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|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
291,567 | 40 | 10 | 11 | 173 | 9 | 0 | 56 | 181 | test_valid_country | Add valid country tests to workday sensors (#82799)
fixes undefined | https://github.com/home-assistant/core.git | def test_valid_country(self):
# Invalid UTF-8, must not contain U+D800 to U+DFFF
with pytest.raises(vol.Invalid):
binary_sensor.valid_country("\ud800")
with pytest.raises(vol.Invalid):
binary_sensor.valid_country("\udfff")
# Country MUST NOT be empty
with pytest.raises(vol.Invalid):
binary_sensor.valid_country("")
# Country must be supported by holidays
with pytest.raises(vol.Invalid):
binary_sensor.valid_country("HomeAssistantLand")
# Valid country code validation must not raise an exception
for country in ("IM", "LI", "US"):
assert binary_sensor.valid_country(country) == country
| 90 | test_binary_sensor.py | Python | tests/components/workday/test_binary_sensor.py | eb25968b31dcf76d6790cee99ff30ead3d27b8af | core | 2 |
|
216,560 | 12 | 9 | 3 | 50 | 6 | 1 | 15 | 20 | _pyeapi_conn | Deprecated netmiko_conn and pyeapi_conn in napalm_mod.py as these function should not be called from the CLI | https://github.com/saltstack/salt.git | def _pyeapi_conn(**kwargs):
pyeapi_kwargs = pyeapi_nxos_api_args(**kwargs)
return __salt__["pyeapi.get_connection"](**pyeapi_kwargs)
# ----------------------------------------------------------------------------------------------------------------------
# callable functions
# ----------------------------------------------------------------------------------------------------------------------
@proxy_napalm_wrap | @proxy_napalm_wrap | 23 | napalm_mod.py | Python | salt/modules/napalm_mod.py | d8305bfaa7b98d898f5963b01ca75f277c266322 | salt | 1 |
80,135 | 45 | 13 | 39 | 638 | 18 | 0 | 61 | 402 | test_blocks_and_data_not_operated_on_intact | Add tests for streamfield migration helpers
Currently failing due to wagtail-factories being broken on Wagtail 4.1: https://github.com/wagtail/wagtail-factories/issues/65 | https://github.com/wagtail/wagtail.git | def test_blocks_and_data_not_operated_on_intact(self):
altered_raw_data = apply_changes_to_raw_data(
raw_data=self.raw_data,
block_path_str="nestedstruct.stream1",
operation=RenameStreamChildrenOperation(
old_name="char1", new_name="renamed1"
),
streamfield=models.SampleModel.content,
)
self.assertEqual(altered_raw_data[0], self.raw_data[0])
self.assertEqual(altered_raw_data[3], self.raw_data[3])
self.assertEqual(altered_raw_data[1]["id"], self.raw_data[1]["id"])
self.assertEqual(altered_raw_data[2]["id"], self.raw_data[2]["id"])
self.assertEqual(altered_raw_data[1]["type"], self.raw_data[1]["type"])
self.assertEqual(altered_raw_data[2]["type"], self.raw_data[2]["type"])
for key in self.raw_data[1]["value"].keys():
self.assertIn(key, altered_raw_data[1]["value"])
for key in self.raw_data[1]["value"].keys():
self.assertIn(key, altered_raw_data[2]["value"])
self.assertEqual(
altered_raw_data[1]["value"]["char1"], self.raw_data[1]["value"]["char1"]
)
self.assertEqual(
altered_raw_data[2]["value"]["char1"], self.raw_data[2]["value"]["char1"]
)
self.assertEqual(
altered_raw_data[1]["value"]["struct1"],
self.raw_data[1]["value"]["struct1"],
)
self.assertEqual(
altered_raw_data[2]["value"]["struct1"],
self.raw_data[2]["value"]["struct1"],
)
self.assertEqual(
altered_raw_data[1]["value"]["list1"], self.raw_data[1]["value"]["list1"]
)
self.assertEqual(
altered_raw_data[2]["value"]["list1"], self.raw_data[2]["value"]["list1"]
)
| 394 | test_nested_structures.py | Python | wagtail/tests/streamfield_migrations/test_nested_structures.py | ad65741b94f36fbe793cf15f0ab002482070cdb6 | wagtail | 3 |
|
246,920 | 18 | 6 | 27 | 15 | 2 | 0 | 19 | 40 | test_third_party_rules | Replace assertEquals and friends with non-deprecated versions. (#12092) | https://github.com/matrix-org/synapse.git | def test_third_party_rules(self):
# patch the rules module with a Mock which will return False for some event
# types | 194 | test_third_party_rules.py | Python | tests/rest/client/test_third_party_rules.py | 02d708568b476f2f7716000b35c0adfa4cbd31b3 | synapse | 2 |
|
275,783 | 40 | 9 | 20 | 203 | 21 | 0 | 44 | 232 | get_config | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | https://github.com/keras-team/keras.git | def get_config(self):
json_word_counts = json.dumps(self.word_counts)
json_word_docs = json.dumps(self.word_docs)
json_index_docs = json.dumps(self.index_docs)
json_word_index = json.dumps(self.word_index)
json_index_word = json.dumps(self.index_word)
return {
"num_words": self.num_words,
"filters": self.filters,
"lower": self.lower,
"split": self.split,
"char_level": self.char_level,
"oov_token": self.oov_token,
"document_count": self.document_count,
"word_counts": json_word_counts,
"word_docs": json_word_docs,
"index_docs": json_index_docs,
"index_word": json_index_word,
"word_index": json_word_index,
}
| 121 | text.py | Python | keras/preprocessing/text.py | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | 1 |
|
169,041 | 50 | 12 | 21 | 192 | 18 | 0 | 75 | 277 | _process_converter | TYP: Autotyping (#48191)
* annotate-magics
* annotate-imprecise-magics
* none-return
* scalar-return
* pyi files
* ignore vendored file
* manual changes
* ignore pyright in pickle_compat (these errors would be legit if the current __new__ methods were called but I think these pickle tests call older __new__ methods which allowed providing multiple positional arguments)
* run autotyping in pre-commit
* remove final and expand safe (and add annotate-imprecise-magics) | https://github.com/pandas-dev/pandas.git | def _process_converter(self, f, filt=None) -> None:
if filt is None:
filt = lambda col, c: True
obj = self.obj
assert obj is not None # for mypy
needs_new_obj = False
new_obj = {}
for i, (col, c) in enumerate(obj.items()):
if filt(col, c):
new_data, result = f(col, c)
if result:
c = new_data
needs_new_obj = True
new_obj[i] = c
if needs_new_obj:
# possibly handle dup columns
new_frame = DataFrame(new_obj, index=obj.index)
new_frame.columns = obj.columns
self.obj = new_frame
| 122 | _json.py | Python | pandas/io/json/_json.py | 54347fe684e0f7844bf407b1fb958a5269646825 | pandas | 6 |
|
257,510 | 7 | 6 | 109 | 13 | 1 | 0 | 7 | 13 | tutorial14_query_classifier | Tutorial 14 edit (#2663)
* Rewrite Tutorial 14 for increased user-friendliness
* Update Tutorial14 .py file to match .ipynb file
* Update Documentation & Code Style
* unblock the ci
* ignore error in jitterbit/get-changed-files
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Sara Zan <[email protected]> | https://github.com/deepset-ai/haystack.git | def tutorial14_query_classifier():
# Useful for framing headers | 728 | Tutorial14_Query_Classifier.py | Python | tutorials/Tutorial14_Query_Classifier.py | b87c0c950b2243f47fb249aa3865d4c46edb16df | haystack | 5 |
|
273,362 | 11 | 10 | 6 | 68 | 9 | 0 | 15 | 41 | listify_tensors | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | https://github.com/keras-team/keras.git | def listify_tensors(x):
if tf.is_tensor(x):
x = x.numpy()
if isinstance(x, np.ndarray):
x = x.tolist()
return x
| 40 | preprocessing_utils.py | Python | keras/layers/preprocessing/preprocessing_utils.py | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | 3 |
|
42,118 | 27 | 10 | 4 | 219 | 21 | 0 | 27 | 90 | tick_params | Adding Grid.tick_params() method. (#2944)
* Adding Grid.tick_params() method.
* Address PR comments.
* Add What's New entry.
* Switch tick_params() test to use pad. | https://github.com/mwaskom/seaborn.git | def tick_params(self, axis='both', **kwargs):
for ax in self.figure.axes:
ax.tick_params(axis=axis, **kwargs)
return self
_facet_docs = dict(
data=dedent(),
rowcol=dedent(),
rowcol_order=dedent(),
col_wrap=dedent(),
share_xy=dedent(),
height=dedent(),
aspect=dedent(),
palette=dedent(),
legend_out=dedent(),
margin_titles=dedent(),
facet_kws=dedent(),
)
| 35 | axisgrid.py | Python | seaborn/axisgrid.py | 72d1322ee583eb481346e5e661c2998c8a7445dd | seaborn | 2 |
|
178,331 | 23 | 13 | 13 | 89 | 10 | 0 | 29 | 140 | isDebianPackagePython | Plugins: Avoid warning from pkg_resources for deprecated versions
* We don't care about these, and this warning makes it look like
we are doing something wrong. | https://github.com/Nuitka/Nuitka.git | def isDebianPackagePython():
if not isLinux():
return False
if python_version < 0x300:
return hasattr(sys, "_multiarch")
else:
with withNoDeprecationWarning():
try:
from distutils.dir_util import _multiarch
except ImportError:
return False
else:
return True
| 49 | PythonFlavors.py | Python | nuitka/PythonFlavors.py | 51e4ae8239bd7824ec3c117780be82e1193b2f7a | Nuitka | 4 |
|
314,865 | 38 | 10 | 15 | 225 | 23 | 0 | 67 | 118 | test_pushed_variable_status_change | Add tests for LCN sensor and binary_sensor platforms (#67263) | https://github.com/home-assistant/core.git | async def test_pushed_variable_status_change(hass, entry, lcn_connection):
device_connection = get_device_connection(hass, (0, 7, False), entry)
address = LcnAddr(0, 7, False)
# push status variable
inp = ModStatusVar(address, Var.VAR1, VarValue.from_celsius(42))
await device_connection.async_process_input(inp)
await hass.async_block_till_done()
state = hass.states.get(SENSOR_VAR1)
assert state is not None
assert float(state.state) == 42.0
# push status setpoint
inp = ModStatusVar(address, Var.R1VARSETPOINT, VarValue.from_celsius(42))
await device_connection.async_process_input(inp)
await hass.async_block_till_done()
state = hass.states.get(SENSOR_SETPOINT1)
assert state is not None
assert float(state.state) == 42.0
| 148 | test_sensor.py | Python | tests/components/lcn/test_sensor.py | b7b8feda0ffb7487954545c96c50e7f64e2195bc | core | 1 |
|
243,060 | 13 | 9 | 3 | 59 | 7 | 0 | 13 | 34 | textsize | add textbbox and textlength to ImageDraw2 and update tests | https://github.com/python-pillow/Pillow.git | def textsize(self, text, font):
deprecate("textsize", 10, "textbbox or textlength")
return self.draw.textsize(text, font=font.font, __internal__=True)
| 37 | ImageDraw2.py | Python | src/PIL/ImageDraw2.py | 1bf87556ef9953eeea5751714d87bdcc98b49702 | Pillow | 1 |
|
100,727 | 24 | 13 | 15 | 105 | 13 | 0 | 28 | 102 | _check_valid_data | Bugfixes:
- Stats graph - Handle NaNs in data
- logger - de-elevate matplotlib font messages | https://github.com/deepfakes/faceswap.git | def _check_valid_data(self) -> bool:
logger.debug("Validating data. %s",
{key: len(val) for key, val in self._display_data.stats.items()})
if any(len(val) == 0 # pylint:disable=len-as-condition
for val in self._display_data.stats.values()):
return False
return True
| 64 | popup_session.py | Python | lib/gui/popup_session.py | afec52309326304f4323029039e49bfcf928ef43 | faceswap | 4 |
|
268,720 | 37 | 10 | 5 | 71 | 7 | 0 | 47 | 112 | cgroupns_option_supported | ansible-test - Improve container management. (#78550)
See changelogs/fragments/ansible-test-container-management.yml for details. | https://github.com/ansible/ansible.git | def cgroupns_option_supported(self) -> bool:
if self.engine == 'docker':
# Docker added support for the `--cgroupns` option in version 20.10.
# Both the client and server must support the option to use it.
# See: https://docs.docker.com/engine/release-notes/#20100
return self.client_major_minor_version >= (20, 10) and self.server_major_minor_version >= (20, 10)
raise NotImplementedError(self.engine)
| 42 | docker_util.py | Python | test/lib/ansible_test/_internal/docker_util.py | cda16cc5e9aa8703fb4e1ac0a0be6b631d9076cc | ansible | 3 |
|
216,118 | 60 | 14 | 28 | 379 | 20 | 0 | 78 | 280 | test_remove_not_installed | Fix exception in yumpkg.remove for not installed package | https://github.com/saltstack/salt.git | def test_remove_not_installed():
name = "foo"
list_pkgs_mock = MagicMock(return_value={})
cmd_mock = MagicMock(
return_value={"pid": 12345, "retcode": 0, "stdout": "", "stderr": ""}
)
salt_mock = {
"cmd.run_all": cmd_mock,
"lowpkg.version_cmp": rpm.version_cmp,
"pkg_resource.parse_targets": MagicMock(
return_value=({name: None}, "repository")
),
}
with patch.object(yumpkg, "list_pkgs", list_pkgs_mock), patch(
"salt.utils.systemd.has_scope", MagicMock(return_value=False)
), patch.dict(yumpkg.__salt__, salt_mock):
# Test yum
with patch.dict(yumpkg.__context__, {"yum_bin": "yum"}), patch.dict(
yumpkg.__grains__, {"os": "CentOS", "osrelease": 7}
):
yumpkg.remove(name)
cmd_mock.assert_not_called()
# Test dnf
yumpkg.__context__.pop("yum_bin")
cmd_mock.reset_mock()
with patch.dict(yumpkg.__context__, {"yum_bin": "dnf"}), patch.dict(
yumpkg.__grains__, {"os": "Fedora", "osrelease": 27}
):
yumpkg.remove(name)
cmd_mock.assert_not_called()
| 212 | test_yumpkg.py | Python | tests/pytests/unit/modules/test_yumpkg.py | 8ea5342cbde034383938e244cdb16a0bf8a777e8 | salt | 1 |
|
177,017 | 18 | 8 | 8 | 100 | 7 | 0 | 21 | 77 | test_naive_lowest_common_ancestor2 | Naive lowest common ancestor implementation (#5736)
* Add naive lca methods
* Naive algorithm implementation for LCA
* Modify naive lca functions
* Correct parameters of nx.ancestors
* Update lowest_common_ancestors.py
* Parametrize tests
* Apply suggestions from code review
Co-authored-by: Dan Schult <[email protected]>
* Yield instead of append
* Tests for naive lca
* Correct test cases for naive lca algorithms
* Apply suggestions from code review
Co-authored-by: Mridul Seth <[email protected]>
* Fix function name -when calling
* Make requested changes
* Inlining _get_a_lowest_common_ancestor
Co-authored-by: dtuncturk <[email protected]>
Co-authored-by: Dan Schult <[email protected]>
Co-authored-by: Mridul Seth <[email protected]> | https://github.com/networkx/networkx.git | def test_naive_lowest_common_ancestor2(self):
G = nx.DiGraph()
G.add_edge(0, 1)
G.add_edge(2, 0)
G.add_edge(2, 3)
G.add_edge(4, 0)
G.add_edge(5, 2)
assert naive_lca(G, 1, 3) == 2
| 64 | test_lowest_common_ancestors.py | Python | networkx/algorithms/tests/test_lowest_common_ancestors.py | b2f91c34a23058dd70b41784af0d87890216026a | networkx | 1 |
|
141,325 | 17 | 9 | 3 | 73 | 8 | 0 | 18 | 39 | all | [Data/AIR] Move `TensorExtension` to `ray.air` for use in other packages (#25517)
Moves Tensor extensions to ray.air to facilitate their use in other Ray libraries (AIR, Serve). | https://github.com/ray-project/ray.git | def all(self, axis=None, out=None, keepdims=False):
result = self._tensor.all(axis=axis, out=out, keepdims=keepdims)
return result if axis is None else TensorArray(result)
| 49 | pandas.py | Python | python/ray/air/util/tensor_extensions/pandas.py | e0a63f770f9afd6eda2d4da9bf508067429585ae | ray | 2 |
|
46,701 | 23 | 13 | 9 | 103 | 9 | 0 | 27 | 118 | redirect_or_json | Add details drawer to Grid View (#22123)
* make UI and tree work with mapped tasks
basic slide drawer
reformat grid background colors
improve rendering and add selected dag run
fix hover and extra prop
switch from drawer to details section
add tooltip info to details
use API
make side panel collapsible, useTasks,
dag run actions
dag run actions w/ react-query
task instance links
task actions
remove modals
adjust panel width and use status color
minor details styling
add duration to tooltips
add last scheduling decision and fix tests
* move ref and selection to providers
* fix test with mock providers
* update TI and DR buttons
* download logs and external logs
* add extra links to TI details
* download log bug fixes
* fix extra links, hide local TZ if UTC,
* confirm mark task failed/success
* Update confirm modals for runs and tasks
- async/await on mutations instead of useeffect
- add confirmation for run actions
* Fix dialog scrolling
* Code cleanup and fix task clear
* Fix task/run label, dialog focus, dag details overflow, panel open/close
* Add timezone provider
* Fix TimezoneEvent import
* Improve button UX
- Remove details panel title
- Add button to reset root
- Make "More Details" buttons more specific
- Specify timezone as DAG timezone
* autorefresh dag run details
* auto-refresh task instance details
* revert useTreeData changes
None of these changes were relevant to this PR. Better to be done separately.
* Address PR feedback
- useState vs useDisclosure
- Remove extraneous elements
- Copy changes
- Wire up params for runTask
- Breadcrumb padding
* Handle task/run action sideeffects by separating autorefresh and treeData hooks
* Clean up views.py endpoints
- Pass 'Accept' headers for json returns
- Consolidate more endpoints to return json or redirect
* pass request as arg
* remove request as arg
* Anticipate when the 'Accept' header is not present
* Fix argument count errors
* Replace hard coded urls
* Replace hard coded urls in react components
* Update filter upstream link
* Split TaskInstance details component
* Fix undefined variables in tests
* init_api_connexion in tests
- add readme
- rename context providers to avoid confusion with Airflow Providers
* Fix url params, hide last item breadcrumb links
* Update task run failed copy
* Fix taskinstance/list buttons
Co-authored-by: Tzu-ping Chung <[email protected]> | https://github.com/apache/airflow.git | def redirect_or_json(origin, msg, status=""):
if request.headers.get('Accept') == 'application/json':
return {'status': status, 'message': msg}
else:
if status:
flash(msg, status)
else:
flash(msg)
return redirect(origin)
######################################################################################
# Error handlers
######################################################################################
| 56 | views.py | Python | airflow/www/views.py | 2bb26a38070a4b949bfb210ef1d5644e016e373a | airflow | 3 |
|
164,472 | 24 | 12 | 15 | 141 | 13 | 0 | 31 | 78 | test_assert_extension_array_equal_less_precise | ⬆️ UPGRADE: Autoupdate pre-commit config (#45752)
Co-authored-by: MarcoGorelli <[email protected]> | https://github.com/pandas-dev/pandas.git | def test_assert_extension_array_equal_less_precise(decimals):
rtol = 0.5 * 10**-decimals
arr1 = SparseArray([0.5, 0.123456])
arr2 = SparseArray([0.5, 0.123457])
if decimals >= 5:
msg =
with pytest.raises(AssertionError, match=msg):
tm.assert_extension_array_equal(arr1, arr2, rtol=rtol)
else:
tm.assert_extension_array_equal(arr1, arr2, rtol=rtol)
| 89 | test_assert_extension_array_equal.py | Python | pandas/tests/util/test_assert_extension_array_equal.py | 419331c598a097896edae40bc0687e4127f97b6b | pandas | 2 |
|
34,808 | 47 | 11 | 7 | 150 | 21 | 0 | 57 | 113 | register_for_auto_class | Save code of registered custom models (#15379)
* Allow dynamic modules to use relative imports
* Work for configs
* Fix last merge conflict
* Save code of registered custom objects
* Map strings to strings
* Fix test
* Add tokenizer
* Rework tests
* Tests
* Ignore fixtures py files for tests
* Tokenizer test + fix collection
* With full path
* Rework integration
* Fix typo
* Remove changes in conftest
* Test for tokenizers
* Add documentation
* Update docs/source/custom_models.mdx
Co-authored-by: Lysandre Debut <[email protected]>
* Add file structure and file content
* Add more doc
* Style
* Update docs/source/custom_models.mdx
Co-authored-by: Suraj Patil <[email protected]>
* Address review comments
Co-authored-by: Lysandre Debut <[email protected]>
Co-authored-by: Suraj Patil <[email protected]> | https://github.com/huggingface/transformers.git | def register_for_auto_class(cls, auto_class="FlaxAutoModel"):
if not isinstance(auto_class, str):
auto_class = auto_class.__name__
import transformers.models.auto as auto_module
if not hasattr(auto_module, auto_class):
raise ValueError(f"{auto_class} is not a valid auto class.")
cls._auto_class = auto_class
# To update the docstring, we need to copy the method, otherwise we change the original docstring.
FlaxPreTrainedModel.push_to_hub = copy_func(FlaxPreTrainedModel.push_to_hub)
FlaxPreTrainedModel.push_to_hub.__doc__ = FlaxPreTrainedModel.push_to_hub.__doc__.format(
object="model", object_class="FlaxAutoModel", object_files="model checkpoint"
)
| 52 | modeling_flax_utils.py | Python | src/transformers/modeling_flax_utils.py | 44b21f117bcf71e3d88a11c3523c94b27949fdbf | transformers | 3 |
|
125,444 | 26 | 13 | 7 | 102 | 12 | 1 | 30 | 74 | process_dict_for_yaml_dump | [Serve] Fix Formatting of Error Messages printed in `serve status` (#26578) | https://github.com/ray-project/ray.git | def process_dict_for_yaml_dump(data):
for k, v in data.items():
if isinstance(v, dict):
data[k] = process_dict_for_yaml_dump(v)
elif isinstance(v, str):
data[k] = remove_ansi_escape_sequences(v)
return data
@click.group(help="CLI for managing Serve instances on a Ray cluster.") | @click.group(help="CLI for managing Serve instances on a Ray cluster.") | 53 | scripts.py | Python | python/ray/serve/scripts.py | b856daebbdc923a216ce412be477c61e6cc5707e | ray | 4 |
247,436 | 77 | 12 | 48 | 391 | 20 | 0 | 138 | 577 | test_redact_relation_thread | Invalidate caches when an event with a relation is redacted. (#12121)
The caches for the target of the relation must be cleared
so that the bundled aggregations are re-calculated after
the redaction is processed. | https://github.com/matrix-org/synapse.git | def test_redact_relation_thread(self) -> None:
channel = self._send_relation(
RelationTypes.THREAD,
EventTypes.Message,
content={"body": "reply 1", "msgtype": "m.text"},
)
self.assertEqual(200, channel.code, channel.json_body)
unredacted_event_id = channel.json_body["event_id"]
# Note that the *last* event in the thread is redacted, as that gets
# included in the bundled aggregation.
channel = self._send_relation(
RelationTypes.THREAD,
EventTypes.Message,
content={"body": "reply 2", "msgtype": "m.text"},
)
self.assertEqual(200, channel.code, channel.json_body)
to_redact_event_id = channel.json_body["event_id"]
# Both relations exist.
event_ids, relations = self._make_relation_requests()
self.assertEquals(event_ids, [to_redact_event_id, unredacted_event_id])
self.assertDictContainsSubset(
{
"count": 2,
"current_user_participated": True,
},
relations[RelationTypes.THREAD],
)
# And the latest event returned is the event that will be redacted.
self.assertEqual(
relations[RelationTypes.THREAD]["latest_event"]["event_id"],
to_redact_event_id,
)
# Redact one of the reactions.
self._redact(to_redact_event_id)
# The unredacted relation should still exist.
event_ids, relations = self._make_relation_requests()
self.assertEquals(event_ids, [unredacted_event_id])
self.assertDictContainsSubset(
{
"count": 1,
"current_user_participated": True,
},
relations[RelationTypes.THREAD],
)
# And the latest event is now the unredacted event.
self.assertEqual(
relations[RelationTypes.THREAD]["latest_event"]["event_id"],
unredacted_event_id,
)
| 238 | test_relations.py | Python | tests/rest/client/test_relations.py | f63bedef07360216a8de71dc38f00f1aea503903 | synapse | 1 |
|
20,848 | 18 | 12 | 8 | 67 | 8 | 0 | 23 | 80 | _extra_width | 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 | https://github.com/pypa/pipenv.git | def _extra_width(self) -> int:
width = 0
if self.box and self.show_edge:
width += 2
if self.box:
width += len(self.columns) - 1
return width
| 40 | table.py | Python | pipenv/patched/notpip/_vendor/rich/table.py | f3166e673fe8d40277b804d35d77dcdb760fc3b3 | pipenv | 4 |
|
159,357 | 6 | 7 | 3 | 27 | 3 | 0 | 6 | 20 | required_packages | Add Logistic Regression to our NLU classifiers. (#10650)
* added-logistic-regression
* added
* d0h! gotta copy the imports correctly
* run black
* black issues fixed
* stash
* added tolerance hyperparam
* added random seed
* fixed testing path
* ran black
* use joblib directly
* insurance against sklearn changes
* added try except
* ran black
* make code more DRY
* flake8
* added type information
* add train -> persists -> load -> load
* add to test_train.py
* fixed style issues
* actually persist model
* persist, i insist
* fixed-bug
* added-documentation
* black
* added changelog
* added
* moar-whitespace
* removed stale param
* added comments | https://github.com/RasaHQ/rasa.git | def required_packages() -> List[Text]:
return ["sklearn"]
| 14 | logistic_regression_classifier.py | Python | rasa/nlu/classifiers/logistic_regression_classifier.py | dc762814317ce46873a5226ee09033031a7d3604 | rasa | 1 |
|
136,360 | 33 | 12 | 9 | 94 | 9 | 0 | 36 | 123 | delete_job | [Jobs] Add DELETE endpoint (#30056)
Adds a DELETE endpoint to the REST API, SDK and CLI for Ray Jobs.
Before this, there was no way to delete the job info from the cluster, so the memory could potentially grow without bound.
Deleting a job immediately deletes all its associated info (status, metadata) from memory. We only support deleting jobs that are in a terminal state.
We don't delete the log files of a deleted job. | https://github.com/ray-project/ray.git | async def delete_job(self, job_id):
job_status = await self._job_info_client.get_status(job_id)
if job_status is None or not job_status.is_terminal():
raise RuntimeError(
f"Attempted to delete job '{job_id}', "
f"but it is in a non-terminal state {job_status}."
)
await self._job_info_client.delete_info(job_id)
return True
| 50 | job_manager.py | Python | dashboard/modules/job/job_manager.py | 1639914ba5a37ed56a644fdb4c712f6da064746c | ray | 3 |
|
290,402 | 17 | 11 | 9 | 91 | 11 | 0 | 20 | 92 | async_media_play_pause | Update mypy to 0.990 (#81783)
* Update mypy to 0.990
* Remove type ignore - overriding attr with property (13475)
* Remove type ignores - hasattr (13544)
* Adjust type ignore - assignment (13549)
* New error code - type-abstract (13785)
* Disable annotation-unchecked (13851) | https://github.com/home-assistant/core.git | async def async_media_play_pause(self) -> None:
if hasattr(self, "media_play_pause"):
await self.hass.async_add_executor_job(self.media_play_pause)
return
if self.state == MediaPlayerState.PLAYING:
await self.async_media_pause()
else:
await self.async_media_play()
| 51 | __init__.py | Python | homeassistant/components/media_player/__init__.py | 0c8eeaa6436b04ba6da46bccab8b11523f314d9b | core | 3 |
|
180,405 | 134 | 15 | 113 | 1,287 | 38 | 0 | 279 | 1,685 | test_component_functions | Wrap dataframe (#1571)
* add suport for table cell wrapping
* revert pkginfo change
* revert pkginfo change
* fixed tests
* formatting
* type hint
Co-authored-by: Abubakar Abid <[email protected]> | https://github.com/gradio-app/gradio.git | def test_component_functions(self):
x_data = [["Tim", 12, False], ["Jan", 24, True]]
dataframe_input = gr.Dataframe(headers=["Name", "Age", "Member"])
output = dataframe_input.preprocess(x_data)
self.assertEqual(output["Age"][1], 24)
self.assertEqual(output["Member"][0], False)
self.assertEqual(dataframe_input.preprocess_example(x_data), x_data)
self.assertEqual(dataframe_input.serialize(x_data, True), x_data)
with tempfile.TemporaryDirectory() as tmpdirname:
to_save = dataframe_input.save_flagged(
tmpdirname, "dataframe_input", x_data, None
)
self.assertEqual(json.dumps(x_data), to_save)
restored = dataframe_input.restore_flagged(tmpdirname, to_save, None)
self.assertEqual(x_data, restored)
self.assertIsInstance(dataframe_input.generate_sample(), list)
dataframe_input = gr.Dataframe(
headers=["Name", "Age", "Member"], label="Dataframe Input"
)
self.assertEqual(
dataframe_input.get_config(),
{
"headers": ["Name", "Age", "Member"],
"datatype": "str",
"row_count": (3, "dynamic"),
"col_count": (3, "dynamic"),
"value": [
["", "", ""],
["", "", ""],
["", "", ""],
],
"name": "dataframe",
"show_label": True,
"label": "Dataframe Input",
"max_rows": 20,
"max_cols": None,
"overflow_row_behaviour": "paginate",
"style": {},
"elem_id": None,
"visible": True,
"interactive": None,
"wrap": False,
},
)
dataframe_input = gr.Dataframe()
output = dataframe_input.preprocess(x_data)
self.assertEqual(output[1][1], 24)
with self.assertRaises(ValueError):
wrong_type = gr.Dataframe(type="unknown")
wrong_type.preprocess(x_data)
# Output functionalities
dataframe_output = gr.Dataframe()
output = dataframe_output.postprocess(np.zeros((2, 2)))
self.assertDictEqual(output, {"data": [[0, 0], [0, 0]]})
output = dataframe_output.postprocess([[1, 3, 5]])
self.assertDictEqual(output, {"data": [[1, 3, 5]]})
output = dataframe_output.postprocess(
pd.DataFrame([[2, True], [3, True], [4, False]], columns=["num", "prime"])
)
self.assertDictEqual(
output,
{
"headers": ["num", "prime"],
"data": [[2, True], [3, True], [4, False]],
},
)
self.assertEqual(
dataframe_output.get_config(),
{
"headers": None,
"max_rows": 20,
"max_cols": None,
"overflow_row_behaviour": "paginate",
"name": "dataframe",
"show_label": True,
"label": None,
"style": {},
"elem_id": None,
"visible": True,
"datatype": "str",
"row_count": (3, "dynamic"),
"col_count": (3, "dynamic"),
"value": [
["", "", ""],
["", "", ""],
["", "", ""],
],
"interactive": None,
"wrap": False,
},
)
with self.assertRaises(ValueError):
wrong_type = gr.Dataframe(type="unknown")
wrong_type.postprocess(0)
with tempfile.TemporaryDirectory() as tmpdirname:
to_save = dataframe_output.save_flagged(
tmpdirname, "dataframe_output", output, None
)
self.assertEqual(
to_save,
json.dumps(
{
"headers": ["num", "prime"],
"data": [[2, True], [3, True], [4, False]],
}
),
)
self.assertEqual(
dataframe_output.restore_flagged(tmpdirname, to_save, None),
{
"headers": ["num", "prime"],
"data": [[2, True], [3, True], [4, False]],
},
)
| 780 | test_components.py | Python | test/test_components.py | 8710d3a079d38b857620ec6f1bb4d261ae242263 | gradio | 1 |
|
108,514 | 33 | 12 | 11 | 130 | 17 | 0 | 44 | 166 | _sci | Cleanup documentation generation for pyplot
- remove the awkward `pyplot.plotting()` function, which only served
as a namespace to take up the docs for pyplot and output them via
`.. autofunction`
- Instead generate the same information using `.. autosummary::`. We
have to list the desired methods here explicitly. I've added a test
that these are the same as previously auto-generated in the
`plotting()` docstring. If we change anything in pyplot, we'll be
notified through the test failure that we have to adapt the
autosummary list.
- Removed the docstring generation logic
`_setup_pyplot_info_docstrings()`. Apart from generating the
`plotting()` docstring, this added docstrings to the pyplot colormap
setters. Instead, we now add these docstrings directly via
boilerplate.py
Co-authored-by: Elliott Sales de Andrade <[email protected]> | https://github.com/matplotlib/matplotlib.git | def _sci(self, im):
_api.check_isinstance(
(mpl.contour.ContourSet, mcoll.Collection, mimage.AxesImage),
im=im)
if isinstance(im, mpl.contour.ContourSet):
if im.collections[0] not in self._children:
raise ValueError("ContourSet must be in current Axes")
elif im not in self._children:
raise ValueError("Argument must be an image, collection, or "
"ContourSet in this Axes")
self._current_image = im
| 81 | _base.py | Python | lib/matplotlib/axes/_base.py | 032316bc6c7798fca6c82de24167c975f237687f | matplotlib | 4 |
|
113,697 | 23 | 10 | 11 | 113 | 12 | 0 | 36 | 63 | hook_to_dtype_layout | fix(speedup): support for a special torchscript op 'aten::to.layout' with no corresponding torch.to (#5178) | https://github.com/microsoft/nni.git | def hook_to_dtype_layout(positional, keyword, undetermined, undetermined_special_treat):
assert 'layout' not in undetermined
assert 'pin_memory' not in undetermined
assert 'non_blocking' not in undetermined
to_layout = arg_trans_layout(keyword['layout'])
del keyword['layout']
del keyword['pin_memory']
del keyword['non_blocking']
real_to = FuncAdapter(torch.Tensor.to, positional, keyword, undetermined, undetermined_special_treat)
| 73 | jit_translate.py | Python | nni/compression/pytorch/speedup/jit_translate.py | 9a289ec21a40d870c0b80b93651d72a6693f7386 | nni | 1 |
|
265,901 | 30 | 16 | 19 | 180 | 28 | 0 | 34 | 299 | test_cache_multiple_objects | Closes #10560: New global search (#10676)
* Initial work on new search backend
* Clean up search backends
* Return only the most relevant result per object
* Clear any pre-existing cached entries on cache()
* #6003: Implement global search functionality for custom field values
* Tweak field weights & document guidance
* Extend search() to accept a lookup type
* Move get_registry() out of SearchBackend
* Enforce object permissions when returning search results
* Add indexers for remaining models
* Avoid calling remove() on non-cacheable objects
* Use new search backend by default
* Extend search backend to filter by object type
* Clean up search view form
* Enable specifying lookup logic
* Add indexes for value field
* Remove object type selector from search bar
* Introduce SearchTable and enable HTMX for results
* Enable pagination
* Remove legacy search backend
* Cleanup
* Use a UUID for CachedValue primary key
* Refactoring search methods
* Define max search results limit
* Extend reindex command to support specifying particular models
* Add clear() and size to SearchBackend
* Optimize bulk caching performance
* Highlight matched portion of field value
* Performance improvements for reindexing
* Started on search tests
* Cleanup & docs
* Documentation updates
* Clean up SearchIndex
* Flatten search registry to register by app_label.model_name
* Clean up search backend classes
* Clean up RestrictedGenericForeignKey and RestrictedPrefetch
* Resolve migrations conflict | https://github.com/netbox-community/netbox.git | def test_cache_multiple_objects(self):
sites = Site.objects.all()
search_backend.cache(sites)
content_type = ContentType.objects.get_for_model(Site)
self.assertEqual(
CachedValue.objects.filter(object_type=content_type).count(),
len(SiteIndex.fields) * sites.count()
)
for site in sites:
for field_name, weight in SiteIndex.fields:
self.assertTrue(
CachedValue.objects.filter(
object_type=content_type,
object_id=site.pk,
field=field_name,
value=getattr(site, field_name),
weight=weight
),
)
| 116 | test_search.py | Python | netbox/netbox/tests/test_search.py | 9628dead07ccef9608b32906aa8194bc948e5a09 | netbox | 3 |
|
270,669 | 12 | 9 | 5 | 54 | 8 | 0 | 14 | 53 | _get_trainable_state | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | https://github.com/keras-team/keras.git | def _get_trainable_state(self):
trainable_state = weakref.WeakKeyDictionary()
for layer in self._flatten_layers():
trainable_state[layer] = layer.trainable
return trainable_state
| 32 | base_layer.py | Python | keras/engine/base_layer.py | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | 2 |
|
215,761 | 27 | 12 | 10 | 182 | 9 | 0 | 39 | 85 | _acl_changes | [merge jam] Master port 49261 - consul modules (#58101)
* add consul states and acl function present/absent
* add consul to states doc index
* refact/fix consul states
* fix doc, fix states
* fix name parameter for acl_changes
* fixing pylint errors
* small changes after review by @rallytime
* fix header count
* Update consul.py
* fix acl_exists description, fix when both id and name are missing
* Adding some tests for consul module and consul state module. Some additional fixes in the consul module.
* Fixing tests.
* Fixing failing tests on Windows.
* Adding changelog.
* Adding some tests for consul module and consul state module. Some additional fixes in the consul module.
* moving tests to pytest.
* manual black changes.
* One more manual black change.
* fixing formatting. Adding versionadded for state module.
Co-authored-by: Rémi Jouannet <[email protected]>
Co-authored-by: Mike Place <[email protected]>
Co-authored-by: Daniel Wozniak <[email protected]>
Co-authored-by: Wayne Werner <[email protected]> | https://github.com/saltstack/salt.git | def _acl_changes(name, id=None, type=None, rules=None, consul_url=None, token=None):
info = __salt__["consul.acl_info"](id=id, token=token, consul_url=consul_url)
if info["res"] and info["data"][0]["Name"] != name:
return True
elif info["res"] and info["data"][0]["Rules"] != rules:
return True
elif info["res"] and info["data"][0]["Type"] != type:
return True
else:
return False
| 112 | consul.py | Python | salt/states/consul.py | fb825aa760fa0585a2c8fdafc6e62be8aec8cecf | salt | 7 |
|
181,898 | 32 | 17 | 10 | 128 | 12 | 0 | 41 | 97 | generate_export_pipeline_code | Revert "Deployed 7ccda9a with MkDocs version: 1.3.0"
This reverts commit bd9629c40e01241766197119b581a99409b07068. | https://github.com/EpistasisLab/tpot.git | def generate_export_pipeline_code(pipeline_tree, operators):
steps = _process_operator(pipeline_tree, operators)
# number of steps in a pipeline
num_step = len(steps)
if num_step > 1:
pipeline_text = "make_pipeline(\n{STEPS}\n)".format(
STEPS=_indent(",\n".join(steps), 4)
)
# only one operator (root = True)
else:
pipeline_text = "{STEPS}".format(STEPS=_indent(",\n".join(steps), 0))
return pipeline_text
| 71 | export_utils.py | Python | tpot/export_utils.py | 388616b6247ca4ea8de4e2f340d6206aee523541 | tpot | 2 |
|
158,190 | 43 | 13 | 15 | 274 | 26 | 0 | 62 | 142 | load_data_imdb | [PaddlePaddle] Merge master into Paddle branch (#1186)
* change 15.2 title in chinese version (#1109)
change title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘
* 修改部分语义表述 (#1105)
* Update r0.17.5 (#1120)
* Bump versions in installation
* 94行typo: （“bert.mall”）->（“bert.small”） (#1129)
* line 313: "bert.mall" -> "bert.small" (#1130)
* fix: update language as native reader (#1114)
* Fix the translation of "stride" (#1115)
* Update index.md (#1118)
修改部分语义表述
* Update self-attention-and-positional-encoding.md (#1133)
依照本书的翻译习惯，将pooling翻译成汇聚
* maybe a comment false (#1149)
* maybe a little false
* maybe a little false
* A minor bug in the rcnn section (Chinese edition) (#1148)
* Update bert.md (#1137)
一个笔误
# 假设batch_size=2，num_pred_positions=3
# 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1]
* Update calculus.md (#1135)
* fix typo in git documentation (#1106)
* fix: Update the Chinese translation in lr-scheduler.md (#1136)
* Update lr-scheduler.md
* Update chapter_optimization/lr-scheduler.md
Co-authored-by: goldmermaid <[email protected]>
Co-authored-by: goldmermaid <[email protected]>
* fix translation for kaggle-house-price.md (#1107)
* fix translation for kaggle-house-price.md
* fix translation for kaggle-house-price.md
Signed-off-by: sunhaizhou <[email protected]>
* Update weight-decay.md (#1150)
* Update weight-decay.md
关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解
关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。
并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释
解释为何会增加复杂性以及为何需要细粒度工具。
* Update chapter_multilayer-perceptrons/weight-decay.md
yep
Co-authored-by: goldmermaid <[email protected]>
* Update chapter_multilayer-perceptrons/weight-decay.md
yep
Co-authored-by: goldmermaid <[email protected]>
Co-authored-by: goldmermaid <[email protected]>
* Fix a spelling error (#1161)
* Update gru.md (#1152)
The key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state.
翻译错误
* Unify the function naming (#1113)
Unify naming of the function 'init_xavier()'.
* Update mlp-concise.md (#1166)
* Update mlp-concise.md
语句不通顺
* Update environment.md
语序异常
* Update config.ini
* fix the imprecise description (#1168)
Co-authored-by: yuande <yuande>
* fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175)
* Fix some typos. (#1163)
* Update batch-norm.md (#1170)
fixing typos u->x in article
* Update linear-regression.md (#1090)
We invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that
原译文把who也直接翻译出来了。
* Update mlp.md (#1117)
* Update mlp.md
修改部分语义表述
* Update chapter_multilayer-perceptrons/mlp.md
Co-authored-by: goldmermaid <[email protected]>
* Update chapter_multilayer-perceptrons/mlp.md
Co-authored-by: Aston Zhang <[email protected]>
Co-authored-by: goldmermaid <[email protected]>
* Correct a translation error. (#1091)
* Correct a translation error.
* Update chapter_computer-vision/image-augmentation.md
Co-authored-by: Aston Zhang <[email protected]>
* Update aws.md (#1121)
* Update aws.md
* Update chapter_appendix-tools-for-deep-learning/aws.md
Co-authored-by: Aston Zhang <[email protected]>
* Update image-augmentation.md (#1093)
* Update anchor.md (#1088)
fix a minor issue in code
* Update anchor.md
* Update image-augmentation.md
* fix typo and improve translation in chapter_linear-networks\softmax-regression.md (#1087)
* Avoid `torch.meshgrid` user warning (#1174)
Avoids the following user warning:
```python
~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2228.)
return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]
```
* bump to 2.0.0-beta1
* Update sequence.md
* bump beta1 on readme
* Add latex code block background to config
* BLD: Bump python support version 3.9 (#1183)
* BLD: Bump python support version 3.9
* Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4
* BLD: Bump torch and tensorflow
* Update Jenkinsfile
* Update chapter_installation/index.md
* Update chapter_installation/index.md
Co-authored-by: Aston Zhang <[email protected]>
* Update config.ini
* Update INFO.md
* Update INFO.md
* Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187)
* resolve the conflicts
* revise from publisher (#1089)
* revise from publisher
* d2l api
* post_latex
* revise from publisher
* revise ch11
* Delete d2l-Copy1.bib
* clear cache
* rm d2lbook clear
* debug anchor
* keep original d2l doc
Co-authored-by: Ubuntu <[email protected]>
Co-authored-by: Aston Zhang <[email protected]>
Co-authored-by: Aston Zhang <[email protected]>
* 重复语句 (#1188)
Co-authored-by: Aston Zhang <[email protected]>
* Improve expression for chapter_preliminaries/pandas.md (#1184)
* Update pandas.md
* Improve expression
* Improve expression
* Update chapter_preliminaries/pandas.md
Co-authored-by: Aston Zhang <[email protected]>
* Improce expression for chapter_preliminaries/linear-algebra.md (#1185)
* Improce expression
* Improve code comments
* Update chapter_preliminaries/linear-algebra.md
* Update chapter_preliminaries/linear-algebra.md
* Update chapter_preliminaries/linear-algebra.md
* Update chapter_preliminaries/linear-algebra.md
Co-authored-by: Aston Zhang <[email protected]>
* Fix multibox_detection bugs
* Update d2l to 0.17.5 version
* restore older version
* Upgrade pandas
* change to python3.8
* Test warning log
* relocate warning log
* test logs filtering
* Update gru.md
* Add DeprecationWarning filter
* Test warning log
* Update attention mechanisms & computational performance
* Update multilayer perceptron& linear & convolution networks & computer vision
* Update recurrent&optimition&nlp pretraining & nlp applications
* ignore warnings
* Update index.md
* Update linear networks
* Update multilayer perceptrons&deep learning computation
* Update preliminaries
* Check and Add warning filter
* Update kaggle-cifar10.md
* Update object-detection-dataset.md
* Update ssd.md fcn.md
* Update hybridize.md
* Update hybridize.md
Signed-off-by: sunhaizhou <[email protected]>
Co-authored-by: zhou201505013 <[email protected]>
Co-authored-by: Xinwei Liu <[email protected]>
Co-authored-by: Anirudh Dagar <[email protected]>
Co-authored-by: Aston Zhang <[email protected]>
Co-authored-by: hugo_han <[email protected]>
Co-authored-by: gyro永不抽风 <[email protected]>
Co-authored-by: CanChengZheng <[email protected]>
Co-authored-by: linlin <[email protected]>
Co-authored-by: iuk <[email protected]>
Co-authored-by: yoos <[email protected]>
Co-authored-by: Mr. Justice Lawrence John Wargrave <[email protected]>
Co-authored-by: Chiyuan Fu <[email protected]>
Co-authored-by: Sunhuashan <[email protected]>
Co-authored-by: Haiker Sun <[email protected]>
Co-authored-by: Ming Liu <[email protected]>
Co-authored-by: goldmermaid <[email protected]>
Co-authored-by: silenceZheng66 <[email protected]>
Co-authored-by: Wenchao Yan <[email protected]>
Co-authored-by: Kiki2049 <[email protected]>
Co-authored-by: Krahets <[email protected]>
Co-authored-by: friedmainfunction <[email protected]>
Co-authored-by: Jameson <[email protected]>
Co-authored-by: P. Yao <[email protected]>
Co-authored-by: Yulv-git <[email protected]>
Co-authored-by: Liu,Xiao <[email protected]>
Co-authored-by: YIN, Gang <[email protected]>
Co-authored-by: Joe-HZ <[email protected]>
Co-authored-by: lybloveyou <[email protected]>
Co-authored-by: VigourJiang <[email protected]>
Co-authored-by: zxhd863943427 <[email protected]>
Co-authored-by: LYF <[email protected]>
Co-authored-by: Aston Zhang <[email protected]>
Co-authored-by: xiaotinghe <[email protected]>
Co-authored-by: Ubuntu <[email protected]>
Co-authored-by: Holly-Max <[email protected]>
Co-authored-by: HinGwenWoong <[email protected]>
Co-authored-by: Shuai Zhang <[email protected]> | https://github.com/d2l-ai/d2l-zh.git | def load_data_imdb(batch_size, num_steps=500):
data_dir = d2l.download_extract('aclImdb', 'aclImdb')
train_data = read_imdb(data_dir, True)
test_data = read_imdb(data_dir, False)
train_tokens = d2l.tokenize(train_data[0], token='word')
test_tokens = d2l.tokenize(test_data[0], token='word')
vocab = d2l.Vocab(train_tokens, min_freq=5)
train_features = np.array([d2l.truncate_pad(
vocab[line], num_steps, vocab['<pad>']) for line in train_tokens])
test_features = np.array([d2l.truncate_pad(
vocab[line], num_steps, vocab['<pad>']) for line in test_tokens])
train_iter = d2l.load_array((train_features, train_data[1]), batch_size)
test_iter = d2l.load_array((test_features, test_data[1]), batch_size,
is_train=False)
return train_iter, test_iter, vocab
| 180 | mxnet.py | Python | d2l/mxnet.py | b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2 | d2l-zh | 3 |
|
35,453 | 95 | 11 | 9 | 138 | 12 | 0 | 129 | 158 | get_tests_dir | [Test refactor 1/5] Per-folder tests reorganization (#15725)
* Per-folder tests reorganization
Co-authored-by: sgugger <[email protected]>
Co-authored-by: Stas Bekman <[email protected]> | https://github.com/huggingface/transformers.git | def get_tests_dir(append_path=None):
# this function caller's __file__
caller__file__ = inspect.stack()[1][1]
tests_dir = os.path.abspath(os.path.dirname(caller__file__))
while not tests_dir.endswith("tests"):
tests_dir = os.path.dirname(tests_dir)
if append_path:
return os.path.join(tests_dir, append_path)
else:
return tests_dir
#
# Helper functions for dealing with testing text outputs
# The original code came from:
# https://github.com/fastai/fastai/blob/master/tests/utils/text.py
# When any function contains print() calls that get overwritten, like progress bars,
# a special care needs to be applied, since under pytest -s captured output (capsys
# or contextlib.redirect_stdout) contains any temporary printed strings, followed by
# \r's. This helper function ensures that the buffer will contain the same output
# with and without -s in pytest, by turning:
# foo bar\r tar mar\r final message
# into:
# final message
# it can handle a single string or a multiline buffer | 75 | testing_utils.py | Python | src/transformers/testing_utils.py | 29c10a41d04f855c433a6cde7797b325651417d2 | transformers | 3 |
|
89,803 | 14 | 9 | 7 | 61 | 12 | 0 | 17 | 45 | _should_operate | feat(hybrid-cloud): Create a base parser and middleware for webhooks (#42267)
See [HC-468](https://getsentry.atlassian.net/browse/HC-468)
Requires https://github.com/getsentry/sentry/pull/42260
This PR establishes the base parser that will be inherited from to
forward webhooks to the appropriate integration. It is a slightly
modified, portion of this [much larger
PR](https://github.com/getsentry/sentry/pull/39169). It was split off in
order to update that PR and make it more reviewable.
Some background:
The IntegrationControlMiddleware catches any incoming requests to the
control silo with the `/extensions/` path prefix. It parses the provider
out of the URL (e.g. `sentry.io/extensions/slack/something`), and passes
the request along to that parser to determine how we handle the request
(e.g. do we forward it to a region, multiple regions, handle it async,
respond immediately from control, etc.)
The BaseRequestParser provides a bunch of helpful methods to these
parsers to make the actual integration-specific parsers as minimal as
possible. They only need to implement a method for identifying the
integration (e.g. from headers, from a signature, from a payload, etc),
and how we respond to the webhook (allowing for different behaviour from
different webhooks). | https://github.com/getsentry/sentry.git | def _should_operate(self, request) -> bool:
is_correct_silo = SiloMode.get_current_mode() == SiloMode.CONTROL
is_external = request.path.startswith(self.webhook_prefix)
return is_correct_silo and is_external
| 37 | integration_control.py | Python | src/sentry/middleware/integrations/integration_control.py | d8609112d6e2f373692b414acff6d4a2f7466750 | sentry | 2 |
|
2,278 | 55 | 11 | 41 | 351 | 24 | 0 | 79 | 299 | set | replaced all methods of usermanager class,
working login
Co-Authored By: Ionesio | https://github.com/OpenMined/PySyft.git | def set(self, **kwargs) -> None: # nosec
attributes = {}
user_id = kwargs["user_id"]
user = self.first(id_int=int(user_id))
if not user:
raise UserNotFoundError
for k, v in kwargs.items():
if k in user.__attr_searchable__:
attributes[k] = v
if kwargs.get("email", None):
user.email = kwargs["email"]
elif kwargs.get("role", None):
user.role = kwargs["role"]
elif kwargs.get("name", None):
user.name = kwargs["name"]
elif kwargs.get("budget", None):
user.budget = kwargs["budget"]
elif kwargs.get("website", None):
user.website = kwargs["website"]
elif kwargs.get("institution", None):
user.institution = kwargs["institution"]
else:
raise Exception
attributes["__blob__"] = user.to_bytes()
self.update_one({"id_int": int(user_id)}, {"$set": attributes})
| 205 | user_manager.py | Python | packages/syft/src/syft/core/node/common/node_manager/user_manager.py | 066545e8a88e842aa7d0a5d57bac88716001bced | PySyft | 10 |
|
124,671 | 67 | 15 | 25 | 217 | 25 | 0 | 105 | 415 | _optimize_stages | Object GC for block splitting inside the dataset splitting (#26196)
The pipeline will spill objects when splitting the dataset into multiple equal parts.
Co-authored-by: Ubuntu <[email protected]> | https://github.com/ray-project/ray.git | def _optimize_stages(self):
context = DatasetContext.get_current()
if not context.optimize_fuse_stages:
self._optimized_stages = self._stages
return
# This dummy dataset will be used to get a set of optimized stages.
dummy_ds = Dataset(
ExecutionPlan(BlockList([], []), DatasetStats(stages={}, parent=None)),
0,
True,
used_from_dataset_pipeline=True,
)
# Apply all pipeline operations to the dummy dataset.
for stage in self._stages:
dummy_ds = stage(dummy_ds)
# Get the optimized stages.
_, _, stages = dummy_ds._plan._optimize()
# Apply these optimized stages to the datasets underlying the pipeline.
# These optimized stages will be executed by the PipelineExecutor.
optimized_stages = []
for stage in stages:
optimized_stages.append(
lambda ds, stage=stage: Dataset(
ds._plan.with_stage(stage),
ds._epoch,
True,
used_from_dataset_pipeline=True,
)
)
self._optimized_stages = optimized_stages
| 138 | dataset_pipeline.py | Python | python/ray/data/dataset_pipeline.py | 45ba0e3cacbf4f38b9724437798c75341c2ddc7c | ray | 4 |
|
38,287 | 31 | 11 | 11 | 58 | 6 | 0 | 37 | 110 | num_layers | Black preview (#17217)
* Black preview
* Fixup too!
* Fix check copies
* Use the same version as the CI
* Bump black | https://github.com/huggingface/transformers.git | def num_layers(self) -> int:
if not hasattr(self._config, "num_layers"):
raise AttributeError(
"could not find the number of layers attribute in the model configuration, override the num_layers"
" property of the model OnnxConfig to solve this"
)
return self._config.num_layers
| 31 | config.py | Python | src/transformers/onnx/config.py | afe5d42d8d1d80af911ed980c2936bfe887078f6 | transformers | 2 |
|
248,496 | 9 | 11 | 6 | 50 | 9 | 0 | 10 | 68 | _get_canonical_alias | Reduce the amount of state we pull from the DB (#12811) | https://github.com/matrix-org/synapse.git | def _get_canonical_alias(self):
return self.get_success(
self._storage_controllers.state.get_current_state_event(
self.room_id, EventTypes.CanonicalAlias, ""
)
)
| 30 | test_directory.py | Python | tests/handlers/test_directory.py | e3163e2e11cf8bffa4cb3e58ac0b86a83eca314c | synapse | 1 |
|
242,493 | 23 | 12 | 10 | 137 | 8 | 0 | 28 | 122 | histogram | Document that histogram() uses 256 bins per channel | https://github.com/python-pillow/Pillow.git | def histogram(self, mask=None, extrema=None):
self.load()
if mask:
mask.load()
return self.im.histogram((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.histogram(extrema)
return self.im.histogram()
| 84 | Image.py | Python | src/PIL/Image.py | de968dd920eaa3d1a27877059c6bbb9043a9d26b | Pillow | 4 |
|
300,734 | 33 | 21 | 24 | 204 | 24 | 0 | 42 | 434 | async_step_onvif_devices | Decouple stream options from PyAV options (#71247)
Co-authored-by: Allen Porter <[email protected]> | https://github.com/home-assistant/core.git | async def async_step_onvif_devices(self, user_input=None):
if user_input is not None:
self.options[CONF_EXTRA_ARGUMENTS] = user_input[CONF_EXTRA_ARGUMENTS]
self.options[CONF_RTSP_TRANSPORT] = user_input[CONF_RTSP_TRANSPORT]
return self.async_create_entry(title="", data=self.options)
return self.async_show_form(
step_id="onvif_devices",
data_schema=vol.Schema(
{
vol.Optional(
CONF_EXTRA_ARGUMENTS,
default=self.config_entry.options.get(
CONF_EXTRA_ARGUMENTS, DEFAULT_ARGUMENTS
),
): str,
vol.Optional(
CONF_RTSP_TRANSPORT,
default=self.config_entry.options.get(
CONF_RTSP_TRANSPORT, next(iter(RTSP_TRANSPORTS))
),
): vol.In(RTSP_TRANSPORTS),
}
),
)
| 134 | config_flow.py | Python | homeassistant/components/onvif/config_flow.py | 617b0d04dcab521ce3b68b4f4956c1f341f6ea60 | core | 2 |
|
9,888 | 6 | 7 | 7 | 28 | 4 | 0 | 6 | 20 | uses_before_args | feat: star routing (#3900)
* feat(proto): adjust proto for star routing (#3844)
* feat(proto): adjust proto for star routing
* feat(proto): generate proto files
* feat(grpc): refactor grpclet interface (#3846)
* feat: refactor connection pool for star routing (#3872)
* feat(k8s): add more labels to k8s deployments
* feat(network): refactor connection pool
* feat(network): refactor k8s pool
* feat: star routing graph gateway (#3877)
* feat: star routing - refactor grpc data runtime (#3887)
* feat(runtimes): refactor grpc dataruntime
* fix(tests): adapt worker runtime tests
* fix(import): fix import
* feat(proto): enable sending multiple lists (#3891)
* feat: star routing gateway (#3893)
* feat: star routing gateway all protocols (#3897)
* test: add streaming and prefetch tests (#3901)
* feat(head): new head runtime for star routing (#3899)
* feat(head): new head runtime
* feat(head): new head runtime
* style: fix overload and cli autocomplete
* feat(network): improve proto comments
Co-authored-by: Jina Dev Bot <[email protected]>
* feat(worker): merge docs in worker runtime (#3905)
* feat(worker): merge docs in worker runtime
* feat(tests): assert after clean up
* feat(tests): star routing runtime integration tests (#3908)
* fix(tests): fix integration tests
* test: test runtimes fast slow request (#3910)
* feat(zmq): purge zmq, zed, routing_table (#3915)
* feat(zmq): purge zmq, zed, routing_table
* style: fix overload and cli autocomplete
* feat(zmq): adapt comment in dependency list
* style: fix overload and cli autocomplete
* fix(tests): fix type tests
Co-authored-by: Jina Dev Bot <[email protected]>
* test: add test gateway to worker connection (#3921)
* feat(pea): adapt peas for star routing (#3918)
* feat(pea): adapt peas for star routing
* style: fix overload and cli autocomplete
* feat(pea): add tests
* feat(tests): add failing head pea test
Co-authored-by: Jina Dev Bot <[email protected]>
* feat(tests): integration tests for peas (#3923)
* feat(tests): integration tests for peas
* feat(pea): remove _inner_pea function
* feat: star routing container pea (#3922)
* test: rescue tests (#3942)
* fix: fix streaming tests (#3945)
* refactor: move docker run to run (#3948)
* feat: star routing pods (#3940)
* feat(pod): adapt pods for star routing
* feat(pods): adapt basepod to star routing
* feat(pod): merge pod and compound pod
* feat(tests): fix tests
* style: fix overload and cli autocomplete
* feat(test): add container pea int test
* feat(ci): remove more unnecessary tests
* fix(tests): remove jinad runtime
* feat(ci): remove latency tracking
* fix(ci): fix ci def
* fix(runtime): enable runtime to be exited
* fix(tests): wrap runtime test in process
* fix(runtimes): remove unused runtimes
* feat(runtimes): improve cancel wait
* fix(ci): build test pip again in ci
* fix(tests): fix a test
* fix(test): run async in its own process
* feat(pod): include shard in activate msg
* fix(pea): dont join
* feat(pod): more debug out
* feat(grpc): manage channels properly
* feat(pods): remove exitfifo
* feat(network): add simple send retry mechanism
* fix(network): await pool close
* fix(test): always close grpc server in worker
* fix(tests): remove container pea from tests
* fix(tests): reorder tests
* fix(ci): split tests
* fix(ci): allow alias setting
* fix(test): skip a test
* feat(pods): address comments
Co-authored-by: Jina Dev Bot <[email protected]>
* test: unblock skipped test (#3957)
* feat: jinad pea (#3949)
* feat: jinad pea
* feat: jinad pea
* test: remote peas
* test: toplogy tests with jinad
* ci: parallel jobs
* feat(tests): add pod integration tests (#3958)
* feat(tests): add pod integration tests
* fix(tests): make tests less flaky
* fix(test): fix test
* test(pea): remote pea topologies (#3961)
* test(pea): remote pea simple topology
* test: remote pea topologies
* refactor: refactor streamer result handling (#3960)
* feat(k8s): adapt K8s Pod for StarRouting (#3964)
* test: optimize k8s test
* test: increase timeout and use different namespace
* test: optimize k8s test
* test: build and load image when needed
* test: refactor k8s test
* test: fix image name error
* test: fix k8s image load
* test: fix typoe port expose
* test: update tests in connection pool and handling
* test: remove unused fixture
* test: parameterize docker images
* test: parameterize docker images
* test: parameterize docker images
* feat(k8s): adapt k8s pod for star routing
* fix(k8s): dont overwrite add/remove function in pool
* fix(k8s): some fixes
* fix(k8s): some more fixes
* fix(k8s): linting
* fix(tests): fix tests
* fix(tests): fix k8s unit tests
* feat(k8s): complete k8s integration test
* feat(k8s): finish k8s tests
* feat(k8s): fix test
* fix(tests): fix test with no name
* feat(k8s): unify create/replace interface
* feat(k8s): extract k8s port constants
* fix(tests): fix tests
* fix(tests): wait for runtime being ready in tests
* feat(k8s): address comments
Co-authored-by: bwanglzu <[email protected]>
* feat(flow): adapt Flow for StarRouting (#3986)
* feat(flow): add routes
* feat(flow): adapt flow to star routing
* style: fix overload and cli autocomplete
* feat(flow): handle empty topologies
* feat(k8s): allow k8s pool disabling
* style: fix overload and cli autocomplete
* fix(test): fix test with mock
* fix(tests): fix more tests
* feat(flow): clean up tests
* style: fix overload and cli autocomplete
* fix(tests): fix more tests
* feat: add plot function (#3994)
* fix(tests): avoid hanging tests
* feat(flow): add type hinting
* fix(test): fix duplicate exec name in test
* fix(tests): fix more tests
* fix(tests): enable jinad test again
* fix(tests): random port fixture
* fix(style): replace quotes
Co-authored-by: Jina Dev Bot <[email protected]>
Co-authored-by: Joan Fontanals <[email protected]>
* feat(ci): bring back ci (#3997)
* feat(ci): enable ci again
* style: fix overload and cli autocomplete
* feat(ci): add latency tracking
* feat(ci): bring back some tests
* fix(tests): remove invalid port test
* feat(ci): disable daemon and distributed tests
* fix(tests): fix entrypoint in hub test
* fix(tests): wait for gateway to be ready
* fix(test): fix more tests
* feat(flow): do rolling update and scale sequentially
* fix(tests): fix more tests
* style: fix overload and cli autocomplete
* feat: star routing hanging pods (#4011)
* fix: try to handle hanging pods better
* test: hanging pods test work
* fix: fix topology graph problem
* test: add unit test to graph
* fix(tests): fix k8s tests
* fix(test): fix k8s test
* fix(test): fix k8s pool test
* fix(test): fix k8s test
* fix(test): fix k8s connection pool setting
* fix(tests): make runtime test more reliable
* fix(test): fix routes test
* fix(tests): make rolling update test less flaky
* feat(network): gurantee unique ports
* feat(network): do round robin for shards
* fix(ci): increase pytest timeout to 10 min
Co-authored-by: Jina Dev Bot <[email protected]>
Co-authored-by: Joan Fontanals <[email protected]>
* fix(ci): fix ci file
* feat(daemon): jinad pod for star routing
* Revert "feat(daemon): jinad pod for star routing"
This reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92.
* feat(daemon): remote jinad pod support (#4042)
* feat(daemon): add pod tests for star routing
* feat(daemon): add remote pod test
* test(daemon): add remote pod arguments test
* test(daemon): add async scale test
* test(daemon): add rolling update test
* test(daemon): fix host
* feat(proto): remove message proto (#4051)
* feat(proto): remove message proto
* fix(tests): fix tests
* fix(tests): fix some more tests
* fix(tests): fix more tests
* fix(tests): fix more tests
* fix(tests): fix more tests
* fix(tests): fix more tests
* feat(proto): put docs back in data
* fix(proto): clean up
* feat(proto): clean up
* fix(tests): skip latency tracking
* fix(test): fix hub test
* fix(tests): fix k8s test
* fix(test): some test clean up
* fix(style): clean up style issues
* feat(proto): adjust for rebase
* fix(tests): bring back latency tracking
* fix(tests): fix merge accident
* feat(proto): skip request serialization (#4074)
* feat: add reduce to star routing (#4070)
* feat: add reduce on shards to head runtime
* test: add reduce integration tests with fixed order
* feat: add reduce on needs
* chore: get_docs_matrix_from_request becomes public
* style: fix overload and cli autocomplete
* docs: remove undeterministic results warning
* fix: fix uses_after
* test: assert correct num docs after reducing in test_external_pod
* test: correct asserts after reduce in test_rolling_update
* fix: no reduce if uses_after_address is set
* fix: get_docs_from_request only if needed
* fix: fix tests after merge
* refactor: move reduce from data_request_handler to head
* style: fix overload and cli autocomplete
* chore: apply suggestions
* fix: fix asserts
* chore: minor test fix
* chore: apply suggestions
* test: remove flow tests with external executor (pea)
* fix: fix test_expected_messages_routing
* fix: fix test_func_joiner
* test: adapt k8s test
Co-authored-by: Jina Dev Bot <[email protected]>
* fix(k8s): fix static pool config
* fix: use custom protoc doc generator image (#4088)
* fix: use custom protoc doc generator image
* fix(docs): minor doc improvement
* fix(docs): use custom image
* fix(docs): copy docarray
* fix: doc building local only
* fix: timeout doc building
* fix: use updated args when building ContainerPea
* test: add container PeaFactory test
* fix: force pea close on windows (#4098)
* fix: dont reduce if uses exist (#4099)
* fix: dont use reduce if uses exist
* fix: adjust reduce tests
* fix: adjust more reduce tests
* fix: fix more tests
* fix: adjust more tests
* fix: ignore non jina resources (#4101)
* feat(executor): enable async executors (#4102)
* feat(daemon): daemon flow on star routing (#4096)
* test(daemon): add remote flow test
* feat(daemon): call scale in daemon
* feat(daemon): remove tail args and identity
* test(daemon): rename scalable executor
* test(daemon): add a small delay in async test
* feat(daemon): scale partial flow only
* feat(daemon): call scale directly in partial flow store
* test(daemon): use asyncio sleep
* feat(daemon): enable flow level distributed tests
* test(daemon): fix jinad env workspace config
* test(daemon): fix pod test use new port rolling update
* feat(daemon): enable distribuetd tests
* test(daemon): remove duplicate tests and zed runtime test
* test(daemon): fix stores unit test
* feat(daemon): enable part of distributed tests
* feat(daemon): enable part of distributed tests
* test: correct test paths
* test(daemon): add client test for remote flows
* test(daemon): send a request with jina client
* test(daemon): assert async generator
* test(daemon): small interval between tests
* test(daemon): add flow test for container runtime
* test(daemon): add flow test for container runtime
* test(daemon): fix executor name
* test(daemon): fix executor name
* test(daemon): use async client fetch result
* test(daemon): finish container flow test
* test(daemon): enable distributed in ci
* test(daemon): enable distributed in ci
* test(daemon): decare flows and pods
* test(daemon): debug ci if else
* test(daemon): debug ci if else
* test(daemon): decare flows and pods
* test(daemon): correct test paths
* test(daemon): add small delay for async tests
* fix: star routing fixes (#4100)
* docs: update docs
* fix: fix Request.__repr__
* docs: update flow remarks
* docs: fix typo
* test: add non_empty_fields test
* chore: remove non_empty_fields test
* feat: polling per endpoint (#4111)
* feat(polling): polling per endpoint configurable
* fix: adjust tests
* feat(polling): extend documentation
* style: fix overload and cli autocomplete
* fix: clean up
* fix: adjust more tests
* fix: remove repeat from flaky test
* fix: k8s test
* feat(polling): address pr feedback
* feat: improve docs
Co-authored-by: Jina Dev Bot <[email protected]>
* feat(grpc): support connect grpc server via ssl tunnel (#4092)
* feat(grpc): support ssl grpc connect if port is 443
* fix(grpc): use https option instead of detect port automatically
* chore: fix typo
* fix: update jina/peapods/networking.py
Co-authored-by: Joan Fontanals <[email protected]>
* fix: update jina/peapods/networking.py
Co-authored-by: Joan Fontanals <[email protected]>
* fix: update jina/peapods/networking.py
Co-authored-by: Joan Fontanals <[email protected]>
* test(networking): add test for peapods networking
* fix: address comments
Co-authored-by: Joan Fontanals <[email protected]>
* feat(polling): unify polling args (#4113)
* fix: several issues for jinad pods (#4119)
* fix: activate for jinad pods
* fix: dont expose worker pod in partial daemon
* fix: workspace setting
* fix: containerized flows
* fix: hub test
* feat(daemon): remote peas on star routing (#4112)
* test(daemon): fix request in peas
* test(daemon): fix request in peas
* test(daemon): fix sync async client test
* test(daemon): enable remote peas test
* test(daemon): replace send message to send request
* test(daemon): declare pea tests in ci
* test(daemon): use pea args fixture
* test(daemon): head pea use default host
* test(daemon): fix peas topologies
* test(daemon): fix pseudo naming
* test(daemon): use default host as host
* test(daemon): fix executor path
* test(daemon): add remote worker back
* test(daemon): skip local remote remote topology
* fix: jinad pea test setup
* fix: jinad pea tests
* fix: remove invalid assertion
Co-authored-by: jacobowitz <[email protected]>
* feat: enable daemon tests again (#4132)
* feat: enable daemon tests again
* fix: remove bogy empty script file
* fix: more jinad test fixes
* style: fix overload and cli autocomplete
* fix: scale and ru in jinad
* fix: fix more jinad tests
Co-authored-by: Jina Dev Bot <[email protected]>
* fix: fix flow test
* fix: improve pea tests reliability (#4136)
Co-authored-by: Joan Fontanals <[email protected]>
Co-authored-by: Jina Dev Bot <[email protected]>
Co-authored-by: Deepankar Mahapatro <[email protected]>
Co-authored-by: bwanglzu <[email protected]>
Co-authored-by: AlaeddineAbdessalem <[email protected]>
Co-authored-by: Zhaofeng Miao <[email protected]> | https://github.com/jina-ai/jina.git | def uses_before_args(self) -> Namespace:
return self.peas_args['uses_before']
| 15 | __init__.py | Python | jina/peapods/pods/__init__.py | 933415bfa1f9eb89f935037014dfed816eb9815d | jina | 1 |
|
102,397 | 5 | 6 | 19 | 23 | 5 | 0 | 5 | 8 | no_batch_dim_reference_fn | [rnn/gru] no batch dim (#70442)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/60585
TODO:
* [x] Doc updates
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70442
Reviewed By: zou3519
Differential Revision: D33460427
Pulled By: jbschlosser
fbshipit-source-id: c64d9624c305d90570c79d11a28557f9ec667b27 | https://github.com/pytorch/pytorch.git | def no_batch_dim_reference_fn(m, p, *args, **kwargs):
| 152 | common_modules.py | Python | torch/testing/_internal/common_modules.py | 6eba936082a641be8ece156f70c0f5c435f7a7aa | pytorch | 9 |
|
107,534 | 10 | 10 | 4 | 47 | 5 | 0 | 10 | 54 | fix_minus | Properly capitalize "Unicode".
See e.g. https://en.wikipedia.org/wiki/Unicode,
https://docs.python.org/3/howto/unicode.html.
Also associated minor doc cleanups. | https://github.com/matplotlib/matplotlib.git | def fix_minus(s):
return (s.replace('-', '\N{MINUS SIGN}')
if mpl.rcParams['axes.unicode_minus']
else s)
| 26 | ticker.py | Python | lib/matplotlib/ticker.py | 88cb4c9d0aa1e790fc4689ca7e68725bf851bf63 | matplotlib | 2 |
|
248,369 | 92 | 13 | 26 | 284 | 31 | 0 | 125 | 441 | test_prune_gap_if_dummy_remote | Pull out less state when handling gaps mk2 (#12852) | https://github.com/matrix-org/synapse.git | def test_prune_gap_if_dummy_remote(self):
body = self.helper.send_event(
self.room_id, type=EventTypes.Dummy, content={}, tok=self.token
)
local_message_event_id = body["event_id"]
self.assert_extremities([local_message_event_id])
# Advance the clock for many days to make the old extremity "old". We
# also set the depth to "lots".
self.reactor.advance(7 * 24 * 60 * 60)
# Fudge a second event which points to an event we don't have. This is a
# state event so that the state changes (otherwise we won't prune the
# extremity as they'll have the same state group).
remote_event_2 = event_from_pdu_json(
{
"type": EventTypes.Member,
"state_key": "@user:other2",
"content": {"membership": Membership.JOIN},
"room_id": self.room_id,
"sender": "@user:other2",
"depth": 10000,
"prev_events": ["$some_unknown_message"],
"auth_events": [],
"origin_server_ts": self.clock.time_msec(),
},
RoomVersions.V6,
)
state_before_gap = self.get_success(
self.state.get_current_state_ids(self.room_id)
)
self.persist_event(remote_event_2, state=state_before_gap)
# Check the new extremity is just the new remote event.
self.assert_extremities([remote_event_2.event_id])
| 167 | test_events.py | Python | tests/storage/test_events.py | b83bc5fab57b37f75a79d02213d6032c586fd36e | synapse | 1 |
|
215,549 | 219 | 19 | 107 | 1,087 | 60 | 0 | 431 | 2,121 | sign_in | Use salt.channel.client instead of salt.transport.client | https://github.com/saltstack/salt.git | def sign_in(self, timeout=60, safe=True, tries=1, channel=None):
auth = {}
auth_timeout = self.opts.get("auth_timeout", None)
if auth_timeout is not None:
timeout = auth_timeout
auth_safemode = self.opts.get("auth_safemode", None)
if auth_safemode is not None:
safe = auth_safemode
auth_tries = self.opts.get("auth_tries", None)
if auth_tries is not None:
tries = auth_tries
m_pub_fn = os.path.join(self.opts["pki_dir"], self.mpub)
auth["master_uri"] = self.opts["master_uri"]
close_channel = False
if not channel:
close_channel = True
channel = salt.channel.client.AsyncReqChannel.factory(
self.opts, crypt="clear", io_loop=self.io_loop
)
sign_in_payload = self.minion_sign_in_payload()
try:
payload = yield channel.send(sign_in_payload, tries=tries, timeout=timeout)
except SaltReqTimeoutError as e:
if safe:
log.warning("SaltReqTimeoutError: %s", e)
raise salt.ext.tornado.gen.Return("retry")
if self.opts.get("detect_mode") is True:
raise salt.ext.tornado.gen.Return("retry")
else:
raise SaltClientError(
"Attempt to authenticate with the salt master failed with timeout"
" error"
)
finally:
if close_channel:
channel.close()
if not isinstance(payload, dict):
log.error("Sign-in attempt failed: %s", payload)
raise salt.ext.tornado.gen.Return(False)
if "load" in payload:
if "ret" in payload["load"]:
if not payload["load"]["ret"]:
if self.opts["rejected_retry"]:
log.error(
"The Salt Master has rejected this minion's public "
"key.\nTo repair this issue, delete the public key "
"for this minion on the Salt Master.\nThe Salt "
"Minion will attempt to to re-authenicate."
)
raise salt.ext.tornado.gen.Return("retry")
else:
log.critical(
"The Salt Master has rejected this minion's public "
"key!\nTo repair this issue, delete the public key "
"for this minion on the Salt Master and restart this "
"minion.\nOr restart the Salt Master in open mode to "
"clean out the keys. The Salt Minion will now exit."
)
# Add a random sleep here for systems that are using a
# a service manager to immediately restart the service
# to avoid overloading the system
time.sleep(random.randint(10, 20))
sys.exit(salt.defaults.exitcodes.EX_NOPERM)
# has the master returned that its maxed out with minions?
elif payload["load"]["ret"] == "full":
raise salt.ext.tornado.gen.Return("full")
else:
log.error(
"The Salt Master has cached the public key for this "
"node, this salt minion will wait for %s seconds "
"before attempting to re-authenticate",
self.opts["acceptance_wait_time"],
)
raise salt.ext.tornado.gen.Return("retry")
auth["aes"] = self.verify_master(payload, master_pub="token" in sign_in_payload)
if not auth["aes"]:
log.critical(
"The Salt Master server's public key did not authenticate!\n"
"The master may need to be updated if it is a version of Salt "
"lower than %s, or\n"
"If you are confident that you are connecting to a valid Salt "
"Master, then remove the master public key and restart the "
"Salt Minion.\nThe master public key can be found "
"at:\n%s",
salt.version.__version__,
m_pub_fn,
)
raise SaltClientError("Invalid master key")
if self.opts.get("syndic_master", False): # Is syndic
syndic_finger = self.opts.get(
"syndic_finger", self.opts.get("master_finger", False)
)
if syndic_finger:
if (
salt.utils.crypt.pem_finger(
m_pub_fn, sum_type=self.opts["hash_type"]
)
!= syndic_finger
):
self._finger_fail(syndic_finger, m_pub_fn)
else:
if self.opts.get("master_finger", False):
if (
salt.utils.crypt.pem_finger(
m_pub_fn, sum_type=self.opts["hash_type"]
)
!= self.opts["master_finger"]
):
self._finger_fail(self.opts["master_finger"], m_pub_fn)
auth["publish_port"] = payload["publish_port"]
raise salt.ext.tornado.gen.Return(auth)
| 626 | crypt.py | Python | salt/crypt.py | 70972c8016ff5d6fbdd7f83776077b0936f60dea | salt | 22 |
|
101,595 | 32 | 15 | 10 | 168 | 21 | 0 | 41 | 138 | _get_count_and_filelist | Overhaul sort:
- Standardize image data reading and writing
- Optimize loading (just one pass required)
- Make all sort groups binnable (to greater or lesser results)
- Add sort by pitch
- Deprecate multiple options
- linting, docs + locales | https://github.com/deepfakes/faceswap.git | def _get_count_and_filelist(self, fast_count, count):
if isinstance(self.location, (list, tuple)):
file_list = self.location
else:
file_list = get_image_paths(self.location)
self._file_list = [fname for fname in file_list
if os.path.splitext(fname)[-1].lower() == ".png"]
self._count = len(self.file_list) if count is None else count
logger.debug("count: %s", self.count)
logger.trace("filelist: %s", self.file_list)
| 105 | image.py | Python | lib/image.py | 98d01760e469fd2108eed8d0b0a1ba6297c3177c | faceswap | 5 |
|
271,005 | 28 | 11 | 9 | 145 | 17 | 0 | 31 | 105 | test_adapt_doesnt_overwrite_input_shape | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | https://github.com/keras-team/keras.git | def test_adapt_doesnt_overwrite_input_shape(self):
# Shape: (3, 1, 2)
adapt_dataset = np.array(
[[[1.0, 2.0]], [[3.0, 4.0]], [[5.0, 6.0]]], dtype=np.float32
)
layer = AddingPreprocessingLayer(input_shape=[1, 2])
layer.adapt(adapt_dataset)
model = keras.Sequential([layer])
self.assertTrue(model.built)
self.assertEqual(model.input_shape, (None, 1, 2))
| 108 | base_preprocessing_layer_test.py | Python | keras/engine/base_preprocessing_layer_test.py | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | 1 |
|
47,665 | 40 | 12 | 21 | 186 | 25 | 0 | 49 | 256 | test_deps_sorted | Replace usage of `DummyOperator` with `EmptyOperator` (#22974)
* Replace usage of `DummyOperator` with `EmptyOperator` | https://github.com/apache/airflow.git | def test_deps_sorted(self):
from airflow.operators.empty import EmptyOperator
from airflow.sensors.external_task import ExternalTaskSensor
execution_date = datetime(2020, 1, 1)
with DAG(dag_id="test_deps_sorted", start_date=execution_date) as dag:
task1 = ExternalTaskSensor(
task_id="task1",
external_dag_id="external_dag_id",
mode="reschedule",
)
task2 = EmptyOperator(task_id="task2")
task1 >> task2
serialize_op = SerializedBaseOperator.serialize_operator(dag.task_dict["task1"])
deps = serialize_op["deps"]
assert deps == [
'airflow.ti_deps.deps.not_in_retry_period_dep.NotInRetryPeriodDep',
'airflow.ti_deps.deps.not_previously_skipped_dep.NotPreviouslySkippedDep',
'airflow.ti_deps.deps.prev_dagrun_dep.PrevDagrunDep',
'airflow.ti_deps.deps.ready_to_reschedule.ReadyToRescheduleDep',
'airflow.ti_deps.deps.trigger_rule_dep.TriggerRuleDep',
]
| 109 | test_dag_serialization.py | Python | tests/serialization/test_dag_serialization.py | 49e336ae0302b386a2f47269a6d13988382d975f | airflow | 1 |
|
176,169 | 11 | 8 | 4 | 41 | 5 | 0 | 13 | 25 | tetrahedral_graph | Docstrings for the small.py module (#5240)
* added description for the first 5 small graphs
* modified descriptions based on comment and added description for two more functions
* added doctrings to all the functions
* Minor touchups.
Co-authored-by: Ross Barnowski <[email protected]> | https://github.com/networkx/networkx.git | def tetrahedral_graph(create_using=None):
G = complete_graph(4, create_using)
G.name = "Platonic Tetrahedral graph"
return G
| 23 | small.py | Python | networkx/generators/small.py | dec723f072eb997a497a159dbe8674cd39999ee9 | networkx | 1 |
|
155,297 | 62 | 16 | 18 | 252 | 35 | 0 | 78 | 178 | test_zero_copy_export_for_primitives | REFACTOR-#5303: Fix code scanning alert - Unused local variable (#5304)
Signed-off-by: Myachev <[email protected]>
Co-authored-by: Mahesh Vashishtha <[email protected]> | https://github.com/modin-project/modin.git | def test_zero_copy_export_for_primitives(data_has_nulls):
data = get_data_of_all_types(
has_nulls=data_has_nulls, include_dtypes=["int", "uint", "float"]
)
at = pa.Table.from_pydict(data)
md_df = from_arrow(at)
protocol_df = md_df.__dataframe__(allow_copy=False)
for i, col in enumerate(protocol_df.get_columns()):
col_arr, _ = primitive_column_to_ndarray(col)
exported_ptr = col_arr.__array_interface__["data"][0]
producer_ptr = at.column(i).chunks[0].buffers()[-1].address
# Verify that the pointers of produce and exported objects point to the same data
assert producer_ptr == exported_ptr
# Can't export `md_df` zero-copy no more as it has delayed 'fillna' operation
md_df = md_df.fillna({"float32": 32.0})
non_zero_copy_protocol_df = md_df.__dataframe__(allow_copy=False)
with pytest.raises(RuntimeError):
primitive_column_to_ndarray(
non_zero_copy_protocol_df.get_column_by_name("float32")
)
| 151 | test_protocol.py | Python | modin/test/interchange/dataframe_protocol/hdk/test_protocol.py | eb99c500a40c5565012e3fe83c5e6ef333d1b487 | modin | 2 |
|
259,734 | 41 | 11 | 8 | 188 | 21 | 1 | 48 | 80 | test_minibatch_nmf_negative_beta_loss | FEA Online implementation of non-negative matrix factorization (#16948)
Co-authored-by: Tom Dupré la Tour <[email protected]>
Co-authored-by: jeremie du boisberranger <[email protected]>
Co-authored-by: Thomas J. Fan <[email protected]>
Co-authored-by: Jérémie du Boisberranger <[email protected]> | https://github.com/scikit-learn/scikit-learn.git | def test_minibatch_nmf_negative_beta_loss(beta_loss):
rng = np.random.RandomState(0)
X = rng.normal(size=(6, 5))
X[X < 0] = 0
nmf = MiniBatchNMF(beta_loss=beta_loss, random_state=0)
msg = "When beta_loss <= 0 and X contains zeros, the solver may diverge."
with pytest.raises(ValueError, match=msg):
nmf.fit(X)
@pytest.mark.parametrize(
["Estimator", "solver"],
[[NMF, {"solver": "cd"}], [NMF, {"solver": "mu"}], [MiniBatchNMF, {}]],
) | @pytest.mark.parametrize(
["Estimator", "solver"],
[[NMF, {"solver": "cd"}], [NMF, {"solver": "mu"}], [MiniBatchNMF, {}]],
) | 71 | test_nmf.py | Python | sklearn/decomposition/tests/test_nmf.py | 69132ebbd39f070590ca01813340b5b12c0d02ab | scikit-learn | 1 |
246,283 | 19 | 8 | 3 | 42 | 7 | 0 | 19 | 39 | get_logcontext_id | Add missing type hints to synapse.replication. (#11938) | https://github.com/matrix-org/synapse.git | def get_logcontext_id(self) -> str:
# by default, we just use the command name.
return self.NAME
SC = TypeVar("SC", bound="_SimpleCommand")
| 12 | commands.py | Python | synapse/replication/tcp/commands.py | d0e78af35e519ff76bd23e786007f3e7130d90f7 | synapse | 1 |
|
145,235 | 58 | 9 | 7 | 231 | 18 | 1 | 80 | 338 | _get_gpu_complaint | [KubeRay] Format autoscaling config based on RayCluster CR (#22348)
Closes #21655. At the start of each autoscaler iteration, we read the Ray Cluster CR from K8s and use it to extract the autoscaling config. | https://github.com/ray-project/ray.git | def _get_gpu_complaint() -> str:
return (
"Detected GPUs in container resources for group small-group."
"To ensure Ray and the autoscaler are aware of the GPUs,"
" set the `--num-gpus` rayStartParam."
)
PARAM_ARGS = ",".join(
[
"ray_cr_in",
"expected_config_out",
"expected_error",
"expected_error_message",
"expected_log_warning",
]
)
TEST_DATA = [
pytest.param(
_get_basic_ray_cr(),
_get_basic_autoscaling_config(),
None,
None,
None,
id="basic",
),
pytest.param(
_get_ray_cr_no_cpu_error(),
None,
ValueError,
_get_no_cpu_error(),
None,
id="no-cpu-error",
),
pytest.param(
_get_ray_cr_memory_and_gpu(),
_get_autoscaling_config_memory_and_gpu(),
None,
None,
None,
id="memory-and-gpu",
),
pytest.param(
_get_ray_cr_missing_gpu_arg(),
_get_basic_autoscaling_config(),
None,
None,
_get_gpu_complaint(),
id="gpu-complaint",
),
]
@pytest.mark.parametrize(PARAM_ARGS, TEST_DATA) | @pytest.mark.parametrize(PARAM_ARGS, TEST_DATA) | 13 | test_autoscaling_config.py | Python | docker/kuberay-autoscaler/test_autoscaling_config.py | a402e956a4e1ebe9bc4e2b404536466967c497af | ray | 1 |
261,761 | 26 | 12 | 8 | 100 | 17 | 0 | 29 | 61 | test_kbinsdiscretizer_wrong_strategy_with_weights | ENH add support for sample_weight in KBinsDiscretizer with strategy="quantile" (#24935)
Co-authored-by: seladus <[email protected]>
Co-authored-by: Seladus <[email protected]>
Co-authored-by: Guillaume Lemaitre <[email protected]> | https://github.com/scikit-learn/scikit-learn.git | def test_kbinsdiscretizer_wrong_strategy_with_weights(strategy):
sample_weight = np.ones(shape=(len(X)))
est = KBinsDiscretizer(n_bins=3, strategy=strategy)
err_msg = (
"`sample_weight` was provided but it can only be used with strategy='quantile'."
)
with pytest.raises(ValueError, match=err_msg):
est.fit(X, sample_weight=sample_weight)
| 60 | test_discretization.py | Python | sklearn/preprocessing/tests/test_discretization.py | 1f3c1be77a5b15d6bc1a5bfd9eb64315928679b1 | scikit-learn | 1 |
|
156,511 | 11 | 8 | 17 | 26 | 4 | 0 | 11 | 25 | __dask_graph__ | Collection Protocol (#8674)
[PEP 544](https://www.python.org/dev/peps/pep-0544/) introduces the `Protocol` class to the `typing` module in Python 3.8 (the soon be the minimum supported version, https://github.com/dask/community/issues/213). Writing new Dask collections for [dask-awkward](https://github.com/ContinuumIO/dask-awkward/) has had me thinking about working on a `DaskCollection` protocol. I imagine the benefits to be:
- usage with static type checkers
- other activity in this area at
- #8295
- #8706
- #8854
- Python supporting IDEs take advantage of typing
- self-documenting; some improvements to [the custom collections page](https://docs.dask.org/en/latest/custom-collections.html) of the docs. The protocol docs can be autogenerated and added to that page.
- purely opt-in feature
The `typing.runtime_checkable` decorator allows use of `isinstance(x, DaskCollection)` in any code base
that uses Dask collections; for example:
```python
>>> from dask.typing import DaskCollection
>>> import dask.array as da
>>> x = da.zeros((10, 3))
>>> isinstance(x, DaskCollection)
True
```
(though this is an order of magnitude slower than `dask.base.is_dask_collection` which only checks for `x.__dask_graph__() is not None`; static typing checking & built-in interface documentation are the core benefits IMO)
Something else that came up in the brief discussion on a call last week was having `{Scheduler,Worker,Nanny}Plugin` protocols in `distributed`; and perhaps those are better places to start introducing protocols to Dask since on the user side typically more folks would write plugins than new collections. | https://github.com/dask/dask.git | def __dask_graph__(self) -> Mapping:
raise NotImplementedError("Inheriting class must implement this method.")
| 13 | typing.py | Python | dask/typing.py | 1e783d9a714160e968936cb22d54d085959ab09e | dask | 1 |
|
309,557 | 50 | 18 | 27 | 240 | 18 | 0 | 62 | 383 | test_notify_credential_profile | Upgrade boto3 to 1.20.24 + aiobotocore to 2.1.0 (#64045) | https://github.com/home-assistant/core.git | async def test_notify_credential_profile(hass):
with async_patch("aiobotocore.session.AioSession", new=MockAioSession):
await async_setup_component(
hass,
"aws",
{
"aws": {
"notify": [
{
"service": "sqs",
"name": "SQS Test",
"region_name": "us-east-1",
"profile_name": "test",
}
]
}
},
)
await hass.async_block_till_done()
sessions = hass.data[aws.DATA_SESSIONS]
assert sessions is not None
assert len(sessions) == 1
assert isinstance(sessions.get("default"), MockAioSession)
assert hass.services.has_service("notify", "sqs_test") is True
await hass.services.async_call(
"notify", "sqs_test", {"message": "test", "target": "ARN"}, blocking=True
)
| 131 | test_init.py | Python | tests/components/aws/test_init.py | b17860a7dd283d54bc452e5dca23532d05822589 | core | 1 |
|
288,027 | 31 | 11 | 6 | 61 | 5 | 0 | 36 | 97 | model | Refactor apcupsd to use config flow (#64809)
* Add Config Flow to APCUPSd integration and remove YAML support.
* Hide the binary sensor if user does not select STATFLAG resource.
* Add tests for config flows.
* Simplify config flow code.
* Spell fix.
* Fix pylint warnings.
* Simplify the code for config flow.
* First attempt to implement import flows to suppport legacy YAML configurations.
* Remove unnecessary log calls.
* Wrap synchronous update call with `hass.async_add_executor_job`.
* Import the YAML configurations when sensor platform is set up.
* Move the logger call since the variables are not properly set up.
* Add codeowner.
* Fix name field of manifest.json.
* Fix linting issue.
* Fix incorrect dependency due to incorrect rebase.
* Update codeowner and config flows via hassfest.
* Postpone the deprecation warning to 2022.7.
* Import future annotations for init file.
* Add an newline at the end to make prettier happy.
* Update github id.
* Add type hints for return types of steps in config flow.
* Move the deprecation date for YAML config to 2022.12.
* Update according to reviews.
* Use async_forward_entry_setups.
* Add helper properties to `APCUPSdData` class.
* Add device_info for binary sensor.
* Simplify config flow.
* Remove options flow strings.
* update the tests according to the changes.
* Add `entity_registry_enabled_default` to entities and use imported CONF_RESOURCES to disable entities instead of skipping them.
* Update according to reviews.
* Do not use model of the UPS as the title for the integration.
Instead, simply use "APCUPSd" as the integration title and let the device info serve as title for each device instead.
* Change schema to be a global variable.
* Add more comments.
* Rewrite the tests for config flows.
* Fix enabled_by_default.
* Show friendly titles in the integration.
* Add import check in `async_setup_platform` to avoid importing in sensor platform setup.
* Add import check in `async_setup_platform` to avoid importing in sensor platform setup.
* Update comments in test files.
* Use parametrize instead of manually iterating different test cases.
* Swap the order of the platform constants.
* Avoid using broad exceptions.
* Set up device info via `_attr_device_info`.
* Remove unrelated test in `test_config_flow`.
* Use `DeviceInfo` instead of dict to assign to `_attr_device_info`.
* Add english translation.
* Add `async_create_issue` for deprecated YAML configuration.
* Enable UPS status by default since it could show "online, charging, on battery etc" which is meaningful for all users.
* Apply suggestions from code review
* Apply suggestion
* Apply suggestion
Co-authored-by: Martin Hjelmare <[email protected]> | https://github.com/home-assistant/core.git | def model(self) -> str | None:
# Different UPS models may report slightly different keys for model, here we
# try them all.
for model_key in ("APCMODEL", "MODEL"):
if model_key in self.status:
return self.status[model_key]
return None
| 35 | __init__.py | Python | homeassistant/components/apcupsd/__init__.py | 52307708c843b947a2d631f2fe7ddaa8bd9a90d7 | core | 3 |
|
46,209 | 2 | 6 | 17 | 12 | 1 | 0 | 2 | 5 | lazy_add_provider_discovered_options_to_connection_form | Add generic connection type (#22310)
See https://github.com/apache/airflow/discussions/20350. | https://github.com/apache/airflow.git | def lazy_add_provider_discovered_options_to_connection_form():
| 102 | views.py | Python | airflow/www/views.py | 6d1d53b780c48297fa2e6d8e075fdaa0f0f42e22 | airflow | 2 |
|
275,864 | 43 | 14 | 9 | 88 | 13 | 0 | 50 | 109 | _legacy_weights | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | https://github.com/keras-team/keras.git | def _legacy_weights(layer):
weights = layer.trainable_weights + layer.non_trainable_weights
if any(not isinstance(w, tf.Variable) for w in weights):
raise NotImplementedError(
f"Save or restore weights that is not an instance of `tf.Variable` is "
f"not supported in h5, use `save_format='tf'` instead. Received a "
f"model or layer {layer.__class__.__name__} with weights {weights}"
)
return weights
| 45 | hdf5_format.py | Python | keras/saving/hdf5_format.py | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | 3 |
|
104,754 | 153 | 23 | 55 | 669 | 35 | 0 | 280 | 1,003 | _create_builder_config | fix outdated docstring about default dataset config (#4186) | https://github.com/huggingface/datasets.git | def _create_builder_config(self, name=None, custom_features=None, **config_kwargs) -> Tuple[BuilderConfig, str]:
builder_config = None
# try default config
if name is None and self.BUILDER_CONFIGS and not config_kwargs:
if self.DEFAULT_CONFIG_NAME is not None:
builder_config = self.builder_configs.get(self.DEFAULT_CONFIG_NAME)
logger.warning(f"No config specified, defaulting to: {self.name}/{builder_config.name}")
else:
if len(self.BUILDER_CONFIGS) > 1:
example_of_usage = f"load_dataset('{self.name}', '{self.BUILDER_CONFIGS[0].name}')"
raise ValueError(
"Config name is missing."
f"\nPlease pick one among the available configs: {list(self.builder_configs.keys())}"
+ f"\nExample of usage:\n\t`{example_of_usage}`"
)
builder_config = self.BUILDER_CONFIGS[0]
logger.info(f"No config specified, defaulting to the single config: {self.name}/{builder_config.name}")
# try get config by name
if isinstance(name, str):
builder_config = self.builder_configs.get(name)
if builder_config is None and self.BUILDER_CONFIGS:
raise ValueError(f"BuilderConfig {name} not found. Available: {list(self.builder_configs.keys())}")
# if not using an existing config, then create a new config on the fly with config_kwargs
if not builder_config:
if name is not None:
config_kwargs["name"] = name
if "version" not in config_kwargs and hasattr(self, "VERSION") and self.VERSION:
config_kwargs["version"] = self.VERSION
builder_config = self.BUILDER_CONFIG_CLASS(**config_kwargs)
# otherwise use the config_kwargs to overwrite the attributes
else:
builder_config = copy.deepcopy(builder_config)
for key, value in config_kwargs.items():
if value is not None:
if not hasattr(builder_config, key):
raise ValueError(f"BuilderConfig {builder_config} doesn't have a '{key}' key.")
setattr(builder_config, key, value)
if not builder_config.name:
raise ValueError(f"BuilderConfig must have a name, got {builder_config.name}")
# compute the config id that is going to be used for caching
config_id = builder_config.create_config_id(
config_kwargs,
custom_features=custom_features,
)
is_custom = config_id not in self.builder_configs
if is_custom:
logger.warning(f"Using custom data configuration {config_id}")
else:
if builder_config != self.builder_configs[builder_config.name]:
raise ValueError(
"Cannot name a custom BuilderConfig the same as an available "
f"BuilderConfig. Change the name. Available BuilderConfigs: {list(self.builder_configs.keys())}"
)
if not builder_config.version:
raise ValueError(f"BuilderConfig {builder_config.name} must have a version")
# if not builder_config.description:
# raise ValueError(f"BuilderConfig {builder_config.name} must have a description" )
return builder_config, config_id
| 320 | builder.py | Python | src/datasets/builder.py | 27973e4fcf45c16dc9f81f18459ce54e4165aa2a | datasets | 21 |
|
3,358 | 52 | 15 | 18 | 387 | 29 | 0 | 71 | 141 | test_valid_incremental_read_with_no_interval | CDK: Fix typing errors (#9037)
* fix typing, drop AirbyteLogger
* format
* bump the version
* use logger instead of fixture logger
Co-authored-by: Eugene Kulak <[email protected]>
Co-authored-by: auganbay <[email protected]> | https://github.com/airbytehq/airbyte.git | def test_valid_incremental_read_with_no_interval(mocker):
stream_output = [{"k1": "v1"}, {"k2": "v2"}]
s1 = MockStream([({"sync_mode": SyncMode.incremental, "stream_state": {}}, stream_output)], name="s1")
s2 = MockStream([({"sync_mode": SyncMode.incremental, "stream_state": {}}, stream_output)], name="s2")
state = {"cursor": "value"}
mocker.patch.object(MockStream, "get_updated_state", return_value=state)
mocker.patch.object(MockStream, "supports_incremental", return_value=True)
mocker.patch.object(MockStream, "get_json_schema", return_value={})
src = MockSource(streams=[s1, s2])
catalog = ConfiguredAirbyteCatalog(streams=[_configured_stream(s1, SyncMode.incremental), _configured_stream(s2, SyncMode.incremental)])
expected = [
*_as_records("s1", stream_output),
_state({"s1": state}),
*_as_records("s2", stream_output),
_state({"s1": state, "s2": state}),
]
messages = _fix_emitted_at(list(src.read(logger, {}, catalog, state=defaultdict(dict))))
assert expected == messages
| 235 | test_abstract_source.py | Python | airbyte-cdk/python/unit_tests/sources/test_abstract_source.py | f83eca58eaf2129d21b5796a301732ab22675130 | airbyte | 1 |
|
267,940 | 4 | 6 | 2 | 23 | 5 | 0 | 4 | 11 | supported_pythons | ansible-test - Use more native type hints. (#78435)
* ansible-test - Use more native type hints.
Simple search and replace to switch from comments to native type hints for return types of functions with no arguments.
* ansible-test - Use more native type hints.
Conversion of simple single-line function annotation type comments to native type hints.
* ansible-test - Use more native type hints.
Conversion of single-line function annotation type comments with default values to native type hints.
* ansible-test - Use more native type hints.
Manual conversion of type annotation comments for functions which have pylint directives. | https://github.com/ansible/ansible.git | def supported_pythons(self) -> t.List[str]:
| 13 | completion.py | Python | test/lib/ansible_test/_internal/completion.py | 3eb0485dd92c88cc92152d3656d94492db44b183 | ansible | 1 |
|
261,504 | 47 | 12 | 16 | 279 | 34 | 1 | 63 | 141 | test_predict_iris | ENH add newton-cholesky solver to LogisticRegression (#24767) | https://github.com/scikit-learn/scikit-learn.git | def test_predict_iris(clf):
n_samples, n_features = iris.data.shape
target = iris.target_names[iris.target]
if clf.solver == "lbfgs":
# lbfgs has convergence issues on the iris data with its default max_iter=100
with warnings.catch_warnings():
warnings.simplefilter("ignore", ConvergenceWarning)
clf.fit(iris.data, target)
else:
clf.fit(iris.data, target)
assert_array_equal(np.unique(target), clf.classes_)
pred = clf.predict(iris.data)
assert np.mean(pred == target) > 0.95
probabilities = clf.predict_proba(iris.data)
assert_allclose(probabilities.sum(axis=1), np.ones(n_samples))
pred = iris.target_names[probabilities.argmax(axis=1)]
assert np.mean(pred == target) > 0.95
@pytest.mark.parametrize("LR", [LogisticRegression, LogisticRegressionCV]) | @pytest.mark.parametrize("LR", [LogisticRegression, LogisticRegressionCV]) | 161 | test_logistic.py | Python | sklearn/linear_model/tests/test_logistic.py | bb080aa690364d84d11232c73dc8db2f0dde3578 | scikit-learn | 2 |
268,686 | 57 | 13 | 22 | 374 | 36 | 0 | 80 | 262 | configure_source_trees | ansible-test - Improve container management. (#78550)
See changelogs/fragments/ansible-test-container-management.yml for details. | https://github.com/ansible/ansible.git | def configure_source_trees(cls):
current_ansible = pathlib.Path(os.environ['PYTHONPATH']).parent
root_ansible = pathlib.Path('~').expanduser() / 'ansible'
test_ansible = pathlib.Path(f'~{UNPRIVILEGED_USER_NAME}').expanduser() / 'ansible'
if current_ansible != root_ansible:
display.info(f'copying {current_ansible} -> {root_ansible} ...')
rmtree(root_ansible)
shutil.copytree(current_ansible, root_ansible)
run_command('chown', '-R', 'root:root', str(root_ansible))
display.info(f'copying {current_ansible} -> {test_ansible} ...')
rmtree(test_ansible)
shutil.copytree(current_ansible, test_ansible)
run_command('chown', '-R', f'{UNPRIVILEGED_USER_NAME}:{UNPRIVILEGED_USER_NAME}', str(test_ansible))
paths = [pathlib.Path(test_ansible)]
for root, dir_names, file_names in os.walk(test_ansible):
paths.extend(pathlib.Path(root, dir_name) for dir_name in dir_names)
paths.extend(pathlib.Path(root, file_name) for file_name in file_names)
user = pwd.getpwnam(UNPRIVILEGED_USER_NAME)
uid = user.pw_uid
gid = user.pw_gid
for path in paths:
os.chown(path, uid, gid)
| 211 | runme.py | Python | test/integration/targets/ansible-test-container/runme.py | cda16cc5e9aa8703fb4e1ac0a0be6b631d9076cc | ansible | 6 |
|
177,995 | 56 | 15 | 6 | 371 | 36 | 1 | 81 | 470 | perform_create | 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]> | https://github.com/heartexlabs/label-studio.git | 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'
),
],
)) | @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'
),
],
)) | 71 | api.py | Python | label_studio/tasks/api.py | 71a9ada93224ed6433fb5b45bfcd60d5fe3edd4c | label-studio | 1 |
122,415 | 39 | 13 | 9 | 155 | 14 | 0 | 64 | 79 | _multi_dot_three | Call _check_arraylike for jnp.linalg & jnp.fft functions | https://github.com/google/jax.git | def _multi_dot_three(A, B, C, precision):
a0, a1b0 = A.shape
b1c0, c1 = C.shape
# cost1 = cost((AB)C) = a0*a1b0*b1c0 + a0*b1c0*c1
cost1 = a0 * b1c0 * (a1b0 + c1)
# cost2 = cost(A(BC)) = a1b0*b1c0*c1 + a0*a1b0*c1
cost2 = a1b0 * c1 * (a0 + b1c0)
if cost1 < cost2:
return jnp.dot(jnp.dot(A, B, precision=precision), C, precision=precision)
else:
return jnp.dot(A, jnp.dot(B, C, precision=precision), precision=precision)
| 103 | linalg.py | Python | jax/_src/third_party/numpy/linalg.py | 2416d154355f19e77b5c1ddf1de1f8552e4a98ad | jax | 2 |
|
20,826 | 15 | 11 | 3 | 59 | 8 | 0 | 15 | 29 | meta | 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 | https://github.com/pypa/pipenv.git | def meta(self) -> Dict[str, Any]:
return {} if self._meta is None else cast(Dict[str, Any], loads(self._meta))
| 39 | style.py | Python | pipenv/patched/notpip/_vendor/rich/style.py | f3166e673fe8d40277b804d35d77dcdb760fc3b3 | pipenv | 2 |
|
293,911 | 85 | 12 | 31 | 381 | 28 | 1 | 145 | 362 | test_get_states_no_attributes | Avoid selecting attributes in the history api when `no_attributes` is passed (#68352) | https://github.com/home-assistant/core.git | def test_get_states_no_attributes(hass_recorder):
hass = hass_recorder()
now, future, states = _setup_get_states(hass)
for state in states:
state.attributes = {}
# Get states returns everything before POINT for all entities
for state1, state2 in zip(
states,
sorted(
history.get_states(hass, future, no_attributes=True),
key=lambda state: state.entity_id,
),
):
assert state1 == state2
# Get states returns everything before POINT for tested entities
entities = [f"test.point_in_time_{i % 5}" for i in range(5)]
for state1, state2 in zip(
states,
sorted(
history.get_states(hass, future, entities, no_attributes=True),
key=lambda state: state.entity_id,
),
):
assert state1 == state2
# Test get_state here because we have a DB setup
assert states[0] == history.get_state(
hass, future, states[0].entity_id, no_attributes=True
)
time_before_recorder_ran = now - timedelta(days=1000)
assert history.get_states(hass, time_before_recorder_ran, no_attributes=True) == []
assert (
history.get_state(hass, time_before_recorder_ran, "demo.id", no_attributes=True)
is None
)
@pytest.mark.parametrize(
"attributes, no_attributes, limit",
[
({"attr": True}, False, 5000),
({}, True, 5000),
({"attr": True}, False, 3),
({}, True, 3),
],
) | @pytest.mark.parametrize(
"attributes, no_attributes, limit",
[
({"attr": True}, False, 5000),
({}, True, 5000),
({"attr": True}, False, 3),
({}, True, 3),
],
) | 199 | test_history.py | Python | tests/components/recorder/test_history.py | 816695cc96c19110ccda10431d92160ea6064d32 | core | 5 |
68,683 | 39 | 20 | 25 | 235 | 25 | 0 | 51 | 31 | _generate_dependants_map | style: Update docstrings and fix/add type hints + Collapsible progress section in Log | https://github.com/frappe/erpnext.git | def _generate_dependants_map() -> defaultdict:
bom = frappe.qb.DocType("BOM")
bom_item = frappe.qb.DocType("BOM Item")
bom_parents = (
frappe.qb.from_(bom_item)
.join(bom)
.on(bom_item.parent == bom.name)
.select(bom_item.bom_no, bom_item.parent)
.where(
(bom_item.bom_no.isnotnull())
& (bom_item.bom_no != "")
& (bom.docstatus == 1)
& (bom.is_active == 1)
& (bom_item.parenttype == "BOM")
)
).run(as_dict=True)
child_parent_map = defaultdict(list)
for bom in bom_parents:
child_parent_map[bom.bom_no].append(bom.parent)
return child_parent_map
| 144 | bom_updation_utils.py | Python | erpnext/manufacturing/doctype/bom_update_log/bom_updation_utils.py | 9f5f18e94da4254255a32d792abc94407ca5fde0 | erpnext | 2 |
|
133,165 | 37 | 12 | 12 | 83 | 10 | 0 | 39 | 126 | register_ray | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | https://github.com/ray-project/ray.git | def register_ray():
try:
from ray.util.joblib.ray_backend import RayBackend
register_parallel_backend("ray", RayBackend)
except ImportError:
msg = (
"To use the ray backend you must install ray."
"Try running 'pip install ray'."
"See https://docs.ray.io/en/master/installation.html"
"for more information."
)
raise ImportError(msg)
__all__ = ["register_ray"]
| 39 | __init__.py | Python | python/ray/util/joblib/__init__.py | 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | ray | 2 |
|
246,874 | 16 | 11 | 8 | 80 | 13 | 0 | 16 | 88 | test_aggregation_must_be_annotation | Replace assertEquals and friends with non-deprecated versions. (#12092) | https://github.com/matrix-org/synapse.git | def test_aggregation_must_be_annotation(self):
channel = self.make_request(
"GET",
"/_matrix/client/unstable/rooms/%s/aggregations/%s/%s?limit=1"
% (self.room, self.parent_id, RelationTypes.REPLACE),
access_token=self.user_token,
)
self.assertEqual(400, channel.code, channel.json_body)
| 51 | test_relations.py | Python | tests/rest/client/test_relations.py | 02d708568b476f2f7716000b35c0adfa4cbd31b3 | synapse | 1 |
|
43,465 | 11 | 10 | 4 | 59 | 12 | 0 | 12 | 40 | test_get_service_bus_message_conn | Implement Azure Service Bus Queue Operators (#24038)
Implemented Azure Service Bus Queue based Operator's to create queue, send message to the queue and receive message(list of message or batch message) and delete queue in azure service
- Added `AzureServiceBusCreateQueueOperator`
- Added `AzureServiceBusSendMessageOperator`
- Added `AzureServiceBusReceiveMessageOperator`
- Added `AzureServiceBusDeleteQueueOperator`
- Added Example DAG
- Added Documentation
- Added hooks and connection type in - provider yaml file
- Added unit Test case, doc strings | https://github.com/apache/airflow.git | def test_get_service_bus_message_conn(self, mock_connection):
mock_connection.return_value = self.conn
hook = MessageHook(azure_service_bus_conn_id=self.conn_id)
assert isinstance(hook.get_conn(), ServiceBusClient)
| 36 | test_asb.py | Python | tests/providers/microsoft/azure/hooks/test_asb.py | 09f38ad3f6872bae5059a1de226362eb358c4a7a | airflow | 1 |
|
299,440 | 11 | 10 | 7 | 46 | 7 | 0 | 12 | 66 | available | Fix Sonos races related to grouping and startup (#71026) | https://github.com/home-assistant/core.git | def available(self) -> bool:
return (
self.speaker.available
and self.speaker.sonos_group_entities
and self.media.playback_status
)
| 28 | media_player.py | Python | homeassistant/components/sonos/media_player.py | 1f1932d224f26ec8b80fa41bea3cf127a97ca7fb | core | 3 |
|
176,253 | 66 | 25 | 39 | 413 | 23 | 1 | 126 | 783 | strongly_connected_components | Fixing Tarjan's strongly connected components algorithm implementation to have O(|E|+|V|) time complexity instead of O(|V|^3). (#5288)
Prevent unnecessary traversal of edges multiple times | https://github.com/networkx/networkx.git | def strongly_connected_components(G):
preorder = {}
lowlink = {}
scc_found = set()
scc_queue = []
i = 0 # Preorder counter
neighbors = {v: iter(G[v]) for v in G}
for source in G:
if source not in scc_found:
queue = [source]
while queue:
v = queue[-1]
if v not in preorder:
i = i + 1
preorder[v] = i
done = True
for w in neighbors[v]:
if w not in preorder:
queue.append(w)
done = False
break
if done:
lowlink[v] = preorder[v]
for w in G[v]:
if w not in scc_found:
if preorder[w] > preorder[v]:
lowlink[v] = min([lowlink[v], lowlink[w]])
else:
lowlink[v] = min([lowlink[v], preorder[w]])
queue.pop()
if lowlink[v] == preorder[v]:
scc = {v}
while scc_queue and preorder[scc_queue[-1]] > preorder[v]:
k = scc_queue.pop()
scc.add(k)
scc_found.update(scc)
yield scc
else:
scc_queue.append(v)
@not_implemented_for("undirected") | @not_implemented_for("undirected") | 257 | strongly_connected.py | Python | networkx/algorithms/components/strongly_connected.py | 77c49c16e10693dbe566d20601b28dd2b1e8df03 | networkx | 15 |
189,028 | 50 | 18 | 14 | 232 | 24 | 0 | 72 | 140 | disk_io_counters | Use a generator to avoid a needless list allocation (#1567) | https://github.com/giampaolo/psutil.git | def disk_io_counters(perdisk=False, nowrap=True):
kwargs = dict(perdisk=perdisk) if LINUX else {}
rawdict = _psplatform.disk_io_counters(**kwargs)
if not rawdict:
return {} if perdisk else None
if nowrap:
rawdict = _wrap_numbers(rawdict, 'psutil.disk_io_counters')
nt = getattr(_psplatform, "sdiskio", _common.sdiskio)
if perdisk:
for disk, fields in rawdict.items():
rawdict[disk] = nt(*fields)
return rawdict
else:
return nt(*(sum(x) for x in zip(*rawdict.values())))
disk_io_counters.cache_clear = functools.partial(
_wrap_numbers.cache_clear, 'psutil.disk_io_counters')
disk_io_counters.cache_clear.__doc__ = "Clears nowrap argument cache"
# =====================================================================
# --- network related functions
# =====================================================================
| 119 | __init__.py | Python | psutil/__init__.py | 83bb5f8cdcbe10fadf64e62e61d011afe73b6a27 | psutil | 8 |
|
292,401 | 36 | 12 | 13 | 192 | 24 | 0 | 43 | 150 | post | Only set require_restart on config entry reload if its not recoverable (#66994) | https://github.com/home-assistant/core.git | async def post(self, request, entry_id):
if not request["hass_user"].is_admin:
raise Unauthorized(config_entry_id=entry_id, permission="remove")
hass = request.app["hass"]
entry = hass.config_entries.async_get_entry(entry_id)
if not entry:
return self.json_message("Invalid entry specified", HTTPStatus.NOT_FOUND)
assert isinstance(entry, config_entries.ConfigEntry)
try:
await hass.config_entries.async_reload(entry_id)
except config_entries.OperationNotAllowed:
return self.json_message("Entry cannot be reloaded", HTTPStatus.FORBIDDEN)
return self.json({"require_restart": not entry.state.recoverable})
| 115 | config_entries.py | Python | homeassistant/components/config/config_entries.py | 9a5eec561a18cd0bffbbd65afe68f70c0893d28c | core | 4 |
|
132,696 | 20 | 8 | 29 | 41 | 6 | 0 | 21 | 49 | testPlacementGroupRequests | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | https://github.com/ray-project/ray.git | def testPlacementGroupRequests(self, reuse_actors=False, scheduled=10):
# Since we check per-step placement groups, set the reconcilation
# interval to 0
os.environ["TUNE_PLACEMENT_GROUP_RECON_INTERVAL"] = "0"
| 181 | test_trial_runner_pg.py | Python | python/ray/tune/tests/test_trial_runner_pg.py | 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | ray | 2 |
|
269,303 | 8 | 8 | 2 | 57 | 9 | 1 | 8 | 12 | gelu | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | https://github.com/keras-team/keras.git | def gelu(x, approximate=False):
return tf.nn.gelu(x, approximate)
@keras_export("keras.activations.tanh")
@tf.__internal__.dispatch.add_dispatch_support | @keras_export("keras.activations.tanh")
@tf.__internal__.dispatch.add_dispatch_support | 21 | activations.py | Python | keras/activations.py | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | 1 |
199,700 | 13 | 8 | 13 | 47 | 7 | 0 | 13 | 18 | legendre_poly | Run orthopolys and appellseqs through a common interface
Including unifying the two Chebyshev generators into one function.
There are also two kinds of Hermite polynomials, and they too share the
same recurrence, but the second type He_n(x) (aka the probabilist,
reduced or small polynomials) will not be added here. | https://github.com/sympy/sympy.git | def legendre_poly(n, x=None, polys=False):
r
return named_poly(n, dup_legendre, QQ, "Legendre polynomial", (x,), polys)
| 33 | orthopolys.py | Python | sympy/polys/orthopolys.py | d1d46df73ebaad94089847558d00a8b7269f554d | sympy | 1 |
|
19,147 | 7 | 6 | 5 | 28 | 6 | 0 | 7 | 21 | metrics | Improve evaluation api (#5256)
* init
Signed-off-by: Weichen Xu <[email protected]>
* update
Signed-off-by: Weichen Xu <[email protected]>
* update
Signed-off-by: Weichen Xu <[email protected]>
* update doc
Signed-off-by: Weichen Xu <[email protected]>
* update doc
Signed-off-by: Weichen Xu <[email protected]>
* address comments
Signed-off-by: Weichen Xu <[email protected]>
* update doc
Signed-off-by: Weichen Xu <[email protected]>
* add shap limitation on value type
Signed-off-by: Weichen Xu <[email protected]>
* fix format
Signed-off-by: Weichen Xu <[email protected]>
* update
Signed-off-by: Weichen Xu <[email protected]>
* update
Signed-off-by: Weichen Xu <[email protected]>
* update
Signed-off-by: Weichen Xu <[email protected]>
* update
Signed-off-by: Weichen Xu <[email protected]>
* update
Signed-off-by: Weichen Xu <[email protected]> | https://github.com/mlflow/mlflow.git | def metrics(self) -> Dict[str, Any]:
return self._metrics
| 17 | base.py | Python | mlflow/models/evaluation/base.py | 4c58179509e6f6047789efb0a95c2b0e20cb6c8f | mlflow | 1 |
|
260,150 | 112 | 16 | 55 | 646 | 25 | 0 | 400 | 1,068 | _generate_invalid_param_val_interval | FIX Param validation: fix generating invalid param when 2 interval constraints (#23513)
Co-authored-by: Julien Jerphanion <[email protected]>
Co-authored-by: Guillaume Lemaitre <[email protected]> | https://github.com/scikit-learn/scikit-learn.git | def _generate_invalid_param_val_interval(interval, constraints):
if interval.type is Real:
# generate a non-integer value such that it can't be valid even if there's also
# an integer interval constraint.
if interval.left is None and interval.right is None:
if interval.closed in ("left", "neither"):
return np.inf
elif interval.closed in ("right", "neither"):
return -np.inf
else:
raise NotImplementedError
if interval.left is not None:
return np.floor(interval.left) - 0.5
else: # right is not None
return np.ceil(interval.right) + 0.5
else: # interval.type is Integral
if interval.left is None and interval.right is None:
raise NotImplementedError
# We need to check if there's also a real interval constraint to generate a
# value that is not valid for any of the 2 interval constraints.
real_intervals = [
i for i in constraints if isinstance(i, Interval) and i.type is Real
]
real_interval = real_intervals[0] if real_intervals else None
if real_interval is None:
# Only the integer interval constraint -> easy
if interval.left is not None:
return interval.left - 1
else: # interval.right is not None
return interval.right + 1
# There's also a real interval constraint. Try to find a value left to both or
# right to both or in between them.
# redefine left and right bounds to be smallest and largest valid integers in
# both intervals.
int_left = interval.left
if int_left is not None and interval.closed in ("right", "neither"):
int_left = int_left + 1
int_right = interval.right
if int_right is not None and interval.closed in ("left", "neither"):
int_right = int_right - 1
real_left = real_interval.left
if real_interval.left is not None:
real_left = int(np.ceil(real_interval.left))
if real_interval.closed in ("right", "neither"):
real_left = real_left + 1
real_right = real_interval.right
if real_interval.right is not None:
real_right = int(np.floor(real_interval.right))
if real_interval.closed in ("left", "neither"):
real_right = real_right - 1
if int_left is not None and real_left is not None:
# there exists an int left to both intervals
return min(int_left, real_left) - 1
if int_right is not None and real_right is not None:
# there exists an int right to both intervals
return max(int_right, real_right) + 1
if int_left is not None:
if real_right is not None and int_left - real_right >= 2:
# there exists an int between the 2 intervals
return int_left - 1
else:
raise NotImplementedError
else: # int_right is not None
if real_left is not None and real_left - int_right >= 2:
# there exists an int between the 2 intervals
return int_right + 1
else:
raise NotImplementedError
| 399 | _param_validation.py | Python | sklearn/utils/_param_validation.py | 02cbe01e67165d7d38e5e441cfccd6b57b2207b6 | scikit-learn | 32 |
|
289,375 | 18 | 10 | 5 | 75 | 11 | 0 | 21 | 36 | test_fetch_period_api_with_no_timestamp | Ensure recorder test fixture is setup before hass fixture (#80528)
* Ensure recorder test fixture is setup before hass fixture
* Adjust more tests | https://github.com/home-assistant/core.git | async def test_fetch_period_api_with_no_timestamp(recorder_mock, hass, hass_client):
await async_setup_component(hass, "history", {})
client = await hass_client()
response = await client.get("/api/history/period")
assert response.status == HTTPStatus.OK
| 43 | test_init.py | Python | tests/components/history/test_init.py | 31a787558fd312331b55e5c2c4b33341fc3601fc | core | 1 |
|
172,886 | 64 | 17 | 39 | 567 | 40 | 0 | 103 | 331 | search_query | Refactored load read status for web access and opds access
Refactored and removed discover html page
Bugfix show author
Bugfix open dialog in author page
Fix for #2341 (advanced search with linked read column and read column having a higher number than number of available custom columns) | https://github.com/janeczku/calibre-web.git | def search_query(self, term, config_read_column, *join):
term.strip().lower()
self.session.connection().connection.connection.create_function("lower", 1, lcase)
q = list()
authorterms = re.split("[, ]+", term)
for authorterm in authorterms:
q.append(Books.authors.any(func.lower(Authors.name).ilike("%" + authorterm + "%")))
query = self.generate_linked_query(config_read_column, Books)
if len(join) == 6:
query = query.outerjoin(join[0], join[1]).outerjoin(join[2]).outerjoin(join[3], join[4]).outerjoin(join[5])
if len(join) == 3:
query = query.outerjoin(join[0], join[1]).outerjoin(join[2])
elif len(join) == 2:
query = query.outerjoin(join[0], join[1])
elif len(join) == 1:
query = query.outerjoin(join[0])
return query.filter(self.common_filters(True)).filter(
or_(Books.tags.any(func.lower(Tags.name).ilike("%" + term + "%")),
Books.series.any(func.lower(Series.name).ilike("%" + term + "%")),
Books.authors.any(and_(*q)),
Books.publishers.any(func.lower(Publishers.name).ilike("%" + term + "%")),
func.lower(Books.title).ilike("%" + term + "%")
))
# read search results from calibre-database and return it (function is used for feed and simple search | 353 | db.py | Python | cps/db.py | 32a3c45ee0f7e13bd61075f32a4dcebc415585a1 | calibre-web | 6 |
|
292,764 | 22 | 11 | 13 | 149 | 11 | 0 | 45 | 196 | async_attribute_updated | Presets for single ZONNSMART TRV (#67157)
* Presets for single ZONNSMART TRV
* added zonnsmart climate tests
* black8 fix | https://github.com/home-assistant/core.git | async def async_attribute_updated(self, record):
if record.attr_name == "operation_preset":
if record.value == 0:
self._preset = PRESET_SCHEDULE
if record.value == 1:
self._preset = PRESET_NONE
if record.value == 2:
self._preset = self.PRESET_HOLIDAY
if record.value == 3:
self._preset = self.PRESET_HOLIDAY
if record.value == 4:
self._preset = self.PRESET_FROST
await super().async_attribute_updated(record)
| 90 | climate.py | Python | homeassistant/components/zha/climate.py | cbdfff25ca510a5d7dff9a1cb39ce2da8afc7d65 | core | 7 |
|
22,658 | 25 | 11 | 7 | 76 | 8 | 0 | 26 | 62 | axpy | refactor: clean code
Signed-off-by: slowy07 <[email protected]> | https://github.com/geekcomputers/Python.git | def axpy(scalar, x, y):
# precondition
assert (
isinstance(x, Vector)
and (isinstance(y, Vector))
and (isinstance(scalar, int) or isinstance(scalar, float))
)
return x * scalar + y
| 50 | lib.py | Python | linear-algebra-python/src/lib.py | f0af0c43340763724f139fa68aa1e5a9ffe458b4 | Python | 4 |
|
22,718 | 34 | 15 | 17 | 207 | 21 | 0 | 45 | 133 | search_button | refactor: clean code
Signed-off-by: slowy07 <[email protected]> | https://github.com/geekcomputers/Python.git | def search_button(p1):
global cursor
global results
global index
w.errorOutput.configure(text="")
sql_command =
sql_command = sql_command.format(w.inputSearchTitle.get())
try:
cursor.execute(sql_command)
results = cursor.fetchall()
w.errorOutput.configure(text=str(len(results)) + " results")
index = 0
if index >= 0 and index < len(results):
w.outputNotice.delete(1.0, END)
w.outputNotice.insert(1.0, results[index][2])
except:
w.errorOutput.configure(text="Please create at first a database.")
| 128 | notepad_support.py | Python | notepad/notepad_support.py | f0af0c43340763724f139fa68aa1e5a9ffe458b4 | Python | 4 |
|
258,457 | 105 | 16 | 33 | 473 | 46 | 0 | 147 | 333 | silhouette_samples | FIX Support integers in silhouette_score for precomputed distances (#22108)
Co-authored-by: Guillaume Lemaitre <[email protected]> | https://github.com/scikit-learn/scikit-learn.git | def silhouette_samples(X, labels, *, metric="euclidean", **kwds):
X, labels = check_X_y(X, labels, accept_sparse=["csc", "csr"])
# Check for non-zero diagonal entries in precomputed distance matrix
if metric == "precomputed":
error_msg = ValueError(
"The precomputed distance matrix contains non-zero "
"elements on the diagonal. Use np.fill_diagonal(X, 0)."
)
if X.dtype.kind == "f":
atol = np.finfo(X.dtype).eps * 100
if np.any(np.abs(np.diagonal(X)) > atol):
raise ValueError(error_msg)
elif np.any(np.diagonal(X) != 0): # integral dtype
raise ValueError(error_msg)
le = LabelEncoder()
labels = le.fit_transform(labels)
n_samples = len(labels)
label_freqs = np.bincount(labels)
check_number_of_labels(len(le.classes_), n_samples)
kwds["metric"] = metric
reduce_func = functools.partial(
_silhouette_reduce, labels=labels, label_freqs=label_freqs
)
results = zip(*pairwise_distances_chunked(X, reduce_func=reduce_func, **kwds))
intra_clust_dists, inter_clust_dists = results
intra_clust_dists = np.concatenate(intra_clust_dists)
inter_clust_dists = np.concatenate(inter_clust_dists)
denom = (label_freqs - 1).take(labels, mode="clip")
with np.errstate(divide="ignore", invalid="ignore"):
intra_clust_dists /= denom
sil_samples = inter_clust_dists - intra_clust_dists
with np.errstate(divide="ignore", invalid="ignore"):
sil_samples /= np.maximum(intra_clust_dists, inter_clust_dists)
# nan values are for clusters of size 1, and should be 0
return np.nan_to_num(sil_samples)
| 284 | _unsupervised.py | Python | sklearn/metrics/cluster/_unsupervised.py | e4015289e0eeb390190ce0d051cee756bc5ecb33 | scikit-learn | 5 |
|
20,452 | 31 | 13 | 10 | 123 | 14 | 0 | 42 | 116 | get_lexer_for_mimetype | 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 | https://github.com/pypa/pipenv.git | def get_lexer_for_mimetype(_mime, **options):
for modname, name, _, _, mimetypes in LEXERS.values():
if _mime in mimetypes:
if name not in _lexer_cache:
_load_lexers(modname)
return _lexer_cache[name](**options)
for cls in find_plugin_lexers():
if _mime in cls.mimetypes:
return cls(**options)
raise ClassNotFound('no lexer for mimetype %r found' % _mime)
| 77 | __init__.py | Python | pipenv/patched/notpip/_vendor/pygments/lexers/__init__.py | f3166e673fe8d40277b804d35d77dcdb760fc3b3 | pipenv | 6 |
|
118,503 | 85 | 13 | 72 | 634 | 25 | 0 | 208 | 583 | test_complex_joins | join multiple tables
https://github.com/mindsdb/mindsdb_sql/issues/246 | https://github.com/mindsdb/mindsdb.git | def test_complex_joins(self, data_handler):
df1 = pd.DataFrame([
{'a': 1, 'c': 1, 'b': dt.datetime(2020, 1, 1)},
{'a': 2, 'c': 1, 'b': dt.datetime(2020, 1, 2)},
{'a': 1, 'c': 3, 'b': dt.datetime(2020, 1, 3)},
{'a': 3, 'c': 2, 'b': dt.datetime(2020, 1, 2)},
])
df2 = pd.DataFrame([
{'a': 6, 'c': 1},
{'a': 4, 'c': 2},
{'a': 2, 'c': 3},
])
self.set_handler(data_handler, name='pg', tables={'tbl1': df1, 'tbl2': df2})
self.run_sql(
)
self.run_sql()
# --- test join table-table-table ---
ret = self.run_sql()
# must be 2 rows
assert len(ret) == 2
# all t1.a values are 1
assert list(ret.t1a) == [1, 1]
# t3.a has 2 and None
assert len(ret[ret.t3a == 2]) == 1
assert len(ret[ret.t3a.isna()]) == 1
# --- test join table-predictor-view ---
ret = self.run_sql()
# must be 2 rows
assert len(ret) == 2
# t1.a > 1
assert ret[ret.t1a <= 1].empty
# view: a!=4
assert ret[ret.t3a == 4].empty
# t3.a has 6 and None
assert len(ret[ret.t3a == 6]) == 1
assert len(ret[ret.t3a.isna()]) == 1
# contents predicted values
assert list(ret.predicted.unique()) == [42]
# --- tests table-subselect-view ---
ret = self.run_sql()
# 1 row
assert len(ret) == 1
# check row values
row = ret.iloc[0].to_dict()
assert row['t1a'] == 2
assert row['t2t3a'] == 2
assert row['t2t1a'] == 1
assert row['t3c'] == 1
assert row['t3a'] == 6
| 383 | test_project_structure.py | Python | tests/unit/test_project_structure.py | 602d5dfea04d73c5c8d4f9d43a6e3deb8a945f18 | mindsdb | 1 |
|
267,759 | 30 | 12 | 12 | 124 | 17 | 0 | 35 | 92 | get_ci_provider | ansible-test - Use more native type hints. (#78435)
* ansible-test - Use more native type hints.
Simple search and replace to switch from comments to native type hints for return types of functions with no arguments.
* ansible-test - Use more native type hints.
Conversion of simple single-line function annotation type comments to native type hints.
* ansible-test - Use more native type hints.
Conversion of single-line function annotation type comments with default values to native type hints.
* ansible-test - Use more native type hints.
Manual conversion of type annotation comments for functions which have pylint directives. | https://github.com/ansible/ansible.git | def get_ci_provider() -> CIProvider:
provider = None
import_plugins('ci')
candidates = sorted(get_subclasses(CIProvider), key=lambda c: (c.priority, c.__name__))
for candidate in candidates:
if candidate.is_supported():
provider = candidate()
break
if provider.code:
display.info('Detected CI provider: %s' % provider.name)
return provider
| 73 | __init__.py | Python | test/lib/ansible_test/_internal/ci/__init__.py | 3eb0485dd92c88cc92152d3656d94492db44b183 | ansible | 4 |
|
276,450 | 48 | 12 | 22 | 282 | 43 | 0 | 61 | 257 | testWithEmbeddings | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | https://github.com/keras-team/keras.git | def testWithEmbeddings(self):
state_input = keras.layers.Input(
shape=(1,), name="state_input", dtype="int32"
)
output = keras.layers.Embedding(
output_dim=16, input_dim=100, input_length=1, name="state"
)(state_input)
model = keras.models.Model(inputs=[state_input], outputs=[output])
model.compile(
loss={"state": "sparse_categorical_crossentropy"}, optimizer="adam"
)
# Freeze the graph.
sess = keras.backend.get_session()
variable_graph_def = sess.graph_def
output_tensor = self._get_tensor_names(model.outputs)
constant_graph_def = (
tf.compat.v1.graph_util.convert_variables_to_constants(
sess, variable_graph_def, output_tensor
)
)
# Validate converted graph.
input_data = np.array(np.random.random_sample([1, 1]), dtype=np.int32)
self._ensure_no_variables_in_graph(constant_graph_def)
self._test_converted_keras_model(model, constant_graph_def, input_data)
| 177 | graph_util_test.py | Python | keras/tests/graph_util_test.py | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | 1 |
|
19,671 | 48 | 12 | 21 | 212 | 28 | 0 | 61 | 255 | sys_path | Issue 4993 Add standard pre commit hooks and apply linting. (#4994)
* Add .pre-commit-config.yaml to the project and exclude tests (for now). This does not include the MyPy linting that pip does but does include everything else. | https://github.com/pypa/pipenv.git | def sys_path(self):
# type: () -> List[str]
from .vendor.vistir.compat import JSONDecodeError
current_executable = Path(sys.executable).as_posix()
if not self.python or self.python == current_executable:
return sys.path
elif any([sys.prefix == self.prefix, not self.is_venv]):
return sys.path
cmd_args = [self.python, "-c", "import json, sys; print(json.dumps(sys.path))"]
path, _ = vistir.misc.run(
cmd_args,
return_object=False,
nospin=True,
block=True,
combine_stderr=False,
write_to_stdout=False,
)
try:
path = json.loads(path.strip())
except JSONDecodeError:
path = sys.path
return path
| 134 | environment.py | Python | pipenv/environment.py | 9a3b3ce70621af6f9adaa9eeac9cf83fa149319c | pipenv | 5 |
|
250,139 | 138 | 17 | 121 | 991 | 49 | 0 | 275 | 1,863 | test_out_of_order_events | Require types in tests.storage. (#14646)
Adds missing type hints to `tests.storage` package
and does not allow untyped definitions. | https://github.com/matrix-org/synapse.git | def test_out_of_order_events(self) -> None:
event_factory = self.hs.get_event_builder_factory()
bob = "@creator:test"
alice = "@alice:test"
room_id = "!room:test"
# Ensure that we have a rooms entry so that we generate the chain index.
self.get_success(
self.store.store_room(
room_id=room_id,
room_creator_user_id="",
is_public=True,
room_version=RoomVersions.V6,
)
)
# First persist the base room.
create = self.get_success(
event_factory.for_room_version(
RoomVersions.V6,
{
"type": EventTypes.Create,
"state_key": "",
"sender": bob,
"room_id": room_id,
"content": {"tag": "create"},
},
).build(prev_event_ids=[], auth_event_ids=[])
)
bob_join = self.get_success(
event_factory.for_room_version(
RoomVersions.V6,
{
"type": EventTypes.Member,
"state_key": bob,
"sender": bob,
"room_id": room_id,
"content": {"tag": "bob_join"},
},
).build(prev_event_ids=[], auth_event_ids=[create.event_id])
)
power = self.get_success(
event_factory.for_room_version(
RoomVersions.V6,
{
"type": EventTypes.PowerLevels,
"state_key": "",
"sender": bob,
"room_id": room_id,
"content": {"tag": "power"},
},
).build(
prev_event_ids=[],
auth_event_ids=[create.event_id, bob_join.event_id],
)
)
self.persist([create, bob_join, power])
# Now persist an invite and a couple of memberships out of order.
alice_invite = self.get_success(
event_factory.for_room_version(
RoomVersions.V6,
{
"type": EventTypes.Member,
"state_key": alice,
"sender": bob,
"room_id": room_id,
"content": {"tag": "alice_invite"},
},
).build(
prev_event_ids=[],
auth_event_ids=[create.event_id, bob_join.event_id, power.event_id],
)
)
alice_join = self.get_success(
event_factory.for_room_version(
RoomVersions.V6,
{
"type": EventTypes.Member,
"state_key": alice,
"sender": alice,
"room_id": room_id,
"content": {"tag": "alice_join"},
},
).build(
prev_event_ids=[],
auth_event_ids=[create.event_id, alice_invite.event_id, power.event_id],
)
)
alice_join2 = self.get_success(
event_factory.for_room_version(
RoomVersions.V6,
{
"type": EventTypes.Member,
"state_key": alice,
"sender": alice,
"room_id": room_id,
"content": {"tag": "alice_join2"},
},
).build(
prev_event_ids=[],
auth_event_ids=[create.event_id, alice_join.event_id, power.event_id],
)
)
self.persist([alice_join])
self.persist([alice_join2])
self.persist([alice_invite])
# The end result should be sane.
events = [create, bob_join, power, alice_invite, alice_join]
chain_map, link_map = self.fetch_chains(events)
expected_links = [
(bob_join, create),
(power, create),
(power, bob_join),
(alice_invite, create),
(alice_invite, power),
(alice_invite, bob_join),
]
# Check that the expected links and only the expected links have been
# added.
self.assertEqual(len(expected_links), len(list(link_map.get_additions())))
for start, end in expected_links:
start_id, start_seq = chain_map[start.event_id]
end_id, end_seq = chain_map[end.event_id]
self.assertIn(
(start_seq, end_seq), list(link_map.get_links_between(start_id, end_id))
)
| 620 | test_event_chain.py | Python | tests/storage/test_event_chain.py | 3ac412b4e2f8c5ba11dc962b8a9d871c1efdce9b | synapse | 2 |
|
246,112 | 26 | 11 | 14 | 180 | 17 | 0 | 27 | 130 | test_limit_and_from | Add admin API to get a list of federated rooms (#11658) | https://github.com/matrix-org/synapse.git | def test_limit_and_from(self) -> None:
number_destinations = 20
self._create_destinations(number_destinations)
channel = self.make_request(
"GET",
self.url + "?from=5&limit=10",
access_token=self.admin_user_tok,
)
self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body)
self.assertEqual(channel.json_body["total"], number_destinations)
self.assertEqual(channel.json_body["next_token"], "15")
self.assertEqual(len(channel.json_body["destinations"]), 10)
self._check_fields(channel.json_body["destinations"])
| 109 | test_federation.py | Python | tests/rest/admin/test_federation.py | 6a72c910f180ee8b4bd78223775af48492769472 | synapse | 1 |
|
167,802 | 68 | 11 | 42 | 290 | 27 | 0 | 96 | 195 | cartesian_product | TYP: more return annotations in core/ (#47618)
* TYP: more return annotations in core/
* from __future__ import annotations
* more __future__ | https://github.com/pandas-dev/pandas.git | def cartesian_product(X) -> list[np.ndarray]:
msg = "Input must be a list-like of list-likes"
if not is_list_like(X):
raise TypeError(msg)
for x in X:
if not is_list_like(x):
raise TypeError(msg)
if len(X) == 0:
return []
lenX = np.fromiter((len(x) for x in X), dtype=np.intp)
cumprodX = np.cumproduct(lenX)
if np.any(cumprodX < 0):
raise ValueError("Product space too large to allocate arrays!")
a = np.roll(cumprodX, 1)
a[0] = 1
if cumprodX[-1] != 0:
b = cumprodX[-1] / cumprodX
else:
# if any factor is empty, the cartesian product is empty
b = np.zeros_like(cumprodX)
return [tile_compat(np.repeat(x, b[i]), np.product(a[i])) for i, x in enumerate(X)]
| 182 | util.py | Python | pandas/core/reshape/util.py | f65417656ba8c59438d832b6e2a431f78d40c21c | pandas | 9 |
|
273,407 | 6 | 8 | 2 | 38 | 5 | 0 | 6 | 20 | set_vocabulary | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | https://github.com/keras-team/keras.git | def set_vocabulary(self, vocabulary, idf_weights=None):
self._lookup_layer.set_vocabulary(vocabulary, idf_weights=idf_weights)
| 24 | text_vectorization.py | Python | keras/layers/preprocessing/text_vectorization.py | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | 1 |
|
189,932 | 30 | 15 | 14 | 170 | 16 | 0 | 37 | 111 | select_resolution | Moved functionality over from `manim new` to `manim init` and added deprecation warning for `manim new` (#2842)
* moved functionality over from manim new to manim init and deprecated manim new
* Updated tests to fit new functionality
* added a test for project creation using manim init project
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
Co-authored-by: Benjamin Hackl <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> | https://github.com/ManimCommunity/manim.git | def select_resolution():
resolution_options = []
for quality in QUALITIES.items():
resolution_options.append(
(quality[1]["pixel_height"], quality[1]["pixel_width"]),
)
resolution_options.pop()
choice = click.prompt(
"\nSelect resolution:\n",
type=click.Choice([f"{i[0]}p" for i in resolution_options]),
show_default=False,
default="480p",
)
return [res for res in resolution_options if f"{res[0]}p" == choice][0]
| 95 | commands.py | Python | manim/cli/init/commands.py | 9b731037d9f2c9e647737c9ca44f1a968675feb6 | manim | 5 |
|
12,699 | 8 | 9 | 6 | 33 | 7 | 0 | 8 | 22 | is_decompressed_with_data | feat: allow to access parameters of data request wo loading data (#4991) | https://github.com/jina-ai/jina.git | def is_decompressed_with_data(self) -> bool:
return type(self._pb_body) is jina_pb2.DataRequestProto
| 19 | data.py | Python | jina/types/request/data.py | c3849c6fee4a65a77a82b2cfda9670d727ff0f53 | jina | 1 |
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