5f | 14 | convert.py | 423 | Bugfix: convert - Gif Writer
- Fix non-launch error on Gif Writer
- convert plugins - linting
- convert/fs_media/preview/queue_manager - typing
- Change convert items from dict to Dataclass | 20,791 | 0 | 727 | 224 | 125 | 101,376 | 230 | faceswap | 23 | scripts/convert.py | Python | 49 | {
"docstring": " Validate the Command Line Options.\n\n Ensure that certain cli selections are valid and won't result in an error. Checks:\n * If frames have been passed in with video output, ensure user supplies reference\n video.\n * If \"on-the-fly\" and a Neural Network mask is selected, warn and switch to 'extended'\n * If a mask-type is selected, ensure it exists in the alignments file.\n * If a predicted mask-type is selected, ensure model has been trained with a mask\n otherwise attempt to select first available masks, otherwise raise error.\n\n Raises\n ------\n FaceswapError\n If an invalid selection has been found.\n\n ",
"language": "en",
"n_whitespaces": 210,
"n_words": 97,
"vocab_size": 66
} | https://github.com/deepfakes/faceswap.git |
|
3 | test_cas_redirect_confirm | def test_cas_redirect_confirm(self) -> None:
base_url = "/_matrix/client/r0/login/cas/ticket?redirectUrl"
redirect_url = "https://dodgy-site.com/"
url_parts = list(urllib.parse.urlparse(base_url))
query = dict(urllib.parse.parse_qsl(url_parts[4]))
query.update({"redirectUrl": redirect_url})
query.update({"ticket": "ticket"})
url_parts[4] = urllib.parse.urlencode(query)
cas_ticket_url = urllib.parse.urlunparse(url_parts)
# Get Synapse to call the fake CAS and serve the template.
channel = self.make_request("GET", cas_ticket_url)
# Test that the response is HTML.
self.assertEqual(channel.code, 200, channel.result)
content_type_header_value = ""
for header in channel.result.get("headers", []):
if header[0] == b"Content-Type":
content_type_header_value = header[1].decode("utf8")
self.assertTrue(content_type_header_value.startswith("text/html"))
# Test that the body isn't empty.
self.assertTrue(len(channel.result["body"]) > 0)
# And that it contains our redirect link
self.assertIn(redirect_url, channel.result["body"].decode("UTF-8"))
| 64c73c6ac88a740ee480a0ad1f9afc8596bccfa4 | 13 | test_login.py | 333 | Add type hints to `tests/rest/client` (#12066) | 71,284 | 0 | 254 | 193 | 70 | 246,592 | 88 | synapse | 29 | tests/rest/client/test_login.py | Python | 21 | {
"docstring": "Tests that the SSO login flow serves a confirmation page before redirecting a\n user to the redirect URL.\n ",
"language": "en",
"n_whitespaces": 32,
"n_words": 18,
"vocab_size": 16
} | https://github.com/matrix-org/synapse.git |
|
1 | test_state_default_level | def test_state_default_level(self):
creator = "@creator:example.com"
pleb = "@joiner:example.com"
king = "@joiner2:example.com"
auth_events = [
_create_event(RoomVersions.V1, creator),
_join_event(RoomVersions.V1, creator),
_power_levels_event(
RoomVersions.V1,
creator,
{"state_default": "30", "users": {pleb: "29", king: "30"}},
),
_join_event(RoomVersions.V1, pleb),
_join_event(RoomVersions.V1, king),
]
# pleb should not be able to send state
self.assertRaises(
AuthError,
event_auth.check_auth_rules_for_event,
RoomVersions.V1,
_random_state_event(RoomVersions.V1, pleb),
auth_events,
),
# king should be able to send state
event_auth.check_auth_rules_for_event(
RoomVersions.V1,
_random_state_event(RoomVersions.V1, king),
auth_events,
)
| 2959184a42398277ff916206235b844a8f7be5d7 | 14 | test_event_auth.py | 202 | EventAuthTestCase: build events for the right room version
In practice, when we run the auth rules, all of the events have the right room
version. Let's stop building Room V1 events for these tests and use the right
version. | 72,341 | 0 | 348 | 130 | 43 | 248,549 | 65 | synapse | 16 | tests/test_event_auth.py | Python | 27 | {
"docstring": "\n Check that users above the state_default level can send state and\n those below cannot\n ",
"language": "en",
"n_whitespaces": 36,
"n_words": 14,
"vocab_size": 14
} | https://github.com/matrix-org/synapse.git |
|
5 | P | def P(self):
if self.data.minute == 0 and self.data.hour == 0:
return _("midnight")
if self.data.minute == 0 and self.data.hour == 12:
return _("noon")
return "%s %s" % (self.f(), self.a())
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 10 | dateformat.py | 112 | Refs #33476 -- Reformatted code with Black. | 51,583 | 0 | 78 | 66 | 18 | 206,599 | 28 | django | 8 | django/utils/dateformat.py | Python | 6 | {
"docstring": "\n Time, in 12-hour hours, minutes and 'a.m.'/'p.m.', with minutes left off\n if they're zero and the strings 'midnight' and 'noon' if appropriate.\n Examples: '1 a.m.', '1:30 p.m.', 'midnight', 'noon', '12:30 p.m.'\n Proprietary extension.\n ",
"language": "en",
"n_whitespaces": 69,
"n_words": 33,
"vocab_size": 29
} | https://github.com/django/django.git |
|
17 | sample | def sample(self) -> SampleBatchType:
if self.fake_sampler and self.last_batch is not None:
return self.last_batch
elif self.input_reader is None:
raise ValueError(
"RolloutWorker has no `input_reader` object! "
"Cannot call `sample()`. You can try setting "
"`create_env_on_driver` to True."
)
if log_once("sample_start"):
logger.info(
"Generating sample batch of size {}".format(
self.rollout_fragment_length
)
)
batches = [self.input_reader.next()]
steps_so_far = (
batches[0].count
if self.count_steps_by == "env_steps"
else batches[0].agent_steps()
)
# In truncate_episodes mode, never pull more than 1 batch per env.
# This avoids over-running the target batch size.
if self.batch_mode == "truncate_episodes":
max_batches = self.num_envs
else:
max_batches = float("inf")
while steps_so_far < self.rollout_fragment_length and (
len(batches) < max_batches or self.policy_config.get("offline_sampling")
):
batch = self.input_reader.next()
steps_so_far += (
batch.count
if self.count_steps_by == "env_steps"
else batch.agent_steps()
)
batches.append(batch)
batch = batches[0].concat_samples(batches) if len(batches) > 1 else batches[0]
self.callbacks.on_sample_end(worker=self, samples=batch)
# Always do writes prior to compression for consistency and to allow
# for better compression inside the writer.
self.output_writer.write(batch)
# Do off-policy estimation, if needed.
if self.reward_estimators:
for estimator in self.reward_estimators:
estimator.process(batch)
if log_once("sample_end"):
logger.info("Completed sample batch:\n\n{}\n".format(summarize(batch)))
if self.compress_observations:
batch.compress(bulk=self.compress_observations == "bulk")
if self.fake_sampler:
self.last_batch = batch
return batch
| 1243ed62bf4121c83881c3ddc095bc6a873a09f3 | 13 | rollout_worker.py | 483 | [RLlib] Make Dataset reader default reader and enable CRR to use dataset (#26304)
Co-authored-by: avnish <[email protected]> | 27,618 | 0 | 713 | 284 | 119 | 124,505 | 182 | ray | 41 | rllib/evaluation/rollout_worker.py | Python | 65 | {
"docstring": "Returns a batch of experience sampled from this worker.\n\n This method must be implemented by subclasses.\n\n Returns:\n A columnar batch of experiences (e.g., tensors).\n\n Examples:\n >>> import gym\n >>> from ray.rllib.evaluation.rollout_worker import RolloutWorker\n >>> from ray.rllib.algorithms.pg.pg_tf_policy import PGStaticGraphTFPolicy\n >>> worker = RolloutWorker( # doctest: +SKIP\n ... env_creator=lambda _: gym.make(\"CartPole-v0\"), # doctest: +SKIP\n ... policy_spec=PGStaticGraphTFPolicy) # doctest: +SKIP\n >>> print(worker.sample()) # doctest: +SKIP\n SampleBatch({\"obs\": [...], \"action\": [...], ...})\n ",
"language": "en",
"n_whitespaces": 198,
"n_words": 67,
"vocab_size": 46
} | https://github.com/ray-project/ray.git |
|
3 | to_dict | def to_dict(self) -> dict[str, str | float | bool | None]:
# Needed because dataclasses asdict() can't serialize Templates and ignores Properties.
dic = {
CONF_PLATFORM: self.platform,
CONF_ENTITY_ID: self.entity_id,
CONF_VALUE_TEMPLATE: self.template,
CONF_TO_STATE: self.to_state,
CONF_ABOVE: self.above,
CONF_BELOW: self.below,
CONF_P_GIVEN_T: self.prob_given_true,
CONF_P_GIVEN_F: self.prob_given_false,
"observed": self.observed,
}
for key, value in dic.copy().items():
if value is None:
del dic[key]
return dic
| dd1463da287f591652e47b00eee0c5b77f5f5b7c | 10 | helpers.py | 155 | Refactor bayesian observations using dataclass (#79590)
* refactor
* remove some changes
* remove typehint
* improve codestyle
* move docstring to comment
* < 88 chars
* avoid short var names
* more readable
* fix rename
* Update homeassistant/components/bayesian/helpers.py
Co-authored-by: epenet <[email protected]>
* Update homeassistant/components/bayesian/binary_sensor.py
Co-authored-by: epenet <[email protected]>
* Update homeassistant/components/bayesian/binary_sensor.py
Co-authored-by: epenet <[email protected]>
* no intermediate
* comment why set before list
Co-authored-by: epenet <[email protected]> | 87,643 | 0 | 224 | 104 | 53 | 288,486 | 57 | core | 28 | homeassistant/components/bayesian/helpers.py | Python | 17 | {
"docstring": "Represent Class as a Dict for easier serialization.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/home-assistant/core.git |
|
1 | test_slicing | def test_slicing(self):
s1 = SampleBatch(
{
"a": np.array([1, 2, 3, 2, 3, 4]),
"b": {"c": np.array([4, 5, 6, 5, 6, 7])},
}
)
check(
s1[:3],
{
"a": [1, 2, 3],
"b": {"c": [4, 5, 6]},
},
)
check(
s1[0:3],
{
"a": [1, 2, 3],
"b": {"c": [4, 5, 6]},
},
)
check(
s1[1:4],
{
"a": [2, 3, 2],
"b": {"c": [5, 6, 5]},
},
)
check(
s1[1:],
{
"a": [2, 3, 2, 3, 4],
"b": {"c": [5, 6, 5, 6, 7]},
},
)
check(
s1[3:4],
{
"a": [2],
"b": {"c": [5]},
},
)
# When we change the slice, the original SampleBatch should also
# change (shared underlying data).
s1[:3]["a"][0] = 100
s1[1:2]["a"][0] = 200
check(s1["a"][0], 100)
check(s1["a"][1], 200)
# Seq-len batches should be auto-sliced along sequences,
# no matter what.
s2 = SampleBatch(
{
"a": np.array([1, 2, 3, 2, 3, 4]),
"b": {"c": np.array([4, 5, 6, 5, 6, 7])},
SampleBatch.SEQ_LENS: [2, 3, 1],
"state_in_0": [1.0, 3.0, 4.0],
}
)
# We would expect a=[1, 2, 3] now, but due to the sequence
# boundary, we stop earlier.
check(
s2[:3],
{
"a": [1, 2],
"b": {"c": [4, 5]},
SampleBatch.SEQ_LENS: [2],
"state_in_0": [1.0],
},
)
# Split exactly at a seq-len boundary.
check(
s2[:5],
{
"a": [1, 2, 3, 2, 3],
"b": {"c": [4, 5, 6, 5, 6]},
SampleBatch.SEQ_LENS: [2, 3],
"state_in_0": [1.0, 3.0],
},
)
# Split above seq-len boundary.
check(
s2[:50],
{
"a": [1, 2, 3, 2, 3, 4],
"b": {"c": [4, 5, 6, 5, 6, 7]},
SampleBatch.SEQ_LENS: [2, 3, 1],
"state_in_0": [1.0, 3.0, 4.0],
},
)
check(
s2[:],
{
"a": [1, 2, 3, 2, 3, 4],
"b": {"c": [4, 5, 6, 5, 6, 7]},
SampleBatch.SEQ_LENS: [2, 3, 1],
"state_in_0": [1.0, 3.0, 4.0],
},
)
| 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | 15 | test_sample_batch.py | 903 | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | 33,076 | 0 | 1,352 | 639 | 101 | 143,840 | 286 | ray | 9 | rllib/policy/tests/test_sample_batch.py | Python | 90 | {
"docstring": "Tests, whether slicing can be done on SampleBatches.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/ray-project/ray.git |
|
1 | test_list_statistic_ids | async def test_list_statistic_ids(recorder_mock, hass, hass_ws_client, caplog):
await async_setup_component(hass, "history", {})
client = await hass_ws_client()
# Test the WS API works and issues a warning
await client.send_json({"id": 1, "type": "history/list_statistic_ids"})
response = await client.receive_json()
assert response["success"]
assert response["result"] == []
assert (
"WS API 'history/list_statistic_ids' is deprecated and will be removed in "
"Home Assistant Core 2022.12. Use 'recorder/list_statistic_ids' instead"
) in caplog.text
with patch(
"homeassistant.components.history.recorder_ws.ws_handle_list_statistic_ids",
wraps=ws_handle_list_statistic_ids,
) as ws_mock:
await client.send_json({"id": 2, "type": "history/list_statistic_ids"})
await client.receive_json()
ws_mock.assert_called_once()
| 31a787558fd312331b55e5c2c4b33341fc3601fc | 13 | test_init.py | 206 | Ensure recorder test fixture is setup before hass fixture (#80528)
* Ensure recorder test fixture is setup before hass fixture
* Adjust more tests | 88,515 | 0 | 162 | 112 | 61 | 289,373 | 77 | core | 16 | tests/components/history/test_init.py | Python | 18 | {
"docstring": "Test history/list_statistic_ids forwards to recorder.",
"language": "en",
"n_whitespaces": 4,
"n_words": 5,
"vocab_size": 5
} | https://github.com/home-assistant/core.git |
|
24 | copy_left_only | def copy_left_only(src, dest, module):
changed = False
owner = module.params['owner']
group = module.params['group']
local_follow = module.params['local_follow']
left_only = filecmp.dircmp(src, dest).left_only
if len(left_only):
changed = True
if not module.check_mode:
for item in left_only:
src_item_path = os.path.join(src, item)
dest_item_path = os.path.join(dest, item)
b_src_item_path = to_bytes(src_item_path, errors='surrogate_or_strict')
b_dest_item_path = to_bytes(dest_item_path, errors='surrogate_or_strict')
if os.path.islink(b_src_item_path) and os.path.isdir(b_src_item_path) and local_follow is True:
shutil.copytree(b_src_item_path, b_dest_item_path, symlinks=not local_follow)
chown_recursive(b_dest_item_path, module)
if os.path.islink(b_src_item_path) and os.path.isdir(b_src_item_path) and local_follow is False:
linkto = os.readlink(b_src_item_path)
os.symlink(linkto, b_dest_item_path)
if os.path.islink(b_src_item_path) and os.path.isfile(b_src_item_path) and local_follow is True:
shutil.copyfile(b_src_item_path, b_dest_item_path)
if owner is not None:
module.set_owner_if_different(b_dest_item_path, owner, False)
if group is not None:
module.set_group_if_different(b_dest_item_path, group, False)
if os.path.islink(b_src_item_path) and os.path.isfile(b_src_item_path) and local_follow is False:
linkto = os.readlink(b_src_item_path)
os.symlink(linkto, b_dest_item_path)
if not os.path.islink(b_src_item_path) and os.path.isfile(b_src_item_path):
shutil.copyfile(b_src_item_path, b_dest_item_path)
shutil.copymode(b_src_item_path, b_dest_item_path)
if owner is not None:
module.set_owner_if_different(b_dest_item_path, owner, False)
if group is not None:
module.set_group_if_different(b_dest_item_path, group, False)
if not os.path.islink(b_src_item_path) and os.path.isdir(b_src_item_path):
shutil.copytree(b_src_item_path, b_dest_item_path, symlinks=not local_follow)
chown_recursive(b_dest_item_path, module)
changed = True
return changed
| 650befed37eadcaea735673638d5475fa957ca7e | 15 | copy.py | 634 | Add missing space after keywords. (#78480)
Also remove unnecessary parenthesis. | 79,439 | 0 | 618 | 408 | 63 | 268,182 | 155 | ansible | 38 | lib/ansible/modules/copy.py | Python | 41 | {
"docstring": "Copy files that exist in `src` directory only to the `dest` directory.",
"language": "en",
"n_whitespaces": 11,
"n_words": 12,
"vocab_size": 12
} | https://github.com/ansible/ansible.git |
|
2 | __del__ | def __del__(self):
if self.frame_id is not None:
self._server.dropTable(self.frame_id)
| 1c0935c1bc0856d43f69c1e32498636ee24ebc85 | 10 | partition.py | 41 | FEAT-#4913: Enabling pyhdk (#4900)
Co-authored-by: ienkovich <[email protected]>
Signed-off-by: izamyati <[email protected]> | 35,961 | 0 | 33 | 24 | 8 | 154,404 | 8 | modin | 5 | modin/experimental/core/execution/native/implementations/omnisci_on_native/partitioning/partition.py | Python | 3 | {
"docstring": "Deallocate OmniSci resources related to the partition.",
"language": "en",
"n_whitespaces": 6,
"n_words": 7,
"vocab_size": 7
} | https://github.com/modin-project/modin.git |
|
1 | PowerFunction | def PowerFunction(name, alpha, a, b):
r
return rv(name, PowerFunctionDistribution, (alpha, a, b))
#-------------------------------------------------------------------------------
# QuadraticU distribution ------------------------------------------------------
| 9ad8ab9fe58051cf11626ba6654852fcfec60147 | 8 | crv_types.py | 40 | Documentation cleanup 5 | 48,091 | 0 | 20 | 28 | 16 | 196,673 | 17 | sympy | 7 | sympy/stats/crv_types.py | Python | 63 | {
"docstring": "\n Creates a continuous random variable with a Power Function Distribution.\n\n Explanation\n ===========\n\n The density of PowerFunction distribution is given by\n\n .. math::\n f(x) := \\frac{{\\alpha}(x - a)^{\\alpha - 1}}{(b - a)^{\\alpha}}\n\n with :math:`x \\in [a,b]`.\n\n Parameters\n ==========\n\n alpha: Positive number, `0 < alpha`, the shape paramater\n a : Real number, :math:`-\\infty < a`, the left boundary\n b : Real number, :math:`a < b < \\infty`, the right boundary\n\n Returns\n =======\n\n RandomSymbol\n\n Examples\n ========\n\n >>> from sympy.stats import PowerFunction, density, cdf, E, variance\n >>> from sympy import Symbol\n >>> alpha = Symbol(\"alpha\", positive=True)\n >>> a = Symbol(\"a\", real=True)\n >>> b = Symbol(\"b\", real=True)\n >>> z = Symbol(\"z\")\n\n >>> X = PowerFunction(\"X\", 2, a, b)\n\n >>> density(X)(z)\n (-2*a + 2*z)/(-a + b)**2\n\n >>> cdf(X)(z)\n Piecewise((a**2/(a**2 - 2*a*b + b**2) - 2*a*z/(a**2 - 2*a*b + b**2) +\n z**2/(a**2 - 2*a*b + b**2), a <= z), (0, True))\n\n >>> alpha = 2\n >>> a = 0\n >>> b = 1\n >>> Y = PowerFunction(\"Y\", alpha, a, b)\n\n >>> E(Y)\n 2/3\n\n >>> variance(Y)\n 1/18\n\n References\n ==========\n\n .. [1] http://www.mathwave.com/help/easyfit/html/analyses/distributions/power_func.html\n\n ",
"language": "en",
"n_whitespaces": 302,
"n_words": 174,
"vocab_size": 111
} | https://github.com/sympy/sympy.git |
|
1 | get_employees | def get_employees(filters):
conditions = get_conditions(filters)
return frappe.db.sql(
% conditions,
as_list=1,
)
| 494bd9ef78313436f0424b918f200dab8fc7c20b | 9 | employee_analytics.py | 44 | style: format code with black | 14,144 | 0 | 5 | 27 | 11 | 66,234 | 11 | erpnext | 8 | erpnext/hr/report/employee_analytics/employee_analytics.py | Python | 9 | {
"docstring": "select name, employee_name, date_of_birth,\n\tbranch, department, designation,\n\tgender, company from `tabEmployee` where status = 'Active' %s",
"language": "en",
"n_whitespaces": 13,
"n_words": 16,
"vocab_size": 16
} | https://github.com/frappe/erpnext.git |
|
11 | build_dependency | def build_dependency(self):
self.groups = {}
for node in self.graph.nodes_py.nodes_op:
if node.op_type in ['Conv2d', 'ConvTranspose2d', "GroupNorm"]:
if node.op_type in ['Conv2d', 'ConvTranspose2d']:
group = self._get_conv_groups(node)
elif node.op_type == "GroupNorm":
group = self._get_group_norm_condition(node)
if node.name in self.groups:
# the conv layer whose group is larger than 1 will require that
# it's number of output channel to be divisible by the number of group.
self.groups[node.name].append(group)
else:
self.groups[node.name] = [group]
if group > 1:
# for the conv layer whose group is larger than 1, it will require the number
# of output channels of their parent conv layer to be divisible by group.
parent_convs = self._get_parent_convs(node)
for parent in parent_convs:
if parent in self.groups:
self.groups[parent].append(group)
else:
self.groups[parent] = [group]
for name in self.groups:
self.dependency[name] = lcm_list(self.groups[name])
if min(self.groups[name]) == gcd_list(self.groups[name]):
self.min_groups[name] = min(self.groups[name])
else:
self.min_groups[name] = 1
return self.dependency
| 4cf680090f8a07fdffaebca2e0c2a4f41a9e4315 | 19 | shape_dependency.py | 369 | Add Group Norm support for Pruning model (#5069) | 24,906 | 0 | 610 | 228 | 69 | 113,425 | 136 | nni | 21 | nni/compression/pytorch/utils/shape_dependency.py | Python | 26 | {
"docstring": "\n Build the channel dependency for the conv layers\n in the model. This function return the group number\n of each conv layers. Note that, here, the group count\n of conv layers may be larger than their originl groups.\n This is because that the input channel will also be grouped\n for the group conv layers. To make this clear, assume we\n have two group conv layers: conv1(group=2), conv2(group=4).\n conv2 takes the output features of conv1 as input.\n Then we have to the filters of conv1 can still be\n divided into 4 groups after filter pruning, because\n the input channels of conv2 should be divided into\n 4 groups.\n\n Returns\n -------\n self.dependency : dict\n key: the name of conv layers, value: the minimum value that the number of\n filters should be divisible to.\n ",
"language": "en",
"n_whitespaces": 264,
"n_words": 129,
"vocab_size": 80
} | https://github.com/microsoft/nni.git |
|
15 | try_cast_to_pandas | def try_cast_to_pandas(obj, squeeze=False):
if hasattr(obj, "_to_pandas"):
result = obj._to_pandas()
if squeeze:
result = result.squeeze(axis=1)
return result
if hasattr(obj, "to_pandas"):
result = obj.to_pandas()
if squeeze:
result = result.squeeze(axis=1)
# Query compiler case, it doesn't have logic about convertion to Series
if (
isinstance(getattr(result, "name", None), str)
and result.name == MODIN_UNNAMED_SERIES_LABEL
):
result.name = None
return result
if isinstance(obj, (list, tuple)):
return type(obj)([try_cast_to_pandas(o, squeeze=squeeze) for o in obj])
if isinstance(obj, dict):
return {k: try_cast_to_pandas(v, squeeze=squeeze) for k, v in obj.items()}
if callable(obj):
module_hierarchy = getattr(obj, "__module__", "").split(".")
fn_name = getattr(obj, "__name__", None)
if fn_name and module_hierarchy[0] == "modin":
return (
getattr(pandas.DataFrame, fn_name, obj)
if module_hierarchy[-1] == "dataframe"
else getattr(pandas.Series, fn_name, obj)
)
return obj
| 3f985ed6864cc1b5b587094d75ca5b2695e4139f | 14 | utils.py | 376 | REFACTOR-#4796: Introduce constant for __reduced__ column name (#4799)
Co-authored-by: Mahesh Vashishtha <[email protected]>
Co-authored-by: Alexey Prutskov <[email protected]>
Co-authored-by: Yaroslav Igoshev <[email protected]>
Signed-off-by: Jonathan Shi <[email protected]> | 35,865 | 0 | 353 | 237 | 71 | 154,218 | 112 | modin | 28 | modin/utils.py | Python | 30 | {
"docstring": "\n Convert `obj` and all nested objects from Modin to pandas if it is possible.\n\n If no convertion possible return `obj`.\n\n Parameters\n ----------\n obj : object\n Object to convert from Modin to pandas.\n squeeze : bool, default: False\n Squeeze the converted object(s) before returning them.\n\n Returns\n -------\n object\n Converted object.\n ",
"language": "en",
"n_whitespaces": 101,
"n_words": 49,
"vocab_size": 43
} | https://github.com/modin-project/modin.git |
|
1 | test_backfill_floating_outlier_membership_auth | def test_backfill_floating_outlier_membership_auth(self):
OTHER_SERVER = "otherserver"
OTHER_USER = "@otheruser:" + OTHER_SERVER
# create the room
user_id = self.register_user("kermit", "test")
tok = self.login("kermit", "test")
room_id = self.helper.create_room_as(
room_creator=user_id,
is_public=True,
tok=tok,
extra_content={
"preset": "public_chat",
},
)
room_version = self.get_success(self.store.get_room_version(room_id))
prev_event_ids = self.get_success(self.store.get_prev_events_for_room(room_id))
(
most_recent_prev_event_id,
most_recent_prev_event_depth,
) = self.get_success(self.store.get_max_depth_of(prev_event_ids))
# mapping from (type, state_key) -> state_event_id
prev_state_map = self.get_success(
self.state_store.get_state_ids_for_event(most_recent_prev_event_id)
)
# List of state event ID's
prev_state_ids = list(prev_state_map.values())
auth_event_ids = prev_state_ids
auth_events = list(
self.get_success(self.store.get_events(auth_event_ids)).values()
)
# build a floating outlier member state event
fake_prev_event_id = "$" + random_string(43)
member_event_dict = {
"type": EventTypes.Member,
"content": {
"membership": "join",
},
"state_key": OTHER_USER,
"room_id": room_id,
"sender": OTHER_USER,
"depth": most_recent_prev_event_depth,
"prev_events": [fake_prev_event_id],
"origin_server_ts": self.clock.time_msec(),
"signatures": {OTHER_SERVER: {"ed25519:key_version": "SomeSignatureHere"}},
}
builder = self.hs.get_event_builder_factory().for_room_version(
room_version, member_event_dict
)
member_event = self.get_success(
builder.build(
prev_event_ids=member_event_dict["prev_events"],
auth_event_ids=self._event_auth_handler.compute_auth_events(
builder,
prev_state_map,
for_verification=False,
),
depth=member_event_dict["depth"],
)
)
# Override the signature added from "test" homeserver that we created the event with
member_event.signatures = member_event_dict["signatures"]
# Add the new member_event to the StateMap
prev_state_map[
(member_event.type, member_event.state_key)
] = member_event.event_id
auth_events.append(member_event)
# build and send an event authed based on the member event
message_event_dict = {
"type": EventTypes.Message,
"content": {},
"room_id": room_id,
"sender": OTHER_USER,
"depth": most_recent_prev_event_depth,
"prev_events": prev_event_ids.copy(),
"origin_server_ts": self.clock.time_msec(),
"signatures": {OTHER_SERVER: {"ed25519:key_version": "SomeSignatureHere"}},
}
builder = self.hs.get_event_builder_factory().for_room_version(
room_version, message_event_dict
)
message_event = self.get_success(
builder.build(
prev_event_ids=message_event_dict["prev_events"],
auth_event_ids=self._event_auth_handler.compute_auth_events(
builder,
prev_state_map,
for_verification=False,
),
depth=message_event_dict["depth"],
)
)
# Override the signature added from "test" homeserver that we created the event with
message_event.signatures = message_event_dict["signatures"]
# Stub the /event_auth response from the OTHER_SERVER | 0fb3dd0830e476c0e0b89c3bf6c7855a4129ff11 | 15 | test_federation.py | 755 | Refactor the way we set `outlier` (#11634)
* `_auth_and_persist_outliers`: mark persisted events as outliers
Mark any events that get persisted via `_auth_and_persist_outliers` as, well,
outliers.
Currently this will be a no-op as everything will already be flagged as an
outlier, but I'm going to change that.
* `process_remote_join`: stop flagging as outlier
The events are now flagged as outliers later on, by `_auth_and_persist_outliers`.
* `send_join`: remove `outlier=True`
The events created here are returned in the result of `send_join` to
`FederationHandler.do_invite_join`. From there they are passed into
`FederationEventHandler.process_remote_join`, which passes them to
`_auth_and_persist_outliers`... which sets the `outlier` flag.
* `get_event_auth`: remove `outlier=True`
stop flagging the events returned by `get_event_auth` as outliers. This method
is only called by `_get_remote_auth_chain_for_event`, which passes the results
into `_auth_and_persist_outliers`, which will flag them as outliers.
* `_get_remote_auth_chain_for_event`: remove `outlier=True`
we pass all the events into `_auth_and_persist_outliers`, which will now flag
the events as outliers.
* `_check_sigs_and_hash_and_fetch`: remove unused `outlier` parameter
This param is now never set to True, so we can remove it.
* `_check_sigs_and_hash_and_fetch_one`: remove unused `outlier` param
This is no longer set anywhere, so we can remove it.
* `get_pdu`: remove unused `outlier` parameter
... and chase it down into `get_pdu_from_destination_raw`.
* `event_from_pdu_json`: remove redundant `outlier` param
This is never set to `True`, so can be removed.
* changelog
* update docstring | 70,950 | 0 | 1,189 | 523 | 136 | 246,021 | 243 | synapse | 58 | tests/handlers/test_federation.py | Python | 98 | {
"docstring": "\n As the local homeserver, check that we can properly process a federated\n event from the OTHER_SERVER with auth_events that include a floating\n membership event from the OTHER_SERVER.\n\n Regression test, see #10439.\n ",
"language": "en",
"n_whitespaces": 67,
"n_words": 31,
"vocab_size": 25
} | https://github.com/matrix-org/synapse.git |
|
7 | check_against_chunks | def check_against_chunks(self, chunks):
# type: (Iterator[bytes]) -> None
gots = {}
for hash_name in self._allowed.keys():
try:
gots[hash_name] = hashlib.new(hash_name)
except (ValueError, TypeError):
raise InstallationError(f"Unknown hash name: {hash_name}")
for chunk in chunks:
for hash in gots.values():
hash.update(chunk)
for hash_name, got in gots.items():
if got.hexdigest() in self._allowed[hash_name]:
return
self._raise(gots)
| f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | 14 | hashes.py | 167 | upd; format | 12,436 | 0 | 200 | 101 | 38 | 61,197 | 47 | transferlearning | 20 | .venv/lib/python3.8/site-packages/pip/_internal/utils/hashes.py | Python | 14 | {
"docstring": "Check good hashes against ones built from iterable of chunks of\n data.\n\n Raise HashMismatch if none match.\n\n ",
"language": "en",
"n_whitespaces": 38,
"n_words": 17,
"vocab_size": 16
} | https://github.com/jindongwang/transferlearning.git |
|
2 | world_size | def world_size(self) -> int:
world_size = os.environ.get("JSM_NAMESPACE_SIZE")
if world_size is None:
raise ValueError(
"Cannot determine world size. Environment variable `JSM_NAMESPACE_SIZE` not found."
"Make sure you run your executable with `jsrun`."
)
return int(world_size)
| dbf1acd5a553ffc1546734be164cc89cef2b741d | 11 | lsf_environment.py | 64 | Modify LSFEnvironment to use more reliable environment variable (#10825)
Co-authored-by: thomas chaton <[email protected]>
Co-authored-by: Carlos Mocholí <[email protected]>
Co-authored-by: Adrian Wälchli <[email protected]>
Co-authored-by: Jirka Borovec <[email protected]> | 69,627 | 0 | 113 | 34 | 32 | 241,623 | 33 | lightning | 7 | pytorch_lightning/plugins/environments/lsf_environment.py | Python | 9 | {
"docstring": "The world size is read from the environment variable ``JSM_NAMESPACE_SIZE``.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | https://github.com/Lightning-AI/lightning.git |
|
4 | write_to_directory | def write_to_directory(self, dataset_info_dir, pretty_print=False, fs=None):
fs = fs or LocalFileSystem()
is_local = not is_remote_filesystem(fs)
path_join = os.path.join if is_local else posixpath.join
with fs.open(path_join(dataset_info_dir, config.DATASET_INFO_FILENAME), "wb") as f:
self._dump_info(f, pretty_print=pretty_print)
if self.license:
with fs.open(path_join(dataset_info_dir, config.LICENSE_FILENAME), "wb") as f:
self._dump_license(f)
| 139d210b05f0ca9e9bbe29fdd628a3339d1fa813 | 15 | info.py | 167 | Download and prepare as Parquet for cloud storage (#4724)
* use fsspec for caching
* add parquet writer
* add file_format argument
* style
* use "gs" instead of "gcs" for apache beam + use is_remote_filesystem
* typo
* fix test
* test ArrowWriter with filesystem
* test parquet writer
* more tests
* more tests
* fix nullcontext on 3.6
* parquet_writer.write_batch is not available in pyarrow 6
* remove reference to open file
* fix test
* docs
* docs: dask from parquet files
* Apply suggestions from code review
Co-authored-by: Mario Šaško <[email protected]>
* use contextlib.nullcontext
* fix missing import
* Use unstrip_protocol to merge protocol and path
* remove bad "raise" and add TODOs
* add output_dir arg to download_and_prepare
* update tests
* update docs
* fix tests
* fix tests
* fix output parent dir creattion
* Apply suggestions from code review
Co-authored-by: Albert Villanova del Moral <[email protected]>
* revert changes for remote cache_dir
* fix wording in the docs: load -> download and prepare
* style
* fix
* simplify incomplete_dir
* fix tests
* albert's comments
Co-authored-by: Mario Šaško <[email protected]>
Co-authored-by: Albert Villanova del Moral <[email protected]> | 22,165 | 0 | 117 | 102 | 28 | 105,576 | 38 | datasets | 21 | src/datasets/info.py | Python | 9 | {
"docstring": "Write `DatasetInfo` and license (if present) as JSON files to `dataset_info_dir`.\n\n Args:\n dataset_info_dir (str): Destination directory.\n pretty_print (bool, default ``False``): If True, the JSON will be pretty-printed with the indent level of 4.\n fs (``fsspec.spec.AbstractFileSystem``, optional, defaults ``None``):\n Instance of the remote filesystem used to download the files from.\n\n <Added version=\"2.5.0\"/>\n\n Example:\n\n ```py\n >>> from datasets import load_dataset\n >>> ds = load_dataset(\"rotten_tomatoes\", split=\"validation\")\n >>> ds.info.write_to_directory(\"/path/to/directory/\")\n ```\n ",
"language": "en",
"n_whitespaces": 185,
"n_words": 66,
"vocab_size": 57
} | https://github.com/huggingface/datasets.git |
|
1 | test_span_selector_animated_artists_callback | def test_span_selector_animated_artists_callback():
x = np.linspace(0, 2 * np.pi, 100)
values = np.sin(x)
fig, ax = plt.subplots()
(ln,) = ax.plot(x, values, animated=True)
(ln2, ) = ax.plot([], animated=True)
plt.pause(0.1)
ax.draw_artist(ln)
fig.canvas.blit(fig.bbox)
| e4dadb672ac01525f7f41ddabd844cb99e871502 | 10 | test_widgets.py | 147 | Fix getting tuple of animated artists; add comments and test | 22,578 | 0 | 56 | 352 | 24 | 107,064 | 29 | matplotlib | 20 | lib/matplotlib/tests/test_widgets.py | Python | 36 | {
"docstring": "Check that the animated artists changed in callbacks are updated.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | https://github.com/matplotlib/matplotlib.git |
|
2 | _visibility_unit | def _visibility_unit(self) -> str:
if (
weather_option_visibility_unit := self._weather_option_visibility_unit
) is not None:
return weather_option_visibility_unit
return self._default_visibility_unit
| 90e1fb6ce2faadb9a35fdbe1774fce7b4456364f | 9 | __init__.py | 43 | Weather unit conversion (#73441)
Co-authored-by: Erik <[email protected]> | 112,843 | 0 | 67 | 26 | 15 | 314,235 | 17 | core | 6 | homeassistant/components/weather/__init__.py | Python | 10 | {
"docstring": "Return the converted unit of measurement for visibility.\n\n Should not be set by integrations.\n ",
"language": "en",
"n_whitespaces": 28,
"n_words": 14,
"vocab_size": 14
} | https://github.com/home-assistant/core.git |
|
1 | test_consent | def test_consent(self) -> None:
# Have the admin user accept the terms.
self.get_success(self.store.user_set_consent_version(self.admin_user, "1.0"))
# First, cheekily accept the terms and create a room
self.get_success(self.store.user_set_consent_version(self.other_user, "1.0"))
room_id = self.helper.create_room_as(self.other_user, tok=self.other_user_tok)
self.helper.send_event(room_id, "com.example.test", tok=self.other_user_tok)
# Now unaccept it and check that we can't send an event
self.get_success(self.store.user_set_consent_version(self.other_user, "0.0"))
self.helper.send_event(
room_id,
"com.example.test",
tok=self.other_user_tok,
expect_code=HTTPStatus.FORBIDDEN,
)
# Login in as the user
puppet_token = self._get_token()
# Sending an event on their behalf should work fine
self.helper.send_event(room_id, "com.example.test", tok=puppet_token)
| 901b264c0c88f39cbfb8b2229e0dc57968882658 | 10 | test_user.py | 225 | Add type hints to `tests/rest/admin` (#11851) | 71,079 | 0 | 224 | 137 | 56 | 246,185 | 75 | synapse | 18 | tests/rest/admin/test_user.py | Python | 15 | {
"docstring": "Test that sending a message is not subject to the privacy policies.",
"language": "en",
"n_whitespaces": 11,
"n_words": 12,
"vocab_size": 12
} | https://github.com/matrix-org/synapse.git |
|
1 | perform_create | def perform_create(self, serializer):
project_id = self.request.data.get('project')
project = generics.get_object_or_404(Project, pk=project_id)
instance = serializer.save(project=project)
emit_webhooks_for_instance(self.request.user.active_organization, project, WebhookAction.TASKS_CREATED, [instance])
@method_decorator(name='get', decorator=swagger_auto_schema(
tags=['Tasks'],
operation_summary='Get task',
operation_description=,
manual_parameters=[
openapi.Parameter(
name='id',
type=openapi.TYPE_STRING,
in_=openapi.IN_PATH,
description='Task ID'
),
]))
@method_decorator(name='patch', decorator=swagger_auto_schema(
tags=['Tasks'],
operation_summary='Update task',
operation_description='Update the attributes of an existing labeling task.',
manual_parameters=[
openapi.Parameter(
name='id',
type=openapi.TYPE_STRING,
in_=openapi.IN_PATH,
description='Task ID'
),
],
request_body=TaskSimpleSerializer))
@method_decorator(name='delete', decorator=swagger_auto_schema(
tags=['Tasks'],
operation_summary='Delete task',
operation_description='Delete a task in Label Studio. This action cannot be undone!',
manual_parameters=[
openapi.Parameter(
name='id',
type=openapi.TYPE_STRING,
in_=openapi.IN_PATH,
description='Task ID'
),
],
)) | 71a9ada93224ed6433fb5b45bfcd60d5fe3edd4c | @method_decorator(name='get', decorator=swagger_auto_schema(
tags=['Tasks'],
operation_summary='Get task',
operation_description="""
Get task data, metadata, annotations and other attributes for a specific labeling task by task ID.
""",
manual_parameters=[
openapi.Parameter(
name='id',
type=openapi.TYPE_STRING,
in_=openapi.IN_PATH,
description='Task ID'
),
]))
@method_decorator(name='patch', decorator=swagger_auto_schema(
tags=['Tasks'],
operation_summary='Update task',
operation_description='Update the attributes of an existing labeling task.',
manual_parameters=[
openapi.Parameter(
name='id',
type=openapi.TYPE_STRING,
in_=openapi.IN_PATH,
description='Task ID'
),
],
request_body=TaskSimpleSerializer))
@method_decorator(name='delete', decorator=swagger_auto_schema(
tags=['Tasks'],
operation_summary='Delete task',
operation_description='Delete a task in Label Studio. This action cannot be undone!',
manual_parameters=[
openapi.Parameter(
name='id',
type=openapi.TYPE_STRING,
in_=openapi.IN_PATH,
description='Task ID'
),
],
)) | 15 | api.py | 371 | feat: DEV-2896: Comment List API (#2704)
* feat: DEV-2896: Comment List API
* Fix
* Fix tests
* Fix more tests
* Fixes
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/dm2
* Fix feature flags
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
* Add fixes
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/dm2
* [submodules] Build static heartexlabs/label-studio-frontend
* Add user id to base.html
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/dm2
* [submodules] Build static heartexlabs/dm2
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/dm2
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/dm2
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/dm2
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/dm2
* [submodules] Build static heartexlabs/label-studio-frontend
* [submodules] Build static heartexlabs/label-studio-frontend
Co-authored-by: Brandon Martel <[email protected]> | 42,564 | 1 | 470 | 71 | 56 | 177,995 | 81 | label-studio | 36 | label_studio/tasks/api.py | Python | 6 | {
"docstring": "\n Get task data, metadata, annotations and other attributes for a specific labeling task by task ID.\n ",
"language": "en",
"n_whitespaces": 31,
"n_words": 16,
"vocab_size": 14
} | https://github.com/heartexlabs/label-studio.git |
3 | prepare_test_settings | def prepare_test_settings(self, alias):
try:
conn = self.databases[alias]
except KeyError:
raise self.exception_class(f"The connection '{alias}' doesn't exist.")
test_settings = conn.setdefault("TEST", {})
default_test_settings = [
("CHARSET", None),
("COLLATION", None),
("MIGRATE", True),
("MIRROR", None),
("NAME", None),
]
for key, value in default_test_settings:
test_settings.setdefault(key, value)
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 12 | utils.py | 146 | Refs #33476 -- Reformatted code with Black. | 51,278 | 0 | 177 | 89 | 35 | 205,912 | 40 | django | 12 | django/db/utils.py | Python | 15 | {
"docstring": "\n Make sure the test settings are available in the 'TEST' sub-dictionary.\n ",
"language": "en",
"n_whitespaces": 26,
"n_words": 11,
"vocab_size": 10
} | https://github.com/django/django.git |
|
2 | execute | def execute():
accounting_dimensions = frappe.db.sql(
,
as_dict=1,
)
doclist = get_doctypes_with_dimensions()
for dimension in accounting_dimensions:
frappe.db.sql(
% ("%s", ", ".join(["%s"] * len(doclist))), # nosec
tuple([dimension.fieldname] + doclist),
)
| 494bd9ef78313436f0424b918f200dab8fc7c20b | 16 | update_owner_fields_in_acc_dimension_custom_fields.py | 114 | style: format code with black | 14,300 | 0 | 18 | 67 | 25 | 66,700 | 28 | erpnext | 13 | erpnext/patches/v12_0/update_owner_fields_in_acc_dimension_custom_fields.py | Python | 17 | {
"docstring": "select fieldname from\n\t\t`tabAccounting Dimension`\n\t\t\tUPDATE `tabCustom Field`\n\t\t\tSET owner = 'Administrator'\n\t\t\tWHERE fieldname = %s\n\t\t\tAND dt IN (%s)",
"language": "en",
"n_whitespaces": 14,
"n_words": 20,
"vocab_size": 18
} | https://github.com/frappe/erpnext.git |
|
1 | async_setup_entity | async def async_setup_entity(hass, entity_id):
return (await async_setup_entities(hass, [entity_id]))[0]
| 923fa473e171fcdf396556ea200612e378f9b0a5 | 11 | conftest.py | 38 | Blebox add thermoBox to climate (#81090)
Co-authored-by: Martin Hjelmare <[email protected]> | 96,116 | 0 | 14 | 23 | 8 | 297,147 | 8 | core | 4 | tests/components/blebox/conftest.py | Python | 2 | {
"docstring": "Return a configured entry with the given entity_id.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/home-assistant/core.git |
|
1 | outputs | def outputs(self) -> Mapping[str, Mapping[int, str]]:
common_outputs = self._tasks_to_common_outputs[self.task]
return copy.deepcopy(common_outputs)
| 50dd314d939a86f3a81e19af01459f449fbaeeca | 8 | config.py | 54 | Add ONNX export for ViT (#15658)
* Add ONNX support for ViT
* Refactor to use generic preprocessor
* Add vision dep to tests
* Extend ONNX slow tests to ViT
* Add dummy image generator
* Use model_type to determine modality
* Add deprecation warnings for tokenizer argument
* Add warning when overwriting the preprocessor
* Add optional args to docstrings
* Add minimum PyTorch version to OnnxConfig
* Refactor OnnxConfig class variables from CONSTANT_NAME to snake_case
* Add reasonable value for default atol
Co-authored-by: Sylvain Gugger <[email protected]> | 6,563 | 0 | 32 | 35 | 11 | 36,021 | 11 | transformers | 10 | src/transformers/onnx/config.py | Python | 9 | {
"docstring": "\n Mapping containing the axis definition of the output tensors to provide to the model\n\n Returns:\n For each output: its name associated to the axes symbolic name and the axis position within the tensor\n ",
"language": "en",
"n_whitespaces": 66,
"n_words": 33,
"vocab_size": 24
} | https://github.com/huggingface/transformers.git |
|
3 | test_valid_search_order | def test_valid_search_order(self) -> None:
# fetch the most recent first, largest timestamp
channel = self.make_request(
"GET",
self.url + "?dir=b",
access_token=self.admin_user_tok,
)
self.assertEqual(200, channel.code, msg=channel.json_body)
self.assertEqual(channel.json_body["total"], 20)
self.assertEqual(len(channel.json_body["event_reports"]), 20)
report = 1
while report < len(channel.json_body["event_reports"]):
self.assertGreaterEqual(
channel.json_body["event_reports"][report - 1]["received_ts"],
channel.json_body["event_reports"][report]["received_ts"],
)
report += 1
# fetch the oldest first, smallest timestamp
channel = self.make_request(
"GET",
self.url + "?dir=f",
access_token=self.admin_user_tok,
)
self.assertEqual(200, channel.code, msg=channel.json_body)
self.assertEqual(channel.json_body["total"], 20)
self.assertEqual(len(channel.json_body["event_reports"]), 20)
report = 1
while report < len(channel.json_body["event_reports"]):
self.assertLessEqual(
channel.json_body["event_reports"][report - 1]["received_ts"],
channel.json_body["event_reports"][report]["received_ts"],
)
report += 1
| c97042f7eef3748e17c90e48a4122389a89c4735 | 13 | test_event_reports.py | 398 | Use literals in place of `HTTPStatus` constants in tests (#13469) | 72,595 | 0 | 394 | 244 | 42 | 249,088 | 83 | synapse | 15 | tests/rest/admin/test_event_reports.py | Python | 34 | {
"docstring": "\n Testing search order. Order by timestamps.\n ",
"language": "en",
"n_whitespaces": 21,
"n_words": 6,
"vocab_size": 6
} | https://github.com/matrix-org/synapse.git |
|
1 | report_failure | def report_failure(self, out, test, example, got):
out(self._failure_header(test, example) +
self._checker.output_difference(example, got, self.optionflags))
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 11 | doctest.py | 59 | add python 3.10.4 for windows | 56,908 | 0 | 37 | 40 | 12 | 223,450 | 12 | XX-Net | 10 | python3.10.4/Lib/doctest.py | Python | 3 | {
"docstring": "\n Report that the given example failed.\n ",
"language": "en",
"n_whitespaces": 21,
"n_words": 6,
"vocab_size": 6
} | https://github.com/XX-net/XX-Net.git |
|
5 | tmpfile | def tmpfile(extension="", dir=None):
extension = extension.lstrip(".")
if extension:
extension = "." + extension
handle, filename = tempfile.mkstemp(extension, dir=dir)
os.close(handle)
os.remove(filename)
try:
yield filename
finally:
if os.path.exists(filename):
with suppress(OSError): # sometimes we can't remove a generated temp file
if os.path.isdir(filename):
shutil.rmtree(filename)
else:
os.remove(filename)
@contextmanager | bf66221722cce8f09a9b09895bdb4596f14a5430 | @contextmanager | 17 | utils.py | 179 | `tmpfile` does not end files with period on empty extension (#9429) | 36,805 | 1 | 167 | 100 | 35 | 156,915 | 43 | dask | 19 | dask/utils.py | Python | 16 | {
"docstring": "\n Function to create and return a unique temporary file with the given extension, if provided.\n\n Parameters\n ----------\n extension : str\n The extension of the temporary file to be created\n dir : str\n If ``dir`` is not None, the file will be created in that directory; otherwise,\n Python's default temporary directory is used.\n\n Returns\n -------\n out : str\n Path to the temporary file\n\n See Also\n --------\n NamedTemporaryFile : Built-in alternative for creating temporary files\n tmp_path : pytest fixture for creating a temporary directory unique to the test invocation\n\n Notes\n -----\n This context manager is particularly useful on Windows for opening temporary files multiple times.\n ",
"language": "en",
"n_whitespaces": 180,
"n_words": 103,
"vocab_size": 69
} | https://github.com/dask/dask.git |
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