Search is not available for this dataset
identifier stringlengths 1 155 | parameters stringlengths 2 6.09k | docstring stringlengths 11 63.4k | docstring_summary stringlengths 0 63.4k | function stringlengths 29 99.8k | function_tokens list | start_point list | end_point list | language stringclasses 1
value | docstring_language stringlengths 2 7 | docstring_language_predictions stringlengths 18 23 | is_langid_reliable stringclasses 2
values |
|---|---|---|---|---|---|---|---|---|---|---|---|
Font.size | (self) |
The 'size' property is a number and may be specified as:
- An int or float in the interval [1, inf]
- A tuple, list, or one-dimensional numpy array of the above
Returns
-------
int|float|numpy.ndarray
|
The 'size' property is a number and may be specified as:
- An int or float in the interval [1, inf]
- A tuple, list, or one-dimensional numpy array of the above | def size(self):
"""
The 'size' property is a number and may be specified as:
- An int or float in the interval [1, inf]
- A tuple, list, or one-dimensional numpy array of the above
Returns
-------
int|float|numpy.ndarray
"""
return self["size"... | [
"def",
"size",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"size\"",
"]"
] | [
145,
4
] | [
155,
27
] | python | en | ['en', 'error', 'th'] | False |
Font.sizesrc | (self) |
Sets the source reference on Chart Studio Cloud for size .
The 'sizesrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
|
Sets the source reference on Chart Studio Cloud for size .
The 'sizesrc' property must be specified as a string or
as a plotly.grid_objs.Column object | def sizesrc(self):
"""
Sets the source reference on Chart Studio Cloud for size .
The 'sizesrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["sizesrc"] | [
"def",
"sizesrc",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"sizesrc\"",
"]"
] | [
164,
4
] | [
175,
30
] | python | en | ['en', 'error', 'th'] | False |
Font.__init__ | (
self,
arg=None,
color=None,
colorsrc=None,
family=None,
familysrc=None,
size=None,
sizesrc=None,
**kwargs
) |
Construct a new Font object
Sets the font used for `title`. Note that the title's font used
to be set by the now deprecated `titlefont` attribute.
Parameters
----------
arg
dict of properties compatible with this constructor or
an instan... |
Construct a new Font object
Sets the font used for `title`. Note that the title's font used
to be set by the now deprecated `titlefont` attribute. | def __init__(
self,
arg=None,
color=None,
colorsrc=None,
family=None,
familysrc=None,
size=None,
sizesrc=None,
**kwargs
):
"""
Construct a new Font object
Sets the font used for `title`. Note that the title's fo... | [
"def",
"__init__",
"(",
"self",
",",
"arg",
"=",
"None",
",",
"color",
"=",
"None",
",",
"colorsrc",
"=",
"None",
",",
"family",
"=",
"None",
",",
"familysrc",
"=",
"None",
",",
"size",
"=",
"None",
",",
"sizesrc",
"=",
"None",
",",
"*",
"*",
"kw... | [
215,
4
] | [
330,
34
] | python | en | ['en', 'error', 'th'] | False |
VerifyFileExists | (directory, relative_path) | Verifies that the given file exists; aborts on failure.
relative_path is the file path relative to the given directory.
| Verifies that the given file exists; aborts on failure. | def VerifyFileExists(directory, relative_path):
"""Verifies that the given file exists; aborts on failure.
relative_path is the file path relative to the given directory.
"""
if not os.path.isfile(os.path.join(directory, relative_path)):
print('ERROR: Cannot find %s in directory %s.' % (relative_path,
... | [
"def",
"VerifyFileExists",
"(",
"directory",
",",
"relative_path",
")",
":",
"if",
"not",
"os",
".",
"path",
".",
"isfile",
"(",
"os",
".",
"path",
".",
"join",
"(",
"directory",
",",
"relative_path",
")",
")",
":",
"print",
"(",
"'ERROR: Cannot find %s in... | [
88,
0
] | [
99,
15
] | python | en | ['en', 'en', 'en'] | True |
ValidateGTestRootDir | (gtest_root) | Makes sure gtest_root points to a valid gtest root directory.
The function aborts the program on failure.
| Makes sure gtest_root points to a valid gtest root directory. | def ValidateGTestRootDir(gtest_root):
"""Makes sure gtest_root points to a valid gtest root directory.
The function aborts the program on failure.
"""
VerifyFileExists(gtest_root, GTEST_H_SEED)
VerifyFileExists(gtest_root, GTEST_ALL_CC_SEED) | [
"def",
"ValidateGTestRootDir",
"(",
"gtest_root",
")",
":",
"VerifyFileExists",
"(",
"gtest_root",
",",
"GTEST_H_SEED",
")",
"VerifyFileExists",
"(",
"gtest_root",
",",
"GTEST_ALL_CC_SEED",
")"
] | [
102,
0
] | [
109,
49
] | python | en | ['en', 'en', 'en'] | True |
VerifyOutputFile | (output_dir, relative_path) | Verifies that the given output file path is valid.
relative_path is relative to the output_dir directory.
| Verifies that the given output file path is valid. | def VerifyOutputFile(output_dir, relative_path):
"""Verifies that the given output file path is valid.
relative_path is relative to the output_dir directory.
"""
# Makes sure the output file either doesn't exist or can be overwritten.
output_file = os.path.join(output_dir, relative_path)
if os.path.exists... | [
"def",
"VerifyOutputFile",
"(",
"output_dir",
",",
"relative_path",
")",
":",
"# Makes sure the output file either doesn't exist or can be overwritten.",
"output_file",
"=",
"os",
".",
"path",
".",
"join",
"(",
"output_dir",
",",
"relative_path",
")",
"if",
"os",
".",
... | [
112,
0
] | [
135,
33
] | python | en | ['en', 'en', 'en'] | True |
ValidateOutputDir | (output_dir) | Makes sure output_dir points to a valid output directory.
The function aborts the program on failure.
| Makes sure output_dir points to a valid output directory. | def ValidateOutputDir(output_dir):
"""Makes sure output_dir points to a valid output directory.
The function aborts the program on failure.
"""
VerifyOutputFile(output_dir, GTEST_H_OUTPUT)
VerifyOutputFile(output_dir, GTEST_ALL_CC_OUTPUT) | [
"def",
"ValidateOutputDir",
"(",
"output_dir",
")",
":",
"VerifyOutputFile",
"(",
"output_dir",
",",
"GTEST_H_OUTPUT",
")",
"VerifyOutputFile",
"(",
"output_dir",
",",
"GTEST_ALL_CC_OUTPUT",
")"
] | [
138,
0
] | [
145,
51
] | python | en | ['en', 'en', 'en'] | True |
FuseGTestH | (gtest_root, output_dir) | Scans folder gtest_root to generate gtest/gtest.h in output_dir. | Scans folder gtest_root to generate gtest/gtest.h in output_dir. | def FuseGTestH(gtest_root, output_dir):
"""Scans folder gtest_root to generate gtest/gtest.h in output_dir."""
output_file = open(os.path.join(output_dir, GTEST_H_OUTPUT), 'w')
processed_files = set() # Holds all gtest headers we've processed.
def ProcessFile(gtest_header_path):
"""Processes the given gt... | [
"def",
"FuseGTestH",
"(",
"gtest_root",
",",
"output_dir",
")",
":",
"output_file",
"=",
"open",
"(",
"os",
".",
"path",
".",
"join",
"(",
"output_dir",
",",
"GTEST_H_OUTPUT",
")",
",",
"'w'",
")",
"processed_files",
"=",
"set",
"(",
")",
"# Holds all gtes... | [
148,
0
] | [
174,
21
] | python | en | ['af', 'en', 'en'] | True |
FuseGTestAllCcToFile | (gtest_root, output_file) | Scans folder gtest_root to generate gtest/gtest-all.cc in output_file. | Scans folder gtest_root to generate gtest/gtest-all.cc in output_file. | def FuseGTestAllCcToFile(gtest_root, output_file):
"""Scans folder gtest_root to generate gtest/gtest-all.cc in output_file."""
processed_files = set()
def ProcessFile(gtest_source_file):
"""Processes the given gtest source file."""
# We don't process the same #included file twice.
if gtest_source_... | [
"def",
"FuseGTestAllCcToFile",
"(",
"gtest_root",
",",
"output_file",
")",
":",
"processed_files",
"=",
"set",
"(",
")",
"def",
"ProcessFile",
"(",
"gtest_source_file",
")",
":",
"\"\"\"Processes the given gtest source file.\"\"\"",
"# We don't process the same #included file... | [
177,
0
] | [
217,
32
] | python | en | ['af', 'en', 'en'] | True |
FuseGTestAllCc | (gtest_root, output_dir) | Scans folder gtest_root to generate gtest/gtest-all.cc in output_dir. | Scans folder gtest_root to generate gtest/gtest-all.cc in output_dir. | def FuseGTestAllCc(gtest_root, output_dir):
"""Scans folder gtest_root to generate gtest/gtest-all.cc in output_dir."""
output_file = open(os.path.join(output_dir, GTEST_ALL_CC_OUTPUT), 'w')
FuseGTestAllCcToFile(gtest_root, output_file)
output_file.close() | [
"def",
"FuseGTestAllCc",
"(",
"gtest_root",
",",
"output_dir",
")",
":",
"output_file",
"=",
"open",
"(",
"os",
".",
"path",
".",
"join",
"(",
"output_dir",
",",
"GTEST_ALL_CC_OUTPUT",
")",
",",
"'w'",
")",
"FuseGTestAllCcToFile",
"(",
"gtest_root",
",",
"ou... | [
220,
0
] | [
225,
21
] | python | en | ['af', 'en', 'en'] | True |
FuseGTest | (gtest_root, output_dir) | Fuses gtest.h and gtest-all.cc. | Fuses gtest.h and gtest-all.cc. | def FuseGTest(gtest_root, output_dir):
"""Fuses gtest.h and gtest-all.cc."""
ValidateGTestRootDir(gtest_root)
ValidateOutputDir(output_dir)
FuseGTestH(gtest_root, output_dir)
FuseGTestAllCc(gtest_root, output_dir) | [
"def",
"FuseGTest",
"(",
"gtest_root",
",",
"output_dir",
")",
":",
"ValidateGTestRootDir",
"(",
"gtest_root",
")",
"ValidateOutputDir",
"(",
"output_dir",
")",
"FuseGTestH",
"(",
"gtest_root",
",",
"output_dir",
")",
"FuseGTestAllCc",
"(",
"gtest_root",
",",
"out... | [
228,
0
] | [
235,
40
] | python | en | ['en', 'en', 'en'] | True |
maintain_dialog_history | (
history,
observation,
reply='',
historyLength=1,
useReplies='label_else_model',
dict=None,
useStartEndIndices=True,
splitSentences=False,
) |
Keep track of dialog history, up to a truncation length.
Either includes replies from the labels, model, or not all using param
'replies'.
DEPRECATED. USE PARLAI.CORE.TORCH_AGENT INSTEAD.
|
Keep track of dialog history, up to a truncation length. | def maintain_dialog_history(
history,
observation,
reply='',
historyLength=1,
useReplies='label_else_model',
dict=None,
useStartEndIndices=True,
splitSentences=False,
):
"""
Keep track of dialog history, up to a truncation length.
Either includes replies from the labels, mod... | [
"def",
"maintain_dialog_history",
"(",
"history",
",",
"observation",
",",
"reply",
"=",
"''",
",",
"historyLength",
"=",
"1",
",",
"useReplies",
"=",
"'label_else_model'",
",",
"dict",
"=",
"None",
",",
"useStartEndIndices",
"=",
"True",
",",
"splitSentences",
... | [
51,
0
] | [
118,
28
] | python | en | ['en', 'error', 'th'] | False |
load_cands | (path, lines_have_ids=False, cands_are_replies=False) |
Load global fixed set of candidate labels that the teacher provides.
Every example will include these as candidates. The true labels for a specific
example are also added to this set, so that it's possible to get the right answer.
|
Load global fixed set of candidate labels that the teacher provides. | def load_cands(path, lines_have_ids=False, cands_are_replies=False):
"""
Load global fixed set of candidate labels that the teacher provides.
Every example will include these as candidates. The true labels for a specific
example are also added to this set, so that it's possible to get the right answer.... | [
"def",
"load_cands",
"(",
"path",
",",
"lines_have_ids",
"=",
"False",
",",
"cands_are_replies",
"=",
"False",
")",
":",
"if",
"path",
"is",
"None",
":",
"return",
"None",
"cands",
"=",
"[",
"]",
"cnt",
"=",
"0",
"with",
"PathManager",
".",
"open",
"("... | [
121,
0
] | [
155,
16
] | python | en | ['en', 'error', 'th'] | False |
_report_sort_key | (report_key: str) |
Sorting name for reports.
Sorts by main metric alphabetically, then by task.
|
Sorting name for reports. | def _report_sort_key(report_key: str) -> Tuple[str, str]:
"""
Sorting name for reports.
Sorts by main metric alphabetically, then by task.
"""
# if metric is on its own, like "f1", we will return ('', 'f1')
# if metric is from multitask, we denote it.
# e.g. "convai2/f1" -> ('convai2', 'f1'... | [
"def",
"_report_sort_key",
"(",
"report_key",
":",
"str",
")",
"->",
"Tuple",
"[",
"str",
",",
"str",
"]",
":",
"# if metric is on its own, like \"f1\", we will return ('', 'f1')",
"# if metric is from multitask, we denote it.",
"# e.g. \"convai2/f1\" -> ('convai2', 'f1')",
"# we... | [
329,
0
] | [
343,
39
] | python | en | ['en', 'error', 'th'] | False |
float_formatter | (f: Union[float, int]) |
Format a float as a pretty string.
|
Format a float as a pretty string.
| def float_formatter(f: Union[float, int]) -> str:
"""
Format a float as a pretty string.
"""
if f != f:
# instead of returning nan, return "" so it shows blank in table
return ""
if isinstance(f, int):
# don't do any rounding of integers, leave them alone
return str(f... | [
"def",
"float_formatter",
"(",
"f",
":",
"Union",
"[",
"float",
",",
"int",
"]",
")",
"->",
"str",
":",
"if",
"f",
"!=",
"f",
":",
"# instead of returning nan, return \"\" so it shows blank in table",
"return",
"\"\"",
"if",
"isinstance",
"(",
"f",
",",
"int",... | [
346,
0
] | [
371,
12
] | python | en | ['en', 'error', 'th'] | False |
nice_report | (report) |
Render an agent Report as a beautiful string.
If pandas is installed, we will use it to render as a table. Multitask
metrics will be shown per row, e.g.
.. code-block:
f1 ppl
all .410 27.0
task1 .400 32.0
task2 .420 22.0
If pandas is not availa... |
Render an agent Report as a beautiful string. | def nice_report(report) -> str:
"""
Render an agent Report as a beautiful string.
If pandas is installed, we will use it to render as a table. Multitask
metrics will be shown per row, e.g.
.. code-block:
f1 ppl
all .410 27.0
task1 .400 32.0
task2 ... | [
"def",
"nice_report",
"(",
"report",
")",
"->",
"str",
":",
"if",
"not",
"report",
":",
"return",
"\"\"",
"from",
"parlai",
".",
"core",
".",
"metrics",
"import",
"Metric",
"try",
":",
"import",
"pandas",
"as",
"pd",
"use_pandas",
"=",
"True",
"except",
... | [
388,
0
] | [
447,
9
] | python | en | ['en', 'error', 'th'] | False |
round_sigfigs | (x: Union[float, 'torch.Tensor'], sigfigs=4) |
Round value to specified significant figures.
:param x: input number
:param sigfigs: number of significant figures to return
:returns: float number rounded to specified sigfigs
|
Round value to specified significant figures. | def round_sigfigs(x: Union[float, 'torch.Tensor'], sigfigs=4) -> float:
"""
Round value to specified significant figures.
:param x: input number
:param sigfigs: number of significant figures to return
:returns: float number rounded to specified sigfigs
"""
x_: float
if __TORCH_AVAILABL... | [
"def",
"round_sigfigs",
"(",
"x",
":",
"Union",
"[",
"float",
",",
"'torch.Tensor'",
"]",
",",
"sigfigs",
"=",
"4",
")",
"->",
"float",
":",
"x_",
":",
"float",
"if",
"__TORCH_AVAILABLE",
"and",
"isinstance",
"(",
"x",
",",
"torch",
".",
"Tensor",
")",... | [
450,
0
] | [
473,
20
] | python | en | ['en', 'error', 'th'] | False |
no_lock | () |
Build a nolock for other classes to use for no-op locking.
|
Build a nolock for other classes to use for no-op locking.
| def no_lock():
"""
Build a nolock for other classes to use for no-op locking.
"""
return single_nolock | [
"def",
"no_lock",
"(",
")",
":",
"return",
"single_nolock"
] | [
479,
0
] | [
483,
24
] | python | en | ['en', 'error', 'th'] | False |
clip_text | (text, max_len) |
Clip text to max length, adding ellipses.
|
Clip text to max length, adding ellipses.
| def clip_text(text, max_len):
"""
Clip text to max length, adding ellipses.
"""
if len(text) > max_len:
begin_text = ' '.join(text[: math.floor(0.8 * max_len)].split(' ')[:-1])
end_text = ' '.join(
text[(len(text) - math.floor(0.2 * max_len)) :].split(' ')[1:]
)
... | [
"def",
"clip_text",
"(",
"text",
",",
"max_len",
")",
":",
"if",
"len",
"(",
"text",
")",
">",
"max_len",
":",
"begin_text",
"=",
"' '",
".",
"join",
"(",
"text",
"[",
":",
"math",
".",
"floor",
"(",
"0.8",
"*",
"max_len",
")",
"]",
".",
"split",... | [
486,
0
] | [
499,
15
] | python | en | ['en', 'error', 'th'] | False |
_ellipse | (lst: List[str], max_display: int = 5, sep: str = '|') |
Like join, but possibly inserts an ellipsis.
:param lst: The list to join on
:param int max_display: the number of items to display for ellipsing.
If -1, shows all items
:param string sep: the delimiter to join on
|
Like join, but possibly inserts an ellipsis. | def _ellipse(lst: List[str], max_display: int = 5, sep: str = '|') -> str:
"""
Like join, but possibly inserts an ellipsis.
:param lst: The list to join on
:param int max_display: the number of items to display for ellipsing.
If -1, shows all items
:param string sep: the delimiter to join o... | [
"def",
"_ellipse",
"(",
"lst",
":",
"List",
"[",
"str",
"]",
",",
"max_display",
":",
"int",
"=",
"5",
",",
"sep",
":",
"str",
"=",
"'|'",
")",
"->",
"str",
":",
"# copy the list (or force it to a list if it's a set)",
"choices",
"=",
"list",
"(",
"lst",
... | [
502,
0
] | [
517,
44
] | python | en | ['en', 'error', 'th'] | False |
display_messages | (
msgs: List[Dict[str, Any]],
prettify: bool = False,
ignore_agent_reply: bool = False,
add_fields: str = '',
max_len: int = 1000,
verbose: bool = False,
) |
Return a string describing the set of messages provided.
If prettify is true, candidates are displayed using prettytable. add_fields provides
a list of fields in the msgs which should be displayed if verbose is off.
|
Return a string describing the set of messages provided. | def display_messages(
msgs: List[Dict[str, Any]],
prettify: bool = False,
ignore_agent_reply: bool = False,
add_fields: str = '',
max_len: int = 1000,
verbose: bool = False,
) -> Optional[str]:
"""
Return a string describing the set of messages provided.
If prettify is true, candida... | [
"def",
"display_messages",
"(",
"msgs",
":",
"List",
"[",
"Dict",
"[",
"str",
",",
"Any",
"]",
"]",
",",
"prettify",
":",
"bool",
"=",
"False",
",",
"ignore_agent_reply",
":",
"bool",
"=",
"False",
",",
"add_fields",
":",
"str",
"=",
"''",
",",
"max_... | [
520,
0
] | [
653,
27
] | python | en | ['en', 'error', 'th'] | False |
str_to_msg | (txt, ignore_fields='') |
Convert formatted string to ParlAI message dict.
:param txt:
formatted string to convert. String format is tab-separated fields,
with colon separating field name and contents.
:param ignore_fields:
(default '') comma-separated field names to not
include in the msg dict even... |
Convert formatted string to ParlAI message dict. | def str_to_msg(txt, ignore_fields=''):
"""
Convert formatted string to ParlAI message dict.
:param txt:
formatted string to convert. String format is tab-separated fields,
with colon separating field name and contents.
:param ignore_fields:
(default '') comma-separated field nam... | [
"def",
"str_to_msg",
"(",
"txt",
",",
"ignore_fields",
"=",
"''",
")",
":",
"def",
"tostr",
"(",
"txt",
")",
":",
"txt",
"=",
"str",
"(",
"txt",
")",
"txt",
"=",
"txt",
".",
"replace",
"(",
"'\\\\t'",
",",
"'\\t'",
")",
"txt",
"=",
"txt",
".",
... | [
656,
0
] | [
707,
23
] | python | en | ['en', 'error', 'th'] | False |
msg_to_str | (msg, ignore_fields='') |
Convert ParlAI message dict to string.
:param msg:
dict to convert into a string.
:param ignore_fields:
(default '') comma-separated field names to not include in the string
even if they're in the msg dict.
|
Convert ParlAI message dict to string. | def msg_to_str(msg, ignore_fields=''):
"""
Convert ParlAI message dict to string.
:param msg:
dict to convert into a string.
:param ignore_fields:
(default '') comma-separated field names to not include in the string
even if they're in the msg dict.
"""
def filter(txt):... | [
"def",
"msg_to_str",
"(",
"msg",
",",
"ignore_fields",
"=",
"''",
")",
":",
"def",
"filter",
"(",
"txt",
")",
":",
"txt",
"=",
"str",
"(",
"txt",
")",
"txt",
"=",
"txt",
".",
"replace",
"(",
"'\\t'",
",",
"'\\\\t'",
")",
"txt",
"=",
"txt",
".",
... | [
710,
0
] | [
760,
27
] | python | en | ['en', 'error', 'th'] | False |
set_namedtuple_defaults | (namedtuple, default=None) |
Set *all* of the fields for a given nametuple to a singular value.
Additionally removes the default docstring for each field.
Modifies the tuple in place, but returns it anyway.
More info:
https://stackoverflow.com/a/18348004
:param namedtuple: A constructed collections.namedtuple
:param... |
Set *all* of the fields for a given nametuple to a singular value. | def set_namedtuple_defaults(namedtuple, default=None):
"""
Set *all* of the fields for a given nametuple to a singular value.
Additionally removes the default docstring for each field.
Modifies the tuple in place, but returns it anyway.
More info:
https://stackoverflow.com/a/18348004
:par... | [
"def",
"set_namedtuple_defaults",
"(",
"namedtuple",
",",
"default",
"=",
"None",
")",
":",
"namedtuple",
".",
"__new__",
".",
"__defaults__",
"=",
"(",
"default",
",",
")",
"*",
"len",
"(",
"namedtuple",
".",
"_fields",
")",
"for",
"f",
"in",
"namedtuple"... | [
764,
0
] | [
782,
21
] | python | en | ['en', 'error', 'th'] | False |
warn_once | (msg: str) |
Log a warning, but only once.
:param str msg: Message to display
|
Log a warning, but only once. | def warn_once(msg: str) -> None:
"""
Log a warning, but only once.
:param str msg: Message to display
"""
global _seen_logs
if msg not in _seen_logs:
_seen_logs.add(msg)
logging.warn(msg) | [
"def",
"warn_once",
"(",
"msg",
":",
"str",
")",
"->",
"None",
":",
"global",
"_seen_logs",
"if",
"msg",
"not",
"in",
"_seen_logs",
":",
"_seen_logs",
".",
"add",
"(",
"msg",
")",
"logging",
".",
"warn",
"(",
"msg",
")"
] | [
788,
0
] | [
797,
25
] | python | en | ['en', 'error', 'th'] | False |
error_once | (msg: str) |
Log an error, but only once.
:param str msg: Message to display
|
Log an error, but only once. | def error_once(msg: str) -> None:
"""
Log an error, but only once.
:param str msg: Message to display
"""
global _seen_logs
if msg not in _seen_logs:
_seen_logs.add(msg)
logging.error(msg) | [
"def",
"error_once",
"(",
"msg",
":",
"str",
")",
"->",
"None",
":",
"global",
"_seen_logs",
"if",
"msg",
"not",
"in",
"_seen_logs",
":",
"_seen_logs",
".",
"add",
"(",
"msg",
")",
"logging",
".",
"error",
"(",
"msg",
")"
] | [
800,
0
] | [
809,
26
] | python | en | ['en', 'error', 'th'] | False |
recursive_getattr | (obj, attr, *args) |
Recursive call to getattr for nested attributes.
|
Recursive call to getattr for nested attributes.
| def recursive_getattr(obj, attr, *args):
"""
Recursive call to getattr for nested attributes.
"""
def _getattr(obj, attr):
return getattr(obj, attr, *args)
return functools.reduce(_getattr, [obj] + attr.split('.')) | [
"def",
"recursive_getattr",
"(",
"obj",
",",
"attr",
",",
"*",
"args",
")",
":",
"def",
"_getattr",
"(",
"obj",
",",
"attr",
")",
":",
"return",
"getattr",
"(",
"obj",
",",
"attr",
",",
"*",
"args",
")",
"return",
"functools",
".",
"reduce",
"(",
"... | [
812,
0
] | [
820,
62
] | python | en | ['en', 'error', 'th'] | False |
Timer.__init__ | (self) |
Initialize timer.
|
Initialize timer.
| def __init__(self):
"""
Initialize timer.
"""
self.running = True
self.total = 0
self.start = time.time() | [
"def",
"__init__",
"(",
"self",
")",
":",
"self",
".",
"running",
"=",
"True",
"self",
".",
"total",
"=",
"0",
"self",
".",
"start",
"=",
"time",
".",
"time",
"(",
")"
] | [
163,
4
] | [
169,
32
] | python | en | ['en', 'error', 'th'] | False |
Timer.reset | (self) |
Reset timer to zero.
|
Reset timer to zero.
| def reset(self):
"""
Reset timer to zero.
"""
self.running = True
self.total = 0
self.start = time.time()
return self | [
"def",
"reset",
"(",
"self",
")",
":",
"self",
".",
"running",
"=",
"True",
"self",
".",
"total",
"=",
"0",
"self",
".",
"start",
"=",
"time",
".",
"time",
"(",
")",
"return",
"self"
] | [
171,
4
] | [
178,
19
] | python | en | ['en', 'error', 'th'] | False |
Timer.resume | (self) |
Resume timer.
|
Resume timer.
| def resume(self):
"""
Resume timer.
"""
if not self.running:
self.running = True
self.start = time.time()
return self | [
"def",
"resume",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"running",
":",
"self",
".",
"running",
"=",
"True",
"self",
".",
"start",
"=",
"time",
".",
"time",
"(",
")",
"return",
"self"
] | [
180,
4
] | [
187,
19
] | python | en | ['en', 'error', 'th'] | False |
Timer.stop | (self) |
Pause timer.
|
Pause timer.
| def stop(self):
"""
Pause timer.
"""
if self.running:
self.running = False
self.total += time.time() - self.start
return self | [
"def",
"stop",
"(",
"self",
")",
":",
"if",
"self",
".",
"running",
":",
"self",
".",
"running",
"=",
"False",
"self",
".",
"total",
"+=",
"time",
".",
"time",
"(",
")",
"-",
"self",
".",
"start",
"return",
"self"
] | [
189,
4
] | [
196,
19
] | python | en | ['en', 'error', 'th'] | False |
Timer.time | (self) |
Get current timer time.
|
Get current timer time.
| def time(self):
"""
Get current timer time.
"""
if self.running:
return self.total + time.time() - self.start
return self.total | [
"def",
"time",
"(",
"self",
")",
":",
"if",
"self",
".",
"running",
":",
"return",
"self",
".",
"total",
"+",
"time",
".",
"time",
"(",
")",
"-",
"self",
".",
"start",
"return",
"self",
".",
"total"
] | [
198,
4
] | [
204,
25
] | python | en | ['en', 'error', 'th'] | False |
TimeLogger.__init__ | (self) |
Set up timer.
|
Set up timer.
| def __init__(self):
"""
Set up timer.
"""
self.timer = Timer()
self.tot_time = 0 | [
"def",
"__init__",
"(",
"self",
")",
":",
"self",
".",
"timer",
"=",
"Timer",
"(",
")",
"self",
".",
"tot_time",
"=",
"0"
] | [
212,
4
] | [
217,
25
] | python | en | ['en', 'error', 'th'] | False |
TimeLogger.total_time | (self) |
Return time elapsed at last log call.
|
Return time elapsed at last log call.
| def total_time(self):
"""
Return time elapsed at last log call.
"""
return self.tot_time | [
"def",
"total_time",
"(",
"self",
")",
":",
"return",
"self",
".",
"tot_time"
] | [
219,
4
] | [
223,
28
] | python | en | ['en', 'error', 'th'] | False |
TimeLogger.time | (self) |
Return current timer time.
|
Return current timer time.
| def time(self):
"""
Return current timer time.
"""
return self.timer.time() | [
"def",
"time",
"(",
"self",
")",
":",
"return",
"self",
".",
"timer",
".",
"time",
"(",
")"
] | [
225,
4
] | [
229,
32
] | python | en | ['en', 'error', 'th'] | False |
TimeLogger.log | (self, done, total, report=None) |
Log report, time elapsed, and percentage progress towards goal.
:param done: number of examples completed so far
:param total: total number of elements to be completed. if total > 0,
calculates the time remaining and percentage complete.
:param report: dict of pai... |
Log report, time elapsed, and percentage progress towards goal. | def log(self, done, total, report=None):
"""
Log report, time elapsed, and percentage progress towards goal.
:param done: number of examples completed so far
:param total: total number of elements to be completed. if total > 0,
calculates the time remaining and per... | [
"def",
"log",
"(",
"self",
",",
"done",
",",
"total",
",",
"report",
"=",
"None",
")",
":",
"from",
"parlai",
".",
"core",
".",
"metrics",
"import",
"Metric",
"# delay import to prevent circular dep",
"if",
"isinstance",
"(",
"done",
",",
"Metric",
")",
":... | [
231,
4
] | [
270,
27
] | python | en | ['en', 'error', 'th'] | False |
AttrDict.__init__ | (self, *args, **kwargs) |
Initialize AttrDict using input dict.
|
Initialize AttrDict using input dict.
| def __init__(self, *args, **kwargs):
"""
Initialize AttrDict using input dict.
"""
super().__init__(*args, **kwargs)
self.__dict__ = self | [
"def",
"__init__",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"super",
"(",
")",
".",
"__init__",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"self",
".",
"__dict__",
"=",
"self"
] | [
286,
4
] | [
291,
28
] | python | en | ['en', 'error', 'th'] | False |
NoLock.__enter__ | (self) |
No-op.
|
No-op.
| def __enter__(self):
"""
No-op.
"""
return self | [
"def",
"__enter__",
"(",
"self",
")",
":",
"return",
"self"
] | [
301,
4
] | [
305,
19
] | python | en | ['en', 'error', 'th'] | False |
NoLock.__exit__ | (self, exc_type, exc_value, exc_traceback) |
No-op.
|
No-op.
| def __exit__(self, exc_type, exc_value, exc_traceback):
"""
No-op.
"""
pass | [
"def",
"__exit__",
"(",
"self",
",",
"exc_type",
",",
"exc_value",
",",
"exc_traceback",
")",
":",
"pass"
] | [
307,
4
] | [
311,
12
] | python | en | ['en', 'error', 'th'] | False |
preprocess_schema | (plotly_schema) |
Central location to make changes to schema before it's seen by the
PlotlyNode classes
|
Central location to make changes to schema before it's seen by the
PlotlyNode classes
| def preprocess_schema(plotly_schema):
"""
Central location to make changes to schema before it's seen by the
PlotlyNode classes
"""
# Update template
# ---------------
layout = plotly_schema["layout"]["layoutAttributes"]
# Create codegen-friendly template scheme
template = {
... | [
"def",
"preprocess_schema",
"(",
"plotly_schema",
")",
":",
"# Update template",
"# ---------------",
"layout",
"=",
"plotly_schema",
"[",
"\"layout\"",
"]",
"[",
"\"layoutAttributes\"",
"]",
"# Create codegen-friendly template scheme",
"template",
"=",
"{",
"\"data\"",
"... | [
38,
0
] | [
84,
62
] | python | en | ['en', 'error', 'th'] | False |
opt_to_kwargs | (opt) |
Get kwargs for seq2seq from opt.
|
Get kwargs for seq2seq from opt.
| def opt_to_kwargs(opt):
"""
Get kwargs for seq2seq from opt.
"""
kwargs = {}
for k in [
'numlayers',
'dropout',
'bidirectional',
'rnn_class',
'lookuptable',
'decoder',
'numsoftmax',
'attention',
'attention_length',
'atte... | [
"def",
"opt_to_kwargs",
"(",
"opt",
")",
":",
"kwargs",
"=",
"{",
"}",
"for",
"k",
"in",
"[",
"'numlayers'",
",",
"'dropout'",
",",
"'bidirectional'",
",",
"'rnn_class'",
",",
"'lookuptable'",
",",
"'decoder'",
",",
"'numsoftmax'",
",",
"'attention'",
",",
... | [
20,
0
] | [
41,
17
] | python | en | ['en', 'error', 'th'] | False |
pad | (tensor, length, dim=0, pad=0) |
Pad tensor to a specific length.
:param tensor: vector to pad
:param length: new length
:param dim: (default 0) dimension to pad
:returns: padded tensor if the tensor is shorter than length
|
Pad tensor to a specific length. | def pad(tensor, length, dim=0, pad=0):
"""
Pad tensor to a specific length.
:param tensor: vector to pad
:param length: new length
:param dim: (default 0) dimension to pad
:returns: padded tensor if the tensor is shorter than length
"""
if tensor.size(dim) < length:
return torc... | [
"def",
"pad",
"(",
"tensor",
",",
"length",
",",
"dim",
"=",
"0",
",",
"pad",
"=",
"0",
")",
":",
"if",
"tensor",
".",
"size",
"(",
"dim",
")",
"<",
"length",
":",
"return",
"torch",
".",
"cat",
"(",
"[",
"tensor",
",",
"tensor",
".",
"new",
... | [
44,
0
] | [
67,
21
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq.__init__ | (
self,
num_features,
embeddingsize,
hiddensize,
numlayers=2,
dropout=0,
bidirectional=False,
rnn_class='lstm',
lookuptable='unique',
decoder='same',
numsoftmax=1,
attention='none',
attention_length=48,
atten... |
Initialize seq2seq model.
See cmdline args in Seq2seqAgent for description of arguments.
|
Initialize seq2seq model. | def __init__(
self,
num_features,
embeddingsize,
hiddensize,
numlayers=2,
dropout=0,
bidirectional=False,
rnn_class='lstm',
lookuptable='unique',
decoder='same',
numsoftmax=1,
attention='none',
attention_length=48,
... | [
"def",
"__init__",
"(",
"self",
",",
"num_features",
",",
"embeddingsize",
",",
"hiddensize",
",",
"numlayers",
"=",
"2",
",",
"dropout",
"=",
"0",
",",
"bidirectional",
"=",
"False",
",",
"rnn_class",
"=",
"'lstm'",
",",
"lookuptable",
"=",
"'unique'",
",... | [
77,
4
] | [
164,
9
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq._encode | (self, xs, prev_enc=None) |
Encode the input or return cached encoder state.
|
Encode the input or return cached encoder state.
| def _encode(self, xs, prev_enc=None):
"""
Encode the input or return cached encoder state.
"""
if prev_enc is not None:
return prev_enc
else:
return self.encoder(xs) | [
"def",
"_encode",
"(",
"self",
",",
"xs",
",",
"prev_enc",
"=",
"None",
")",
":",
"if",
"prev_enc",
"is",
"not",
"None",
":",
"return",
"prev_enc",
"else",
":",
"return",
"self",
".",
"encoder",
"(",
"xs",
")"
] | [
166,
4
] | [
173,
35
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq._starts | (self, bsz) |
Return bsz start tokens.
|
Return bsz start tokens.
| def _starts(self, bsz):
"""
Return bsz start tokens.
"""
return self.START.detach().expand(bsz, 1) | [
"def",
"_starts",
"(",
"self",
",",
"bsz",
")",
":",
"return",
"self",
".",
"START",
".",
"detach",
"(",
")",
".",
"expand",
"(",
"bsz",
",",
"1",
")"
] | [
175,
4
] | [
179,
49
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq._decode_forced | (self, ys, ctrl_inputs, encoder_states) |
Decode with teacher forcing.
|
Decode with teacher forcing.
| def _decode_forced(self, ys, ctrl_inputs, encoder_states):
"""
Decode with teacher forcing.
"""
bsz = ys.size(0)
seqlen = ys.size(1)
hidden = encoder_states[1]
attn_params = (encoder_states[0], encoder_states[2])
# input to model is START + each target e... | [
"def",
"_decode_forced",
"(",
"self",
",",
"ys",
",",
"ctrl_inputs",
",",
"encoder_states",
")",
":",
"bsz",
"=",
"ys",
".",
"size",
"(",
"0",
")",
"seqlen",
"=",
"ys",
".",
"size",
"(",
"1",
")",
"hidden",
"=",
"encoder_states",
"[",
"1",
"]",
"at... | [
181,
4
] | [
210,
21
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq._decode | (self, ctrl_inputs, encoder_states, maxlen) |
Decode maxlen tokens.
|
Decode maxlen tokens.
| def _decode(self, ctrl_inputs, encoder_states, maxlen):
"""
Decode maxlen tokens.
"""
hidden = encoder_states[1]
attn_params = (encoder_states[0], encoder_states[2])
bsz = encoder_states[0].size(0)
xs = self._starts(bsz) # input start token
scores = []
... | [
"def",
"_decode",
"(",
"self",
",",
"ctrl_inputs",
",",
"encoder_states",
",",
"maxlen",
")",
":",
"hidden",
"=",
"encoder_states",
"[",
"1",
"]",
"attn_params",
"=",
"(",
"encoder_states",
"[",
"0",
"]",
",",
"encoder_states",
"[",
"2",
"]",
")",
"bsz",... | [
212,
4
] | [
231,
21
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq._align_inds | (self, encoder_states, cand_inds) |
Select the encoder states relevant to valid candidates.
|
Select the encoder states relevant to valid candidates.
| def _align_inds(self, encoder_states, cand_inds):
"""
Select the encoder states relevant to valid candidates.
"""
enc_out, hidden, attn_mask = encoder_states
# LSTM or GRU/RNN hidden state?
if isinstance(hidden, torch.Tensor):
hid, cell = hidden, None
... | [
"def",
"_align_inds",
"(",
"self",
",",
"encoder_states",
",",
"cand_inds",
")",
":",
"enc_out",
",",
"hidden",
",",
"attn_mask",
"=",
"encoder_states",
"# LSTM or GRU/RNN hidden state?",
"if",
"isinstance",
"(",
"hidden",
",",
"torch",
".",
"Tensor",
")",
":",
... | [
233,
4
] | [
260,
41
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq._extract_cur | (self, encoder_states, index, num_cands) |
Extract encoder states at current index and expand them.
|
Extract encoder states at current index and expand them.
| def _extract_cur(self, encoder_states, index, num_cands):
"""
Extract encoder states at current index and expand them.
"""
enc_out, hidden, attn_mask = encoder_states
if isinstance(hidden, torch.Tensor):
cur_hid = hidden.select(1, index).unsqueeze(1).expand(-1, num_ca... | [
"def",
"_extract_cur",
"(",
"self",
",",
"encoder_states",
",",
"index",
",",
"num_cands",
")",
":",
"enc_out",
",",
"hidden",
",",
"attn_mask",
"=",
"encoder_states",
"if",
"isinstance",
"(",
"hidden",
",",
"torch",
".",
"Tensor",
")",
":",
"cur_hid",
"="... | [
262,
4
] | [
287,
41
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq._rank | (self, cands, cand_inds, encoder_states) |
Rank each cand by the average log-probability of the sequence.
|
Rank each cand by the average log-probability of the sequence.
| def _rank(self, cands, cand_inds, encoder_states):
"""
Rank each cand by the average log-probability of the sequence.
"""
if cands is None:
return None
encoder_states = self._align_inds(encoder_states, cand_inds)
cand_scores = []
for batch_idx in rang... | [
"def",
"_rank",
"(",
"self",
",",
"cands",
",",
"cand_inds",
",",
"encoder_states",
")",
":",
"if",
"cands",
"is",
"None",
":",
"return",
"None",
"encoder_states",
"=",
"self",
".",
"_align_inds",
"(",
"encoder_states",
",",
"cand_inds",
")",
"cand_scores",
... | [
289,
4
] | [
318,
26
] | python | en | ['en', 'error', 'th'] | False |
Seq2seq.forward | (
self,
xs,
ctrl_inputs=None,
ys=None,
cands=None,
prev_enc=None,
maxlen=None,
seq_len=None,
) |
Get output predictions from the model.
:param xs:
(bsz x seqlen) LongTensor input to the encoder
:param ys:
expected output from the decoder. used for teacher forcing
to calculate loss.
:param cands:
set of candidates to rank
:par... |
Get output predictions from the model. | def forward(
self,
xs,
ctrl_inputs=None,
ys=None,
cands=None,
prev_enc=None,
maxlen=None,
seq_len=None,
):
"""
Get output predictions from the model.
:param xs:
(bsz x seqlen) LongTensor input to the encoder
... | [
"def",
"forward",
"(",
"self",
",",
"xs",
",",
"ctrl_inputs",
"=",
"None",
",",
"ys",
"=",
"None",
",",
"cands",
"=",
"None",
",",
"prev_enc",
"=",
"None",
",",
"maxlen",
"=",
"None",
",",
"seq_len",
"=",
"None",
",",
")",
":",
"if",
"ys",
"is",
... | [
320,
4
] | [
398,
50
] | python | en | ['en', 'error', 'th'] | False |
ControlEncoder.forward | (self, control_inputs) |
Forward pass.
:param control_inputs: (bsz x num_control_vars) LongTensor of control
variable values (i.e. bucket ids)
:returns: control_embs, (bsz x sum of control emb sizes) FloatTensor of
control variable embeddings, concatenated
|
Forward pass. | def forward(self, control_inputs):
"""
Forward pass.
:param control_inputs: (bsz x num_control_vars) LongTensor of control
variable values (i.e. bucket ids)
:returns: control_embs, (bsz x sum of control emb sizes) FloatTensor of
control variable embeddings, conc... | [
"def",
"forward",
"(",
"self",
",",
"control_inputs",
")",
":",
"# list length num_control_vars of tensors shape (bsz, 1)",
"control_inputs",
"=",
"torch",
".",
"split",
"(",
"control_inputs",
",",
"1",
",",
"dim",
"=",
"1",
")",
"# list length num_control_vars of tenso... | [
423,
4
] | [
448,
27
] | python | en | ['en', 'error', 'th'] | False |
UnknownDropout.__init__ | (self, unknown_idx, probability) |
Initialize layer.
:param unknown_idx: index of unknown token, replace tokens with this
:param probability: during training, replaces tokens with unknown token
at this rate.
|
Initialize layer. | def __init__(self, unknown_idx, probability):
"""
Initialize layer.
:param unknown_idx: index of unknown token, replace tokens with this
:param probability: during training, replaces tokens with unknown token
at this rate.
"""
super().__init__... | [
"def",
"__init__",
"(",
"self",
",",
"unknown_idx",
",",
"probability",
")",
":",
"super",
"(",
")",
".",
"__init__",
"(",
")",
"self",
".",
"unknown_idx",
"=",
"unknown_idx",
"self",
".",
"prob",
"=",
"probability"
] | [
459,
4
] | [
469,
31
] | python | en | ['en', 'error', 'th'] | False |
UnknownDropout.forward | (self, input) |
If training and dropout rate > 0, masks input with unknown token.
|
If training and dropout rate > 0, masks input with unknown token.
| def forward(self, input):
"""
If training and dropout rate > 0, masks input with unknown token.
"""
if self.training and self.prob > 0:
mask = input.new(input.size()).float().uniform_(0, 1) < self.prob
input.masked_fill_(mask, self.unknown_idx)
return inpu... | [
"def",
"forward",
"(",
"self",
",",
"input",
")",
":",
"if",
"self",
".",
"training",
"and",
"self",
".",
"prob",
">",
"0",
":",
"mask",
"=",
"input",
".",
"new",
"(",
"input",
".",
"size",
"(",
")",
")",
".",
"float",
"(",
")",
".",
"uniform_"... | [
471,
4
] | [
478,
20
] | python | en | ['en', 'error', 'th'] | False |
RNNEncoder.__init__ | (
self,
num_features,
embeddingsize,
hiddensize,
padding_idx=0,
rnn_class='lstm',
numlayers=2,
dropout=0.1,
bidirectional=False,
shared_lt=None,
shared_rnn=None,
input_dropout=0,
unknown_idx=None,
sparse=Fals... |
Initialize recurrent encoder.
|
Initialize recurrent encoder.
| def __init__(
self,
num_features,
embeddingsize,
hiddensize,
padding_idx=0,
rnn_class='lstm',
numlayers=2,
dropout=0.1,
bidirectional=False,
shared_lt=None,
shared_rnn=None,
input_dropout=0,
unknown_idx=None,
... | [
"def",
"__init__",
"(",
"self",
",",
"num_features",
",",
"embeddingsize",
",",
"hiddensize",
",",
"padding_idx",
"=",
"0",
",",
"rnn_class",
"=",
"'lstm'",
",",
"numlayers",
"=",
"2",
",",
"dropout",
"=",
"0.1",
",",
"bidirectional",
"=",
"False",
",",
... | [
486,
4
] | [
535,
33
] | python | en | ['en', 'error', 'th'] | False |
RNNEncoder.forward | (self, xs) |
Encode sequence.
:param xs: (bsz x seqlen) LongTensor of input token indices
:returns: encoder outputs, hidden state, attention mask
encoder outputs are the output state at each step of the encoding.
the hidden state is the final hidden state of the encoder.
... |
Encode sequence. | def forward(self, xs):
"""
Encode sequence.
:param xs: (bsz x seqlen) LongTensor of input token indices
:returns: encoder outputs, hidden state, attention mask
encoder outputs are the output state at each step of the encoding.
the hidden state is the final hidde... | [
"def",
"forward",
"(",
"self",
",",
"xs",
")",
":",
"bsz",
"=",
"len",
"(",
"xs",
")",
"# embed input tokens",
"xs",
"=",
"self",
".",
"input_dropout",
"(",
"xs",
")",
"xes",
"=",
"self",
".",
"dropout",
"(",
"self",
".",
"lt",
"(",
"xs",
")",
")... | [
537,
4
] | [
575,
48
] | python | en | ['en', 'error', 'th'] | False |
RNNDecoder.__init__ | (
self,
num_features,
embeddingsize,
hiddensize,
padding_idx=0,
rnn_class='lstm',
numlayers=2,
dropout=0.1,
bidir_input=False,
attn_type='none',
attn_time='pre',
attn_length=-1,
sparse=False,
control_settings... |
Initialize recurrent decoder.
|
Initialize recurrent decoder.
| def __init__(
self,
num_features,
embeddingsize,
hiddensize,
padding_idx=0,
rnn_class='lstm',
numlayers=2,
dropout=0.1,
bidir_input=False,
attn_type='none',
attn_time='pre',
attn_length=-1,
sparse=False,
cont... | [
"def",
"__init__",
"(",
"self",
",",
"num_features",
",",
"embeddingsize",
",",
"hiddensize",
",",
"padding_idx",
"=",
"0",
",",
"rnn_class",
"=",
"'lstm'",
",",
"numlayers",
"=",
"2",
",",
"dropout",
"=",
"0.1",
",",
"bidir_input",
"=",
"False",
",",
"a... | [
585,
4
] | [
639,
80
] | python | en | ['en', 'error', 'th'] | False |
RNNDecoder.forward | (self, xs, ctrl_inputs=None, hidden=None, attn_params=None) |
Decode from input tokens.
:param xs: (bsz x seqlen) LongTensor of input token indices
:param ctrl_inputs: (bsz, num_controls) LongTensor
:param hidden: hidden state to feed into decoder. default (None)
initializes tensors using the RNN's defaul... |
Decode from input tokens. | def forward(self, xs, ctrl_inputs=None, hidden=None, attn_params=None):
"""
Decode from input tokens.
:param xs: (bsz x seqlen) LongTensor of input token indices
:param ctrl_inputs: (bsz, num_controls) LongTensor
:param hidden: hidden state to feed into decoder. de... | [
"def",
"forward",
"(",
"self",
",",
"xs",
",",
"ctrl_inputs",
"=",
"None",
",",
"hidden",
"=",
"None",
",",
"attn_params",
"=",
"None",
")",
":",
"# sequence indices => sequence embeddings",
"xes",
"=",
"self",
".",
"dropout",
"(",
"self",
".",
"lt",
"(",
... | [
641,
4
] | [
686,
33
] | python | en | ['en', 'error', 'th'] | False |
OutputLayer.__init__ | (
self,
num_features,
embeddingsize,
hiddensize,
dropout=0,
numsoftmax=1,
shared_weight=None,
padding_idx=-1,
) |
Initialize output layer.
:param num_features: number of candidates to rank
:param hiddensize: (last) dimension of the input vectors
:param embeddingsize: (last) dimension of the candidate vectors
:param numsoftmax: (default 1) number of softmaxes to calculate.
... |
Initialize output layer. | def __init__(
self,
num_features,
embeddingsize,
hiddensize,
dropout=0,
numsoftmax=1,
shared_weight=None,
padding_idx=-1,
):
"""
Initialize output layer.
:param num_features: number of candidates to rank
:param hiddens... | [
"def",
"__init__",
"(",
"self",
",",
"num_features",
",",
"embeddingsize",
",",
"hiddensize",
",",
"dropout",
"=",
"0",
",",
"numsoftmax",
"=",
"1",
",",
"shared_weight",
"=",
"None",
",",
"padding_idx",
"=",
"-",
"1",
",",
")",
":",
"super",
"(",
")",... | [
694,
4
] | [
760,
38
] | python | en | ['en', 'error', 'th'] | False |
OutputLayer.reset_parameters | (self) |
Reset bias param.
|
Reset bias param.
| def reset_parameters(self):
"""
Reset bias param.
"""
if hasattr(self, 'bias'):
stdv = 1.0 / math.sqrt(self.bias.size(0))
self.bias.data.uniform_(-stdv, stdv) | [
"def",
"reset_parameters",
"(",
"self",
")",
":",
"if",
"hasattr",
"(",
"self",
",",
"'bias'",
")",
":",
"stdv",
"=",
"1.0",
"/",
"math",
".",
"sqrt",
"(",
"self",
".",
"bias",
".",
"size",
"(",
"0",
")",
")",
"self",
".",
"bias",
".",
"data",
... | [
762,
4
] | [
768,
48
] | python | en | ['en', 'error', 'th'] | False |
OutputLayer.forward | (self, input) |
Compute scores from inputs.
:param input: (bsz x seq_len x num_directions * hiddensize) tensor of
states, e.g. the output states of an RNN
:returns: (bsz x seqlen x num_cands) scores for each candidate
|
Compute scores from inputs. | def forward(self, input):
"""
Compute scores from inputs.
:param input: (bsz x seq_len x num_directions * hiddensize) tensor of
states, e.g. the output states of an RNN
:returns: (bsz x seqlen x num_cands) scores for each candidate
"""
# next comp... | [
"def",
"forward",
"(",
"self",
",",
"input",
")",
":",
"# next compute scores over dictionary",
"if",
"self",
".",
"numsoftmax",
">",
"1",
":",
"bsz",
"=",
"input",
".",
"size",
"(",
"0",
")",
"seqlen",
"=",
"input",
".",
"size",
"(",
"1",
")",
"if",
... | [
770,
4
] | [
811,
21
] | python | en | ['en', 'error', 'th'] | False |
AttentionLayer.__init__ | (
self,
attn_type,
hiddensize,
embeddingsize,
bidirectional=False,
attn_length=-1,
attn_time='pre',
) |
Initialize attention layer.
|
Initialize attention layer.
| def __init__(
self,
attn_type,
hiddensize,
embeddingsize,
bidirectional=False,
attn_length=-1,
attn_time='pre',
):
"""
Initialize attention layer.
"""
super().__init__()
self.attention = attn_type
if self.attent... | [
"def",
"__init__",
"(",
"self",
",",
"attn_type",
",",
"hiddensize",
",",
"embeddingsize",
",",
"bidirectional",
"=",
"False",
",",
"attn_length",
"=",
"-",
"1",
",",
"attn_time",
"=",
"'pre'",
",",
")",
":",
"super",
"(",
")",
".",
"__init__",
"(",
")... | [
821,
4
] | [
864,
64
] | python | en | ['en', 'error', 'th'] | False |
AttentionLayer.forward | (self, xes, hidden, attn_params) |
Compute attention over attn_params given input and hidden states.
:param xes: input state. will be combined with applied
attention.
:param hidden: hidden state from model. will be used to select
states to attend to in from th... |
Compute attention over attn_params given input and hidden states. | def forward(self, xes, hidden, attn_params):
"""
Compute attention over attn_params given input and hidden states.
:param xes: input state. will be combined with applied
attention.
:param hidden: hidden state from model. will be used to select
... | [
"def",
"forward",
"(",
"self",
",",
"xes",
",",
"hidden",
",",
"attn_params",
")",
":",
"if",
"self",
".",
"attention",
"==",
"'none'",
":",
"# do nothing, no attention",
"return",
"xes",
",",
"None",
"if",
"type",
"(",
"hidden",
")",
"==",
"tuple",
":",... | [
866,
4
] | [
943,
35
] | python | en | ['en', 'error', 'th'] | False |
setTTL | (qstate, ttl) | Sets return_msg TTL and all the RRs TTL | Sets return_msg TTL and all the RRs TTL | def setTTL(qstate, ttl):
"""Sets return_msg TTL and all the RRs TTL"""
if qstate.return_msg:
qstate.return_msg.rep.ttl = ttl
if (qstate.return_msg.rep):
for i in range(0,qstate.return_msg.rep.rrset_count):
d = qstate.return_msg.rep.rrsets[i].entry.data
... | [
"def",
"setTTL",
"(",
"qstate",
",",
"ttl",
")",
":",
"if",
"qstate",
".",
"return_msg",
":",
"qstate",
".",
"return_msg",
".",
"rep",
".",
"ttl",
"=",
"ttl",
"if",
"(",
"qstate",
".",
"return_msg",
".",
"rep",
")",
":",
"for",
"i",
"in",
"range",
... | [
49,
0
] | [
57,
37
] | python | en | ['en', 'en', 'en'] | True |
SimpleDictionaryAgent.add_to_dict | (self, tokens) |
Builds dictionary from the list of provided tokens.
Only adds words contained in self.embedding_words, if not None.
|
Builds dictionary from the list of provided tokens. | def add_to_dict(self, tokens):
"""
Builds dictionary from the list of provided tokens.
Only adds words contained in self.embedding_words, if not None.
"""
for token in tokens:
if self.embedding_words is not None and token not in self.embedding_words:
... | [
"def",
"add_to_dict",
"(",
"self",
",",
"tokens",
")",
":",
"for",
"token",
"in",
"tokens",
":",
"if",
"self",
".",
"embedding_words",
"is",
"not",
"None",
"and",
"token",
"not",
"in",
"self",
".",
"embedding_words",
":",
"continue",
"self",
".",
"freq",... | [
84,
4
] | [
97,
43
] | python | en | ['en', 'error', 'th'] | False |
DrqaAgent.act | (self) | Update or predict on a single example (batchsize = 1). | Update or predict on a single example (batchsize = 1). | def act(self):
"""Update or predict on a single example (batchsize = 1)."""
reply = {'id': self.getID()}
ex = self._build_ex(self.observation)
if ex is None:
return reply
batch = batchify(
[ex], null=self.word_dict[self.word_dict.null_token], cuda=self.op... | [
"def",
"act",
"(",
"self",
")",
":",
"reply",
"=",
"{",
"'id'",
":",
"self",
".",
"getID",
"(",
")",
"}",
"ex",
"=",
"self",
".",
"_build_ex",
"(",
"self",
".",
"observation",
")",
"if",
"ex",
"is",
"None",
":",
"return",
"reply",
"batch",
"=",
... | [
344,
4
] | [
366,
20
] | python | en | ['en', 'en', 'en'] | True |
DrqaAgent.batch_act | (self, observations) |
Update or predict on a batch of examples.
More efficient than act().
|
Update or predict on a batch of examples. | def batch_act(self, observations):
"""
Update or predict on a batch of examples.
More efficient than act().
"""
batchsize = len(observations)
batch_reply = [{'id': self.getID()} for _ in range(batchsize)]
# Some examples will be None (no answer found). Filter th... | [
"def",
"batch_act",
"(",
"self",
",",
"observations",
")",
":",
"batchsize",
"=",
"len",
"(",
"observations",
")",
"batch_reply",
"=",
"[",
"{",
"'id'",
":",
"self",
".",
"getID",
"(",
")",
"}",
"for",
"_",
"in",
"range",
"(",
"batchsize",
")",
"]",
... | [
368,
4
] | [
421,
26
] | python | en | ['en', 'error', 'th'] | False |
DrqaAgent.save | (self, fname=None) |
Save the parameters of the agent to a file.
|
Save the parameters of the agent to a file.
| def save(self, fname=None):
"""
Save the parameters of the agent to a file.
"""
fname = self.opt.get('model_file', None) if fname is None else fname
if fname:
print("[ saving model: " + fname + " ]")
self.opt['trained'] = True
self.model.save(f... | [
"def",
"save",
"(",
"self",
",",
"fname",
"=",
"None",
")",
":",
"fname",
"=",
"self",
".",
"opt",
".",
"get",
"(",
"'model_file'",
",",
"None",
")",
"if",
"fname",
"is",
"None",
"else",
"fname",
"if",
"fname",
":",
"print",
"(",
"\"[ saving model: \... | [
423,
4
] | [
434,
43
] | python | en | ['en', 'error', 'th'] | False |
DrqaAgent._build_ex | (self, ex) |
Find the token span of the answer in the context for this example.
If a token span cannot be found, return None. Otherwise, torchify.
|
Find the token span of the answer in the context for this example. | def _build_ex(self, ex):
"""
Find the token span of the answer in the context for this example.
If a token span cannot be found, return None. Otherwise, torchify.
"""
# Check if empty input (end of epoch)
if 'text' not in ex:
return
# Split out docum... | [
"def",
"_build_ex",
"(",
"self",
",",
"ex",
")",
":",
"# Check if empty input (end of epoch)",
"if",
"'text'",
"not",
"in",
"ex",
":",
"return",
"# Split out document + question",
"inputs",
"=",
"{",
"}",
"fields",
"=",
"ex",
"[",
"'text'",
"]",
".",
"strip",
... | [
440,
4
] | [
495,
45
] | python | en | ['en', 'error', 'th'] | False |
DrqaAgent._find_target | (self, document, labels) |
Find the start/end token span for all labels in document.
Return a random one for training.
|
Find the start/end token span for all labels in document. | def _find_target(self, document, labels):
"""
Find the start/end token span for all labels in document.
Return a random one for training.
"""
def _positions(d, l):
for i in range(len(d)):
for j in range(i, min(len(d) - 1, i + len(l))):
... | [
"def",
"_find_target",
"(",
"self",
",",
"document",
",",
"labels",
")",
":",
"def",
"_positions",
"(",
"d",
",",
"l",
")",
":",
"for",
"i",
"in",
"range",
"(",
"len",
"(",
"d",
")",
")",
":",
"for",
"j",
"in",
"range",
"(",
"i",
",",
"min",
... | [
497,
4
] | [
515,
54
] | python | en | ['en', 'error', 'th'] | False |
DrqaAgent._subsample_doc | (self, paras, labels, subsample) |
Subsample paragraphs from the document (mostly for training speed).
|
Subsample paragraphs from the document (mostly for training speed).
| def _subsample_doc(self, paras, labels, subsample):
"""
Subsample paragraphs from the document (mostly for training speed).
"""
# first find a valid paragraph (with a label)
pi = -1
for ind, p in enumerate(paras):
for l in labels:
if p.find(l):... | [
"def",
"_subsample_doc",
"(",
"self",
",",
"paras",
",",
"labels",
",",
"subsample",
")",
":",
"# first find a valid paragraph (with a label)",
"pi",
"=",
"-",
"1",
"for",
"ind",
",",
"p",
"in",
"enumerate",
"(",
"paras",
")",
":",
"for",
"l",
"in",
"label... | [
517,
4
] | [
541,
24
] | python | en | ['en', 'error', 'th'] | False |
Marker.color | (self) |
Sets the marker color of unselected points, applied only when a
selection exists.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
... |
Sets the marker color of unselected points, applied only when a
selection exists.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
... | def color(self):
"""
Sets the marker color of unselected points, applied only when a
selection exists.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla stri... | [
"def",
"color",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"color\"",
"]"
] | [
15,
4
] | [
66,
28
] | python | en | ['en', 'error', 'th'] | False |
Marker.opacity | (self) |
Sets the marker opacity of unselected points, applied only when
a selection exists.
The 'opacity' property is a number and may be specified as:
- An int or float in the interval [0, 1]
Returns
-------
int|float
|
Sets the marker opacity of unselected points, applied only when
a selection exists.
The 'opacity' property is a number and may be specified as:
- An int or float in the interval [0, 1] | def opacity(self):
"""
Sets the marker opacity of unselected points, applied only when
a selection exists.
The 'opacity' property is a number and may be specified as:
- An int or float in the interval [0, 1]
Returns
-------
int|float
"""
... | [
"def",
"opacity",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"opacity\"",
"]"
] | [
75,
4
] | [
87,
30
] | python | en | ['en', 'error', 'th'] | False |
Marker.size | (self) |
Sets the marker size of unselected points, applied only when a
selection exists.
The 'size' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float
|
Sets the marker size of unselected points, applied only when a
selection exists.
The 'size' property is a number and may be specified as:
- An int or float in the interval [0, inf] | def size(self):
"""
Sets the marker size of unselected points, applied only when a
selection exists.
The 'size' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float
"""
r... | [
"def",
"size",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"size\"",
"]"
] | [
96,
4
] | [
108,
27
] | python | en | ['en', 'error', 'th'] | False |
Marker.__init__ | (self, arg=None, color=None, opacity=None, size=None, **kwargs) |
Construct a new Marker object
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of
:class:`plotly.graph_objs.box.unselected.Marker`
color
Sets the marker color of unselected point... |
Construct a new Marker object
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of
:class:`plotly.graph_objs.box.unselected.Marker`
color
Sets the marker color of unselected point... | def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs):
"""
Construct a new Marker object
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of
:class:`plotly.graph_objs.bo... | [
"def",
"__init__",
"(",
"self",
",",
"arg",
"=",
"None",
",",
"color",
"=",
"None",
",",
"opacity",
"=",
"None",
",",
"size",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"super",
"(",
"Marker",
",",
"self",
")",
".",
"__init__",
"(",
"\"marke... | [
130,
4
] | [
202,
34
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.__init__ | (self, context: InjectionContext) |
Initialize a PresentationManager.
Args:
context: The context for this presentation
|
Initialize a PresentationManager. | def __init__(self, context: InjectionContext):
"""
Initialize a PresentationManager.
Args:
context: The context for this presentation
"""
self._context = context
self._logger = logging.getLogger(__name__) | [
"def",
"__init__",
"(",
"self",
",",
"context",
":",
"InjectionContext",
")",
":",
"self",
".",
"_context",
"=",
"context",
"self",
".",
"_logger",
"=",
"logging",
".",
"getLogger",
"(",
"__name__",
")"
] | [
28,
4
] | [
37,
50
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.context | (self) |
Accessor for the current request context.
Returns:
The injection context for this presentation manager
|
Accessor for the current request context. | def context(self) -> InjectionContext:
"""
Accessor for the current request context.
Returns:
The injection context for this presentation manager
"""
return self._context | [
"def",
"context",
"(",
"self",
")",
"->",
"InjectionContext",
":",
"return",
"self",
".",
"_context"
] | [
40,
4
] | [
48,
28
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.create_exchange_for_proposal | (
self,
connection_id: str,
presentation_proposal_message: PresentationProposal,
auto_present: bool = None,
) |
Create a presentation exchange record for input presentation proposal.
Args:
connection_id: connection identifier
presentation_proposal_message: presentation proposal to serialize
to exchange record
auto_present: whether to present proof upon receivi... |
Create a presentation exchange record for input presentation proposal. | async def create_exchange_for_proposal(
self,
connection_id: str,
presentation_proposal_message: PresentationProposal,
auto_present: bool = None,
):
"""
Create a presentation exchange record for input presentation proposal.
Args:
connection_id: co... | [
"async",
"def",
"create_exchange_for_proposal",
"(",
"self",
",",
"connection_id",
":",
"str",
",",
"presentation_proposal_message",
":",
"PresentationProposal",
",",
"auto_present",
":",
"bool",
"=",
"None",
",",
")",
":",
"presentation_exchange_record",
"=",
"V10Pre... | [
50,
4
] | [
83,
43
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.receive_proposal | (self) |
Receive a presentation proposal from message in context on manager creation.
Returns:
Presentation exchange record, created
|
Receive a presentation proposal from message in context on manager creation. | async def receive_proposal(self):
"""
Receive a presentation proposal from message in context on manager creation.
Returns:
Presentation exchange record, created
"""
presentation_proposal_message = self.context.message
presentation_exchange_record = V10Prese... | [
"async",
"def",
"receive_proposal",
"(",
"self",
")",
":",
"presentation_proposal_message",
"=",
"self",
".",
"context",
".",
"message",
"presentation_exchange_record",
"=",
"V10PresentationExchange",
"(",
"connection_id",
"=",
"self",
".",
"context",
".",
"connection... | [
85,
4
] | [
106,
43
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.create_bound_request | (
self,
presentation_exchange_record: V10PresentationExchange,
name: str = None,
version: str = None,
nonce: str = None,
comment: str = None,
) |
Create a presentation request bound to a proposal.
Args:
presentation_exchange_record: Presentation exchange record for which
to create presentation request
name: name to use in presentation request (None for default)
version: version to use in prese... |
Create a presentation request bound to a proposal. | async def create_bound_request(
self,
presentation_exchange_record: V10PresentationExchange,
name: str = None,
version: str = None,
nonce: str = None,
comment: str = None,
):
"""
Create a presentation request bound to a proposal.
Args:
... | [
"async",
"def",
"create_bound_request",
"(",
"self",
",",
"presentation_exchange_record",
":",
"V10PresentationExchange",
",",
"name",
":",
"str",
"=",
"None",
",",
"version",
":",
"str",
"=",
"None",
",",
"nonce",
":",
"str",
"=",
"None",
",",
"comment",
":... | [
108,
4
] | [
159,
73
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.create_exchange_for_request | (
self, connection_id: str, presentation_request_message: PresentationRequest
) |
Create a presentation exchange record for input presentation request.
Args:
connection_id: connection identifier
presentation_request_message: presentation request to use in creating
exchange record, extracting indy proof request and thread id
Returns:
... |
Create a presentation exchange record for input presentation request. | async def create_exchange_for_request(
self, connection_id: str, presentation_request_message: PresentationRequest
):
"""
Create a presentation exchange record for input presentation request.
Args:
connection_id: connection identifier
presentation_request_mes... | [
"async",
"def",
"create_exchange_for_request",
"(",
"self",
",",
"connection_id",
":",
"str",
",",
"presentation_request_message",
":",
"PresentationRequest",
")",
":",
"presentation_exchange_record",
"=",
"V10PresentationExchange",
"(",
"connection_id",
"=",
"connection_id... | [
161,
4
] | [
188,
43
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.receive_request | (
self, presentation_exchange_record: V10PresentationExchange
) |
Receive a presentation request.
Args:
presentation_exchange_record: presentation exchange record with
request to receive
Returns:
The presentation_exchange_record, updated
|
Receive a presentation request. | async def receive_request(
self, presentation_exchange_record: V10PresentationExchange
):
"""
Receive a presentation request.
Args:
presentation_exchange_record: presentation exchange record with
request to receive
Returns:
The presen... | [
"async",
"def",
"receive_request",
"(",
"self",
",",
"presentation_exchange_record",
":",
"V10PresentationExchange",
")",
":",
"presentation_exchange_record",
".",
"state",
"=",
"(",
"V10PresentationExchange",
".",
"STATE_REQUEST_RECEIVED",
")",
"await",
"presentation_excha... | [
190,
4
] | [
211,
43
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.create_presentation | (
self,
presentation_exchange_record: V10PresentationExchange,
requested_credentials: dict,
comment: str = None,
) |
Create a presentation.
Args:
presentation_exchange_record: Record to update
requested_credentials: Indy formatted requested_credentials
e.g.,
::
{
"self_attested_attributes": {
"j233ffbc-bd35... |
Create a presentation. | async def create_presentation(
self,
presentation_exchange_record: V10PresentationExchange,
requested_credentials: dict,
comment: str = None,
):
"""
Create a presentation.
Args:
presentation_exchange_record: Record to update
requested_... | [
"async",
"def",
"create_presentation",
"(",
"self",
",",
"presentation_exchange_record",
":",
"V10PresentationExchange",
",",
"requested_credentials",
":",
"dict",
",",
"comment",
":",
"str",
"=",
"None",
",",
")",
":",
"# Get all credential ids for this presentation",
... | [
213,
4
] | [
324,
65
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.receive_presentation | (self) |
Receive a presentation, from message in context on manager creation.
Returns:
presentation exchange record, retrieved and updated
|
Receive a presentation, from message in context on manager creation. | async def receive_presentation(self):
"""
Receive a presentation, from message in context on manager creation.
Returns:
presentation exchange record, retrieved and updated
"""
presentation = self.context.message.indy_proof()
thread_id = self.context.message.... | [
"async",
"def",
"receive_presentation",
"(",
"self",
")",
":",
"presentation",
"=",
"self",
".",
"context",
".",
"message",
".",
"indy_proof",
"(",
")",
"thread_id",
"=",
"self",
".",
"context",
".",
"message",
".",
"_thread_id",
"(",
"presentation_exchange_re... | [
326,
4
] | [
353,
43
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.verify_presentation | (
self, presentation_exchange_record: V10PresentationExchange
) |
Verify a presentation.
Args:
presentation_exchange_record: presentation exchange record
with presentation request and presentation to verify
Returns:
presentation record, updated
|
Verify a presentation. | async def verify_presentation(
self, presentation_exchange_record: V10PresentationExchange
):
"""
Verify a presentation.
Args:
presentation_exchange_record: presentation exchange record
with presentation request and presentation to verify
Returns... | [
"async",
"def",
"verify_presentation",
"(",
"self",
",",
"presentation_exchange_record",
":",
"V10PresentationExchange",
")",
":",
"indy_proof_request",
"=",
"presentation_exchange_record",
".",
"presentation_request",
"indy_proof",
"=",
"presentation_exchange_record",
".",
"... | [
355,
4
] | [
411,
43
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.send_presentation_ack | (
self, presentation_exchange_record: V10PresentationExchange
) |
Send acknowledgement of presentation receipt.
Args:
presentation_exchange_record: presentation exchange record with thread id
|
Send acknowledgement of presentation receipt. | async def send_presentation_ack(
self, presentation_exchange_record: V10PresentationExchange
):
"""
Send acknowledgement of presentation receipt.
Args:
presentation_exchange_record: presentation exchange record with thread id
"""
responder = await self.c... | [
"async",
"def",
"send_presentation_ack",
"(",
"self",
",",
"presentation_exchange_record",
":",
"V10PresentationExchange",
")",
":",
"responder",
"=",
"await",
"self",
".",
"context",
".",
"inject",
"(",
"BaseResponder",
",",
"required",
"=",
"False",
")",
"if",
... | [
413,
4
] | [
436,
13
] | python | en | ['en', 'error', 'th'] | False |
PresentationManager.receive_presentation_ack | (self) |
Receive a presentation ack, from message in context on manager creation.
Returns:
presentation exchange record, retrieved and updated
|
Receive a presentation ack, from message in context on manager creation. | async def receive_presentation_ack(self):
"""
Receive a presentation ack, from message in context on manager creation.
Returns:
presentation exchange record, retrieved and updated
"""
(
presentation_exchange_record
) = await V10PresentationExchan... | [
"async",
"def",
"receive_presentation_ack",
"(",
"self",
")",
":",
"(",
"presentation_exchange_record",
")",
"=",
"await",
"V10PresentationExchange",
".",
"retrieve_by_tag_filter",
"(",
"self",
".",
"context",
",",
"tag_filter",
"=",
"{",
"\"thread_id\"",
":",
"self... | [
438,
4
] | [
465,
43
] | python | en | ['en', 'error', 'th'] | False |
Marker.color | (self) |
Sets the marker color of unselected points, applied only when a
selection exists.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
... |
Sets the marker color of unselected points, applied only when a
selection exists.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
... | def color(self):
"""
Sets the marker color of unselected points, applied only when a
selection exists.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla stri... | [
"def",
"color",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"color\"",
"]"
] | [
15,
4
] | [
66,
28
] | python | en | ['en', 'error', 'th'] | False |
Marker.opacity | (self) |
Sets the marker opacity of unselected points, applied only when
a selection exists.
The 'opacity' property is a number and may be specified as:
- An int or float in the interval [0, 1]
Returns
-------
int|float
|
Sets the marker opacity of unselected points, applied only when
a selection exists.
The 'opacity' property is a number and may be specified as:
- An int or float in the interval [0, 1] | def opacity(self):
"""
Sets the marker opacity of unselected points, applied only when
a selection exists.
The 'opacity' property is a number and may be specified as:
- An int or float in the interval [0, 1]
Returns
-------
int|float
"""
... | [
"def",
"opacity",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"opacity\"",
"]"
] | [
75,
4
] | [
87,
30
] | python | en | ['en', 'error', 'th'] | False |
Marker.size | (self) |
Sets the marker size of unselected points, applied only when a
selection exists.
The 'size' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float
|
Sets the marker size of unselected points, applied only when a
selection exists.
The 'size' property is a number and may be specified as:
- An int or float in the interval [0, inf] | def size(self):
"""
Sets the marker size of unselected points, applied only when a
selection exists.
The 'size' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float
"""
r... | [
"def",
"size",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"size\"",
"]"
] | [
96,
4
] | [
108,
27
] | python | en | ['en', 'error', 'th'] | False |
Marker.__init__ | (self, arg=None, color=None, opacity=None, size=None, **kwargs) |
Construct a new Marker object
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of
:class:`plotly.graph_objs.violin.unselected.Marker`
color
Sets the marker color of unselected po... |
Construct a new Marker object
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of
:class:`plotly.graph_objs.violin.unselected.Marker`
color
Sets the marker color of unselected po... | def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs):
"""
Construct a new Marker object
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of
:class:`plotly.graph_objs.vi... | [
"def",
"__init__",
"(",
"self",
",",
"arg",
"=",
"None",
",",
"color",
"=",
"None",
",",
"opacity",
"=",
"None",
",",
"size",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"super",
"(",
"Marker",
",",
"self",
")",
".",
"__init__",
"(",
"\"marke... | [
130,
4
] | [
202,
34
] | python | en | ['en', 'error', 'th'] | False |
is_this_circleci | () |
Return if we are currently running in CircleCI.
|
Return if we are currently running in CircleCI.
| def is_this_circleci():
"""
Return if we are currently running in CircleCI.
"""
return bool(os.environ.get('CIRCLECI')) | [
"def",
"is_this_circleci",
"(",
")",
":",
"return",
"bool",
"(",
"os",
".",
"environ",
".",
"get",
"(",
"'CIRCLECI'",
")",
")"
] | [
65,
0
] | [
69,
43
] | python | en | ['en', 'error', 'th'] | False |
skipUnlessTorch | (testfn, reason='pytorch is not installed') |
Decorate a test to skip if torch is not installed.
|
Decorate a test to skip if torch is not installed.
| def skipUnlessTorch(testfn, reason='pytorch is not installed'):
"""
Decorate a test to skip if torch is not installed.
"""
return unittest.skipUnless(TORCH_AVAILABLE, reason)(testfn) | [
"def",
"skipUnlessTorch",
"(",
"testfn",
",",
"reason",
"=",
"'pytorch is not installed'",
")",
":",
"return",
"unittest",
".",
"skipUnless",
"(",
"TORCH_AVAILABLE",
",",
"reason",
")",
"(",
"testfn",
")"
] | [
72,
0
] | [
76,
63
] | python | en | ['en', 'error', 'th'] | False |
skipIfGPU | (testfn, reason='Test is CPU-only') |
Decorate a test to skip if a GPU is available.
Useful for disabling hogwild tests.
|
Decorate a test to skip if a GPU is available. | def skipIfGPU(testfn, reason='Test is CPU-only'):
"""
Decorate a test to skip if a GPU is available.
Useful for disabling hogwild tests.
"""
return unittest.skipIf(GPU_AVAILABLE, reason)(testfn) | [
"def",
"skipIfGPU",
"(",
"testfn",
",",
"reason",
"=",
"'Test is CPU-only'",
")",
":",
"return",
"unittest",
".",
"skipIf",
"(",
"GPU_AVAILABLE",
",",
"reason",
")",
"(",
"testfn",
")"
] | [
79,
0
] | [
85,
57
] | python | en | ['en', 'error', 'th'] | False |
skipUnlessGPU | (testfn, reason='Test requires a GPU') |
Decorate a test to skip if no GPU is available.
|
Decorate a test to skip if no GPU is available.
| def skipUnlessGPU(testfn, reason='Test requires a GPU'):
"""
Decorate a test to skip if no GPU is available.
"""
return unittest.skipUnless(GPU_AVAILABLE, reason)(testfn) | [
"def",
"skipUnlessGPU",
"(",
"testfn",
",",
"reason",
"=",
"'Test requires a GPU'",
")",
":",
"return",
"unittest",
".",
"skipUnless",
"(",
"GPU_AVAILABLE",
",",
"reason",
")",
"(",
"testfn",
")"
] | [
88,
0
] | [
92,
61
] | python | en | ['en', 'error', 'th'] | False |
skipUnlessBPE | (testfn, reason='Test requires subword NMT') |
Decorate a test to skip if BPE is not installed.
|
Decorate a test to skip if BPE is not installed.
| def skipUnlessBPE(testfn, reason='Test requires subword NMT'):
"""
Decorate a test to skip if BPE is not installed.
"""
return unittest.skipUnless(BPE_INSTALLED, reason)(testfn) | [
"def",
"skipUnlessBPE",
"(",
"testfn",
",",
"reason",
"=",
"'Test requires subword NMT'",
")",
":",
"return",
"unittest",
".",
"skipUnless",
"(",
"BPE_INSTALLED",
",",
"reason",
")",
"(",
"testfn",
")"
] | [
95,
0
] | [
99,
61
] | python | en | ['en', 'error', 'th'] | False |
skipIfCircleCI | (testfn, reason='Test disabled in CircleCI') |
Decorate a test to skip if running on CircleCI.
|
Decorate a test to skip if running on CircleCI.
| def skipIfCircleCI(testfn, reason='Test disabled in CircleCI'):
"""
Decorate a test to skip if running on CircleCI.
"""
return unittest.skipIf(is_this_circleci(), reason)(testfn) | [
"def",
"skipIfCircleCI",
"(",
"testfn",
",",
"reason",
"=",
"'Test disabled in CircleCI'",
")",
":",
"return",
"unittest",
".",
"skipIf",
"(",
"is_this_circleci",
"(",
")",
",",
"reason",
")",
"(",
"testfn",
")"
] | [
102,
0
] | [
106,
62
] | python | en | ['en', 'error', 'th'] | False |
skipUnlessVision | (testfn, reason='torchvision not installed') |
Decorate a test to skip unless torchvision is installed.
|
Decorate a test to skip unless torchvision is installed.
| def skipUnlessVision(testfn, reason='torchvision not installed'):
"""
Decorate a test to skip unless torchvision is installed.
"""
return unittest.skipUnless(VISION_AVAILABLE, reason)(testfn) | [
"def",
"skipUnlessVision",
"(",
"testfn",
",",
"reason",
"=",
"'torchvision not installed'",
")",
":",
"return",
"unittest",
".",
"skipUnless",
"(",
"VISION_AVAILABLE",
",",
"reason",
")",
"(",
"testfn",
")"
] | [
109,
0
] | [
113,
64
] | python | en | ['en', 'error', 'th'] | False |
skipUnlessDetectron | (
testfn, reason='maskrcnn_benchmark and/or opencv not installed'
) |
Decorate a test to skip unless maskrcnn_benchmark and opencv are installed.
|
Decorate a test to skip unless maskrcnn_benchmark and opencv are installed.
| def skipUnlessDetectron(
testfn, reason='maskrcnn_benchmark and/or opencv not installed'
):
"""
Decorate a test to skip unless maskrcnn_benchmark and opencv are installed.
"""
return unittest.skipUnless(DETECTRON_AVAILABLE, reason)(testfn) | [
"def",
"skipUnlessDetectron",
"(",
"testfn",
",",
"reason",
"=",
"'maskrcnn_benchmark and/or opencv not installed'",
")",
":",
"return",
"unittest",
".",
"skipUnless",
"(",
"DETECTRON_AVAILABLE",
",",
"reason",
")",
"(",
"testfn",
")"
] | [
116,
0
] | [
122,
67
] | python | en | ['en', 'error', 'th'] | False |
git_ls_files | (root=None, skip_nonexisting=True) |
List all files tracked by git.
|
List all files tracked by git.
| def git_ls_files(root=None, skip_nonexisting=True):
"""
List all files tracked by git.
"""
filenames = git_.ls_files(root).split('\n')
if skip_nonexisting:
filenames = [fn for fn in filenames if PathManager.exists(fn)]
return filenames | [
"def",
"git_ls_files",
"(",
"root",
"=",
"None",
",",
"skip_nonexisting",
"=",
"True",
")",
":",
"filenames",
"=",
"git_",
".",
"ls_files",
"(",
"root",
")",
".",
"split",
"(",
"'\\n'",
")",
"if",
"skip_nonexisting",
":",
"filenames",
"=",
"[",
"fn",
"... | [
166,
0
] | [
173,
20
] | python | en | ['en', 'error', 'th'] | False |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.