body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1
value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
|---|---|---|---|---|---|---|---|---|---|
17d739dbbe8728fb06c24aad2d1d32bee5060406583af13f2e3fa0b39ba7ecea | @crprofileset.command(name='verify_url', pass_context=True)
async def crprofileset_verify_url(self, ctx, url):
'Set player verification endpoint'
self.model.verify_url = url
(await self.bot.say('Verification URL updated.'))
(await self.bot.delete_message(ctx.message)) | Set player verification endpoint | crprofile/crprofile.py | crprofileset_verify_url | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='verify_url', pass_context=True)
async def crprofileset_verify_url(self, ctx, url):
self.model.verify_url = url
(await self.bot.say('Verification URL updated.'))
(await self.bot.delete_message(ctx.message)) | @crprofileset.command(name='verify_url', pass_context=True)
async def crprofileset_verify_url(self, ctx, url):
self.model.verify_url = url
(await self.bot.say('Verification URL updated.'))
(await self.bot.delete_message(ctx.message))<|docstring|>Set player verification endpoint<|endoftext|> |
c71772f86032381cc9d3d26b2ac1cdb4f3e50773979b05f7a23a0a2f6f3b3365 | @crprofileset.command(name='auth', pass_context=True)
async def crprofileset_auth(self, ctx, token):
'Set auth header'
self.model.auth = token
(await self.bot.say('Auth updated.'))
(await self.bot.delete_message(ctx.message)) | Set auth header | crprofile/crprofile.py | crprofileset_auth | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='auth', pass_context=True)
async def crprofileset_auth(self, ctx, token):
self.model.auth = token
(await self.bot.say('Auth updated.'))
(await self.bot.delete_message(ctx.message)) | @crprofileset.command(name='auth', pass_context=True)
async def crprofileset_auth(self, ctx, token):
self.model.auth = token
(await self.bot.say('Auth updated.'))
(await self.bot.delete_message(ctx.message))<|docstring|>Set auth header<|endoftext|> |
a391ebc29b0aae59da9652089beec45936eeae7bdde6be1a3207d7c051e0aff9 | @crprofileset.command(name='official_auth', pass_context=True)
async def crprofileset_official_auth(self, ctx, token):
'Set auth header'
self.model.official_auth = token
(await self.bot.say('Auth updated.'))
(await self.bot.delete_message(ctx.message)) | Set auth header | crprofile/crprofile.py | crprofileset_official_auth | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='official_auth', pass_context=True)
async def crprofileset_official_auth(self, ctx, token):
self.model.official_auth = token
(await self.bot.say('Auth updated.'))
(await self.bot.delete_message(ctx.message)) | @crprofileset.command(name='official_auth', pass_context=True)
async def crprofileset_official_auth(self, ctx, token):
self.model.official_auth = token
(await self.bot.say('Auth updated.'))
(await self.bot.delete_message(ctx.message))<|docstring|>Set auth header<|endoftext|> |
86971ccf05a0398bddc91461b2dcf40d61c4d6ca85f8625a7ca2a5535b8bdb9c | @crprofileset.command(name='initserver', pass_context=True)
async def crprofileset_initserver(self, ctx):
'Init CR Profile: server settings.'
server = ctx.message.server
self.model.init_server(server)
(await self.bot.say('Server settings initialized.')) | Init CR Profile: server settings. | crprofile/crprofile.py | crprofileset_initserver | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='initserver', pass_context=True)
async def crprofileset_initserver(self, ctx):
server = ctx.message.server
self.model.init_server(server)
(await self.bot.say('Server settings initialized.')) | @crprofileset.command(name='initserver', pass_context=True)
async def crprofileset_initserver(self, ctx):
server = ctx.message.server
self.model.init_server(server)
(await self.bot.say('Server settings initialized.'))<|docstring|>Init CR Profile: server settings.<|endoftext|> |
60f239d586f55da8508e28fca1af5bc704af1aab7a21600ce0710ee81554a0fe | @crprofileset.command(name='initplayers', pass_context=True)
async def crprofileset_initplayers(self, ctx):
'Init CR Profile: players settings.'
server = ctx.message.server
self.model.init_players(server)
(await self.bot.say('Clan settings initialized.')) | Init CR Profile: players settings. | crprofile/crprofile.py | crprofileset_initplayers | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='initplayers', pass_context=True)
async def crprofileset_initplayers(self, ctx):
server = ctx.message.server
self.model.init_players(server)
(await self.bot.say('Clan settings initialized.')) | @crprofileset.command(name='initplayers', pass_context=True)
async def crprofileset_initplayers(self, ctx):
server = ctx.message.server
self.model.init_players(server)
(await self.bot.say('Clan settings initialized.'))<|docstring|>Init CR Profile: players settings.<|endoftext|> |
c3e0f632d0ddfff7f762f5408acf5a908bd96660dd74ad501b3dafcf46931851 | @crprofileset.command(name='badgeurl', pass_context=True)
async def crprofileset_badgeurl(self, ctx, url):
'badge URL base.\n\n Format:\n If path is hhttp://domain.com/path/LQQ\n Enter http://domain.com/path/\n '
self.model.badge_url = url
(await self.bot.say('Badge URL updated.'... | badge URL base.
Format:
If path is hhttp://domain.com/path/LQQ
Enter http://domain.com/path/ | crprofile/crprofile.py | crprofileset_badgeurl | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='badgeurl', pass_context=True)
async def crprofileset_badgeurl(self, ctx, url):
'badge URL base.\n\n Format:\n If path is hhttp://domain.com/path/LQQ\n Enter http://domain.com/path/\n '
self.model.badge_url = url
(await self.bot.say('Badge URL updated.'... | @crprofileset.command(name='badgeurl', pass_context=True)
async def crprofileset_badgeurl(self, ctx, url):
'badge URL base.\n\n Format:\n If path is hhttp://domain.com/path/LQQ\n Enter http://domain.com/path/\n '
self.model.badge_url = url
(await self.bot.say('Badge URL updated.'... |
4b98e76512518c1b3057c3edeeb546477fd5231793e6e73cc03e752fe07fc650 | @crprofileset.command(name='apitoken', pass_context=True)
async def crprofileset_apiauth(self, ctx, token):
'API Authentication token.'
self.model.profile_api_token = token
(await self.bot.say('API token saved.')) | API Authentication token. | crprofile/crprofile.py | crprofileset_apiauth | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='apitoken', pass_context=True)
async def crprofileset_apiauth(self, ctx, token):
self.model.profile_api_token = token
(await self.bot.say('API token saved.')) | @crprofileset.command(name='apitoken', pass_context=True)
async def crprofileset_apiauth(self, ctx, token):
self.model.profile_api_token = token
(await self.bot.say('API token saved.'))<|docstring|>API Authentication token.<|endoftext|> |
4bbc19232e68a55af4a01b248db7f04cab94fb900e00494db8f190c37956b734 | @crprofileset.command(name='api_provider', pass_context=True)
async def crprofileset_api_provider(self, ctx, value):
'API Provider.\n\n Accepted values:\n cr-api\n official\n '
if ((value == 'cr-api') or (value == 'official')):
self.model.api_provider = value
(await s... | API Provider.
Accepted values:
cr-api
official | crprofile/crprofile.py | crprofileset_api_provider | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='api_provider', pass_context=True)
async def crprofileset_api_provider(self, ctx, value):
'API Provider.\n\n Accepted values:\n cr-api\n official\n '
if ((value == 'cr-api') or (value == 'official')):
self.model.api_provider = value
(await s... | @crprofileset.command(name='api_provider', pass_context=True)
async def crprofileset_api_provider(self, ctx, value):
'API Provider.\n\n Accepted values:\n cr-api\n official\n '
if ((value == 'cr-api') or (value == 'official')):
self.model.api_provider = value
(await s... |
a8aa16fac31020a284773c96e42d1ebf1b26a0510c811c8fc7a86bfe7d59477f | @crprofileset.command(name='rmmembertag', pass_context=True)
async def crprofileset_rm_member_tag(self, ctx, member: discord.Member):
'Remove player tag of a user.'
server = ctx.message.server
self.model.rm_player_tag(server, member=member)
(await self.bot.say('Removed player tag for {}'.format(member))... | Remove player tag of a user. | crprofile/crprofile.py | crprofileset_rm_member_tag | zodpixel/SML-Cogs | 17 | python | @crprofileset.command(name='rmmembertag', pass_context=True)
async def crprofileset_rm_member_tag(self, ctx, member: discord.Member):
server = ctx.message.server
self.model.rm_player_tag(server, member=member)
(await self.bot.say('Removed player tag for {}'.format(member))) | @crprofileset.command(name='rmmembertag', pass_context=True)
async def crprofileset_rm_member_tag(self, ctx, member: discord.Member):
server = ctx.message.server
self.model.rm_player_tag(server, member=member)
(await self.bot.say('Removed player tag for {}'.format(member)))<|docstring|>Remove player ta... |
e5ffb64fdae9d0de8e516b7223b9fe3026576e2ef7fc98834c2fe37c24d0c145 | @checks.mod_or_permissions()
@crprofileset.command(name='rmtag', pass_context=True)
async def crprofileset_rm_tag(self, ctx, tag):
'Remove player tag of a user.'
server = ctx.message.server
self.model.rm_player_tag(server, tag=tag)
(await self.bot.say('Removed player tag {} from associated member'.forma... | Remove player tag of a user. | crprofile/crprofile.py | crprofileset_rm_tag | zodpixel/SML-Cogs | 17 | python | @checks.mod_or_permissions()
@crprofileset.command(name='rmtag', pass_context=True)
async def crprofileset_rm_tag(self, ctx, tag):
server = ctx.message.server
self.model.rm_player_tag(server, tag=tag)
(await self.bot.say('Removed player tag {} from associated member'.format(tag))) | @checks.mod_or_permissions()
@crprofileset.command(name='rmtag', pass_context=True)
async def crprofileset_rm_tag(self, ctx, tag):
server = ctx.message.server
self.model.rm_player_tag(server, tag=tag)
(await self.bot.say('Removed player tag {} from associated member'.format(tag)))<|docstring|>Remove pl... |
12814ec72dd281090bc7ad509a97ec3ee2881f34cf6415a9da283a7aa6520a3a | @commands.group(pass_context=True, no_pm=True)
async def crprofile(self, ctx):
'Clash Royale Player Profile.'
if (self.model.auth is None):
(await self.bot.say('You must have a cr-api.com developer key to run this command. Please visit http://docs.cr-api.com/#/authentication to learn how to obtain one, ... | Clash Royale Player Profile. | crprofile/crprofile.py | crprofile | zodpixel/SML-Cogs | 17 | python | @commands.group(pass_context=True, no_pm=True)
async def crprofile(self, ctx):
if (self.model.auth is None):
(await self.bot.say('You must have a cr-api.com developer key to run this command. Please visit http://docs.cr-api.com/#/authentication to learn how to obtain one, then run `!crprofileset auth i... | @commands.group(pass_context=True, no_pm=True)
async def crprofile(self, ctx):
if (self.model.auth is None):
(await self.bot.say('You must have a cr-api.com developer key to run this command. Please visit http://docs.cr-api.com/#/authentication to learn how to obtain one, then run `!crprofileset auth i... |
d27cacd0865413498a9d5df45120d5bee702b1dc94e0894f5c4bd1b81c6c4690 | @crprofile.command(name='settag', pass_context=True, no_pm=True)
async def crprofile_settag(self, ctx, playertag, member: discord.Member=None):
'Set playertag to discord member.\n\n Setting tag for yourself:\n !crprofile settag C0G20PR2\n\n Setting tag for others (requires Bot Commander role):\... | Set playertag to discord member.
Setting tag for yourself:
!crprofile settag C0G20PR2
Setting tag for others (requires Bot Commander role):
!crprofile settag C0G20PR2 SML
!crprofile settag C0G20PR2 @SML
!crprofile settag C0G20PR2 @SML#6443 | crprofile/crprofile.py | crprofile_settag | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='settag', pass_context=True, no_pm=True)
async def crprofile_settag(self, ctx, playertag, member: discord.Member=None):
'Set playertag to discord member.\n\n Setting tag for yourself:\n !crprofile settag C0G20PR2\n\n Setting tag for others (requires Bot Commander role):\... | @crprofile.command(name='settag', pass_context=True, no_pm=True)
async def crprofile_settag(self, ctx, playertag, member: discord.Member=None):
'Set playertag to discord member.\n\n Setting tag for yourself:\n !crprofile settag C0G20PR2\n\n Setting tag for others (requires Bot Commander role):\... |
11c0d0981681c84872230169e98ab76a1e1ea664d16df67b7691be828c87e9e7 | @crprofile.command(name='gettag', pass_context=True, no_pm=True)
async def crprofile_gettag(self, ctx, member: discord.Member=None):
'Get playertag from Discord member.'
server = ctx.message.server
author = ctx.message.author
if (member is None):
member = author
tag = (await self.model.membe... | Get playertag from Discord member. | crprofile/crprofile.py | crprofile_gettag | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='gettag', pass_context=True, no_pm=True)
async def crprofile_gettag(self, ctx, member: discord.Member=None):
server = ctx.message.server
author = ctx.message.author
if (member is None):
member = author
tag = (await self.model.member2tag(server, member))
if (tag i... | @crprofile.command(name='gettag', pass_context=True, no_pm=True)
async def crprofile_gettag(self, ctx, member: discord.Member=None):
server = ctx.message.server
author = ctx.message.author
if (member is None):
member = author
tag = (await self.model.member2tag(server, member))
if (tag i... |
77490a0440a6cf932bccae82476a03820475fd9dd28e89c846dfd053fafe11c9 | @crprofile.command(name='tag', pass_context=True, no_pm=True)
async def crprofile_tag(self, ctx, tag):
'Player profile by tag\n\n Display player info\n '
(await self.bot.type())
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_error_msg))
return
... | Player profile by tag
Display player info | crprofile/crprofile.py | crprofile_tag | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='tag', pass_context=True, no_pm=True)
async def crprofile_tag(self, ctx, tag):
'Player profile by tag\n\n Display player info\n '
(await self.bot.type())
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_error_msg))
return
... | @crprofile.command(name='tag', pass_context=True, no_pm=True)
async def crprofile_tag(self, ctx, tag):
'Player profile by tag\n\n Display player info\n '
(await self.bot.type())
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_error_msg))
return
... |
c413b38892e0085628b4f5b5414850c8b083591ab8a9903671ad75f4dc2f9563 | async def get_profile(self, ctx, member: discord.Member=None, **kwargs):
'Logic for profile'
(await self.bot.type())
author = ctx.message.author
server = ctx.message.server
if (member is None):
member = author
tag = (await self.model.member2tag(server, member))
if (tag is None):
... | Logic for profile | crprofile/crprofile.py | get_profile | zodpixel/SML-Cogs | 17 | python | async def get_profile(self, ctx, member: discord.Member=None, **kwargs):
(await self.bot.type())
author = ctx.message.author
server = ctx.message.server
if (member is None):
member = author
tag = (await self.model.member2tag(server, member))
if (tag is None):
(await self.bot... | async def get_profile(self, ctx, member: discord.Member=None, **kwargs):
(await self.bot.type())
author = ctx.message.author
server = ctx.message.server
if (member is None):
member = author
tag = (await self.model.member2tag(server, member))
if (tag is None):
(await self.bot... |
b444a0989c36550efeb363aa064d222974fe1d6e58355a607334ffaec34e41c9 | @crprofile.command(name='get', pass_context=True, no_pm=True)
async def crprofile_get(self, ctx, member: discord.Member=None):
'Player profile\n\n if member is not entered, retrieve own profile\n '
try:
(await self.get_profile(ctx, member, sections=['overview', 'stats']))
except APIErr... | Player profile
if member is not entered, retrieve own profile | crprofile/crprofile.py | crprofile_get | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='get', pass_context=True, no_pm=True)
async def crprofile_get(self, ctx, member: discord.Member=None):
'Player profile\n\n if member is not entered, retrieve own profile\n '
try:
(await self.get_profile(ctx, member, sections=['overview', 'stats']))
except APIErr... | @crprofile.command(name='get', pass_context=True, no_pm=True)
async def crprofile_get(self, ctx, member: discord.Member=None):
'Player profile\n\n if member is not entered, retrieve own profile\n '
try:
(await self.get_profile(ctx, member, sections=['overview', 'stats']))
except APIErr... |
940ee8528da20413fd57725e095bc3c8f5ca117cc457ce0d0752a877aa18ee45 | @crprofile.command(name='cards', pass_context=True, no_pm=True)
async def crprofile_cards(self, ctx, member: discord.Member=None):
'Card collection.'
try:
(await self.get_profile(ctx, member, sections=['cards']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format... | Card collection. | crprofile/crprofile.py | crprofile_cards | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='cards', pass_context=True, no_pm=True)
async def crprofile_cards(self, ctx, member: discord.Member=None):
try:
(await self.get_profile(ctx, member, sections=['cards']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.status, ... | @crprofile.command(name='cards', pass_context=True, no_pm=True)
async def crprofile_cards(self, ctx, member: discord.Member=None):
try:
(await self.get_profile(ctx, member, sections=['cards']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.status, ... |
74a3ba387580ace7487d20b4659928eba14c0b75bea1692aae4e8ba452667067 | @crprofile.command(name='trade', pass_context=True, no_pm=True)
async def crprofile_trade(self, ctx, member: discord.Member=None):
'Tradeable cards.'
try:
(await self.get_profile(ctx, member, sections=['trade']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format... | Tradeable cards. | crprofile/crprofile.py | crprofile_trade | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='trade', pass_context=True, no_pm=True)
async def crprofile_trade(self, ctx, member: discord.Member=None):
try:
(await self.get_profile(ctx, member, sections=['trade']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.status, ... | @crprofile.command(name='trade', pass_context=True, no_pm=True)
async def crprofile_trade(self, ctx, member: discord.Member=None):
try:
(await self.get_profile(ctx, member, sections=['trade']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.status, ... |
a3fe98d114cc72860be71b50b3f5c1fe95a235463d672191fda79439ad8ba2f4 | @crprofile.command(name='tradetag', pass_context=True, no_pm=True)
async def crprofile_tradetag(self, ctx, tag):
'Tradeable cards by tag.'
tag = clean_tag(tag)
try:
(await self.display_profile(ctx, tag, sections=['trade']))
except APIError as e:
(await self.bot.say('API Error {status} {m... | Tradeable cards by tag. | crprofile/crprofile.py | crprofile_tradetag | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='tradetag', pass_context=True, no_pm=True)
async def crprofile_tradetag(self, ctx, tag):
tag = clean_tag(tag)
try:
(await self.display_profile(ctx, tag, sections=['trade']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.... | @crprofile.command(name='tradetag', pass_context=True, no_pm=True)
async def crprofile_tradetag(self, ctx, tag):
tag = clean_tag(tag)
try:
(await self.display_profile(ctx, tag, sections=['trade']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.... |
8f8f3c34f7fa7be9fc85af3af7351176d54aff203618c637f6e5ced05ea1d39a | @crprofile.command(name='chests', pass_context=True, no_pm=True)
async def crprofile_chests(self, ctx, member: discord.Member=None):
'Upcoming chests.'
try:
(await self.get_profile(ctx, member, sections=['chests']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.for... | Upcoming chests. | crprofile/crprofile.py | crprofile_chests | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='chests', pass_context=True, no_pm=True)
async def crprofile_chests(self, ctx, member: discord.Member=None):
try:
(await self.get_profile(ctx, member, sections=['chests']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.statu... | @crprofile.command(name='chests', pass_context=True, no_pm=True)
async def crprofile_chests(self, ctx, member: discord.Member=None):
try:
(await self.get_profile(ctx, member, sections=['chests']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.statu... |
fe8a601d218fe97a1d75c84a66fbb8a6bcd00c974b90636751e010f15d30ee45 | @crprofile.command(name='deck', pass_context=True, no_pm=True)
async def crprofile_deck(self, ctx, member: discord.Member=None):
'Current deck.'
try:
(await self.get_profile(ctx, member, sections=['deck']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(statu... | Current deck. | crprofile/crprofile.py | crprofile_deck | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='deck', pass_context=True, no_pm=True)
async def crprofile_deck(self, ctx, member: discord.Member=None):
try:
(await self.get_profile(ctx, member, sections=['deck']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.status, mes... | @crprofile.command(name='deck', pass_context=True, no_pm=True)
async def crprofile_deck(self, ctx, member: discord.Member=None):
try:
(await self.get_profile(ctx, member, sections=['deck']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.status, mes... |
c1574c30be111726e331c01c0b9f4e707e209d3ac02fb29c77070a7220e41574 | @crprofile.command(name='tagdeck', pass_context=True, no_pm=True)
async def crprofile_tagdeck(self, ctx, tag):
'Current deck of player tag.'
try:
(await self.display_profile(ctx, tag, sections=['deck']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e... | Current deck of player tag. | crprofile/crprofile.py | crprofile_tagdeck | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='tagdeck', pass_context=True, no_pm=True)
async def crprofile_tagdeck(self, ctx, tag):
try:
(await self.display_profile(ctx, tag, sections=['deck']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.status, message=e.message))) | @crprofile.command(name='tagdeck', pass_context=True, no_pm=True)
async def crprofile_tagdeck(self, ctx, tag):
try:
(await self.display_profile(ctx, tag, sections=['deck']))
except APIError as e:
(await self.bot.say('API Error {status} {message}'.format(status=e.status, message=e.message)))... |
a2435975d09dc196b33849f9725888a5d8e6c6835facb44b85ea1f56a4ee111e | @crprofile.command(name='mini', pass_context=True, no_pm=True)
async def crprofile_mini(self, ctx, member: discord.Member=None):
'Player profile\n\n if member is not entered, retrieve own profile\n '
try:
(await self.get_profile(ctx, member, sections=['overview']))
except APIError as e... | Player profile
if member is not entered, retrieve own profile | crprofile/crprofile.py | crprofile_mini | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='mini', pass_context=True, no_pm=True)
async def crprofile_mini(self, ctx, member: discord.Member=None):
'Player profile\n\n if member is not entered, retrieve own profile\n '
try:
(await self.get_profile(ctx, member, sections=['overview']))
except APIError as e... | @crprofile.command(name='mini', pass_context=True, no_pm=True)
async def crprofile_mini(self, ctx, member: discord.Member=None):
'Player profile\n\n if member is not entered, retrieve own profile\n '
try:
(await self.get_profile(ctx, member, sections=['overview']))
except APIError as e... |
3feb0c6392176d9d847a270a99debe87d3d4321f70908a3974b02f0bdc86a4d6 | @crprofile.command(name='minitag', pass_context=True, no_pm=True)
async def crprofile_mini(self, ctx, tag):
'Player profile\n\n if member is not entered, retrieve own profile\n '
(await self.bot.type())
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_erro... | Player profile
if member is not entered, retrieve own profile | crprofile/crprofile.py | crprofile_mini | zodpixel/SML-Cogs | 17 | python | @crprofile.command(name='minitag', pass_context=True, no_pm=True)
async def crprofile_mini(self, ctx, tag):
'Player profile\n\n if member is not entered, retrieve own profile\n '
(await self.bot.type())
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_erro... | @crprofile.command(name='minitag', pass_context=True, no_pm=True)
async def crprofile_mini(self, ctx, tag):
'Player profile\n\n if member is not entered, retrieve own profile\n '
(await self.bot.type())
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_erro... |
086ab6ad0a344e6ce38dbf67cbe2b8d70a27d7fceb4e46e5107241a43a9e2bd0 | async def display_profile(self, ctx, tag, **kwargs):
'Display profile.'
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_error_msg))
return
try:
player_data = (await self.model.player_data(sctag.tag))
except json.decoder.JSONDecodeError:
play... | Display profile. | crprofile/crprofile.py | display_profile | zodpixel/SML-Cogs | 17 | python | async def display_profile(self, ctx, tag, **kwargs):
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_error_msg))
return
try:
player_data = (await self.model.player_data(sctag.tag))
except json.decoder.JSONDecodeError:
player_data = self.mod... | async def display_profile(self, ctx, tag, **kwargs):
sctag = SCTag(tag)
if (not sctag.valid):
(await self.bot.say(sctag.invalid_error_msg))
return
try:
player_data = (await self.model.player_data(sctag.tag))
except json.decoder.JSONDecodeError:
player_data = self.mod... |
65bd0a6f4fb328cc4a59f83c3ee077efd6773e7253da504622ae0ed9c038a9b5 | def embed_profile_overview(self, player: CRPlayerModel, server=None, color=None):
'Discord Embed: profile overview.'
bem = self.bot_emoji.name
member = self.model.tag2member(server, player.tag)
mention = '_'
if (member is not None):
mention = member.mention
profile_url = 'http://RoyaleAP... | Discord Embed: profile overview. | crprofile/crprofile.py | embed_profile_overview | zodpixel/SML-Cogs | 17 | python | def embed_profile_overview(self, player: CRPlayerModel, server=None, color=None):
bem = self.bot_emoji.name
member = self.model.tag2member(server, player.tag)
mention = '_'
if (member is not None):
mention = member.mention
profile_url = 'http://RoyaleAPI.com/player/{}'.format(player.tag... | def embed_profile_overview(self, player: CRPlayerModel, server=None, color=None):
bem = self.bot_emoji.name
member = self.model.tag2member(server, player.tag)
mention = '_'
if (member is not None):
mention = member.mention
profile_url = 'http://RoyaleAPI.com/player/{}'.format(player.tag... |
6b808a4c52af042074617ec6cba61df9b6ecc730852ef57b001f6b29aed5f2be | def embed_profile_stats(self, player: CRPlayerModel, color=None):
'Discord Embed: profile stats.'
em = discord.Embed(title=' ', color=color)
bem = self.bot_emoji.name
def fmt(num, emoji_name):
emoji = self.bot_emoji.name(emoji_name)
if (emoji is not None):
return '{:,} {}'.f... | Discord Embed: profile stats. | crprofile/crprofile.py | embed_profile_stats | zodpixel/SML-Cogs | 17 | python | def embed_profile_stats(self, player: CRPlayerModel, color=None):
em = discord.Embed(title=' ', color=color)
bem = self.bot_emoji.name
def fmt(num, emoji_name):
emoji = self.bot_emoji.name(emoji_name)
if (emoji is not None):
return '{:,} {}'.format(num, emoji)
if (playe... | def embed_profile_stats(self, player: CRPlayerModel, color=None):
em = discord.Embed(title=' ', color=color)
bem = self.bot_emoji.name
def fmt(num, emoji_name):
emoji = self.bot_emoji.name(emoji_name)
if (emoji is not None):
return '{:,} {}'.format(num, emoji)
if (playe... |
2615bd807a442e08d8bd376f891cd2826c809f592a33ea5a12fb7e9cf5f29ec1 | def embed_profile_cards(self, player: CRPlayerModel, color=None):
'Card Collection.'
profile_url = 'http://RoyaleAPI.com/player/{}/cards'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}'.format(player.name, player.tag), color=color, url=profile_url)
cards = player.card_collection(self.bo... | Card Collection. | crprofile/crprofile.py | embed_profile_cards | zodpixel/SML-Cogs | 17 | python | def embed_profile_cards(self, player: CRPlayerModel, color=None):
profile_url = 'http://RoyaleAPI.com/player/{}/cards'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}'.format(player.name, player.tag), color=color, url=profile_url)
cards = player.card_collection(self.bot_emoji)
cards... | def embed_profile_cards(self, player: CRPlayerModel, color=None):
profile_url = 'http://RoyaleAPI.com/player/{}/cards'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}'.format(player.name, player.tag), color=color, url=profile_url)
cards = player.card_collection(self.bot_emoji)
cards... |
9aa58a6f633a868223efc154ea35590be42f22061eab36b1a9e1ff15568fc4de | def embed_profile_chests(self, player: CRPlayerModel, color=None):
'Upcoming chests'
profile_url = 'http://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}: Chest Cycle'.format(player.name, player.tag), color=color, url=profile_url)
em.add_field(name='Chests', val... | Upcoming chests | crprofile/crprofile.py | embed_profile_chests | zodpixel/SML-Cogs | 17 | python | def embed_profile_chests(self, player: CRPlayerModel, color=None):
profile_url = 'http://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}: Chest Cycle'.format(player.name, player.tag), color=color, url=profile_url)
em.add_field(name='Chests', value=player.chest_l... | def embed_profile_chests(self, player: CRPlayerModel, color=None):
profile_url = 'http://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}: Chest Cycle'.format(player.name, player.tag), color=color, url=profile_url)
em.add_field(name='Chests', value=player.chest_l... |
f91916684b8b2b819f61b6ed0abcc15962b03e0c9e80969dbbfc17e39c45f0e7 | def embed_profile_deck(self, player: CRPlayerModel, color=None):
'Current deck.'
profile_url = 'https://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
desc_copy = '[Copy deck]({url})'.format(url=player.deck_link)
desc_stats = '[Deck stats]({url})'.format(url=player.deck_stats_url)
desc_log ... | Current deck. | crprofile/crprofile.py | embed_profile_deck | zodpixel/SML-Cogs | 17 | python | def embed_profile_deck(self, player: CRPlayerModel, color=None):
profile_url = 'https://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
desc_copy = '[Copy deck]({url})'.format(url=player.deck_link)
desc_stats = '[Deck stats]({url})'.format(url=player.deck_stats_url)
desc_log = '[Battle Log]... | def embed_profile_deck(self, player: CRPlayerModel, color=None):
profile_url = 'https://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
desc_copy = '[Copy deck]({url})'.format(url=player.deck_link)
desc_stats = '[Deck stats]({url})'.format(url=player.deck_stats_url)
desc_log = '[Battle Log]... |
63511c16a84801aa03086191cdab4f7b91f350f6d05866139a50be81e516246f | def embed_profile_trade(self, player: CRPlayerModel, color=None):
'Current deck.'
decklink_url = player.deck_link
profile_url = 'http://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}'.format(player.name, player.tag), color=color, url=decklink_url)
trade_list... | Current deck. | crprofile/crprofile.py | embed_profile_trade | zodpixel/SML-Cogs | 17 | python | def embed_profile_trade(self, player: CRPlayerModel, color=None):
decklink_url = player.deck_link
profile_url = 'http://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}'.format(player.name, player.tag), color=color, url=decklink_url)
trade_list = player.trade... | def embed_profile_trade(self, player: CRPlayerModel, color=None):
decklink_url = player.deck_link
profile_url = 'http://RoyaleAPI.com/player/{}'.format(player.tag.lstrip('#'))
em = discord.Embed(title='{} #{}'.format(player.name, player.tag), color=color, url=decklink_url)
trade_list = player.trade... |
4bbeccb1515bf344eea3a01b8d6a73b0d4a5fb8362260d305552474b024d7660 | def embeds_profile(self, player: CRPlayerModel, server=None, sections=('overview', 'stats')):
'Return Discord Embed of player profile.'
embeds = []
color = random_discord_color()
if ('overview' in sections):
embeds.append(self.embed_profile_overview(player, server=server, color=color))
if ('... | Return Discord Embed of player profile. | crprofile/crprofile.py | embeds_profile | zodpixel/SML-Cogs | 17 | python | def embeds_profile(self, player: CRPlayerModel, server=None, sections=('overview', 'stats')):
embeds = []
color = random_discord_color()
if ('overview' in sections):
embeds.append(self.embed_profile_overview(player, server=server, color=color))
if ('stats' in sections):
embeds.appen... | def embeds_profile(self, player: CRPlayerModel, server=None, sections=('overview', 'stats')):
embeds = []
color = random_discord_color()
if ('overview' in sections):
embeds.append(self.embed_profile_overview(player, server=server, color=color))
if ('stats' in sections):
embeds.appen... |
a7d228ac4d320a6b1e74d8b772422c7a1f1e447355aabfc2a550000c320f797c | async def on_message(self, msg):
'Do transforms.'
if (self.bot.user.name != 'R2.Dev'):
(await self.transform_friendlink(msg)) | Do transforms. | crprofile/crprofile.py | on_message | zodpixel/SML-Cogs | 17 | python | async def on_message(self, msg):
if (self.bot.user.name != 'R2.Dev'):
(await self.transform_friendlink(msg)) | async def on_message(self, msg):
if (self.bot.user.name != 'R2.Dev'):
(await self.transform_friendlink(msg))<|docstring|>Do transforms.<|endoftext|> |
7eeb60676f66cea81751dd93763583be0a2f5a5bf553160b4bb85fd7c3bb56b5 | async def transform_friendlink(self, msg):
'Convert friend invite links to embeds.\n\n https://link.clashroyale.com/invite/friend/en?tag={tag}&token={token}&platform={platform}\n '
m = re.search('https://link.clashroyale.com/invite/friend/..\\?tag=([A-Z0-9]+)&token=([a-z0-9]+)&platform=([A-Za-z0-9... | Convert friend invite links to embeds.
https://link.clashroyale.com/invite/friend/en?tag={tag}&token={token}&platform={platform} | crprofile/crprofile.py | transform_friendlink | zodpixel/SML-Cogs | 17 | python | async def transform_friendlink(self, msg):
'Convert friend invite links to embeds.\n\n https://link.clashroyale.com/invite/friend/en?tag={tag}&token={token}&platform={platform}\n '
m = re.search('https://link.clashroyale.com/invite/friend/..\\?tag=([A-Z0-9]+)&token=([a-z0-9]+)&platform=([A-Za-z0-9... | async def transform_friendlink(self, msg):
'Convert friend invite links to embeds.\n\n https://link.clashroyale.com/invite/friend/en?tag={tag}&token={token}&platform={platform}\n '
m = re.search('https://link.clashroyale.com/invite/friend/..\\?tag=([A-Z0-9]+)&token=([a-z0-9]+)&platform=([A-Za-z0-9... |
f621ba1c7430e34b3fc6e33a77ce3f35409b38f7dc6827f1a560a43b097a0a66 | def _get_updated_endpoints(original_end_points):
"Adds the keys 'logits' and 'probs' to the\n end points dictionary of ResNet50-v2.\n\n Args:\n original_end_points (dict): Original dictionary of end points\n\n Returns:\n dict: Dictionary of end points with the new keys.\n "
end_points ... | Adds the keys 'logits' and 'probs' to the
end points dictionary of ResNet50-v2.
Args:
original_end_points (dict): Original dictionary of end points
Returns:
dict: Dictionary of end points with the new keys. | shield/models/resnet_50_v2.py | _get_updated_endpoints | yfor1008/jpeg-defense | 0 | python | def _get_updated_endpoints(original_end_points):
"Adds the keys 'logits' and 'probs' to the\n end points dictionary of ResNet50-v2.\n\n Args:\n original_end_points (dict): Original dictionary of end points\n\n Returns:\n dict: Dictionary of end points with the new keys.\n "
end_points ... | def _get_updated_endpoints(original_end_points):
"Adds the keys 'logits' and 'probs' to the\n end points dictionary of ResNet50-v2.\n\n Args:\n original_end_points (dict): Original dictionary of end points\n\n Returns:\n dict: Dictionary of end points with the new keys.\n "
end_points ... |
366c8c3b7a81da3d5dfa2eeab171251b21b42444be7eb016cb3a24384984d640 | def __init__(self, x, num_classes=15, is_training=False):
'Initializes the tensorflow graph for the ResNet50-v2 model.\n\n Args:\n x (tf.Variable): The variable in the tensorflow graph\n that feeds into the model nodes.\n num_classes (int):\n Number of pred... | Initializes the tensorflow graph for the ResNet50-v2 model.
Args:
x (tf.Variable): The variable in the tensorflow graph
that feeds into the model nodes.
num_classes (int):
Number of predicted classes for classification tasks.
If 0 or None, the features before the logit layer are returne... | shield/models/resnet_50_v2.py | __init__ | yfor1008/jpeg-defense | 0 | python | def __init__(self, x, num_classes=15, is_training=False):
'Initializes the tensorflow graph for the ResNet50-v2 model.\n\n Args:\n x (tf.Variable): The variable in the tensorflow graph\n that feeds into the model nodes.\n num_classes (int):\n Number of pred... | def __init__(self, x, num_classes=15, is_training=False):
'Initializes the tensorflow graph for the ResNet50-v2 model.\n\n Args:\n x (tf.Variable): The variable in the tensorflow graph\n that feeds into the model nodes.\n num_classes (int):\n Number of pred... |
6056fa0e5e01d95be165096bb123bb343087cae7f8f68dd46b75d1ecb17798fc | def load_weights(self, checkpoint_path, sess=None):
'Load weights from a checkpoint file into the tensorflow graph.\n\n Args:\n checkpoint_path (str): Path to the checkpoint file.\n sess (tf.Session): The tensorflow session holding the model graph.\n '
if (sess is None):
... | Load weights from a checkpoint file into the tensorflow graph.
Args:
checkpoint_path (str): Path to the checkpoint file.
sess (tf.Session): The tensorflow session holding the model graph. | shield/models/resnet_50_v2.py | load_weights | yfor1008/jpeg-defense | 0 | python | def load_weights(self, checkpoint_path, sess=None):
'Load weights from a checkpoint file into the tensorflow graph.\n\n Args:\n checkpoint_path (str): Path to the checkpoint file.\n sess (tf.Session): The tensorflow session holding the model graph.\n '
if (sess is None):
... | def load_weights(self, checkpoint_path, sess=None):
'Load weights from a checkpoint file into the tensorflow graph.\n\n Args:\n checkpoint_path (str): Path to the checkpoint file.\n sess (tf.Session): The tensorflow session holding the model graph.\n '
if (sess is None):
... |
902a93f2b2c564abcffe48695341a297121a25b140f9e92b4f973407ac341c68 | def get_params(self):
"Lists the model's parameters.\n\n Returns:\n list: A list of the model's parameters.\n "
return None | Lists the model's parameters.
Returns:
list: A list of the model's parameters. | shield/models/resnet_50_v2.py | get_params | yfor1008/jpeg-defense | 0 | python | def get_params(self):
"Lists the model's parameters.\n\n Returns:\n list: A list of the model's parameters.\n "
return None | def get_params(self):
"Lists the model's parameters.\n\n Returns:\n list: A list of the model's parameters.\n "
return None<|docstring|>Lists the model's parameters.
Returns:
list: A list of the model's parameters.<|endoftext|> |
7e60feacda828fe18c636f74784a8f15227c6611ebc46735283b1704a6f3408f | def fprop(self, x):
'Exposes all the layers of the model.\n\n Args:\n x (tf.Variable): Tensor which is input to the model.\n\n Returns:\n dict: A dictionary mapping layer names to the corresponding\n node in the tensorflow graph.\n '
if (x is self.x):
... | Exposes all the layers of the model.
Args:
x (tf.Variable): Tensor which is input to the model.
Returns:
dict: A dictionary mapping layer names to the corresponding
node in the tensorflow graph. | shield/models/resnet_50_v2.py | fprop | yfor1008/jpeg-defense | 0 | python | def fprop(self, x):
'Exposes all the layers of the model.\n\n Args:\n x (tf.Variable): Tensor which is input to the model.\n\n Returns:\n dict: A dictionary mapping layer names to the corresponding\n node in the tensorflow graph.\n '
if (x is self.x):
... | def fprop(self, x):
'Exposes all the layers of the model.\n\n Args:\n x (tf.Variable): Tensor which is input to the model.\n\n Returns:\n dict: A dictionary mapping layer names to the corresponding\n node in the tensorflow graph.\n '
if (x is self.x):
... |
3000f1d88d18c6360fff732db5491fc9d37fa74789e57c659e3dde92e23f36bb | def finalize_options(self):
'Abstract method that is required to be overwritten' | Abstract method that is required to be overwritten | setup.py | finalize_options | mpavlase/nginx-config-builder | 149 | python | def finalize_options(self):
| def finalize_options(self):
<|docstring|>Abstract method that is required to be overwritten<|endoftext|> |
22d06d819c11bd70f87fba9923c4366111478aa18202381e277b79529f6abaf7 | def getHint(self, secret, guess):
'\n :type secret: str\n :type guess: str\n :rtype: str\n '
cnt = defaultdict(int)
A = 0
B = 0
for c in secret:
cnt[c] += 1
for (i, v) in enumerate(guess):
if (v == secret[i]):
A += 1
cnt[v] -= 1... | :type secret: str
:type guess: str
:rtype: str | 299 Bulls and Cows.py | getHint | ChiFire/legend_LeetCode | 1 | python | def getHint(self, secret, guess):
'\n :type secret: str\n :type guess: str\n :rtype: str\n '
cnt = defaultdict(int)
A = 0
B = 0
for c in secret:
cnt[c] += 1
for (i, v) in enumerate(guess):
if (v == secret[i]):
A += 1
cnt[v] -= 1... | def getHint(self, secret, guess):
'\n :type secret: str\n :type guess: str\n :rtype: str\n '
cnt = defaultdict(int)
A = 0
B = 0
for c in secret:
cnt[c] += 1
for (i, v) in enumerate(guess):
if (v == secret[i]):
A += 1
cnt[v] -= 1... |
e9d100e4ca0766691773a21748317edff1e72f272b73c70493106a731b7545f8 | def test_anbieter_mapping(self):
'\n Test that all mapping point to correct fields\n '
for field in set(Anbieter.FIELD_NAME_MAPPING.values()):
if (field is None):
continue
else:
Anbieter._meta.get_field(field) | Test that all mapping point to correct fields | anbieter/tests.py | test_anbieter_mapping | CarliJoy/RoWoOekostromDB | 0 | python | def test_anbieter_mapping(self):
'\n \n '
for field in set(Anbieter.FIELD_NAME_MAPPING.values()):
if (field is None):
continue
else:
Anbieter._meta.get_field(field) | def test_anbieter_mapping(self):
'\n \n '
for field in set(Anbieter.FIELD_NAME_MAPPING.values()):
if (field is None):
continue
else:
Anbieter._meta.get_field(field)<|docstring|>Test that all mapping point to correct fields<|endoftext|> |
89bef0cb915d5b31719d8fe8042a66e020419c481c64a06c1cb88e51606573cd | def test_homepage_kriterium_mapping(self):
'\n Test that all mapping point to correct fields\n '
for field in set(HomepageKriterium.FIELD_NAME_MAPPING.values()):
HomepageKriterium._meta.get_field(field) | Test that all mapping point to correct fields | anbieter/tests.py | test_homepage_kriterium_mapping | CarliJoy/RoWoOekostromDB | 0 | python | def test_homepage_kriterium_mapping(self):
'\n \n '
for field in set(HomepageKriterium.FIELD_NAME_MAPPING.values()):
HomepageKriterium._meta.get_field(field) | def test_homepage_kriterium_mapping(self):
'\n \n '
for field in set(HomepageKriterium.FIELD_NAME_MAPPING.values()):
HomepageKriterium._meta.get_field(field)<|docstring|>Test that all mapping point to correct fields<|endoftext|> |
0fdf527f6c7b9ba1342f660a94d40e9931a31ab34ead6dde51c5e91eac198841 | def np_arr_to_poly(np_arr):
' Using numpy 2d array ([0]-h, [1]-w) to construct polygon.\n\n Parameters\n -------\n np_arr : np.array\n contour with standard numpy 2d array format\n\n Returns\n -------\n poly : Polygon\n contour with shapely polygon format\n\n '
np_arr = swap_w... | Using numpy 2d array ([0]-h, [1]-w) to construct polygon.
Parameters
-------
np_arr : np.array
contour with standard numpy 2d array format
Returns
-------
poly : Polygon
contour with shapely polygon format | pycontour/poly_transform.py | np_arr_to_poly | PingjunChen/pycontour | 8 | python | def np_arr_to_poly(np_arr):
' Using numpy 2d array ([0]-h, [1]-w) to construct polygon.\n\n Parameters\n -------\n np_arr : np.array\n contour with standard numpy 2d array format\n\n Returns\n -------\n poly : Polygon\n contour with shapely polygon format\n\n '
np_arr = swap_w... | def np_arr_to_poly(np_arr):
' Using numpy 2d array ([0]-h, [1]-w) to construct polygon.\n\n Parameters\n -------\n np_arr : np.array\n contour with standard numpy 2d array format\n\n Returns\n -------\n poly : Polygon\n contour with shapely polygon format\n\n '
np_arr = swap_w... |
63c70674d96ecdbab3a394e90310ec7b05b7b869b9bfed54aedafe055975310a | def point_list_to_poly(point_list):
' Using point list to construct polygon.\n\n Parameters\n -------\n point_list : list\n list of point set ([0]-h, [1]-w)\n\n Returns\n -------\n poly : Polygon\n contour with shapely polygon format\n\n '
wh_point_list = []
for ind in np.... | Using point list to construct polygon.
Parameters
-------
point_list : list
list of point set ([0]-h, [1]-w)
Returns
-------
poly : Polygon
contour with shapely polygon format | pycontour/poly_transform.py | point_list_to_poly | PingjunChen/pycontour | 8 | python | def point_list_to_poly(point_list):
' Using point list to construct polygon.\n\n Parameters\n -------\n point_list : list\n list of point set ([0]-h, [1]-w)\n\n Returns\n -------\n poly : Polygon\n contour with shapely polygon format\n\n '
wh_point_list = []
for ind in np.... | def point_list_to_poly(point_list):
' Using point list to construct polygon.\n\n Parameters\n -------\n point_list : list\n list of point set ([0]-h, [1]-w)\n\n Returns\n -------\n poly : Polygon\n contour with shapely polygon format\n\n '
wh_point_list = []
for ind in np.... |
33d9cb29b3dad2f45841ce9563deb3a7d285499f027b81801afcf3cf3ecf6247 | def bbox_to_poly(min_h, min_w, max_h, max_w):
' Using bounding box to construct polygon.\n\n Parameters\n -------\n min_h : int\n minimum y coordinate of polygon\n min_w : int\n minimum x coordinate of polygon\n max_h : int\n maximum y coordinate of polygon\n max_w : int\n ... | Using bounding box to construct polygon.
Parameters
-------
min_h : int
minimum y coordinate of polygon
min_w : int
minimum x coordinate of polygon
max_h : int
maximum y coordinate of polygon
max_w : int
maximum x coordinate of polygon
Returns
-------
poly : Polygon
contour with shapely polygon fo... | pycontour/poly_transform.py | bbox_to_poly | PingjunChen/pycontour | 8 | python | def bbox_to_poly(min_h, min_w, max_h, max_w):
' Using bounding box to construct polygon.\n\n Parameters\n -------\n min_h : int\n minimum y coordinate of polygon\n min_w : int\n minimum x coordinate of polygon\n max_h : int\n maximum y coordinate of polygon\n max_w : int\n ... | def bbox_to_poly(min_h, min_w, max_h, max_w):
' Using bounding box to construct polygon.\n\n Parameters\n -------\n min_h : int\n minimum y coordinate of polygon\n min_w : int\n minimum x coordinate of polygon\n max_h : int\n maximum y coordinate of polygon\n max_w : int\n ... |
4b63b3d6162334c541330e756fcfb39d3efd36b1fa65d57d77e804f356fc84a3 | def poly_to_np_arr(poly):
' Convert shapely Polygon to numpy 2d array ([0]-h, [1]-w).\n\n Parameters\n -------\n poly : Polygon\n contour with shapely polygon format\n\n Returns\n -------\n cnt_arr : np.array\n contour with standard numpy 2d array format\n\n '
(x_coors, y_coor... | Convert shapely Polygon to numpy 2d array ([0]-h, [1]-w).
Parameters
-------
poly : Polygon
contour with shapely polygon format
Returns
-------
cnt_arr : np.array
contour with standard numpy 2d array format | pycontour/poly_transform.py | poly_to_np_arr | PingjunChen/pycontour | 8 | python | def poly_to_np_arr(poly):
' Convert shapely Polygon to numpy 2d array ([0]-h, [1]-w).\n\n Parameters\n -------\n poly : Polygon\n contour with shapely polygon format\n\n Returns\n -------\n cnt_arr : np.array\n contour with standard numpy 2d array format\n\n '
(x_coors, y_coor... | def poly_to_np_arr(poly):
' Convert shapely Polygon to numpy 2d array ([0]-h, [1]-w).\n\n Parameters\n -------\n poly : Polygon\n contour with shapely polygon format\n\n Returns\n -------\n cnt_arr : np.array\n contour with standard numpy 2d array format\n\n '
(x_coors, y_coor... |
bb9bc7de05f6be28311bc5f0dd01a4ac108a94b2e158f2448954b54b79bd6b3b | def reshape(a, recshape=None):
'Convert a nested, non-string iterable into a flat generator and its shape.\n Raggedly shaped data will be processed recursively by calling recshape.\n If recshape is None, then ragged data wil raise ShapeError.\n To leave ragged data unshaped, pass recshape=unshape.\n '
... | Convert a nested, non-string iterable into a flat generator and its shape.
Raggedly shaped data will be processed recursively by calling recshape.
If recshape is None, then ragged data wil raise ShapeError.
To leave ragged data unshaped, pass recshape=unshape. | titanfp/titanic/ndarray.py | reshape | billzorn/fpunreal | 4 | python | def reshape(a, recshape=None):
'Convert a nested, non-string iterable into a flat generator and its shape.\n Raggedly shaped data will be processed recursively by calling recshape.\n If recshape is None, then ragged data wil raise ShapeError.\n To leave ragged data unshaped, pass recshape=unshape.\n '
... | def reshape(a, recshape=None):
'Convert a nested, non-string iterable into a flat generator and its shape.\n Raggedly shaped data will be processed recursively by calling recshape.\n If recshape is None, then ragged data wil raise ShapeError.\n To leave ragged data unshaped, pass recshape=unshape.\n '
... |
1e76c5e350fc96dd064a1bb4a23e45451df67666d104a81444ddbb95a5272332 | def unshape_tuple(data, shape):
'Expand a flat iterable and its shape into a nested tuple.\n '
a = data
for dim in reversed(shape[1:]):
a = zip(*([iter(a)] * dim))
return tuple(a) | Expand a flat iterable and its shape into a nested tuple. | titanfp/titanic/ndarray.py | unshape_tuple | billzorn/fpunreal | 4 | python | def unshape_tuple(data, shape):
'\n '
a = data
for dim in reversed(shape[1:]):
a = zip(*([iter(a)] * dim))
return tuple(a) | def unshape_tuple(data, shape):
'\n '
a = data
for dim in reversed(shape[1:]):
a = zip(*([iter(a)] * dim))
return tuple(a)<|docstring|>Expand a flat iterable and its shape into a nested tuple.<|endoftext|> |
dde06d46b03b19604d824d010d787a2d5640b0da6c4759c1aac6825b3b621797 | def unshape_list(data, shape):
'Expand a flat list and its shape into a nested list.\n '
a = data
for dim in reversed(shape[1:]):
a = [a[(chunk * dim):((chunk + 1) * dim)] for chunk in range((len(a) // dim))]
return a | Expand a flat list and its shape into a nested list. | titanfp/titanic/ndarray.py | unshape_list | billzorn/fpunreal | 4 | python | def unshape_list(data, shape):
'\n '
a = data
for dim in reversed(shape[1:]):
a = [a[(chunk * dim):((chunk + 1) * dim)] for chunk in range((len(a) // dim))]
return a | def unshape_list(data, shape):
'\n '
a = data
for dim in reversed(shape[1:]):
a = [a[(chunk * dim):((chunk + 1) * dim)] for chunk in range((len(a) // dim))]
return a<|docstring|>Expand a flat list and its shape into a nested list.<|endoftext|> |
978ba36717f50178de977e87b75fb243d3be6aee795806ddcff6bd3181d6ca9c | def unshape_gen(data, shape):
'Expand a flat list and its shape into a nested generator.\n '
a = data
for dim in reversed(shape[1:]):
a = (a[(chunk * dim):((chunk + 1) * dim)] for chunk in range((len(a) // dim)))
return a | Expand a flat list and its shape into a nested generator. | titanfp/titanic/ndarray.py | unshape_gen | billzorn/fpunreal | 4 | python | def unshape_gen(data, shape):
'\n '
a = data
for dim in reversed(shape[1:]):
a = (a[(chunk * dim):((chunk + 1) * dim)] for chunk in range((len(a) // dim)))
return a | def unshape_gen(data, shape):
'\n '
a = data
for dim in reversed(shape[1:]):
a = (a[(chunk * dim):((chunk + 1) * dim)] for chunk in range((len(a) // dim)))
return a<|docstring|>Expand a flat list and its shape into a nested generator.<|endoftext|> |
a327ba1f1f3e87d84a764dc061728171f3aed8ca83a8c08a9830691da4a84eba | def describe(a, descr=repr, sep=', ', lparen='(', rparen=')'):
'Convert a shaped or unshaped iterable into a one-line string,\n using the provided printing method and separators.\n '
if (isinstance(a, Iterable) and (not isinstance(a, str))):
return ''.join([lparen, sep.join((describe(elt, descr=de... | Convert a shaped or unshaped iterable into a one-line string,
using the provided printing method and separators. | titanfp/titanic/ndarray.py | describe | billzorn/fpunreal | 4 | python | def describe(a, descr=repr, sep=', ', lparen='(', rparen=')'):
'Convert a shaped or unshaped iterable into a one-line string,\n using the provided printing method and separators.\n '
if (isinstance(a, Iterable) and (not isinstance(a, str))):
return .join([lparen, sep.join((describe(elt, descr=desc... | def describe(a, descr=repr, sep=', ', lparen='(', rparen=')'):
'Convert a shaped or unshaped iterable into a one-line string,\n using the provided printing method and separators.\n '
if (isinstance(a, Iterable) and (not isinstance(a, str))):
return .join([lparen, sep.join((describe(elt, descr=desc... |
16ec861dc4a0c96367d3b44ad1ed28d809cd7b7a3c4860f644edbd2348e56a0a | def describe_nd(a, descr=repr, dimsep=dimsep_array, lparen='(', rparen=')', depth=0):
'Convert a shaped or unshaped iterable into a string and a count of dimensions,\n using the provided printing method and separators.\n dimsep is a function that computes the separator given a logical depth and height\n fr... | Convert a shaped or unshaped iterable into a string and a count of dimensions,
using the provided printing method and separators.
dimsep is a function that computes the separator given a logical depth and height
from the top and bottom of the data structure, and the parentheses. | titanfp/titanic/ndarray.py | describe_nd | billzorn/fpunreal | 4 | python | def describe_nd(a, descr=repr, dimsep=dimsep_array, lparen='(', rparen=')', depth=0):
'Convert a shaped or unshaped iterable into a string and a count of dimensions,\n using the provided printing method and separators.\n dimsep is a function that computes the separator given a logical depth and height\n fr... | def describe_nd(a, descr=repr, dimsep=dimsep_array, lparen='(', rparen=')', depth=0):
'Convert a shaped or unshaped iterable into a string and a count of dimensions,\n using the provided printing method and separators.\n dimsep is a function that computes the separator given a logical depth and height\n fr... |
b711967069254a36e269af2ac96d111c8e0e3b0591b603401fa7328eb1e22e20 | def locate(shape, pos):
'Given a shape and a position vector, return the index of that position in the flat array.\n '
idx = 0
scale = 1
for (dim, coord) in zip(reversed(shape), reversed(pos)):
idx += (coord * scale)
scale *= dim
return idx | Given a shape and a position vector, return the index of that position in the flat array. | titanfp/titanic/ndarray.py | locate | billzorn/fpunreal | 4 | python | def locate(shape, pos):
'\n '
idx = 0
scale = 1
for (dim, coord) in zip(reversed(shape), reversed(pos)):
idx += (coord * scale)
scale *= dim
return idx | def locate(shape, pos):
'\n '
idx = 0
scale = 1
for (dim, coord) in zip(reversed(shape), reversed(pos)):
idx += (coord * scale)
scale *= dim
return idx<|docstring|>Given a shape and a position vector, return the index of that position in the flat array.<|endoftext|> |
7f060b6f522785774e35cd6a883950cd93448eacfe8bc4eca5080ad9cd72ea55 | def position(shape, idx):
'Given a shape and a flat index, return the corresponding position vector.\n '
quot = idx
pos = []
for dim in reversed(shape):
(quot, rem) = divmod(quot, dim)
pos.append(rem)
return tuple(reversed(pos)) | Given a shape and a flat index, return the corresponding position vector. | titanfp/titanic/ndarray.py | position | billzorn/fpunreal | 4 | python | def position(shape, idx):
'\n '
quot = idx
pos = []
for dim in reversed(shape):
(quot, rem) = divmod(quot, dim)
pos.append(rem)
return tuple(reversed(pos)) | def position(shape, idx):
'\n '
quot = idx
pos = []
for dim in reversed(shape):
(quot, rem) = divmod(quot, dim)
pos.append(rem)
return tuple(reversed(pos))<|docstring|>Given a shape and a flat index, return the corresponding position vector.<|endoftext|> |
569b0acbcc486ba568b1b9d987ab4c2d39bc113c3f20c021cc282468b4f3b76e | def check_bounds(shape, pos):
'Given a shape, check if a position vector is in bounds for that shape.\n Raises IndexError if the position is out of bounds.\n '
for (dim, coord) in zip(shape, pos):
if ((coord < 0) or (dim <= coord)):
raise IndexError(f'{pos!r} out of range for shape {sh... | Given a shape, check if a position vector is in bounds for that shape.
Raises IndexError if the position is out of bounds. | titanfp/titanic/ndarray.py | check_bounds | billzorn/fpunreal | 4 | python | def check_bounds(shape, pos):
'Given a shape, check if a position vector is in bounds for that shape.\n Raises IndexError if the position is out of bounds.\n '
for (dim, coord) in zip(shape, pos):
if ((coord < 0) or (dim <= coord)):
raise IndexError(f'{pos!r} out of range for shape {sh... | def check_bounds(shape, pos):
'Given a shape, check if a position vector is in bounds for that shape.\n Raises IndexError if the position is out of bounds.\n '
for (dim, coord) in zip(shape, pos):
if ((coord < 0) or (dim <= coord)):
raise IndexError(f'{pos!r} out of range for shape {sh... |
7a9589bf9970c99b7df2179a92ec0082f0dba5d45ef5792b8600fcbe212fa479 | def calc_size(shape):
'Compute the size of a shape (the len of the backing flat array).\n '
if shape:
scale = 1
for dim in shape:
scale *= dim
return scale
else:
return 0 | Compute the size of a shape (the len of the backing flat array). | titanfp/titanic/ndarray.py | calc_size | billzorn/fpunreal | 4 | python | def calc_size(shape):
'\n '
if shape:
scale = 1
for dim in shape:
scale *= dim
return scale
else:
return 0 | def calc_size(shape):
'\n '
if shape:
scale = 1
for dim in shape:
scale *= dim
return scale
else:
return 0<|docstring|>Compute the size of a shape (the len of the backing flat array).<|endoftext|> |
3f9c2878f8db67a835460edb6bb0eafdaf380a4015fdb904a811febd67cebc49 | def check_size(data, shape):
'Given a shape and a flat sequence, check if the sequence has the expected length.\n Raises ShapeError if the length is wrong.\n '
if shape:
scale = 1
for dim in shape:
scale *= dim
else:
scale = 0
if (len(data) != scale):
ra... | Given a shape and a flat sequence, check if the sequence has the expected length.
Raises ShapeError if the length is wrong. | titanfp/titanic/ndarray.py | check_size | billzorn/fpunreal | 4 | python | def check_size(data, shape):
'Given a shape and a flat sequence, check if the sequence has the expected length.\n Raises ShapeError if the length is wrong.\n '
if shape:
scale = 1
for dim in shape:
scale *= dim
else:
scale = 0
if (len(data) != scale):
ra... | def check_size(data, shape):
'Given a shape and a flat sequence, check if the sequence has the expected length.\n Raises ShapeError if the length is wrong.\n '
if shape:
scale = 1
for dim in shape:
scale *= dim
else:
scale = 0
if (len(data) != scale):
ra... |
bf52dc4f02b85a272299c58ce5f70f8f961532c60454187bf53123b7c477d24f | def calc_strides(shape):
'Calculate stride values for a shape.\n Returns the computed strides, and the overall size of the shape.\n '
if shape:
scale = 1
strides = []
for dim in reversed(shape):
strides.append(scale)
scale *= dim
return (tuple(revers... | Calculate stride values for a shape.
Returns the computed strides, and the overall size of the shape. | titanfp/titanic/ndarray.py | calc_strides | billzorn/fpunreal | 4 | python | def calc_strides(shape):
'Calculate stride values for a shape.\n Returns the computed strides, and the overall size of the shape.\n '
if shape:
scale = 1
strides = []
for dim in reversed(shape):
strides.append(scale)
scale *= dim
return (tuple(revers... | def calc_strides(shape):
'Calculate stride values for a shape.\n Returns the computed strides, and the overall size of the shape.\n '
if shape:
scale = 1
strides = []
for dim in reversed(shape):
strides.append(scale)
scale *= dim
return (tuple(revers... |
a61234325afe805fce013a5a8b379c33fe5a48db64feca185f16d9b7b2cfe8e1 | def calc_offset(shape, strides, lookup):
'Given a shape with strides and a lookup, calculate a start offset and new strides.\n Returns the start offset, the new shape, the new strides, and the rest of the lookup.\n '
new_shape = []
new_strides = []
start = 0
fused = 0
for (dim, stride, que... | Given a shape with strides and a lookup, calculate a start offset and new strides.
Returns the start offset, the new shape, the new strides, and the rest of the lookup. | titanfp/titanic/ndarray.py | calc_offset | billzorn/fpunreal | 4 | python | def calc_offset(shape, strides, lookup):
'Given a shape with strides and a lookup, calculate a start offset and new strides.\n Returns the start offset, the new shape, the new strides, and the rest of the lookup.\n '
new_shape = []
new_strides = []
start = 0
fused = 0
for (dim, stride, que... | def calc_offset(shape, strides, lookup):
'Given a shape with strides and a lookup, calculate a start offset and new strides.\n Returns the start offset, the new shape, the new strides, and the rest of the lookup.\n '
new_shape = []
new_strides = []
start = 0
fused = 0
for (dim, stride, que... |
9611c8697ea2d4f35185dd0c1a0e3580d7c7a231859cd0142d47d1f815c4be1c | def check_offset(data, shape, start, strides):
'Check if a shape with a start offset and given strides is in bounds for some backing list.\n Raises ShapeError if the shape does not fit within the data.\n '
min_offset = 0
max_offset = 0
for (dim, stride) in zip(shape, strides):
offset = (ma... | Check if a shape with a start offset and given strides is in bounds for some backing list.
Raises ShapeError if the shape does not fit within the data. | titanfp/titanic/ndarray.py | check_offset | billzorn/fpunreal | 4 | python | def check_offset(data, shape, start, strides):
'Check if a shape with a start offset and given strides is in bounds for some backing list.\n Raises ShapeError if the shape does not fit within the data.\n '
min_offset = 0
max_offset = 0
for (dim, stride) in zip(shape, strides):
offset = (ma... | def check_offset(data, shape, start, strides):
'Check if a shape with a start offset and given strides is in bounds for some backing list.\n Raises ShapeError if the shape does not fit within the data.\n '
min_offset = 0
max_offset = 0
for (dim, stride) in zip(shape, strides):
offset = (ma... |
c5c06fdf353370c38c0b5d92a14073625142b2e8ed240064b1b97c84dbe6f1df | def _mk_view(cls):
"Create a new view type from an existing n-dimensional sequence type.\n\n Due to the way inheritance works with assigning to __class__\n it is necessary that the derived view type inherit directly from the base sequence type\n or we won't be able to reify due to differing object layout.\... | Create a new view type from an existing n-dimensional sequence type.
Due to the way inheritance works with assigning to __class__
it is necessary that the derived view type inherit directly from the base sequence type
or we won't be able to reify due to differing object layout.
The only way to implement this inherita... | titanfp/titanic/ndarray.py | _mk_view | billzorn/fpunreal | 4 | python | def _mk_view(cls):
"Create a new view type from an existing n-dimensional sequence type.\n\n Due to the way inheritance works with assigning to __class__\n it is necessary that the derived view type inherit directly from the base sequence type\n or we won't be able to reify due to differing object layout.\... | def _mk_view(cls):
"Create a new view type from an existing n-dimensional sequence type.\n\n Due to the way inheritance works with assigning to __class__\n it is necessary that the derived view type inherit directly from the base sequence type\n or we won't be able to reify due to differing object layout.\... |
7ddf55fb2fb9ae22f49e46e736a54f7764b7636e45260500b2666d50800b0963 | def forward(self, input_ids, attention_mask):
'\n\t\tInputs:\n\t\t\t-input_ids : Tensor of shape [B, T] containing token ids of sequences\n\t\t\t-attention_mask : Tensor of shape [B, T] containing attention masks to be used to avoid contibution of PAD tokens\n\t\t\t(where B is the batch size and T is the input leng... | Inputs:
-input_ids : Tensor of shape [B, T] containing token ids of sequences
-attention_mask : Tensor of shape [B, T] containing attention masks to be used to avoid contibution of PAD tokens
(where B is the batch size and T is the input length) | language/models.py | forward | MadryLab/DebuggableDeepNetworks | 32 | python | def forward(self, input_ids, attention_mask):
'\n\t\tInputs:\n\t\t\t-input_ids : Tensor of shape [B, T] containing token ids of sequences\n\t\t\t-attention_mask : Tensor of shape [B, T] containing attention masks to be used to avoid contibution of PAD tokens\n\t\t\t(where B is the batch size and T is the input leng... | def forward(self, input_ids, attention_mask):
'\n\t\tInputs:\n\t\t\t-input_ids : Tensor of shape [B, T] containing token ids of sequences\n\t\t\t-attention_mask : Tensor of shape [B, T] containing attention masks to be used to avoid contibution of PAD tokens\n\t\t\t(where B is the batch size and T is the input leng... |
c13d0da99f854fbc3612926c761c086e9678a58aa41a46502dc525cd17d6308f | def memoized_parse_block(code):
'Memoized version of parse_block.'
try:
result = parse_block_memo[code]
except KeyError:
try:
parsed = COMPILER.parse_block(code)
except Exception as err:
result = err
else:
result = parsed
parse_bloc... | Memoized version of parse_block. | coconut/icoconut/root.py | memoized_parse_block | CS121Fresh/runner | 0 | python | def memoized_parse_block(code):
try:
result = parse_block_memo[code]
except KeyError:
try:
parsed = COMPILER.parse_block(code)
except Exception as err:
result = err
else:
result = parsed
parse_block_memo[code] = result
if isins... | def memoized_parse_block(code):
try:
result = parse_block_memo[code]
except KeyError:
try:
parsed = COMPILER.parse_block(code)
except Exception as err:
result = err
else:
result = parsed
parse_block_memo[code] = result
if isins... |
a33334254ba87823bedf4ba1057dc0a111e0be6434295bb9eb5768e192447918 | def memoized_parse_sys(code):
'Memoized version of parse_sys.'
return COMPILER.header_proc(memoized_parse_block(code), header='sys', initial='none') | Memoized version of parse_sys. | coconut/icoconut/root.py | memoized_parse_sys | CS121Fresh/runner | 0 | python | def memoized_parse_sys(code):
return COMPILER.header_proc(memoized_parse_block(code), header='sys', initial='none') | def memoized_parse_sys(code):
return COMPILER.header_proc(memoized_parse_block(code), header='sys', initial='none')<|docstring|>Memoized version of parse_sys.<|endoftext|> |
635ebafe3bb7654d5161aa82bc527ec30a8f8af4acdf370fe2d9cfd5d59da34e | def ast_parse(self, source, *args, **kwargs):
'Version of ast_parse that compiles Coconut code first.'
try:
compiled = memoized_parse_sys(source)
except CoconutException as err:
raise err.syntax_err()
else:
return super(CoconutCompiler, self).ast_parse(compiled, *args, **kwargs) | Version of ast_parse that compiles Coconut code first. | coconut/icoconut/root.py | ast_parse | CS121Fresh/runner | 0 | python | def ast_parse(self, source, *args, **kwargs):
try:
compiled = memoized_parse_sys(source)
except CoconutException as err:
raise err.syntax_err()
else:
return super(CoconutCompiler, self).ast_parse(compiled, *args, **kwargs) | def ast_parse(self, source, *args, **kwargs):
try:
compiled = memoized_parse_sys(source)
except CoconutException as err:
raise err.syntax_err()
else:
return super(CoconutCompiler, self).ast_parse(compiled, *args, **kwargs)<|docstring|>Version of ast_parse that compiles Coconut c... |
f6394d331642d6000f480ff0dc1d89d8c9c6906f7125cb94e28f6f81b3254f19 | def cache(self, code, *args, **kwargs):
'Version of cache that compiles Coconut code first.'
try:
compiled = memoized_parse_sys(code)
except CoconutException:
traceback.print_exc()
return None
else:
return super(CoconutCompiler, self).cache(compiled, *args, **kwargs) | Version of cache that compiles Coconut code first. | coconut/icoconut/root.py | cache | CS121Fresh/runner | 0 | python | def cache(self, code, *args, **kwargs):
try:
compiled = memoized_parse_sys(code)
except CoconutException:
traceback.print_exc()
return None
else:
return super(CoconutCompiler, self).cache(compiled, *args, **kwargs) | def cache(self, code, *args, **kwargs):
try:
compiled = memoized_parse_sys(code)
except CoconutException:
traceback.print_exc()
return None
else:
return super(CoconutCompiler, self).cache(compiled, *args, **kwargs)<|docstring|>Version of cache that compiles Coconut code ... |
9b3df0f3d55d643327cc78f030f7493e62130a909eaf1d2f93532f96c1e944e7 | def __init__(self, *args, **kwargs):
'Version of __init__ that sets up Coconut code compilation.'
super(CoconutSplitter, self).__init__(*args, **kwargs)
self._compile = self._coconut_compile | Version of __init__ that sets up Coconut code compilation. | coconut/icoconut/root.py | __init__ | CS121Fresh/runner | 0 | python | def __init__(self, *args, **kwargs):
super(CoconutSplitter, self).__init__(*args, **kwargs)
self._compile = self._coconut_compile | def __init__(self, *args, **kwargs):
super(CoconutSplitter, self).__init__(*args, **kwargs)
self._compile = self._coconut_compile<|docstring|>Version of __init__ that sets up Coconut code compilation.<|endoftext|> |
1aae8dc460325507b4d05e801c5dfec61755b35e8747c9676dd5c146db8316cb | def _coconut_compile(self, source, *args, **kwargs):
'Version of _compile that checks Coconut code.\n None means that the code should not be run as is.\n Any other value means that it can.'
if source.endswith('\n\n'):
return True
elif should_indent(source):
return None
... | Version of _compile that checks Coconut code.
None means that the code should not be run as is.
Any other value means that it can. | coconut/icoconut/root.py | _coconut_compile | CS121Fresh/runner | 0 | python | def _coconut_compile(self, source, *args, **kwargs):
'Version of _compile that checks Coconut code.\n None means that the code should not be run as is.\n Any other value means that it can.'
if source.endswith('\n\n'):
return True
elif should_indent(source):
return None
... | def _coconut_compile(self, source, *args, **kwargs):
'Version of _compile that checks Coconut code.\n None means that the code should not be run as is.\n Any other value means that it can.'
if source.endswith('\n\n'):
return True
elif should_indent(source):
return None
... |
e8ea3996ab99a37aa6214678ed998f803482de2751e5a79c19be75f7da1d9ba6 | def init_instance_attrs(self):
'Version of init_instance_attrs that uses CoconutCompiler.'
super(CoconutShell, self).init_instance_attrs()
self.compile = CoconutCompiler() | Version of init_instance_attrs that uses CoconutCompiler. | coconut/icoconut/root.py | init_instance_attrs | CS121Fresh/runner | 0 | python | def init_instance_attrs(self):
super(CoconutShell, self).init_instance_attrs()
self.compile = CoconutCompiler() | def init_instance_attrs(self):
super(CoconutShell, self).init_instance_attrs()
self.compile = CoconutCompiler()<|docstring|>Version of init_instance_attrs that uses CoconutCompiler.<|endoftext|> |
5a37a0170132e7deabb7d8e165acd6e0e1e785b8165197bd6e27d47f134339d3 | def init_create_namespaces(self, *args, **kwargs):
'Version of init_create_namespaces that adds Coconut built-ins to globals.'
super(CoconutShell, self).init_create_namespaces(*args, **kwargs)
RUNNER.update_vars(self.user_global_ns) | Version of init_create_namespaces that adds Coconut built-ins to globals. | coconut/icoconut/root.py | init_create_namespaces | CS121Fresh/runner | 0 | python | def init_create_namespaces(self, *args, **kwargs):
super(CoconutShell, self).init_create_namespaces(*args, **kwargs)
RUNNER.update_vars(self.user_global_ns) | def init_create_namespaces(self, *args, **kwargs):
super(CoconutShell, self).init_create_namespaces(*args, **kwargs)
RUNNER.update_vars(self.user_global_ns)<|docstring|>Version of init_create_namespaces that adds Coconut built-ins to globals.<|endoftext|> |
0ffea3c0220e52118ecaeca5c68c34c827c2e7f7a67da7cd01616ecdf321493b | def run_cell(self, raw_cell, store_history=False, silent=False, shell_futures=None):
'Version of run_cell that always uses shell_futures.'
return super(CoconutShell, self).run_cell(raw_cell, store_history, silent, shell_futures=True) | Version of run_cell that always uses shell_futures. | coconut/icoconut/root.py | run_cell | CS121Fresh/runner | 0 | python | def run_cell(self, raw_cell, store_history=False, silent=False, shell_futures=None):
return super(CoconutShell, self).run_cell(raw_cell, store_history, silent, shell_futures=True) | def run_cell(self, raw_cell, store_history=False, silent=False, shell_futures=None):
return super(CoconutShell, self).run_cell(raw_cell, store_history, silent, shell_futures=True)<|docstring|>Version of run_cell that always uses shell_futures.<|endoftext|> |
50b6c461784b75457aff90a953924b397292eaa4c698bf9595ef6ca7d3e88ca9 | def user_expressions(self, expressions):
'Version of user_expressions that compiles Coconut code first.'
compiled_expressions = {}
for (key, expr) in expressions.items():
try:
compiled_expressions[key] = COMPILER.parse_eval(expr)
except CoconutException:
compiled_expr... | Version of user_expressions that compiles Coconut code first. | coconut/icoconut/root.py | user_expressions | CS121Fresh/runner | 0 | python | def user_expressions(self, expressions):
compiled_expressions = {}
for (key, expr) in expressions.items():
try:
compiled_expressions[key] = COMPILER.parse_eval(expr)
except CoconutException:
compiled_expressions[key] = expr
return super(CoconutShell, self).user_e... | def user_expressions(self, expressions):
compiled_expressions = {}
for (key, expr) in expressions.items():
try:
compiled_expressions[key] = COMPILER.parse_eval(expr)
except CoconutException:
compiled_expressions[key] = expr
return super(CoconutShell, self).user_e... |
fba6cdc8881867e39db7354c2174658c645fac328154160e3b35e90c925739b6 | def test_purge_old_personal_api_key_events_rejects_invalid_arguments(self):
'The purge_old_personal_api_key_events command should reject invalid arguments'
event = PersonApiKeyEventFactory(time=(datetime.datetime.now() - datetime.timedelta(days=30)))
with self.assertRaises(CommandError):
self._call_... | The purge_old_personal_api_key_events command should reject invalid arguments | ietf/person/management/commands/tests.py | test_purge_old_personal_api_key_events_rejects_invalid_arguments | Spectre17/datatracker | 25 | python | def test_purge_old_personal_api_key_events_rejects_invalid_arguments(self):
event = PersonApiKeyEventFactory(time=(datetime.datetime.now() - datetime.timedelta(days=30)))
with self.assertRaises(CommandError):
self._call_command('purge_old_personal_api_key_events')
with self.assertRaises(Command... | def test_purge_old_personal_api_key_events_rejects_invalid_arguments(self):
event = PersonApiKeyEventFactory(time=(datetime.datetime.now() - datetime.timedelta(days=30)))
with self.assertRaises(CommandError):
self._call_command('purge_old_personal_api_key_events')
with self.assertRaises(Command... |
d9495b538d491cc13f8bfc95daec225606cb90643f5e73427285d954c9265177 | def push_monitor(model, name, transfer_experience=False, save_records=False):
'\n When you load a model in a yaml file and you want to store its\n old monitor under a different name and start a new monitor, wrap\n the model in this function call.\n\n\n Parameters\n ----------\n model : pylearn2.mo... | When you load a model in a yaml file and you want to store its
old monitor under a different name and start a new monitor, wrap
the model in this function call.
Parameters
----------
model : pylearn2.models.model.Model
The model you loaded
name : str
Will save the old monitor to model.name
transfer_experience... | pylearn2/monitor.py | push_monitor | fxyu/pylearn2 | 2,045 | python | def push_monitor(model, name, transfer_experience=False, save_records=False):
'\n When you load a model in a yaml file and you want to store its\n old monitor under a different name and start a new monitor, wrap\n the model in this function call.\n\n\n Parameters\n ----------\n model : pylearn2.mo... | def push_monitor(model, name, transfer_experience=False, save_records=False):
'\n When you load a model in a yaml file and you want to store its\n old monitor under a different name and start a new monitor, wrap\n the model in this function call.\n\n\n Parameters\n ----------\n model : pylearn2.mo... |
43600a31e18dc27fed663bc7f1de5eb152522f8bca165bcc159bd7bcada3f03c | def read_channel(model, channel_name, monitor_name='monitor'):
'\n Returns the last value recorded in a channel.\n\n Parameters\n ----------\n model : Model\n The model to read the channel from\n channel_name : str\n The name of the channel to read from\n monitor_name : str, optional... | Returns the last value recorded in a channel.
Parameters
----------
model : Model
The model to read the channel from
channel_name : str
The name of the channel to read from
monitor_name : str, optional
The name of the Monitor to read from
(In case you want to read from an old Monitor moved by
`push... | pylearn2/monitor.py | read_channel | fxyu/pylearn2 | 2,045 | python | def read_channel(model, channel_name, monitor_name='monitor'):
'\n Returns the last value recorded in a channel.\n\n Parameters\n ----------\n model : Model\n The model to read the channel from\n channel_name : str\n The name of the channel to read from\n monitor_name : str, optional... | def read_channel(model, channel_name, monitor_name='monitor'):
'\n Returns the last value recorded in a channel.\n\n Parameters\n ----------\n model : Model\n The model to read the channel from\n channel_name : str\n The name of the channel to read from\n monitor_name : str, optional... |
851c2766bd9c79f35ea4853dd2377b2cd7b34b6a763cc60763a46300104fbbc6 | def get_channel(model, dataset, channel, cost, batch_size):
"\n Make a temporary monitor and return the value of a channel in it.\n\n Parameters\n ----------\n model : pylearn2.models.model.Model\n Will evaluate the channel for this Model.\n dataset : pylearn2.datasets.Dataset\n The Dat... | Make a temporary monitor and return the value of a channel in it.
Parameters
----------
model : pylearn2.models.model.Model
Will evaluate the channel for this Model.
dataset : pylearn2.datasets.Dataset
The Dataset to run on
channel : str
A string identifying the channel name to evaluate
cost : pylearn2.cos... | pylearn2/monitor.py | get_channel | fxyu/pylearn2 | 2,045 | python | def get_channel(model, dataset, channel, cost, batch_size):
"\n Make a temporary monitor and return the value of a channel in it.\n\n Parameters\n ----------\n model : pylearn2.models.model.Model\n Will evaluate the channel for this Model.\n dataset : pylearn2.datasets.Dataset\n The Dat... | def get_channel(model, dataset, channel, cost, batch_size):
"\n Make a temporary monitor and return the value of a channel in it.\n\n Parameters\n ----------\n model : pylearn2.models.model.Model\n Will evaluate the channel for this Model.\n dataset : pylearn2.datasets.Dataset\n The Dat... |
bccbeabe18d6f6ee001b319bcec8c081b137fa402f593befed215d442b80e3cc | def get_monitor_doc(var):
'\n Returns the __doc__ field of var or None. This field is used on\n theano Variables to document the meaning of monitor channels.\n\n Parameters\n ----------\n var : theano.gof.Variable\n The variable to get the documentation of\n\n Returns\n -------\n doc ... | Returns the __doc__ field of var or None. This field is used on
theano Variables to document the meaning of monitor channels.
Parameters
----------
var : theano.gof.Variable
The variable to get the documentation of
Returns
-------
doc : str or None
var.__doc__ if var has an instance-level doc, otherwise None | pylearn2/monitor.py | get_monitor_doc | fxyu/pylearn2 | 2,045 | python | def get_monitor_doc(var):
'\n Returns the __doc__ field of var or None. This field is used on\n theano Variables to document the meaning of monitor channels.\n\n Parameters\n ----------\n var : theano.gof.Variable\n The variable to get the documentation of\n\n Returns\n -------\n doc ... | def get_monitor_doc(var):
'\n Returns the __doc__ field of var or None. This field is used on\n theano Variables to document the meaning of monitor channels.\n\n Parameters\n ----------\n var : theano.gof.Variable\n The variable to get the documentation of\n\n Returns\n -------\n doc ... |
0f50bc99d8fda887284d17e123df0b8646c0fbb239d40ed413a2ad2cb0e8b106 | def _build_data_specs(self):
'\n Computes a nested data_specs for input and all channels\n\n Also computes the mapping to flatten it. This function is\n called from redo_theano.\n '
(m_space, m_source) = self.model.get_monitoring_data_specs()
input_spaces = [m_space]
input_so... | Computes a nested data_specs for input and all channels
Also computes the mapping to flatten it. This function is
called from redo_theano. | pylearn2/monitor.py | _build_data_specs | fxyu/pylearn2 | 2,045 | python | def _build_data_specs(self):
'\n Computes a nested data_specs for input and all channels\n\n Also computes the mapping to flatten it. This function is\n called from redo_theano.\n '
(m_space, m_source) = self.model.get_monitoring_data_specs()
input_spaces = [m_space]
input_so... | def _build_data_specs(self):
'\n Computes a nested data_specs for input and all channels\n\n Also computes the mapping to flatten it. This function is\n called from redo_theano.\n '
(m_space, m_source) = self.model.get_monitoring_data_specs()
input_spaces = [m_space]
input_so... |
d175c435015a096df301f692e54598154c07fb1fba3deec2069f8efd57874cca | def set_theano_function_mode(self, mode):
'\n .. todo::\n\n WRITEME\n\n Parameters\n ----------\n mode : theano.compile.Mode\n Theano functions for the monitoring channels will be\n compiled and run using this mode.\n '
if (self.theano_function... | .. todo::
WRITEME
Parameters
----------
mode : theano.compile.Mode
Theano functions for the monitoring channels will be
compiled and run using this mode. | pylearn2/monitor.py | set_theano_function_mode | fxyu/pylearn2 | 2,045 | python | def set_theano_function_mode(self, mode):
'\n .. todo::\n\n WRITEME\n\n Parameters\n ----------\n mode : theano.compile.Mode\n Theano functions for the monitoring channels will be\n compiled and run using this mode.\n '
if (self.theano_function... | def set_theano_function_mode(self, mode):
'\n .. todo::\n\n WRITEME\n\n Parameters\n ----------\n mode : theano.compile.Mode\n Theano functions for the monitoring channels will be\n compiled and run using this mode.\n '
if (self.theano_function... |
8888bee1e642db432aeb77e71edaf1a97f935736f3071e3c7ef4e00e7e5fce97 | def add_dataset(self, dataset, mode='sequential', batch_size=None, num_batches=None, seed=None):
"\n Determines the data used to calculate the values of each channel.\n\n Parameters\n ----------\n dataset : object\n A `pylearn2.datasets.Dataset` object.\n mode : str or ... | Determines the data used to calculate the values of each channel.
Parameters
----------
dataset : object
A `pylearn2.datasets.Dataset` object.
mode : str or object, optional
Iteration mode; see the docstring of the `iterator` method
on `pylearn2.datasets.Dataset` for details.
batch_size : int, optional
... | pylearn2/monitor.py | add_dataset | fxyu/pylearn2 | 2,045 | python | def add_dataset(self, dataset, mode='sequential', batch_size=None, num_batches=None, seed=None):
"\n Determines the data used to calculate the values of each channel.\n\n Parameters\n ----------\n dataset : object\n A `pylearn2.datasets.Dataset` object.\n mode : str or ... | def add_dataset(self, dataset, mode='sequential', batch_size=None, num_batches=None, seed=None):
"\n Determines the data used to calculate the values of each channel.\n\n Parameters\n ----------\n dataset : object\n A `pylearn2.datasets.Dataset` object.\n mode : str or ... |
c5b759dc09539dfe6c014add9d030cbba2d13f741f7f9e4b54b545ea1dd80298 | def __call__(self):
'\n Runs the model on the monitoring dataset in order to add one\n data point to each of the channels.\n '
if self._dirty:
self.redo_theano()
datasets = self._datasets
self.begin_record_entry()
for (d, i, b, n, a, sd, ne) in safe_izip(datasets, self._... | Runs the model on the monitoring dataset in order to add one
data point to each of the channels. | pylearn2/monitor.py | __call__ | fxyu/pylearn2 | 2,045 | python | def __call__(self):
'\n Runs the model on the monitoring dataset in order to add one\n data point to each of the channels.\n '
if self._dirty:
self.redo_theano()
datasets = self._datasets
self.begin_record_entry()
for (d, i, b, n, a, sd, ne) in safe_izip(datasets, self._... | def __call__(self):
'\n Runs the model on the monitoring dataset in order to add one\n data point to each of the channels.\n '
if self._dirty:
self.redo_theano()
datasets = self._datasets
self.begin_record_entry()
for (d, i, b, n, a, sd, ne) in safe_izip(datasets, self._... |
70b9adf5bc2e2a53ef8eea7216717735bbcc2ca440e1fb5fedd8d78f9e205fc7 | def run_prereqs(self, data, dataset):
'\n Runs all "prerequistie functions" on a batch of data. Always\n called right before computing the monitoring channels on that\n batch.\n\n Parameters\n ----------\n data : tuple or Variable\n a member of the Space used as ... | Runs all "prerequistie functions" on a batch of data. Always
called right before computing the monitoring channels on that
batch.
Parameters
----------
data : tuple or Variable
a member of the Space used as input to the monitoring
functions
dataset : Dataset
the Dataset the data was drawn from | pylearn2/monitor.py | run_prereqs | fxyu/pylearn2 | 2,045 | python | def run_prereqs(self, data, dataset):
'\n Runs all "prerequistie functions" on a batch of data. Always\n called right before computing the monitoring channels on that\n batch.\n\n Parameters\n ----------\n data : tuple or Variable\n a member of the Space used as ... | def run_prereqs(self, data, dataset):
'\n Runs all "prerequistie functions" on a batch of data. Always\n called right before computing the monitoring channels on that\n batch.\n\n Parameters\n ----------\n data : tuple or Variable\n a member of the Space used as ... |
9fa27de96b858fdb362bc46dabac9c8a3aa831461488aa2d2d74860315e0e469 | def get_batches_seen(self):
'\n Returns the number of batches the model has learned on\n (assuming that the learning code has been calling\n Monitor.report_batch correctly).\n '
return self._num_batches_seen | Returns the number of batches the model has learned on
(assuming that the learning code has been calling
Monitor.report_batch correctly). | pylearn2/monitor.py | get_batches_seen | fxyu/pylearn2 | 2,045 | python | def get_batches_seen(self):
'\n Returns the number of batches the model has learned on\n (assuming that the learning code has been calling\n Monitor.report_batch correctly).\n '
return self._num_batches_seen | def get_batches_seen(self):
'\n Returns the number of batches the model has learned on\n (assuming that the learning code has been calling\n Monitor.report_batch correctly).\n '
return self._num_batches_seen<|docstring|>Returns the number of batches the model has learned on
(assuming... |
e990849ac81538ee1aea3960e995caadfa369ded69d3810aab0d56a2a40c4efc | def get_epochs_seen(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n epochs_seen : int\n The number of epochs the model has been trained on.\n One "epoch" is one pass through Dataset.iterator.\n '
return self._epochs_seen | .. todo::
WRITEME
Returns
-------
epochs_seen : int
The number of epochs the model has been trained on.
One "epoch" is one pass through Dataset.iterator. | pylearn2/monitor.py | get_epochs_seen | fxyu/pylearn2 | 2,045 | python | def get_epochs_seen(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n epochs_seen : int\n The number of epochs the model has been trained on.\n One "epoch" is one pass through Dataset.iterator.\n '
return self._epochs_seen | def get_epochs_seen(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n epochs_seen : int\n The number of epochs the model has been trained on.\n One "epoch" is one pass through Dataset.iterator.\n '
return self._epochs_seen<|docstring|>..... |
3bbb7d946908a296a329b60cf8798651678d7236e96aed2dc30e4322c72647b2 | def get_examples_seen(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n examples_seen : int\n The number of examples the model has learned on (assuming\n that the learning code has been calling Monitor.report_batch\n correctly)\n ... | .. todo::
WRITEME
Returns
-------
examples_seen : int
The number of examples the model has learned on (assuming
that the learning code has been calling Monitor.report_batch
correctly) | pylearn2/monitor.py | get_examples_seen | fxyu/pylearn2 | 2,045 | python | def get_examples_seen(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n examples_seen : int\n The number of examples the model has learned on (assuming\n that the learning code has been calling Monitor.report_batch\n correctly)\n ... | def get_examples_seen(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n examples_seen : int\n The number of examples the model has learned on (assuming\n that the learning code has been calling Monitor.report_batch\n correctly)\n ... |
6e1befab375da5db76d3bfa3ec8682efcd395fbacfa95bd8e6bcb597dbc51752 | def report_batch(self, num_examples):
'\n Call this whenever the model has learned on another batch of\n examples. Report how many examples were learned on.\n\n Parameters\n ----------\n num_examples : int\n The number of examples learned on in this minibatch.\n ... | Call this whenever the model has learned on another batch of
examples. Report how many examples were learned on.
Parameters
----------
num_examples : int
The number of examples learned on in this minibatch. | pylearn2/monitor.py | report_batch | fxyu/pylearn2 | 2,045 | python | def report_batch(self, num_examples):
'\n Call this whenever the model has learned on another batch of\n examples. Report how many examples were learned on.\n\n Parameters\n ----------\n num_examples : int\n The number of examples learned on in this minibatch.\n ... | def report_batch(self, num_examples):
'\n Call this whenever the model has learned on another batch of\n examples. Report how many examples were learned on.\n\n Parameters\n ----------\n num_examples : int\n The number of examples learned on in this minibatch.\n ... |
c22fc100b771bae982dd2c5a6629008476c6402395e5ea224d6c9780fa52c541 | def report_epoch(self):
'\n Call this whenever the model has completed another "epoch" of\n learning. We regard one pass through Dataset.iterator as one\n epoch.\n '
self._epochs_seen += 1 | Call this whenever the model has completed another "epoch" of
learning. We regard one pass through Dataset.iterator as one
epoch. | pylearn2/monitor.py | report_epoch | fxyu/pylearn2 | 2,045 | python | def report_epoch(self):
'\n Call this whenever the model has completed another "epoch" of\n learning. We regard one pass through Dataset.iterator as one\n epoch.\n '
self._epochs_seen += 1 | def report_epoch(self):
'\n Call this whenever the model has completed another "epoch" of\n learning. We regard one pass through Dataset.iterator as one\n epoch.\n '
self._epochs_seen += 1<|docstring|>Call this whenever the model has completed another "epoch" of
learning. We regard o... |
11685c2c0a79e8e40375b55b1cfc74bc005cf1ed72fcc1a01db335b6294dd611 | def redo_theano(self):
'\n Recompiles Theano functions used by this monitor.\n\n This is called any time we need to evaluate the channels and\n the channel definitions have changed since last we called it,\n or if the theano functions are unavailable for any other reason\n (first ... | Recompiles Theano functions used by this monitor.
This is called any time we need to evaluate the channels and
the channel definitions have changed since last we called it,
or if the theano functions are unavailable for any other reason
(first time they are needed after construction or
deserialization, etc.)
All chan... | pylearn2/monitor.py | redo_theano | fxyu/pylearn2 | 2,045 | python | def redo_theano(self):
'\n Recompiles Theano functions used by this monitor.\n\n This is called any time we need to evaluate the channels and\n the channel definitions have changed since last we called it,\n or if the theano functions are unavailable for any other reason\n (first ... | def redo_theano(self):
'\n Recompiles Theano functions used by this monitor.\n\n This is called any time we need to evaluate the channels and\n the channel definitions have changed since last we called it,\n or if the theano functions are unavailable for any other reason\n (first ... |
b7dc7209cb1fa893730e5c7ef5f33a8603695bab1497d367b9894da52148f1c1 | def register_names_to_del(self, names):
'\n Register names of fields that should be deleted before pickling.\n\n Parameters\n ----------\n names : list\n A list of attribute names as strings.\n '
for name in names:
if (name not in self.names_to_del):
... | Register names of fields that should be deleted before pickling.
Parameters
----------
names : list
A list of attribute names as strings. | pylearn2/monitor.py | register_names_to_del | fxyu/pylearn2 | 2,045 | python | def register_names_to_del(self, names):
'\n Register names of fields that should be deleted before pickling.\n\n Parameters\n ----------\n names : list\n A list of attribute names as strings.\n '
for name in names:
if (name not in self.names_to_del):
... | def register_names_to_del(self, names):
'\n Register names of fields that should be deleted before pickling.\n\n Parameters\n ----------\n names : list\n A list of attribute names as strings.\n '
for name in names:
if (name not in self.names_to_del):
... |
00c91be01a8bb81a212b868b6f964d45f068378bfa8b721374c6abe373fdf1ec | def __getstate__(self):
"\n In order to avoid pickling a copy of the dataset whenever a\n monitor is saved, the __getstate__ method replaces the dataset\n field with the dataset's yaml source. This is not a perfect\n solution because it won't work with job resuming, which would\n ... | In order to avoid pickling a copy of the dataset whenever a
monitor is saved, the __getstate__ method replaces the dataset
field with the dataset's yaml source. This is not a perfect
solution because it won't work with job resuming, which would
require saving the state of the dataset's random number
generator.
Like in... | pylearn2/monitor.py | __getstate__ | fxyu/pylearn2 | 2,045 | python | def __getstate__(self):
"\n In order to avoid pickling a copy of the dataset whenever a\n monitor is saved, the __getstate__ method replaces the dataset\n field with the dataset's yaml source. This is not a perfect\n solution because it won't work with job resuming, which would\n ... | def __getstate__(self):
"\n In order to avoid pickling a copy of the dataset whenever a\n monitor is saved, the __getstate__ method replaces the dataset\n field with the dataset's yaml source. This is not a perfect\n solution because it won't work with job resuming, which would\n ... |
029c5904fcf1a3f3ebb0d00e953c4da3f374c7267ca411042915a314429cd5db | def __setstate__(self, d):
'\n Sets the object to have the state described by `d`.\n\n Parameters\n ----------\n d : dict\n A dictionary mapping string names of fields to values for\n these fields.\n '
if ('_dataset' in d):
d['_datasets'] = [d['_d... | Sets the object to have the state described by `d`.
Parameters
----------
d : dict
A dictionary mapping string names of fields to values for
these fields. | pylearn2/monitor.py | __setstate__ | fxyu/pylearn2 | 2,045 | python | def __setstate__(self, d):
'\n Sets the object to have the state described by `d`.\n\n Parameters\n ----------\n d : dict\n A dictionary mapping string names of fields to values for\n these fields.\n '
if ('_dataset' in d):
d['_datasets'] = [d['_d... | def __setstate__(self, d):
'\n Sets the object to have the state described by `d`.\n\n Parameters\n ----------\n d : dict\n A dictionary mapping string names of fields to values for\n these fields.\n '
if ('_dataset' in d):
d['_datasets'] = [d['_d... |
2f63dfc76cf601aa15afa52145f8c48b62e0a8a07763293a9e633adb536f9d18 | def add_channel(self, name, ipt, val, dataset=None, prereqs=None, data_specs=None):
'\n Asks the monitor to start tracking a new value. Can be called\n even after the monitor is already in use.\n\n Parameters\n ----------\n name : str\n The display name in the monitor.... | Asks the monitor to start tracking a new value. Can be called
even after the monitor is already in use.
Parameters
----------
name : str
The display name in the monitor.
ipt : tensor_like
The symbolic tensor which should be clamped to the data.
(or a list/tuple containing symbolic tensors, following the
... | pylearn2/monitor.py | add_channel | fxyu/pylearn2 | 2,045 | python | def add_channel(self, name, ipt, val, dataset=None, prereqs=None, data_specs=None):
'\n Asks the monitor to start tracking a new value. Can be called\n even after the monitor is already in use.\n\n Parameters\n ----------\n name : str\n The display name in the monitor.... | def add_channel(self, name, ipt, val, dataset=None, prereqs=None, data_specs=None):
'\n Asks the monitor to start tracking a new value. Can be called\n even after the monitor is already in use.\n\n Parameters\n ----------\n name : str\n The display name in the monitor.... |
cb38977ab1b8b42b6558358c174630fbc679a77afc9c0b0feb0d47b654a29b6d | def _sanity_check(self):
"\n Sometimes we serialize models and then load them somewhere else\n but still try to use their Monitor, and the Monitor is in a\n mangled state. I've added some calls to _sanity_check to try to\n catch when that happens. Not sure what to do for a long term\n ... | Sometimes we serialize models and then load them somewhere else
but still try to use their Monitor, and the Monitor is in a
mangled state. I've added some calls to _sanity_check to try to
catch when that happens. Not sure what to do for a long term
fix. I think it requires making theano graphs serializable
first. | pylearn2/monitor.py | _sanity_check | fxyu/pylearn2 | 2,045 | python | def _sanity_check(self):
"\n Sometimes we serialize models and then load them somewhere else\n but still try to use their Monitor, and the Monitor is in a\n mangled state. I've added some calls to _sanity_check to try to\n catch when that happens. Not sure what to do for a long term\n ... | def _sanity_check(self):
"\n Sometimes we serialize models and then load them somewhere else\n but still try to use their Monitor, and the Monitor is in a\n mangled state. I've added some calls to _sanity_check to try to\n catch when that happens. Not sure what to do for a long term\n ... |
366455c8da314b173b276c45242495837a068addf71d1065cc167da59844afa5 | @classmethod
def get_monitor(cls, model):
"\n Returns a model's monitor. If the model doesn't have a monitor\n yet, installs one and returns that.\n\n Parameters\n ----------\n model : object\n An object that implements the `Model` interface specified\n in `p... | Returns a model's monitor. If the model doesn't have a monitor
yet, installs one and returns that.
Parameters
----------
model : object
An object that implements the `Model` interface specified
in `pylearn2.models`. | pylearn2/monitor.py | get_monitor | fxyu/pylearn2 | 2,045 | python | @classmethod
def get_monitor(cls, model):
"\n Returns a model's monitor. If the model doesn't have a monitor\n yet, installs one and returns that.\n\n Parameters\n ----------\n model : object\n An object that implements the `Model` interface specified\n in `p... | @classmethod
def get_monitor(cls, model):
"\n Returns a model's monitor. If the model doesn't have a monitor\n yet, installs one and returns that.\n\n Parameters\n ----------\n model : object\n An object that implements the `Model` interface specified\n in `p... |
940b096da2fa58243757ee958283c0f9284ddd904a09a006bbcce2d397b040a2 | @property
def batch_size(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n batch_size : int\n The size of the batches used for monitoring\n '
return self._batch_size | .. todo::
WRITEME
Returns
-------
batch_size : int
The size of the batches used for monitoring | pylearn2/monitor.py | batch_size | fxyu/pylearn2 | 2,045 | python | @property
def batch_size(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n batch_size : int\n The size of the batches used for monitoring\n '
return self._batch_size | @property
def batch_size(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n batch_size : int\n The size of the batches used for monitoring\n '
return self._batch_size<|docstring|>.. todo::
WRITEME
Returns
-------
batch_size : int
The size ... |
690472128f13d949f1b900f7b8f1f1fa9dc2b1da63795658c1e59707716e7b83 | @property
def num_batches(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n num_batches : int\n The number of batches used for monitoring\n '
return self._num_batches | .. todo::
WRITEME
Returns
-------
num_batches : int
The number of batches used for monitoring | pylearn2/monitor.py | num_batches | fxyu/pylearn2 | 2,045 | python | @property
def num_batches(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n num_batches : int\n The number of batches used for monitoring\n '
return self._num_batches | @property
def num_batches(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n num_batches : int\n The number of batches used for monitoring\n '
return self._num_batches<|docstring|>.. todo::
WRITEME
Returns
-------
num_batches : int
The num... |
1ecadaadb497038af85c81640a79426e0bdae6942c2361e51efc912e3c91e4ca | def setup(self, dataset, cost, batch_size, num_batches=None, extra_costs=None, mode='sequential', obj_prereqs=None, cost_monitoring_args=None):
"\n Sets up the monitor for a cost minimization problem.\n Adds channels defined by both the model and the cost for\n the specified dataset(s), as well... | Sets up the monitor for a cost minimization problem.
Adds channels defined by both the model and the cost for
the specified dataset(s), as well as a channel called
'objective' defined by the costs' __call__ method.
Parameters
----------
dataset : pylearn2.datasets.Dataset
Dataset or dictionary mapping string names... | pylearn2/monitor.py | setup | fxyu/pylearn2 | 2,045 | python | def setup(self, dataset, cost, batch_size, num_batches=None, extra_costs=None, mode='sequential', obj_prereqs=None, cost_monitoring_args=None):
"\n Sets up the monitor for a cost minimization problem.\n Adds channels defined by both the model and the cost for\n the specified dataset(s), as well... | def setup(self, dataset, cost, batch_size, num_batches=None, extra_costs=None, mode='sequential', obj_prereqs=None, cost_monitoring_args=None):
"\n Sets up the monitor for a cost minimization problem.\n Adds channels defined by both the model and the cost for\n the specified dataset(s), as well... |
f85464a65c5c915473fbf9327ef1016bd32799829c60f8243d2ece0405bf8811 | def __str__(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n s : str\n A reasonably human-readable string representation of the object.\n '
try:
graph_input_str = str(self.graph_input)
except Exception:
graph_input_str = '<bad ... | .. todo::
WRITEME
Returns
-------
s : str
A reasonably human-readable string representation of the object. | pylearn2/monitor.py | __str__ | fxyu/pylearn2 | 2,045 | python | def __str__(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n s : str\n A reasonably human-readable string representation of the object.\n '
try:
graph_input_str = str(self.graph_input)
except Exception:
graph_input_str = '<bad ... | def __str__(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n s : str\n A reasonably human-readable string representation of the object.\n '
try:
graph_input_str = str(self.graph_input)
except Exception:
graph_input_str = '<bad ... |
81214f28ebd419608ee4b250b304d277448185a487f14cf51aa1f31dd92408a7 | def __getstate__(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n d : dict\n A dictionary mapping the string names of the fields of the class\n to values appropriate for pickling.\n '
if hasattr(self, 'val'):
doc = get_monitor_d... | .. todo::
WRITEME
Returns
-------
d : dict
A dictionary mapping the string names of the fields of the class
to values appropriate for pickling. | pylearn2/monitor.py | __getstate__ | fxyu/pylearn2 | 2,045 | python | def __getstate__(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n d : dict\n A dictionary mapping the string names of the fields of the class\n to values appropriate for pickling.\n '
if hasattr(self, 'val'):
doc = get_monitor_d... | def __getstate__(self):
'\n .. todo::\n\n WRITEME\n\n Returns\n -------\n d : dict\n A dictionary mapping the string names of the fields of the class\n to values appropriate for pickling.\n '
if hasattr(self, 'val'):
doc = get_monitor_d... |
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