id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
|---|---|---|---|---|---|---|---|---|---|---|---|
20,700 | fastai/fastai | fastai/core.py | show_some | def show_some(items:Collection, n_max:int=5, sep:str=','):
"Return the representation of the first `n_max` elements in `items`."
if items is None or len(items) == 0: return ''
res = sep.join([f'{o}' for o in items[:n_max]])
if len(items) > n_max: res += '...'
return res | python | def show_some(items:Collection, n_max:int=5, sep:str=','):
"Return the representation of the first `n_max` elements in `items`."
if items is None or len(items) == 0: return ''
res = sep.join([f'{o}' for o in items[:n_max]])
if len(items) > n_max: res += '...'
return res | [
"def",
"show_some",
"(",
"items",
":",
"Collection",
",",
"n_max",
":",
"int",
"=",
"5",
",",
"sep",
":",
"str",
"=",
"','",
")",
":",
"if",
"items",
"is",
"None",
"or",
"len",
"(",
"items",
")",
"==",
"0",
":",
"return",
"''",
"res",
"=",
"sep... | Return the representation of the first `n_max` elements in `items`. | [
"Return",
"the",
"representation",
"of",
"the",
"first",
"n_max",
"elements",
"in",
"items",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/core.py#L340-L345 |
20,701 | fastai/fastai | fastai/core.py | get_tmp_file | def get_tmp_file(dir=None):
"Create and return a tmp filename, optionally at a specific path. `os.remove` when done with it."
with tempfile.NamedTemporaryFile(delete=False, dir=dir) as f: return f.name | python | def get_tmp_file(dir=None):
"Create and return a tmp filename, optionally at a specific path. `os.remove` when done with it."
with tempfile.NamedTemporaryFile(delete=False, dir=dir) as f: return f.name | [
"def",
"get_tmp_file",
"(",
"dir",
"=",
"None",
")",
":",
"with",
"tempfile",
".",
"NamedTemporaryFile",
"(",
"delete",
"=",
"False",
",",
"dir",
"=",
"dir",
")",
"as",
"f",
":",
"return",
"f",
".",
"name"
] | Create and return a tmp filename, optionally at a specific path. `os.remove` when done with it. | [
"Create",
"and",
"return",
"a",
"tmp",
"filename",
"optionally",
"at",
"a",
"specific",
"path",
".",
"os",
".",
"remove",
"when",
"done",
"with",
"it",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/core.py#L347-L349 |
20,702 | fastai/fastai | fastai/core.py | ItemBase.show | def show(self, ax:plt.Axes, **kwargs):
"Subclass this method if you want to customize the way this `ItemBase` is shown on `ax`."
ax.set_title(str(self)) | python | def show(self, ax:plt.Axes, **kwargs):
"Subclass this method if you want to customize the way this `ItemBase` is shown on `ax`."
ax.set_title(str(self)) | [
"def",
"show",
"(",
"self",
",",
"ax",
":",
"plt",
".",
"Axes",
",",
"*",
"*",
"kwargs",
")",
":",
"ax",
".",
"set_title",
"(",
"str",
"(",
"self",
")",
")"
] | Subclass this method if you want to customize the way this `ItemBase` is shown on `ax`. | [
"Subclass",
"this",
"method",
"if",
"you",
"want",
"to",
"customize",
"the",
"way",
"this",
"ItemBase",
"is",
"shown",
"on",
"ax",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/core.py#L157-L159 |
20,703 | fastai/fastai | fastai/vision/models/darknet.py | conv_bn_lrelu | def conv_bn_lrelu(ni:int, nf:int, ks:int=3, stride:int=1)->nn.Sequential:
"Create a seuence Conv2d->BatchNorm2d->LeakyReLu layer."
return nn.Sequential(
nn.Conv2d(ni, nf, kernel_size=ks, bias=False, stride=stride, padding=ks//2),
nn.BatchNorm2d(nf),
nn.LeakyReLU(negative_slope=0.1, inpla... | python | def conv_bn_lrelu(ni:int, nf:int, ks:int=3, stride:int=1)->nn.Sequential:
"Create a seuence Conv2d->BatchNorm2d->LeakyReLu layer."
return nn.Sequential(
nn.Conv2d(ni, nf, kernel_size=ks, bias=False, stride=stride, padding=ks//2),
nn.BatchNorm2d(nf),
nn.LeakyReLU(negative_slope=0.1, inpla... | [
"def",
"conv_bn_lrelu",
"(",
"ni",
":",
"int",
",",
"nf",
":",
"int",
",",
"ks",
":",
"int",
"=",
"3",
",",
"stride",
":",
"int",
"=",
"1",
")",
"->",
"nn",
".",
"Sequential",
":",
"return",
"nn",
".",
"Sequential",
"(",
"nn",
".",
"Conv2d",
"(... | Create a seuence Conv2d->BatchNorm2d->LeakyReLu layer. | [
"Create",
"a",
"seuence",
"Conv2d",
"-",
">",
"BatchNorm2d",
"-",
">",
"LeakyReLu",
"layer",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/vision/models/darknet.py#L6-L11 |
20,704 | fastai/fastai | fastai/vision/models/darknet.py | Darknet.make_group_layer | def make_group_layer(self, ch_in:int, num_blocks:int, stride:int=1):
"starts with conv layer - `ch_in` channels in - then has `num_blocks` `ResLayer`"
return [conv_bn_lrelu(ch_in, ch_in*2,stride=stride)
] + [(ResLayer(ch_in*2)) for i in range(num_blocks)] | python | def make_group_layer(self, ch_in:int, num_blocks:int, stride:int=1):
"starts with conv layer - `ch_in` channels in - then has `num_blocks` `ResLayer`"
return [conv_bn_lrelu(ch_in, ch_in*2,stride=stride)
] + [(ResLayer(ch_in*2)) for i in range(num_blocks)] | [
"def",
"make_group_layer",
"(",
"self",
",",
"ch_in",
":",
"int",
",",
"num_blocks",
":",
"int",
",",
"stride",
":",
"int",
"=",
"1",
")",
":",
"return",
"[",
"conv_bn_lrelu",
"(",
"ch_in",
",",
"ch_in",
"*",
"2",
",",
"stride",
"=",
"stride",
")",
... | starts with conv layer - `ch_in` channels in - then has `num_blocks` `ResLayer` | [
"starts",
"with",
"conv",
"layer",
"-",
"ch_in",
"channels",
"in",
"-",
"then",
"has",
"num_blocks",
"ResLayer"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/vision/models/darknet.py#L24-L27 |
20,705 | fastai/fastai | fastai/collab.py | collab_learner | def collab_learner(data, n_factors:int=None, use_nn:bool=False, emb_szs:Dict[str,int]=None, layers:Collection[int]=None,
ps:Collection[float]=None, emb_drop:float=0., y_range:OptRange=None, use_bn:bool=True,
bn_final:bool=False, **learn_kwargs)->Learner:
"Create a Learner for... | python | def collab_learner(data, n_factors:int=None, use_nn:bool=False, emb_szs:Dict[str,int]=None, layers:Collection[int]=None,
ps:Collection[float]=None, emb_drop:float=0., y_range:OptRange=None, use_bn:bool=True,
bn_final:bool=False, **learn_kwargs)->Learner:
"Create a Learner for... | [
"def",
"collab_learner",
"(",
"data",
",",
"n_factors",
":",
"int",
"=",
"None",
",",
"use_nn",
":",
"bool",
"=",
"False",
",",
"emb_szs",
":",
"Dict",
"[",
"str",
",",
"int",
"]",
"=",
"None",
",",
"layers",
":",
"Collection",
"[",
"int",
"]",
"="... | Create a Learner for collaborative filtering on `data`. | [
"Create",
"a",
"Learner",
"for",
"collaborative",
"filtering",
"on",
"data",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/collab.py#L98-L107 |
20,706 | fastai/fastai | fastai/collab.py | CollabDataBunch.from_df | def from_df(cls, ratings:DataFrame, valid_pct:float=0.2, user_name:Optional[str]=None, item_name:Optional[str]=None,
rating_name:Optional[str]=None, test:DataFrame=None, seed:int=None, path:PathOrStr='.', bs:int=64,
val_bs:int=None, num_workers:int=defaults.cpus, dl_tfms:Optional[Collec... | python | def from_df(cls, ratings:DataFrame, valid_pct:float=0.2, user_name:Optional[str]=None, item_name:Optional[str]=None,
rating_name:Optional[str]=None, test:DataFrame=None, seed:int=None, path:PathOrStr='.', bs:int=64,
val_bs:int=None, num_workers:int=defaults.cpus, dl_tfms:Optional[Collec... | [
"def",
"from_df",
"(",
"cls",
",",
"ratings",
":",
"DataFrame",
",",
"valid_pct",
":",
"float",
"=",
"0.2",
",",
"user_name",
":",
"Optional",
"[",
"str",
"]",
"=",
"None",
",",
"item_name",
":",
"Optional",
"[",
"str",
"]",
"=",
"None",
",",
"rating... | Create a `DataBunch` suitable for collaborative filtering from `ratings`. | [
"Create",
"a",
"DataBunch",
"suitable",
"for",
"collaborative",
"filtering",
"from",
"ratings",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/collab.py#L55-L68 |
20,707 | fastai/fastai | old/fastai/structured.py | set_rf_samples | def set_rf_samples(n):
""" Changes Scikit learn's random forests to give each tree a random sample of
n random rows.
"""
forest._generate_sample_indices = (lambda rs, n_samples:
forest.check_random_state(rs).randint(0, n_samples, n)) | python | def set_rf_samples(n):
""" Changes Scikit learn's random forests to give each tree a random sample of
n random rows.
"""
forest._generate_sample_indices = (lambda rs, n_samples:
forest.check_random_state(rs).randint(0, n_samples, n)) | [
"def",
"set_rf_samples",
"(",
"n",
")",
":",
"forest",
".",
"_generate_sample_indices",
"=",
"(",
"lambda",
"rs",
",",
"n_samples",
":",
"forest",
".",
"check_random_state",
"(",
"rs",
")",
".",
"randint",
"(",
"0",
",",
"n_samples",
",",
"n",
")",
")"
] | Changes Scikit learn's random forests to give each tree a random sample of
n random rows. | [
"Changes",
"Scikit",
"learn",
"s",
"random",
"forests",
"to",
"give",
"each",
"tree",
"a",
"random",
"sample",
"of",
"n",
"random",
"rows",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/old/fastai/structured.py#L382-L387 |
20,708 | fastai/fastai | old/fastai/structured.py | reset_rf_samples | def reset_rf_samples():
""" Undoes the changes produced by set_rf_samples.
"""
forest._generate_sample_indices = (lambda rs, n_samples:
forest.check_random_state(rs).randint(0, n_samples, n_samples)) | python | def reset_rf_samples():
""" Undoes the changes produced by set_rf_samples.
"""
forest._generate_sample_indices = (lambda rs, n_samples:
forest.check_random_state(rs).randint(0, n_samples, n_samples)) | [
"def",
"reset_rf_samples",
"(",
")",
":",
"forest",
".",
"_generate_sample_indices",
"=",
"(",
"lambda",
"rs",
",",
"n_samples",
":",
"forest",
".",
"check_random_state",
"(",
"rs",
")",
".",
"randint",
"(",
"0",
",",
"n_samples",
",",
"n_samples",
")",
")... | Undoes the changes produced by set_rf_samples. | [
"Undoes",
"the",
"changes",
"produced",
"by",
"set_rf_samples",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/old/fastai/structured.py#L389-L393 |
20,709 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | get_global_vars | def get_global_vars(mod):
"Return globally assigned variables."
# https://stackoverflow.com/questions/8820276/docstring-for-variable/31764368#31764368
import ast,re
with open(mod.__file__, 'r') as f: fstr = f.read()
flines = fstr.splitlines()
d = {}
for node in ast.walk(ast.parse(fstr)):
... | python | def get_global_vars(mod):
"Return globally assigned variables."
# https://stackoverflow.com/questions/8820276/docstring-for-variable/31764368#31764368
import ast,re
with open(mod.__file__, 'r') as f: fstr = f.read()
flines = fstr.splitlines()
d = {}
for node in ast.walk(ast.parse(fstr)):
... | [
"def",
"get_global_vars",
"(",
"mod",
")",
":",
"# https://stackoverflow.com/questions/8820276/docstring-for-variable/31764368#31764368",
"import",
"ast",
",",
"re",
"with",
"open",
"(",
"mod",
".",
"__file__",
",",
"'r'",
")",
"as",
"f",
":",
"fstr",
"=",
"f",
".... | Return globally assigned variables. | [
"Return",
"globally",
"assigned",
"variables",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L52-L66 |
20,710 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | execute_nb | def execute_nb(fname, metadata=None, save=True, show_doc_only=False):
"Execute notebook `fname` with `metadata` for preprocessing."
# Any module used in the notebook that isn't inside must be in the same directory as this script
with open(fname) as f: nb = nbformat.read(f, as_version=4)
ep_class = Execu... | python | def execute_nb(fname, metadata=None, save=True, show_doc_only=False):
"Execute notebook `fname` with `metadata` for preprocessing."
# Any module used in the notebook that isn't inside must be in the same directory as this script
with open(fname) as f: nb = nbformat.read(f, as_version=4)
ep_class = Execu... | [
"def",
"execute_nb",
"(",
"fname",
",",
"metadata",
"=",
"None",
",",
"save",
"=",
"True",
",",
"show_doc_only",
"=",
"False",
")",
":",
"# Any module used in the notebook that isn't inside must be in the same directory as this script",
"with",
"open",
"(",
"fname",
")"... | Execute notebook `fname` with `metadata` for preprocessing. | [
"Execute",
"notebook",
"fname",
"with",
"metadata",
"for",
"preprocessing",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L79-L89 |
20,711 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | create_module_page | def create_module_page(mod, dest_path, force=False):
"Create the documentation notebook for module `mod_name` in path `dest_path`"
nb = get_empty_notebook()
mod_name = mod.__name__
strip_name = strip_fastai(mod_name)
init_cell = [get_md_cell(f'## Title for {strip_name} (use plain english, not module... | python | def create_module_page(mod, dest_path, force=False):
"Create the documentation notebook for module `mod_name` in path `dest_path`"
nb = get_empty_notebook()
mod_name = mod.__name__
strip_name = strip_fastai(mod_name)
init_cell = [get_md_cell(f'## Title for {strip_name} (use plain english, not module... | [
"def",
"create_module_page",
"(",
"mod",
",",
"dest_path",
",",
"force",
"=",
"False",
")",
":",
"nb",
"=",
"get_empty_notebook",
"(",
")",
"mod_name",
"=",
"mod",
".",
"__name__",
"strip_name",
"=",
"strip_fastai",
"(",
"mod_name",
")",
"init_cell",
"=",
... | Create the documentation notebook for module `mod_name` in path `dest_path` | [
"Create",
"the",
"documentation",
"notebook",
"for",
"module",
"mod_name",
"in",
"path",
"dest_path"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L93-L117 |
20,712 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | get_module_names | def get_module_names(path_dir, exclude=None):
if exclude is None: exclude = _default_exclude
"Search a given `path_dir` and return all the modules contained inside except those in `exclude`"
files = sorted(path_dir.glob('*'), key=lambda x: (x.is_dir(), x.name), reverse=True) # directories first
res = [f... | python | def get_module_names(path_dir, exclude=None):
if exclude is None: exclude = _default_exclude
"Search a given `path_dir` and return all the modules contained inside except those in `exclude`"
files = sorted(path_dir.glob('*'), key=lambda x: (x.is_dir(), x.name), reverse=True) # directories first
res = [f... | [
"def",
"get_module_names",
"(",
"path_dir",
",",
"exclude",
"=",
"None",
")",
":",
"if",
"exclude",
"is",
"None",
":",
"exclude",
"=",
"_default_exclude",
"files",
"=",
"sorted",
"(",
"path_dir",
".",
"glob",
"(",
"'*'",
")",
",",
"key",
"=",
"lambda",
... | Search a given `path_dir` and return all the modules contained inside except those in `exclude` | [
"Search",
"a",
"given",
"path_dir",
"and",
"return",
"all",
"the",
"modules",
"contained",
"inside",
"except",
"those",
"in",
"exclude"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L121-L132 |
20,713 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | read_nb | def read_nb(fname):
"Read a notebook in `fname` and return its corresponding json"
with open(fname,'r') as f: return nbformat.reads(f.read(), as_version=4) | python | def read_nb(fname):
"Read a notebook in `fname` and return its corresponding json"
with open(fname,'r') as f: return nbformat.reads(f.read(), as_version=4) | [
"def",
"read_nb",
"(",
"fname",
")",
":",
"with",
"open",
"(",
"fname",
",",
"'r'",
")",
"as",
"f",
":",
"return",
"nbformat",
".",
"reads",
"(",
"f",
".",
"read",
"(",
")",
",",
"as_version",
"=",
"4",
")"
] | Read a notebook in `fname` and return its corresponding json | [
"Read",
"a",
"notebook",
"in",
"fname",
"and",
"return",
"its",
"corresponding",
"json"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L134-L136 |
20,714 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | read_nb_content | def read_nb_content(cells, mod_name):
"Build a dictionary containing the position of the `cells`."
doc_fns = {}
for i, cell in enumerate(cells):
if cell['cell_type'] == 'code':
for match in SHOW_DOC_RE.findall(cell['source']):
doc_fns[match] = i
return doc_fns | python | def read_nb_content(cells, mod_name):
"Build a dictionary containing the position of the `cells`."
doc_fns = {}
for i, cell in enumerate(cells):
if cell['cell_type'] == 'code':
for match in SHOW_DOC_RE.findall(cell['source']):
doc_fns[match] = i
return doc_fns | [
"def",
"read_nb_content",
"(",
"cells",
",",
"mod_name",
")",
":",
"doc_fns",
"=",
"{",
"}",
"for",
"i",
",",
"cell",
"in",
"enumerate",
"(",
"cells",
")",
":",
"if",
"cell",
"[",
"'cell_type'",
"]",
"==",
"'code'",
":",
"for",
"match",
"in",
"SHOW_D... | Build a dictionary containing the position of the `cells`. | [
"Build",
"a",
"dictionary",
"containing",
"the",
"position",
"of",
"the",
"cells",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L139-L146 |
20,715 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | link_markdown_cells | def link_markdown_cells(cells, modules):
"Create documentation links for all cells in markdown with backticks."
for i, cell in enumerate(cells):
if cell['cell_type'] == 'markdown':
cell['source'] = link_docstring(modules, cell['source']) | python | def link_markdown_cells(cells, modules):
"Create documentation links for all cells in markdown with backticks."
for i, cell in enumerate(cells):
if cell['cell_type'] == 'markdown':
cell['source'] = link_docstring(modules, cell['source']) | [
"def",
"link_markdown_cells",
"(",
"cells",
",",
"modules",
")",
":",
"for",
"i",
",",
"cell",
"in",
"enumerate",
"(",
"cells",
")",
":",
"if",
"cell",
"[",
"'cell_type'",
"]",
"==",
"'markdown'",
":",
"cell",
"[",
"'source'",
"]",
"=",
"link_docstring",... | Create documentation links for all cells in markdown with backticks. | [
"Create",
"documentation",
"links",
"for",
"all",
"cells",
"in",
"markdown",
"with",
"backticks",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L156-L160 |
20,716 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | get_insert_idx | def get_insert_idx(pos_dict, name):
"Return the position to insert a given function doc in a notebook."
keys,i = list(pos_dict.keys()),0
while i < len(keys) and str.lower(keys[i]) < str.lower(name): i+=1
if i == len(keys): return -1
else: return pos_dict[keys[i]] | python | def get_insert_idx(pos_dict, name):
"Return the position to insert a given function doc in a notebook."
keys,i = list(pos_dict.keys()),0
while i < len(keys) and str.lower(keys[i]) < str.lower(name): i+=1
if i == len(keys): return -1
else: return pos_dict[keys[i]] | [
"def",
"get_insert_idx",
"(",
"pos_dict",
",",
"name",
")",
":",
"keys",
",",
"i",
"=",
"list",
"(",
"pos_dict",
".",
"keys",
"(",
")",
")",
",",
"0",
"while",
"i",
"<",
"len",
"(",
"keys",
")",
"and",
"str",
".",
"lower",
"(",
"keys",
"[",
"i"... | Return the position to insert a given function doc in a notebook. | [
"Return",
"the",
"position",
"to",
"insert",
"a",
"given",
"function",
"doc",
"in",
"a",
"notebook",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L162-L167 |
20,717 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | update_pos | def update_pos(pos_dict, start_key, nbr=2):
"Update the `pos_dict` by moving all positions after `start_key` by `nbr`."
for key,idx in pos_dict.items():
if str.lower(key) >= str.lower(start_key): pos_dict[key] += nbr
return pos_dict | python | def update_pos(pos_dict, start_key, nbr=2):
"Update the `pos_dict` by moving all positions after `start_key` by `nbr`."
for key,idx in pos_dict.items():
if str.lower(key) >= str.lower(start_key): pos_dict[key] += nbr
return pos_dict | [
"def",
"update_pos",
"(",
"pos_dict",
",",
"start_key",
",",
"nbr",
"=",
"2",
")",
":",
"for",
"key",
",",
"idx",
"in",
"pos_dict",
".",
"items",
"(",
")",
":",
"if",
"str",
".",
"lower",
"(",
"key",
")",
">=",
"str",
".",
"lower",
"(",
"start_ke... | Update the `pos_dict` by moving all positions after `start_key` by `nbr`. | [
"Update",
"the",
"pos_dict",
"by",
"moving",
"all",
"positions",
"after",
"start_key",
"by",
"nbr",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L169-L173 |
20,718 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | insert_cells | def insert_cells(cells, pos_dict, ft_name, append=False):
"Insert the function doc `cells` at their correct position and updates `pos_dict`."
idx = get_insert_idx(pos_dict, ft_name)
if append or idx == -1: cells += [get_doc_cell(ft_name), get_empty_cell()]
else:
cells.insert(idx, get_doc_cell(ft... | python | def insert_cells(cells, pos_dict, ft_name, append=False):
"Insert the function doc `cells` at their correct position and updates `pos_dict`."
idx = get_insert_idx(pos_dict, ft_name)
if append or idx == -1: cells += [get_doc_cell(ft_name), get_empty_cell()]
else:
cells.insert(idx, get_doc_cell(ft... | [
"def",
"insert_cells",
"(",
"cells",
",",
"pos_dict",
",",
"ft_name",
",",
"append",
"=",
"False",
")",
":",
"idx",
"=",
"get_insert_idx",
"(",
"pos_dict",
",",
"ft_name",
")",
"if",
"append",
"or",
"idx",
"==",
"-",
"1",
":",
"cells",
"+=",
"[",
"ge... | Insert the function doc `cells` at their correct position and updates `pos_dict`. | [
"Insert",
"the",
"function",
"doc",
"cells",
"at",
"their",
"correct",
"position",
"and",
"updates",
"pos_dict",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L175-L183 |
20,719 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | update_nb_metadata | def update_nb_metadata(nb_path=None, title=None, summary=None, keywords='fastai', overwrite=True, **kwargs):
"Creates jekyll metadata for given notebook path."
nb = read_nb(nb_path)
data = {'title': title, 'summary': summary, 'keywords': keywords, **kwargs}
data = {k:v for (k,v) in data.items() if v is ... | python | def update_nb_metadata(nb_path=None, title=None, summary=None, keywords='fastai', overwrite=True, **kwargs):
"Creates jekyll metadata for given notebook path."
nb = read_nb(nb_path)
data = {'title': title, 'summary': summary, 'keywords': keywords, **kwargs}
data = {k:v for (k,v) in data.items() if v is ... | [
"def",
"update_nb_metadata",
"(",
"nb_path",
"=",
"None",
",",
"title",
"=",
"None",
",",
"summary",
"=",
"None",
",",
"keywords",
"=",
"'fastai'",
",",
"overwrite",
"=",
"True",
",",
"*",
"*",
"kwargs",
")",
":",
"nb",
"=",
"read_nb",
"(",
"nb_path",
... | Creates jekyll metadata for given notebook path. | [
"Creates",
"jekyll",
"metadata",
"for",
"given",
"notebook",
"path",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L204-L212 |
20,720 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | get_imported_modules | def get_imported_modules(cells, nb_module_name=''):
"Finds all submodules of notebook - sorted by submodules > top level modules > manual imports. This gives notebook imports priority"
module_names = get_top_level_modules()
nb_imports = [match.group(1) for cell in cells for match in IMPORT_RE.finditer(cell[... | python | def get_imported_modules(cells, nb_module_name=''):
"Finds all submodules of notebook - sorted by submodules > top level modules > manual imports. This gives notebook imports priority"
module_names = get_top_level_modules()
nb_imports = [match.group(1) for cell in cells for match in IMPORT_RE.finditer(cell[... | [
"def",
"get_imported_modules",
"(",
"cells",
",",
"nb_module_name",
"=",
"''",
")",
":",
"module_names",
"=",
"get_top_level_modules",
"(",
")",
"nb_imports",
"=",
"[",
"match",
".",
"group",
"(",
"1",
")",
"for",
"cell",
"in",
"cells",
"for",
"match",
"in... | Finds all submodules of notebook - sorted by submodules > top level modules > manual imports. This gives notebook imports priority | [
"Finds",
"all",
"submodules",
"of",
"notebook",
"-",
"sorted",
"by",
"submodules",
">",
"top",
"level",
"modules",
">",
"manual",
"imports",
".",
"This",
"gives",
"notebook",
"imports",
"priority"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L221-L229 |
20,721 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | update_module_page | def update_module_page(mod, dest_path='.'):
"Update the documentation notebook of a given module."
doc_path = get_doc_path(mod, dest_path)
strip_name = strip_fastai(mod.__name__)
nb = read_nb(doc_path)
cells = nb['cells']
link_markdown_cells(cells, get_imported_modules(cells, mod.__name__))
... | python | def update_module_page(mod, dest_path='.'):
"Update the documentation notebook of a given module."
doc_path = get_doc_path(mod, dest_path)
strip_name = strip_fastai(mod.__name__)
nb = read_nb(doc_path)
cells = nb['cells']
link_markdown_cells(cells, get_imported_modules(cells, mod.__name__))
... | [
"def",
"update_module_page",
"(",
"mod",
",",
"dest_path",
"=",
"'.'",
")",
":",
"doc_path",
"=",
"get_doc_path",
"(",
"mod",
",",
"dest_path",
")",
"strip_name",
"=",
"strip_fastai",
"(",
"mod",
".",
"__name__",
")",
"nb",
"=",
"read_nb",
"(",
"doc_path",... | Update the documentation notebook of a given module. | [
"Update",
"the",
"documentation",
"notebook",
"of",
"a",
"given",
"module",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L262-L288 |
20,722 | fastai/fastai | fastai/gen_doc/gen_notebooks.py | update_notebooks | def update_notebooks(source_path, dest_path=None, update_html=True, document_new_fns=False,
update_nb_links=True, html_path=None, force=False):
"`source_path` can be a directory or a file. Assume all modules reside in the fastai directory."
from .convert2html import convert_nb
source_pa... | python | def update_notebooks(source_path, dest_path=None, update_html=True, document_new_fns=False,
update_nb_links=True, html_path=None, force=False):
"`source_path` can be a directory or a file. Assume all modules reside in the fastai directory."
from .convert2html import convert_nb
source_pa... | [
"def",
"update_notebooks",
"(",
"source_path",
",",
"dest_path",
"=",
"None",
",",
"update_html",
"=",
"True",
",",
"document_new_fns",
"=",
"False",
",",
"update_nb_links",
"=",
"True",
",",
"html_path",
"=",
"None",
",",
"force",
"=",
"False",
")",
":",
... | `source_path` can be a directory or a file. Assume all modules reside in the fastai directory. | [
"source_path",
"can",
"be",
"a",
"directory",
"or",
"a",
"file",
".",
"Assume",
"all",
"modules",
"reside",
"in",
"the",
"fastai",
"directory",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/gen_doc/gen_notebooks.py#L305-L350 |
20,723 | fastai/fastai | fastai/text/models/awd_lstm.py | dropout_mask | def dropout_mask(x:Tensor, sz:Collection[int], p:float):
"Return a dropout mask of the same type as `x`, size `sz`, with probability `p` to cancel an element."
return x.new(*sz).bernoulli_(1-p).div_(1-p) | python | def dropout_mask(x:Tensor, sz:Collection[int], p:float):
"Return a dropout mask of the same type as `x`, size `sz`, with probability `p` to cancel an element."
return x.new(*sz).bernoulli_(1-p).div_(1-p) | [
"def",
"dropout_mask",
"(",
"x",
":",
"Tensor",
",",
"sz",
":",
"Collection",
"[",
"int",
"]",
",",
"p",
":",
"float",
")",
":",
"return",
"x",
".",
"new",
"(",
"*",
"sz",
")",
".",
"bernoulli_",
"(",
"1",
"-",
"p",
")",
".",
"div_",
"(",
"1"... | Return a dropout mask of the same type as `x`, size `sz`, with probability `p` to cancel an element. | [
"Return",
"a",
"dropout",
"mask",
"of",
"the",
"same",
"type",
"as",
"x",
"size",
"sz",
"with",
"probability",
"p",
"to",
"cancel",
"an",
"element",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/models/awd_lstm.py#L13-L15 |
20,724 | fastai/fastai | fastai/text/models/awd_lstm.py | WeightDropout._setweights | def _setweights(self):
"Apply dropout to the raw weights."
for layer in self.layer_names:
raw_w = getattr(self, f'{layer}_raw')
self.module._parameters[layer] = F.dropout(raw_w, p=self.weight_p, training=self.training) | python | def _setweights(self):
"Apply dropout to the raw weights."
for layer in self.layer_names:
raw_w = getattr(self, f'{layer}_raw')
self.module._parameters[layer] = F.dropout(raw_w, p=self.weight_p, training=self.training) | [
"def",
"_setweights",
"(",
"self",
")",
":",
"for",
"layer",
"in",
"self",
".",
"layer_names",
":",
"raw_w",
"=",
"getattr",
"(",
"self",
",",
"f'{layer}_raw'",
")",
"self",
".",
"module",
".",
"_parameters",
"[",
"layer",
"]",
"=",
"F",
".",
"dropout"... | Apply dropout to the raw weights. | [
"Apply",
"dropout",
"to",
"the",
"raw",
"weights",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/models/awd_lstm.py#L41-L45 |
20,725 | fastai/fastai | fastai/text/models/awd_lstm.py | AWD_LSTM._one_hidden | def _one_hidden(self, l:int)->Tensor:
"Return one hidden state."
nh = (self.n_hid if l != self.n_layers - 1 else self.emb_sz) // self.n_dir
return one_param(self).new(1, self.bs, nh).zero_() | python | def _one_hidden(self, l:int)->Tensor:
"Return one hidden state."
nh = (self.n_hid if l != self.n_layers - 1 else self.emb_sz) // self.n_dir
return one_param(self).new(1, self.bs, nh).zero_() | [
"def",
"_one_hidden",
"(",
"self",
",",
"l",
":",
"int",
")",
"->",
"Tensor",
":",
"nh",
"=",
"(",
"self",
".",
"n_hid",
"if",
"l",
"!=",
"self",
".",
"n_layers",
"-",
"1",
"else",
"self",
".",
"emb_sz",
")",
"//",
"self",
".",
"n_dir",
"return",... | Return one hidden state. | [
"Return",
"one",
"hidden",
"state",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/models/awd_lstm.py#L125-L128 |
20,726 | fastai/fastai | fastai/text/models/awd_lstm.py | AWD_LSTM.reset | def reset(self):
"Reset the hidden states."
[r.reset() for r in self.rnns if hasattr(r, 'reset')]
if self.qrnn: self.hidden = [self._one_hidden(l) for l in range(self.n_layers)]
else: self.hidden = [(self._one_hidden(l), self._one_hidden(l)) for l in range(self.n_layers)] | python | def reset(self):
"Reset the hidden states."
[r.reset() for r in self.rnns if hasattr(r, 'reset')]
if self.qrnn: self.hidden = [self._one_hidden(l) for l in range(self.n_layers)]
else: self.hidden = [(self._one_hidden(l), self._one_hidden(l)) for l in range(self.n_layers)] | [
"def",
"reset",
"(",
"self",
")",
":",
"[",
"r",
".",
"reset",
"(",
")",
"for",
"r",
"in",
"self",
".",
"rnns",
"if",
"hasattr",
"(",
"r",
",",
"'reset'",
")",
"]",
"if",
"self",
".",
"qrnn",
":",
"self",
".",
"hidden",
"=",
"[",
"self",
".",... | Reset the hidden states. | [
"Reset",
"the",
"hidden",
"states",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/models/awd_lstm.py#L135-L139 |
20,727 | fastai/fastai | fastai/text/models/awd_lstm.py | TextClassificationInterpretation.show_top_losses | def show_top_losses(self, k:int, max_len:int=70)->None:
"""
Create a tabulation showing the first `k` texts in top_losses along with their prediction, actual,loss, and probability of
actual class. `max_len` is the maximum number of tokens displayed.
"""
from IPython.display impor... | python | def show_top_losses(self, k:int, max_len:int=70)->None:
"""
Create a tabulation showing the first `k` texts in top_losses along with their prediction, actual,loss, and probability of
actual class. `max_len` is the maximum number of tokens displayed.
"""
from IPython.display impor... | [
"def",
"show_top_losses",
"(",
"self",
",",
"k",
":",
"int",
",",
"max_len",
":",
"int",
"=",
"70",
")",
"->",
"None",
":",
"from",
"IPython",
".",
"display",
"import",
"display",
",",
"HTML",
"items",
"=",
"[",
"]",
"tl_val",
",",
"tl_idx",
"=",
"... | Create a tabulation showing the first `k` texts in top_losses along with their prediction, actual,loss, and probability of
actual class. `max_len` is the maximum number of tokens displayed. | [
"Create",
"a",
"tabulation",
"showing",
"the",
"first",
"k",
"texts",
"in",
"top_losses",
"along",
"with",
"their",
"prediction",
"actual",
"loss",
"and",
"probability",
"of",
"actual",
"class",
".",
"max_len",
"is",
"the",
"maximum",
"number",
"of",
"tokens",... | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/models/awd_lstm.py#L246-L268 |
20,728 | fastai/fastai | fastai/callbacks/general_sched.py | GeneralScheduler.on_train_begin | def on_train_begin(self, epoch:int, **kwargs:Any)->None:
"Initialize the schedulers for training."
res = {'epoch':self.start_epoch} if self.start_epoch is not None else None
self.start_epoch = ifnone(self.start_epoch, epoch)
self.scheds = [p.scheds for p in self.phases]
self.opt ... | python | def on_train_begin(self, epoch:int, **kwargs:Any)->None:
"Initialize the schedulers for training."
res = {'epoch':self.start_epoch} if self.start_epoch is not None else None
self.start_epoch = ifnone(self.start_epoch, epoch)
self.scheds = [p.scheds for p in self.phases]
self.opt ... | [
"def",
"on_train_begin",
"(",
"self",
",",
"epoch",
":",
"int",
",",
"*",
"*",
"kwargs",
":",
"Any",
")",
"->",
"None",
":",
"res",
"=",
"{",
"'epoch'",
":",
"self",
".",
"start_epoch",
"}",
"if",
"self",
".",
"start_epoch",
"is",
"not",
"None",
"e... | Initialize the schedulers for training. | [
"Initialize",
"the",
"schedulers",
"for",
"training",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/general_sched.py#L24-L34 |
20,729 | fastai/fastai | fastai/callbacks/general_sched.py | GeneralScheduler.on_batch_end | def on_batch_end(self, train, **kwargs:Any)->None:
"Take a step in lr,mom sched, start next stepper when the current one is complete."
if train:
if self.idx_s >= len(self.scheds): return {'stop_training': True, 'stop_epoch': True}
sched = self.scheds[self.idx_s]
for k... | python | def on_batch_end(self, train, **kwargs:Any)->None:
"Take a step in lr,mom sched, start next stepper when the current one is complete."
if train:
if self.idx_s >= len(self.scheds): return {'stop_training': True, 'stop_epoch': True}
sched = self.scheds[self.idx_s]
for k... | [
"def",
"on_batch_end",
"(",
"self",
",",
"train",
",",
"*",
"*",
"kwargs",
":",
"Any",
")",
"->",
"None",
":",
"if",
"train",
":",
"if",
"self",
".",
"idx_s",
">=",
"len",
"(",
"self",
".",
"scheds",
")",
":",
"return",
"{",
"'stop_training'",
":",... | Take a step in lr,mom sched, start next stepper when the current one is complete. | [
"Take",
"a",
"step",
"in",
"lr",
"mom",
"sched",
"start",
"next",
"stepper",
"when",
"the",
"current",
"one",
"is",
"complete",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/general_sched.py#L40-L46 |
20,730 | fastai/fastai | fastai/torch_core.py | tensor | def tensor(x:Any, *rest)->Tensor:
"Like `torch.as_tensor`, but handle lists too, and can pass multiple vector elements directly."
if len(rest): x = (x,)+rest
# XXX: Pytorch bug in dataloader using num_workers>0; TODO: create repro and report
if is_listy(x) and len(x)==0: return tensor(0)
res = torch... | python | def tensor(x:Any, *rest)->Tensor:
"Like `torch.as_tensor`, but handle lists too, and can pass multiple vector elements directly."
if len(rest): x = (x,)+rest
# XXX: Pytorch bug in dataloader using num_workers>0; TODO: create repro and report
if is_listy(x) and len(x)==0: return tensor(0)
res = torch... | [
"def",
"tensor",
"(",
"x",
":",
"Any",
",",
"*",
"rest",
")",
"->",
"Tensor",
":",
"if",
"len",
"(",
"rest",
")",
":",
"x",
"=",
"(",
"x",
",",
")",
"+",
"rest",
"# XXX: Pytorch bug in dataloader using num_workers>0; TODO: create repro and report",
"if",
"is... | Like `torch.as_tensor`, but handle lists too, and can pass multiple vector elements directly. | [
"Like",
"torch",
".",
"as_tensor",
"but",
"handle",
"lists",
"too",
"and",
"can",
"pass",
"multiple",
"vector",
"elements",
"directly",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L76-L85 |
20,731 | fastai/fastai | fastai/torch_core.py | to_detach | def to_detach(b:Tensors, cpu:bool=True):
"Recursively detach lists of tensors in `b `; put them on the CPU if `cpu=True`."
if is_listy(b): return [to_detach(o, cpu) for o in b]
if not isinstance(b,Tensor): return b
b = b.detach()
return b.cpu() if cpu else b | python | def to_detach(b:Tensors, cpu:bool=True):
"Recursively detach lists of tensors in `b `; put them on the CPU if `cpu=True`."
if is_listy(b): return [to_detach(o, cpu) for o in b]
if not isinstance(b,Tensor): return b
b = b.detach()
return b.cpu() if cpu else b | [
"def",
"to_detach",
"(",
"b",
":",
"Tensors",
",",
"cpu",
":",
"bool",
"=",
"True",
")",
":",
"if",
"is_listy",
"(",
"b",
")",
":",
"return",
"[",
"to_detach",
"(",
"o",
",",
"cpu",
")",
"for",
"o",
"in",
"b",
"]",
"if",
"not",
"isinstance",
"(... | Recursively detach lists of tensors in `b `; put them on the CPU if `cpu=True`. | [
"Recursively",
"detach",
"lists",
"of",
"tensors",
"in",
"b",
";",
"put",
"them",
"on",
"the",
"CPU",
"if",
"cpu",
"=",
"True",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L91-L96 |
20,732 | fastai/fastai | fastai/torch_core.py | to_data | def to_data(b:ItemsList):
"Recursively map lists of items in `b ` to their wrapped data."
if is_listy(b): return [to_data(o) for o in b]
return b.data if isinstance(b,ItemBase) else b | python | def to_data(b:ItemsList):
"Recursively map lists of items in `b ` to their wrapped data."
if is_listy(b): return [to_data(o) for o in b]
return b.data if isinstance(b,ItemBase) else b | [
"def",
"to_data",
"(",
"b",
":",
"ItemsList",
")",
":",
"if",
"is_listy",
"(",
"b",
")",
":",
"return",
"[",
"to_data",
"(",
"o",
")",
"for",
"o",
"in",
"b",
"]",
"return",
"b",
".",
"data",
"if",
"isinstance",
"(",
"b",
",",
"ItemBase",
")",
"... | Recursively map lists of items in `b ` to their wrapped data. | [
"Recursively",
"map",
"lists",
"of",
"items",
"in",
"b",
"to",
"their",
"wrapped",
"data",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L98-L101 |
20,733 | fastai/fastai | fastai/torch_core.py | to_cpu | def to_cpu(b:ItemsList):
"Recursively map lists of tensors in `b ` to the cpu."
if is_listy(b): return [to_cpu(o) for o in b]
return b.cpu() if isinstance(b,Tensor) else b | python | def to_cpu(b:ItemsList):
"Recursively map lists of tensors in `b ` to the cpu."
if is_listy(b): return [to_cpu(o) for o in b]
return b.cpu() if isinstance(b,Tensor) else b | [
"def",
"to_cpu",
"(",
"b",
":",
"ItemsList",
")",
":",
"if",
"is_listy",
"(",
"b",
")",
":",
"return",
"[",
"to_cpu",
"(",
"o",
")",
"for",
"o",
"in",
"b",
"]",
"return",
"b",
".",
"cpu",
"(",
")",
"if",
"isinstance",
"(",
"b",
",",
"Tensor",
... | Recursively map lists of tensors in `b ` to the cpu. | [
"Recursively",
"map",
"lists",
"of",
"tensors",
"in",
"b",
"to",
"the",
"cpu",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L103-L106 |
20,734 | fastai/fastai | fastai/torch_core.py | to_device | def to_device(b:Tensors, device:torch.device):
"Recursively put `b` on `device`."
device = ifnone(device, defaults.device)
if is_listy(b): return [to_device(o, device) for o in b]
if is_dict(b): return {k: to_device(v, device) for k, v in b.items()}
return b.to(device, non_blocking=True) | python | def to_device(b:Tensors, device:torch.device):
"Recursively put `b` on `device`."
device = ifnone(device, defaults.device)
if is_listy(b): return [to_device(o, device) for o in b]
if is_dict(b): return {k: to_device(v, device) for k, v in b.items()}
return b.to(device, non_blocking=True) | [
"def",
"to_device",
"(",
"b",
":",
"Tensors",
",",
"device",
":",
"torch",
".",
"device",
")",
":",
"device",
"=",
"ifnone",
"(",
"device",
",",
"defaults",
".",
"device",
")",
"if",
"is_listy",
"(",
"b",
")",
":",
"return",
"[",
"to_device",
"(",
... | Recursively put `b` on `device`. | [
"Recursively",
"put",
"b",
"on",
"device",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L118-L123 |
20,735 | fastai/fastai | fastai/torch_core.py | data_collate | def data_collate(batch:ItemsList)->Tensor:
"Convert `batch` items to tensor data."
return torch.utils.data.dataloader.default_collate(to_data(batch)) | python | def data_collate(batch:ItemsList)->Tensor:
"Convert `batch` items to tensor data."
return torch.utils.data.dataloader.default_collate(to_data(batch)) | [
"def",
"data_collate",
"(",
"batch",
":",
"ItemsList",
")",
"->",
"Tensor",
":",
"return",
"torch",
".",
"utils",
".",
"data",
".",
"dataloader",
".",
"default_collate",
"(",
"to_data",
"(",
"batch",
")",
")"
] | Convert `batch` items to tensor data. | [
"Convert",
"batch",
"items",
"to",
"tensor",
"data",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L125-L127 |
20,736 | fastai/fastai | fastai/torch_core.py | requires_grad | def requires_grad(m:nn.Module, b:Optional[bool]=None)->Optional[bool]:
"If `b` is not set return `requires_grad` of first param, else set `requires_grad` on all params as `b`"
ps = list(m.parameters())
if not ps: return None
if b is None: return ps[0].requires_grad
for p in ps: p.requires_grad=b | python | def requires_grad(m:nn.Module, b:Optional[bool]=None)->Optional[bool]:
"If `b` is not set return `requires_grad` of first param, else set `requires_grad` on all params as `b`"
ps = list(m.parameters())
if not ps: return None
if b is None: return ps[0].requires_grad
for p in ps: p.requires_grad=b | [
"def",
"requires_grad",
"(",
"m",
":",
"nn",
".",
"Module",
",",
"b",
":",
"Optional",
"[",
"bool",
"]",
"=",
"None",
")",
"->",
"Optional",
"[",
"bool",
"]",
":",
"ps",
"=",
"list",
"(",
"m",
".",
"parameters",
"(",
")",
")",
"if",
"not",
"ps"... | If `b` is not set return `requires_grad` of first param, else set `requires_grad` on all params as `b` | [
"If",
"b",
"is",
"not",
"set",
"return",
"requires_grad",
"of",
"first",
"param",
"else",
"set",
"requires_grad",
"on",
"all",
"params",
"as",
"b"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L129-L134 |
20,737 | fastai/fastai | fastai/torch_core.py | trainable_params | def trainable_params(m:nn.Module)->ParamList:
"Return list of trainable params in `m`."
res = filter(lambda p: p.requires_grad, m.parameters())
return res | python | def trainable_params(m:nn.Module)->ParamList:
"Return list of trainable params in `m`."
res = filter(lambda p: p.requires_grad, m.parameters())
return res | [
"def",
"trainable_params",
"(",
"m",
":",
"nn",
".",
"Module",
")",
"->",
"ParamList",
":",
"res",
"=",
"filter",
"(",
"lambda",
"p",
":",
"p",
".",
"requires_grad",
",",
"m",
".",
"parameters",
"(",
")",
")",
"return",
"res"
] | Return list of trainable params in `m`. | [
"Return",
"list",
"of",
"trainable",
"params",
"in",
"m",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L136-L139 |
20,738 | fastai/fastai | fastai/torch_core.py | children_and_parameters | def children_and_parameters(m:nn.Module):
"Return the children of `m` and its direct parameters not registered in modules."
children = list(m.children())
children_p = sum([[id(p) for p in c.parameters()] for c in m.children()],[])
for p in m.parameters():
if id(p) not in children_p: children.app... | python | def children_and_parameters(m:nn.Module):
"Return the children of `m` and its direct parameters not registered in modules."
children = list(m.children())
children_p = sum([[id(p) for p in c.parameters()] for c in m.children()],[])
for p in m.parameters():
if id(p) not in children_p: children.app... | [
"def",
"children_and_parameters",
"(",
"m",
":",
"nn",
".",
"Module",
")",
":",
"children",
"=",
"list",
"(",
"m",
".",
"children",
"(",
")",
")",
"children_p",
"=",
"sum",
"(",
"[",
"[",
"id",
"(",
"p",
")",
"for",
"p",
"in",
"c",
".",
"paramete... | Return the children of `m` and its direct parameters not registered in modules. | [
"Return",
"the",
"children",
"of",
"m",
"and",
"its",
"direct",
"parameters",
"not",
"registered",
"in",
"modules",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L161-L167 |
20,739 | fastai/fastai | fastai/torch_core.py | split_model_idx | def split_model_idx(model:nn.Module, idxs:Collection[int])->ModuleList:
"Split `model` according to the indexes in `idxs`."
layers = flatten_model(model)
if idxs[0] != 0: idxs = [0] + idxs
if idxs[-1] != len(layers): idxs.append(len(layers))
return [nn.Sequential(*layers[i:j]) for i,j in zip(idxs[:-... | python | def split_model_idx(model:nn.Module, idxs:Collection[int])->ModuleList:
"Split `model` according to the indexes in `idxs`."
layers = flatten_model(model)
if idxs[0] != 0: idxs = [0] + idxs
if idxs[-1] != len(layers): idxs.append(len(layers))
return [nn.Sequential(*layers[i:j]) for i,j in zip(idxs[:-... | [
"def",
"split_model_idx",
"(",
"model",
":",
"nn",
".",
"Module",
",",
"idxs",
":",
"Collection",
"[",
"int",
"]",
")",
"->",
"ModuleList",
":",
"layers",
"=",
"flatten_model",
"(",
"model",
")",
"if",
"idxs",
"[",
"0",
"]",
"!=",
"0",
":",
"idxs",
... | Split `model` according to the indexes in `idxs`. | [
"Split",
"model",
"according",
"to",
"the",
"indexes",
"in",
"idxs",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L179-L184 |
20,740 | fastai/fastai | fastai/torch_core.py | split_model | def split_model(model:nn.Module=None, splits:Collection[Union[nn.Module,ModuleList]]=None):
"Split `model` according to the layers in `splits`."
splits = listify(splits)
if isinstance(splits[0], nn.Module):
layers = flatten_model(model)
idxs = [layers.index(first_layer(s)) for s in splits]
... | python | def split_model(model:nn.Module=None, splits:Collection[Union[nn.Module,ModuleList]]=None):
"Split `model` according to the layers in `splits`."
splits = listify(splits)
if isinstance(splits[0], nn.Module):
layers = flatten_model(model)
idxs = [layers.index(first_layer(s)) for s in splits]
... | [
"def",
"split_model",
"(",
"model",
":",
"nn",
".",
"Module",
"=",
"None",
",",
"splits",
":",
"Collection",
"[",
"Union",
"[",
"nn",
".",
"Module",
",",
"ModuleList",
"]",
"]",
"=",
"None",
")",
":",
"splits",
"=",
"listify",
"(",
"splits",
")",
"... | Split `model` according to the layers in `splits`. | [
"Split",
"model",
"according",
"to",
"the",
"layers",
"in",
"splits",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L186-L193 |
20,741 | fastai/fastai | fastai/torch_core.py | set_bn_eval | def set_bn_eval(m:nn.Module)->None:
"Set bn layers in eval mode for all recursive children of `m`."
for l in m.children():
if isinstance(l, bn_types) and not next(l.parameters()).requires_grad:
l.eval()
set_bn_eval(l) | python | def set_bn_eval(m:nn.Module)->None:
"Set bn layers in eval mode for all recursive children of `m`."
for l in m.children():
if isinstance(l, bn_types) and not next(l.parameters()).requires_grad:
l.eval()
set_bn_eval(l) | [
"def",
"set_bn_eval",
"(",
"m",
":",
"nn",
".",
"Module",
")",
"->",
"None",
":",
"for",
"l",
"in",
"m",
".",
"children",
"(",
")",
":",
"if",
"isinstance",
"(",
"l",
",",
"bn_types",
")",
"and",
"not",
"next",
"(",
"l",
".",
"parameters",
"(",
... | Set bn layers in eval mode for all recursive children of `m`. | [
"Set",
"bn",
"layers",
"in",
"eval",
"mode",
"for",
"all",
"recursive",
"children",
"of",
"m",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L216-L221 |
20,742 | fastai/fastai | fastai/torch_core.py | bn2float | def bn2float(module:nn.Module)->nn.Module:
"If `module` is batchnorm don't use half precision."
if isinstance(module, torch.nn.modules.batchnorm._BatchNorm): module.float()
for child in module.children(): bn2float(child)
return module | python | def bn2float(module:nn.Module)->nn.Module:
"If `module` is batchnorm don't use half precision."
if isinstance(module, torch.nn.modules.batchnorm._BatchNorm): module.float()
for child in module.children(): bn2float(child)
return module | [
"def",
"bn2float",
"(",
"module",
":",
"nn",
".",
"Module",
")",
"->",
"nn",
".",
"Module",
":",
"if",
"isinstance",
"(",
"module",
",",
"torch",
".",
"nn",
".",
"modules",
".",
"batchnorm",
".",
"_BatchNorm",
")",
":",
"module",
".",
"float",
"(",
... | If `module` is batchnorm don't use half precision. | [
"If",
"module",
"is",
"batchnorm",
"don",
"t",
"use",
"half",
"precision",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L227-L231 |
20,743 | fastai/fastai | fastai/torch_core.py | init_default | def init_default(m:nn.Module, func:LayerFunc=nn.init.kaiming_normal_)->None:
"Initialize `m` weights with `func` and set `bias` to 0."
if func:
if hasattr(m, 'weight'): func(m.weight)
if hasattr(m, 'bias') and hasattr(m.bias, 'data'): m.bias.data.fill_(0.)
return m | python | def init_default(m:nn.Module, func:LayerFunc=nn.init.kaiming_normal_)->None:
"Initialize `m` weights with `func` and set `bias` to 0."
if func:
if hasattr(m, 'weight'): func(m.weight)
if hasattr(m, 'bias') and hasattr(m.bias, 'data'): m.bias.data.fill_(0.)
return m | [
"def",
"init_default",
"(",
"m",
":",
"nn",
".",
"Module",
",",
"func",
":",
"LayerFunc",
"=",
"nn",
".",
"init",
".",
"kaiming_normal_",
")",
"->",
"None",
":",
"if",
"func",
":",
"if",
"hasattr",
"(",
"m",
",",
"'weight'",
")",
":",
"func",
"(",
... | Initialize `m` weights with `func` and set `bias` to 0. | [
"Initialize",
"m",
"weights",
"with",
"func",
"and",
"set",
"bias",
"to",
"0",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L237-L242 |
20,744 | fastai/fastai | fastai/torch_core.py | cond_init | def cond_init(m:nn.Module, init_func:LayerFunc):
"Initialize the non-batchnorm layers of `m` with `init_func`."
if (not isinstance(m, bn_types)) and requires_grad(m): init_default(m, init_func) | python | def cond_init(m:nn.Module, init_func:LayerFunc):
"Initialize the non-batchnorm layers of `m` with `init_func`."
if (not isinstance(m, bn_types)) and requires_grad(m): init_default(m, init_func) | [
"def",
"cond_init",
"(",
"m",
":",
"nn",
".",
"Module",
",",
"init_func",
":",
"LayerFunc",
")",
":",
"if",
"(",
"not",
"isinstance",
"(",
"m",
",",
"bn_types",
")",
")",
"and",
"requires_grad",
"(",
"m",
")",
":",
"init_default",
"(",
"m",
",",
"i... | Initialize the non-batchnorm layers of `m` with `init_func`. | [
"Initialize",
"the",
"non",
"-",
"batchnorm",
"layers",
"of",
"m",
"with",
"init_func",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L244-L246 |
20,745 | fastai/fastai | fastai/torch_core.py | apply_init | def apply_init(m, init_func:LayerFunc):
"Initialize all non-batchnorm layers of `m` with `init_func`."
apply_leaf(m, partial(cond_init, init_func=init_func)) | python | def apply_init(m, init_func:LayerFunc):
"Initialize all non-batchnorm layers of `m` with `init_func`."
apply_leaf(m, partial(cond_init, init_func=init_func)) | [
"def",
"apply_init",
"(",
"m",
",",
"init_func",
":",
"LayerFunc",
")",
":",
"apply_leaf",
"(",
"m",
",",
"partial",
"(",
"cond_init",
",",
"init_func",
"=",
"init_func",
")",
")"
] | Initialize all non-batchnorm layers of `m` with `init_func`. | [
"Initialize",
"all",
"non",
"-",
"batchnorm",
"layers",
"of",
"m",
"with",
"init_func",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L254-L256 |
20,746 | fastai/fastai | fastai/torch_core.py | in_channels | def in_channels(m:nn.Module) -> List[int]:
"Return the shape of the first weight layer in `m`."
for l in flatten_model(m):
if hasattr(l, 'weight'): return l.weight.shape[1]
raise Exception('No weight layer') | python | def in_channels(m:nn.Module) -> List[int]:
"Return the shape of the first weight layer in `m`."
for l in flatten_model(m):
if hasattr(l, 'weight'): return l.weight.shape[1]
raise Exception('No weight layer') | [
"def",
"in_channels",
"(",
"m",
":",
"nn",
".",
"Module",
")",
"->",
"List",
"[",
"int",
"]",
":",
"for",
"l",
"in",
"flatten_model",
"(",
"m",
")",
":",
"if",
"hasattr",
"(",
"l",
",",
"'weight'",
")",
":",
"return",
"l",
".",
"weight",
".",
"... | Return the shape of the first weight layer in `m`. | [
"Return",
"the",
"shape",
"of",
"the",
"first",
"weight",
"layer",
"in",
"m",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L258-L262 |
20,747 | fastai/fastai | fastai/torch_core.py | model_type | def model_type(dtype):
"Return the torch type corresponding to `dtype`."
return (torch.float32 if np.issubdtype(dtype, np.floating) else
torch.int64 if np.issubdtype(dtype, np.integer)
else None) | python | def model_type(dtype):
"Return the torch type corresponding to `dtype`."
return (torch.float32 if np.issubdtype(dtype, np.floating) else
torch.int64 if np.issubdtype(dtype, np.integer)
else None) | [
"def",
"model_type",
"(",
"dtype",
")",
":",
"return",
"(",
"torch",
".",
"float32",
"if",
"np",
".",
"issubdtype",
"(",
"dtype",
",",
"np",
".",
"floating",
")",
"else",
"torch",
".",
"int64",
"if",
"np",
".",
"issubdtype",
"(",
"dtype",
",",
"np",
... | Return the torch type corresponding to `dtype`. | [
"Return",
"the",
"torch",
"type",
"corresponding",
"to",
"dtype",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L292-L296 |
20,748 | fastai/fastai | fastai/torch_core.py | np2model_tensor | def np2model_tensor(a):
"Tranform numpy array `a` to a tensor of the same type."
dtype = model_type(a.dtype)
res = as_tensor(a)
if not dtype: return res
return res.type(dtype) | python | def np2model_tensor(a):
"Tranform numpy array `a` to a tensor of the same type."
dtype = model_type(a.dtype)
res = as_tensor(a)
if not dtype: return res
return res.type(dtype) | [
"def",
"np2model_tensor",
"(",
"a",
")",
":",
"dtype",
"=",
"model_type",
"(",
"a",
".",
"dtype",
")",
"res",
"=",
"as_tensor",
"(",
"a",
")",
"if",
"not",
"dtype",
":",
"return",
"res",
"return",
"res",
".",
"type",
"(",
"dtype",
")"
] | Tranform numpy array `a` to a tensor of the same type. | [
"Tranform",
"numpy",
"array",
"a",
"to",
"a",
"tensor",
"of",
"the",
"same",
"type",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L298-L303 |
20,749 | fastai/fastai | fastai/torch_core.py | _pca | def _pca(x, k=2):
"Compute PCA of `x` with `k` dimensions."
x = x-torch.mean(x,0)
U,S,V = torch.svd(x.t())
return torch.mm(x,U[:,:k]) | python | def _pca(x, k=2):
"Compute PCA of `x` with `k` dimensions."
x = x-torch.mean(x,0)
U,S,V = torch.svd(x.t())
return torch.mm(x,U[:,:k]) | [
"def",
"_pca",
"(",
"x",
",",
"k",
"=",
"2",
")",
":",
"x",
"=",
"x",
"-",
"torch",
".",
"mean",
"(",
"x",
",",
"0",
")",
"U",
",",
"S",
",",
"V",
"=",
"torch",
".",
"svd",
"(",
"x",
".",
"t",
"(",
")",
")",
"return",
"torch",
".",
"m... | Compute PCA of `x` with `k` dimensions. | [
"Compute",
"PCA",
"of",
"x",
"with",
"k",
"dimensions",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L305-L309 |
20,750 | fastai/fastai | fastai/torch_core.py | grab_idx | def grab_idx(x,i,batch_first:bool=True):
"Grab the `i`-th batch in `x`, `batch_first` stating the batch dimension."
if batch_first: return ([o[i].cpu() for o in x] if is_listy(x) else x[i].cpu())
else: return ([o[:,i].cpu() for o in x] if is_listy(x) else x[:,i].cpu()) | python | def grab_idx(x,i,batch_first:bool=True):
"Grab the `i`-th batch in `x`, `batch_first` stating the batch dimension."
if batch_first: return ([o[i].cpu() for o in x] if is_listy(x) else x[i].cpu())
else: return ([o[:,i].cpu() for o in x] if is_listy(x) else x[:,i].cpu()) | [
"def",
"grab_idx",
"(",
"x",
",",
"i",
",",
"batch_first",
":",
"bool",
"=",
"True",
")",
":",
"if",
"batch_first",
":",
"return",
"(",
"[",
"o",
"[",
"i",
"]",
".",
"cpu",
"(",
")",
"for",
"o",
"in",
"x",
"]",
"if",
"is_listy",
"(",
"x",
")"... | Grab the `i`-th batch in `x`, `batch_first` stating the batch dimension. | [
"Grab",
"the",
"i",
"-",
"th",
"batch",
"in",
"x",
"batch_first",
"stating",
"the",
"batch",
"dimension",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L328-L331 |
20,751 | fastai/fastai | fastai/torch_core.py | logit_ | def logit_(x:Tensor)->Tensor:
"Inplace logit of `x`, clamped to avoid inf"
x.clamp_(1e-7, 1-1e-7)
return (x.reciprocal_().sub_(1)).log_().neg_() | python | def logit_(x:Tensor)->Tensor:
"Inplace logit of `x`, clamped to avoid inf"
x.clamp_(1e-7, 1-1e-7)
return (x.reciprocal_().sub_(1)).log_().neg_() | [
"def",
"logit_",
"(",
"x",
":",
"Tensor",
")",
"->",
"Tensor",
":",
"x",
".",
"clamp_",
"(",
"1e-7",
",",
"1",
"-",
"1e-7",
")",
"return",
"(",
"x",
".",
"reciprocal_",
"(",
")",
".",
"sub_",
"(",
"1",
")",
")",
".",
"log_",
"(",
")",
".",
... | Inplace logit of `x`, clamped to avoid inf | [
"Inplace",
"logit",
"of",
"x",
"clamped",
"to",
"avoid",
"inf"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L338-L341 |
20,752 | fastai/fastai | fastai/torch_core.py | try_int | def try_int(o:Any)->Any:
"Try to convert `o` to int, default to `o` if not possible."
# NB: single-item rank-1 array/tensor can be converted to int, but we don't want to do this
if isinstance(o, (np.ndarray,Tensor)): return o if o.ndim else int(o)
if isinstance(o, collections.Sized) or getattr(o,'__arra... | python | def try_int(o:Any)->Any:
"Try to convert `o` to int, default to `o` if not possible."
# NB: single-item rank-1 array/tensor can be converted to int, but we don't want to do this
if isinstance(o, (np.ndarray,Tensor)): return o if o.ndim else int(o)
if isinstance(o, collections.Sized) or getattr(o,'__arra... | [
"def",
"try_int",
"(",
"o",
":",
"Any",
")",
"->",
"Any",
":",
"# NB: single-item rank-1 array/tensor can be converted to int, but we don't want to do this",
"if",
"isinstance",
"(",
"o",
",",
"(",
"np",
".",
"ndarray",
",",
"Tensor",
")",
")",
":",
"return",
"o",... | Try to convert `o` to int, default to `o` if not possible. | [
"Try",
"to",
"convert",
"o",
"to",
"int",
"default",
"to",
"o",
"if",
"not",
"possible",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L365-L371 |
20,753 | fastai/fastai | fastai/torch_core.py | get_model | def get_model(model:nn.Module):
"Return the model maybe wrapped inside `model`."
return model.module if isinstance(model, (DistributedDataParallel, nn.DataParallel)) else model | python | def get_model(model:nn.Module):
"Return the model maybe wrapped inside `model`."
return model.module if isinstance(model, (DistributedDataParallel, nn.DataParallel)) else model | [
"def",
"get_model",
"(",
"model",
":",
"nn",
".",
"Module",
")",
":",
"return",
"model",
".",
"module",
"if",
"isinstance",
"(",
"model",
",",
"(",
"DistributedDataParallel",
",",
"nn",
".",
"DataParallel",
")",
")",
"else",
"model"
] | Return the model maybe wrapped inside `model`. | [
"Return",
"the",
"model",
"maybe",
"wrapped",
"inside",
"model",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L373-L375 |
20,754 | fastai/fastai | fastai/torch_core.py | flatten_check | def flatten_check(out:Tensor, targ:Tensor) -> Tensor:
"Check that `out` and `targ` have the same number of elements and flatten them."
out,targ = out.contiguous().view(-1),targ.contiguous().view(-1)
assert len(out) == len(targ), f"Expected output and target to have the same number of elements but got {len(o... | python | def flatten_check(out:Tensor, targ:Tensor) -> Tensor:
"Check that `out` and `targ` have the same number of elements and flatten them."
out,targ = out.contiguous().view(-1),targ.contiguous().view(-1)
assert len(out) == len(targ), f"Expected output and target to have the same number of elements but got {len(o... | [
"def",
"flatten_check",
"(",
"out",
":",
"Tensor",
",",
"targ",
":",
"Tensor",
")",
"->",
"Tensor",
":",
"out",
",",
"targ",
"=",
"out",
".",
"contiguous",
"(",
")",
".",
"view",
"(",
"-",
"1",
")",
",",
"targ",
".",
"contiguous",
"(",
")",
".",
... | Check that `out` and `targ` have the same number of elements and flatten them. | [
"Check",
"that",
"out",
"and",
"targ",
"have",
"the",
"same",
"number",
"of",
"elements",
"and",
"flatten",
"them",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L377-L381 |
20,755 | fastai/fastai | fastai/torch_core.py | remove_module_load | def remove_module_load(state_dict):
"""create new OrderedDict that does not contain `module.`"""
new_state_dict = OrderedDict()
for k, v in state_dict.items(): new_state_dict[k[7:]] = v
return new_state_dict | python | def remove_module_load(state_dict):
"""create new OrderedDict that does not contain `module.`"""
new_state_dict = OrderedDict()
for k, v in state_dict.items(): new_state_dict[k[7:]] = v
return new_state_dict | [
"def",
"remove_module_load",
"(",
"state_dict",
")",
":",
"new_state_dict",
"=",
"OrderedDict",
"(",
")",
"for",
"k",
",",
"v",
"in",
"state_dict",
".",
"items",
"(",
")",
":",
"new_state_dict",
"[",
"k",
"[",
"7",
":",
"]",
"]",
"=",
"v",
"return",
... | create new OrderedDict that does not contain `module.` | [
"create",
"new",
"OrderedDict",
"that",
"does",
"not",
"contain",
"module",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L388-L392 |
20,756 | fastai/fastai | fastai/torch_core.py | add_metrics | def add_metrics(last_metrics:Collection[Rank0Tensor], mets:Union[Rank0Tensor, Collection[Rank0Tensor]]):
"Return a dictionary for updating `last_metrics` with `mets`."
last_metrics,mets = listify(last_metrics),listify(mets)
return {'last_metrics': last_metrics + mets} | python | def add_metrics(last_metrics:Collection[Rank0Tensor], mets:Union[Rank0Tensor, Collection[Rank0Tensor]]):
"Return a dictionary for updating `last_metrics` with `mets`."
last_metrics,mets = listify(last_metrics),listify(mets)
return {'last_metrics': last_metrics + mets} | [
"def",
"add_metrics",
"(",
"last_metrics",
":",
"Collection",
"[",
"Rank0Tensor",
"]",
",",
"mets",
":",
"Union",
"[",
"Rank0Tensor",
",",
"Collection",
"[",
"Rank0Tensor",
"]",
"]",
")",
":",
"last_metrics",
",",
"mets",
"=",
"listify",
"(",
"last_metrics",... | Return a dictionary for updating `last_metrics` with `mets`. | [
"Return",
"a",
"dictionary",
"for",
"updating",
"last_metrics",
"with",
"mets",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/torch_core.py#L402-L405 |
20,757 | fastai/fastai | fastai/callbacks/tensorboard.py | LearnerTensorboardWriter._get_new_batch | def _get_new_batch(self, ds_type:DatasetType)->Collection[Tensor]:
"Retrieves new batch of DatasetType, and detaches it."
return self.learn.data.one_batch(ds_type=ds_type, detach=True, denorm=False, cpu=False) | python | def _get_new_batch(self, ds_type:DatasetType)->Collection[Tensor]:
"Retrieves new batch of DatasetType, and detaches it."
return self.learn.data.one_batch(ds_type=ds_type, detach=True, denorm=False, cpu=False) | [
"def",
"_get_new_batch",
"(",
"self",
",",
"ds_type",
":",
"DatasetType",
")",
"->",
"Collection",
"[",
"Tensor",
"]",
":",
"return",
"self",
".",
"learn",
".",
"data",
".",
"one_batch",
"(",
"ds_type",
"=",
"ds_type",
",",
"detach",
"=",
"True",
",",
... | Retrieves new batch of DatasetType, and detaches it. | [
"Retrieves",
"new",
"batch",
"of",
"DatasetType",
"and",
"detaches",
"it",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L40-L42 |
20,758 | fastai/fastai | fastai/callbacks/tensorboard.py | LearnerTensorboardWriter._update_batches_if_needed | def _update_batches_if_needed(self)->None:
"one_batch function is extremely slow with large datasets. This is caching the result as an optimization."
if self.learn.data.valid_dl is None: return # Running learning rate finder, so return
update_batches = self.data is not self.learn.data
i... | python | def _update_batches_if_needed(self)->None:
"one_batch function is extremely slow with large datasets. This is caching the result as an optimization."
if self.learn.data.valid_dl is None: return # Running learning rate finder, so return
update_batches = self.data is not self.learn.data
i... | [
"def",
"_update_batches_if_needed",
"(",
"self",
")",
"->",
"None",
":",
"if",
"self",
".",
"learn",
".",
"data",
".",
"valid_dl",
"is",
"None",
":",
"return",
"# Running learning rate finder, so return",
"update_batches",
"=",
"self",
".",
"data",
"is",
"not",
... | one_batch function is extremely slow with large datasets. This is caching the result as an optimization. | [
"one_batch",
"function",
"is",
"extremely",
"slow",
"with",
"large",
"datasets",
".",
"This",
"is",
"caching",
"the",
"result",
"as",
"an",
"optimization",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L44-L51 |
20,759 | fastai/fastai | fastai/callbacks/tensorboard.py | LearnerTensorboardWriter._write_scalar | def _write_scalar(self, name:str, scalar_value, iteration:int)->None:
"Writes single scalar value to Tensorboard."
tag = self.metrics_root + name
self.tbwriter.add_scalar(tag=tag, scalar_value=scalar_value, global_step=iteration) | python | def _write_scalar(self, name:str, scalar_value, iteration:int)->None:
"Writes single scalar value to Tensorboard."
tag = self.metrics_root + name
self.tbwriter.add_scalar(tag=tag, scalar_value=scalar_value, global_step=iteration) | [
"def",
"_write_scalar",
"(",
"self",
",",
"name",
":",
"str",
",",
"scalar_value",
",",
"iteration",
":",
"int",
")",
"->",
"None",
":",
"tag",
"=",
"self",
".",
"metrics_root",
"+",
"name",
"self",
".",
"tbwriter",
".",
"add_scalar",
"(",
"tag",
"=",
... | Writes single scalar value to Tensorboard. | [
"Writes",
"single",
"scalar",
"value",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L67-L70 |
20,760 | fastai/fastai | fastai/callbacks/tensorboard.py | LearnerTensorboardWriter._write_metrics | def _write_metrics(self, iteration:int, last_metrics:MetricsList, start_idx:int=2)->None:
"Writes training metrics to Tensorboard."
recorder = self.learn.recorder
for i, name in enumerate(recorder.names[start_idx:]):
if last_metrics is None or len(last_metrics) < i+1: return
... | python | def _write_metrics(self, iteration:int, last_metrics:MetricsList, start_idx:int=2)->None:
"Writes training metrics to Tensorboard."
recorder = self.learn.recorder
for i, name in enumerate(recorder.names[start_idx:]):
if last_metrics is None or len(last_metrics) < i+1: return
... | [
"def",
"_write_metrics",
"(",
"self",
",",
"iteration",
":",
"int",
",",
"last_metrics",
":",
"MetricsList",
",",
"start_idx",
":",
"int",
"=",
"2",
")",
"->",
"None",
":",
"recorder",
"=",
"self",
".",
"learn",
".",
"recorder",
"for",
"i",
",",
"name"... | Writes training metrics to Tensorboard. | [
"Writes",
"training",
"metrics",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L73-L79 |
20,761 | fastai/fastai | fastai/callbacks/tensorboard.py | LearnerTensorboardWriter.on_epoch_end | def on_epoch_end(self, last_metrics:MetricsList, iteration:int, **kwargs)->None:
"Callback function that writes epoch end appropriate data to Tensorboard."
self._write_metrics(iteration=iteration, last_metrics=last_metrics) | python | def on_epoch_end(self, last_metrics:MetricsList, iteration:int, **kwargs)->None:
"Callback function that writes epoch end appropriate data to Tensorboard."
self._write_metrics(iteration=iteration, last_metrics=last_metrics) | [
"def",
"on_epoch_end",
"(",
"self",
",",
"last_metrics",
":",
"MetricsList",
",",
"iteration",
":",
"int",
",",
"*",
"*",
"kwargs",
")",
"->",
"None",
":",
"self",
".",
"_write_metrics",
"(",
"iteration",
"=",
"iteration",
",",
"last_metrics",
"=",
"last_m... | Callback function that writes epoch end appropriate data to Tensorboard. | [
"Callback",
"function",
"that",
"writes",
"epoch",
"end",
"appropriate",
"data",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L99-L101 |
20,762 | fastai/fastai | fastai/callbacks/tensorboard.py | GANTensorboardWriter._write_gen_model_stats | def _write_gen_model_stats(self, iteration:int)->None:
"Writes gradient statistics for generator to Tensorboard."
generator = self.learn.gan_trainer.generator
self.stats_writer.write(model=generator, iteration=iteration, tbwriter=self.tbwriter, name='gen_model_stats')
self.gen_stats_upda... | python | def _write_gen_model_stats(self, iteration:int)->None:
"Writes gradient statistics for generator to Tensorboard."
generator = self.learn.gan_trainer.generator
self.stats_writer.write(model=generator, iteration=iteration, tbwriter=self.tbwriter, name='gen_model_stats')
self.gen_stats_upda... | [
"def",
"_write_gen_model_stats",
"(",
"self",
",",
"iteration",
":",
"int",
")",
"->",
"None",
":",
"generator",
"=",
"self",
".",
"learn",
".",
"gan_trainer",
".",
"generator",
"self",
".",
"stats_writer",
".",
"write",
"(",
"model",
"=",
"generator",
","... | Writes gradient statistics for generator to Tensorboard. | [
"Writes",
"gradient",
"statistics",
"for",
"generator",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L120-L124 |
20,763 | fastai/fastai | fastai/callbacks/tensorboard.py | GANTensorboardWriter._write_critic_model_stats | def _write_critic_model_stats(self, iteration:int)->None:
"Writes gradient statistics for critic to Tensorboard."
critic = self.learn.gan_trainer.critic
self.stats_writer.write(model=critic, iteration=iteration, tbwriter=self.tbwriter, name='crit_model_stats')
self.crit_stats_updated = T... | python | def _write_critic_model_stats(self, iteration:int)->None:
"Writes gradient statistics for critic to Tensorboard."
critic = self.learn.gan_trainer.critic
self.stats_writer.write(model=critic, iteration=iteration, tbwriter=self.tbwriter, name='crit_model_stats')
self.crit_stats_updated = T... | [
"def",
"_write_critic_model_stats",
"(",
"self",
",",
"iteration",
":",
"int",
")",
"->",
"None",
":",
"critic",
"=",
"self",
".",
"learn",
".",
"gan_trainer",
".",
"critic",
"self",
".",
"stats_writer",
".",
"write",
"(",
"model",
"=",
"critic",
",",
"i... | Writes gradient statistics for critic to Tensorboard. | [
"Writes",
"gradient",
"statistics",
"for",
"critic",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L126-L130 |
20,764 | fastai/fastai | fastai/callbacks/tensorboard.py | GANTensorboardWriter._write_images | def _write_images(self, iteration:int)->None:
"Writes model generated, original and real images to Tensorboard."
trainer = self.learn.gan_trainer
#TODO: Switching gen_mode temporarily seems a bit hacky here. Certainly not a good side-effect. Is there a better way?
gen_mode = trainer.g... | python | def _write_images(self, iteration:int)->None:
"Writes model generated, original and real images to Tensorboard."
trainer = self.learn.gan_trainer
#TODO: Switching gen_mode temporarily seems a bit hacky here. Certainly not a good side-effect. Is there a better way?
gen_mode = trainer.g... | [
"def",
"_write_images",
"(",
"self",
",",
"iteration",
":",
"int",
")",
"->",
"None",
":",
"trainer",
"=",
"self",
".",
"learn",
".",
"gan_trainer",
"#TODO: Switching gen_mode temporarily seems a bit hacky here. Certainly not a good side-effect. Is there a better way?",
"g... | Writes model generated, original and real images to Tensorboard. | [
"Writes",
"model",
"generated",
"original",
"and",
"real",
"images",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L147-L156 |
20,765 | fastai/fastai | fastai/callbacks/tensorboard.py | ImageGenTensorboardWriter._write_images | def _write_images(self, iteration:int)->None:
"Writes model generated, original and real images to Tensorboard"
self.img_gen_vis.write(learn=self.learn, trn_batch=self.trn_batch, val_batch=self.val_batch, iteration=iteration,
tbwriter=self.tbwriter) | python | def _write_images(self, iteration:int)->None:
"Writes model generated, original and real images to Tensorboard"
self.img_gen_vis.write(learn=self.learn, trn_batch=self.trn_batch, val_batch=self.val_batch, iteration=iteration,
tbwriter=self.tbwriter) | [
"def",
"_write_images",
"(",
"self",
",",
"iteration",
":",
"int",
")",
"->",
"None",
":",
"self",
".",
"img_gen_vis",
".",
"write",
"(",
"learn",
"=",
"self",
".",
"learn",
",",
"trn_batch",
"=",
"self",
".",
"trn_batch",
",",
"val_batch",
"=",
"self"... | Writes model generated, original and real images to Tensorboard | [
"Writes",
"model",
"generated",
"original",
"and",
"real",
"images",
"to",
"Tensorboard"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L182-L185 |
20,766 | fastai/fastai | fastai/callbacks/tensorboard.py | AsyncTBWriter.request_write | def request_write(self, request: TBWriteRequest)->None:
"Queues up an asynchronous write request to Tensorboard."
if self.stop_request.isSet(): return
self.queue.put(request) | python | def request_write(self, request: TBWriteRequest)->None:
"Queues up an asynchronous write request to Tensorboard."
if self.stop_request.isSet(): return
self.queue.put(request) | [
"def",
"request_write",
"(",
"self",
",",
"request",
":",
"TBWriteRequest",
")",
"->",
"None",
":",
"if",
"self",
".",
"stop_request",
".",
"isSet",
"(",
")",
":",
"return",
"self",
".",
"queue",
".",
"put",
"(",
"request",
")"
] | Queues up an asynchronous write request to Tensorboard. | [
"Queues",
"up",
"an",
"asynchronous",
"write",
"request",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L216-L219 |
20,767 | fastai/fastai | fastai/callbacks/tensorboard.py | AsyncTBWriter._queue_processor | def _queue_processor(self)->None:
"Processes queued up write requests asynchronously to Tensorboard."
while not self.stop_request.isSet():
while not self.queue.empty():
if self.stop_request.isSet(): return
request = self.queue.get()
request.wri... | python | def _queue_processor(self)->None:
"Processes queued up write requests asynchronously to Tensorboard."
while not self.stop_request.isSet():
while not self.queue.empty():
if self.stop_request.isSet(): return
request = self.queue.get()
request.wri... | [
"def",
"_queue_processor",
"(",
"self",
")",
"->",
"None",
":",
"while",
"not",
"self",
".",
"stop_request",
".",
"isSet",
"(",
")",
":",
"while",
"not",
"self",
".",
"queue",
".",
"empty",
"(",
")",
":",
"if",
"self",
".",
"stop_request",
".",
"isSe... | Processes queued up write requests asynchronously to Tensorboard. | [
"Processes",
"queued",
"up",
"write",
"requests",
"asynchronously",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L221-L228 |
20,768 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelImageSet.get_list_from_model | def get_list_from_model(learn:Learner, ds_type:DatasetType, batch:Tuple)->[]:
"Factory method to convert a batch of model images to a list of ModelImageSet."
image_sets = []
x,y = batch[0],batch[1]
preds = learn.pred_batch(ds_type=ds_type, batch=(x,y), reconstruct=True)
for ori... | python | def get_list_from_model(learn:Learner, ds_type:DatasetType, batch:Tuple)->[]:
"Factory method to convert a batch of model images to a list of ModelImageSet."
image_sets = []
x,y = batch[0],batch[1]
preds = learn.pred_batch(ds_type=ds_type, batch=(x,y), reconstruct=True)
for ori... | [
"def",
"get_list_from_model",
"(",
"learn",
":",
"Learner",
",",
"ds_type",
":",
"DatasetType",
",",
"batch",
":",
"Tuple",
")",
"->",
"[",
"]",
":",
"image_sets",
"=",
"[",
"]",
"x",
",",
"y",
"=",
"batch",
"[",
"0",
"]",
",",
"batch",
"[",
"1",
... | Factory method to convert a batch of model images to a list of ModelImageSet. | [
"Factory",
"method",
"to",
"convert",
"a",
"batch",
"of",
"model",
"images",
"to",
"a",
"list",
"of",
"ModelImageSet",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L248-L257 |
20,769 | fastai/fastai | fastai/callbacks/tensorboard.py | HistogramTBRequest._write_histogram | def _write_histogram(self, param_name:str, values)->None:
"Writes single model histogram to Tensorboard."
tag = self.name + '/weights/' + param_name
self.tbwriter.add_histogram(tag=tag, values=values, global_step=self.iteration) | python | def _write_histogram(self, param_name:str, values)->None:
"Writes single model histogram to Tensorboard."
tag = self.name + '/weights/' + param_name
self.tbwriter.add_histogram(tag=tag, values=values, global_step=self.iteration) | [
"def",
"_write_histogram",
"(",
"self",
",",
"param_name",
":",
"str",
",",
"values",
")",
"->",
"None",
":",
"tag",
"=",
"self",
".",
"name",
"+",
"'/weights/'",
"+",
"param_name",
"self",
".",
"tbwriter",
".",
"add_histogram",
"(",
"tag",
"=",
"tag",
... | Writes single model histogram to Tensorboard. | [
"Writes",
"single",
"model",
"histogram",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L268-L271 |
20,770 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._add_gradient_scalar | def _add_gradient_scalar(self, name:str, scalar_value)->None:
"Writes a single scalar value for a gradient statistic to Tensorboard."
tag = self.name + '/gradients/' + name
self.tbwriter.add_scalar(tag=tag, scalar_value=scalar_value, global_step=self.iteration) | python | def _add_gradient_scalar(self, name:str, scalar_value)->None:
"Writes a single scalar value for a gradient statistic to Tensorboard."
tag = self.name + '/gradients/' + name
self.tbwriter.add_scalar(tag=tag, scalar_value=scalar_value, global_step=self.iteration) | [
"def",
"_add_gradient_scalar",
"(",
"self",
",",
"name",
":",
"str",
",",
"scalar_value",
")",
"->",
"None",
":",
"tag",
"=",
"self",
".",
"name",
"+",
"'/gradients/'",
"+",
"name",
"self",
".",
"tbwriter",
".",
"add_scalar",
"(",
"tag",
"=",
"tag",
",... | Writes a single scalar value for a gradient statistic to Tensorboard. | [
"Writes",
"a",
"single",
"scalar",
"value",
"for",
"a",
"gradient",
"statistic",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L294-L297 |
20,771 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_avg_norm | def _write_avg_norm(self, norms:[])->None:
"Writes the average norm of the gradients to Tensorboard."
avg_norm = sum(norms)/len(self.gradients)
self._add_gradient_scalar('avg_norm', scalar_value=avg_norm) | python | def _write_avg_norm(self, norms:[])->None:
"Writes the average norm of the gradients to Tensorboard."
avg_norm = sum(norms)/len(self.gradients)
self._add_gradient_scalar('avg_norm', scalar_value=avg_norm) | [
"def",
"_write_avg_norm",
"(",
"self",
",",
"norms",
":",
"[",
"]",
")",
"->",
"None",
":",
"avg_norm",
"=",
"sum",
"(",
"norms",
")",
"/",
"len",
"(",
"self",
".",
"gradients",
")",
"self",
".",
"_add_gradient_scalar",
"(",
"'avg_norm'",
",",
"scalar_... | Writes the average norm of the gradients to Tensorboard. | [
"Writes",
"the",
"average",
"norm",
"of",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L299-L302 |
20,772 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_median_norm | def _write_median_norm(self, norms:[])->None:
"Writes the median norm of the gradients to Tensorboard."
median_norm = statistics.median(norms)
self._add_gradient_scalar('median_norm', scalar_value=median_norm) | python | def _write_median_norm(self, norms:[])->None:
"Writes the median norm of the gradients to Tensorboard."
median_norm = statistics.median(norms)
self._add_gradient_scalar('median_norm', scalar_value=median_norm) | [
"def",
"_write_median_norm",
"(",
"self",
",",
"norms",
":",
"[",
"]",
")",
"->",
"None",
":",
"median_norm",
"=",
"statistics",
".",
"median",
"(",
"norms",
")",
"self",
".",
"_add_gradient_scalar",
"(",
"'median_norm'",
",",
"scalar_value",
"=",
"median_no... | Writes the median norm of the gradients to Tensorboard. | [
"Writes",
"the",
"median",
"norm",
"of",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L304-L307 |
20,773 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_max_norm | def _write_max_norm(self, norms:[])->None:
"Writes the maximum norm of the gradients to Tensorboard."
max_norm = max(norms)
self._add_gradient_scalar('max_norm', scalar_value=max_norm) | python | def _write_max_norm(self, norms:[])->None:
"Writes the maximum norm of the gradients to Tensorboard."
max_norm = max(norms)
self._add_gradient_scalar('max_norm', scalar_value=max_norm) | [
"def",
"_write_max_norm",
"(",
"self",
",",
"norms",
":",
"[",
"]",
")",
"->",
"None",
":",
"max_norm",
"=",
"max",
"(",
"norms",
")",
"self",
".",
"_add_gradient_scalar",
"(",
"'max_norm'",
",",
"scalar_value",
"=",
"max_norm",
")"
] | Writes the maximum norm of the gradients to Tensorboard. | [
"Writes",
"the",
"maximum",
"norm",
"of",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L309-L312 |
20,774 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_min_norm | def _write_min_norm(self, norms:[])->None:
"Writes the minimum norm of the gradients to Tensorboard."
min_norm = min(norms)
self._add_gradient_scalar('min_norm', scalar_value=min_norm) | python | def _write_min_norm(self, norms:[])->None:
"Writes the minimum norm of the gradients to Tensorboard."
min_norm = min(norms)
self._add_gradient_scalar('min_norm', scalar_value=min_norm) | [
"def",
"_write_min_norm",
"(",
"self",
",",
"norms",
":",
"[",
"]",
")",
"->",
"None",
":",
"min_norm",
"=",
"min",
"(",
"norms",
")",
"self",
".",
"_add_gradient_scalar",
"(",
"'min_norm'",
",",
"scalar_value",
"=",
"min_norm",
")"
] | Writes the minimum norm of the gradients to Tensorboard. | [
"Writes",
"the",
"minimum",
"norm",
"of",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L314-L317 |
20,775 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_num_zeros | def _write_num_zeros(self)->None:
"Writes the number of zeroes in the gradients to Tensorboard."
gradient_nps = [to_np(x.data) for x in self.gradients]
num_zeros = sum((np.asarray(x) == 0.0).sum() for x in gradient_nps)
self._add_gradient_scalar('num_zeros', scalar_value=num_zeros) | python | def _write_num_zeros(self)->None:
"Writes the number of zeroes in the gradients to Tensorboard."
gradient_nps = [to_np(x.data) for x in self.gradients]
num_zeros = sum((np.asarray(x) == 0.0).sum() for x in gradient_nps)
self._add_gradient_scalar('num_zeros', scalar_value=num_zeros) | [
"def",
"_write_num_zeros",
"(",
"self",
")",
"->",
"None",
":",
"gradient_nps",
"=",
"[",
"to_np",
"(",
"x",
".",
"data",
")",
"for",
"x",
"in",
"self",
".",
"gradients",
"]",
"num_zeros",
"=",
"sum",
"(",
"(",
"np",
".",
"asarray",
"(",
"x",
")",
... | Writes the number of zeroes in the gradients to Tensorboard. | [
"Writes",
"the",
"number",
"of",
"zeroes",
"in",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L319-L323 |
20,776 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_avg_gradient | def _write_avg_gradient(self)->None:
"Writes the average of the gradients to Tensorboard."
avg_gradient = sum(x.data.mean() for x in self.gradients)/len(self.gradients)
self._add_gradient_scalar('avg_gradient', scalar_value=avg_gradient) | python | def _write_avg_gradient(self)->None:
"Writes the average of the gradients to Tensorboard."
avg_gradient = sum(x.data.mean() for x in self.gradients)/len(self.gradients)
self._add_gradient_scalar('avg_gradient', scalar_value=avg_gradient) | [
"def",
"_write_avg_gradient",
"(",
"self",
")",
"->",
"None",
":",
"avg_gradient",
"=",
"sum",
"(",
"x",
".",
"data",
".",
"mean",
"(",
")",
"for",
"x",
"in",
"self",
".",
"gradients",
")",
"/",
"len",
"(",
"self",
".",
"gradients",
")",
"self",
".... | Writes the average of the gradients to Tensorboard. | [
"Writes",
"the",
"average",
"of",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L325-L328 |
20,777 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_median_gradient | def _write_median_gradient(self)->None:
"Writes the median of the gradients to Tensorboard."
median_gradient = statistics.median(x.data.median() for x in self.gradients)
self._add_gradient_scalar('median_gradient', scalar_value=median_gradient) | python | def _write_median_gradient(self)->None:
"Writes the median of the gradients to Tensorboard."
median_gradient = statistics.median(x.data.median() for x in self.gradients)
self._add_gradient_scalar('median_gradient', scalar_value=median_gradient) | [
"def",
"_write_median_gradient",
"(",
"self",
")",
"->",
"None",
":",
"median_gradient",
"=",
"statistics",
".",
"median",
"(",
"x",
".",
"data",
".",
"median",
"(",
")",
"for",
"x",
"in",
"self",
".",
"gradients",
")",
"self",
".",
"_add_gradient_scalar",... | Writes the median of the gradients to Tensorboard. | [
"Writes",
"the",
"median",
"of",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L330-L333 |
20,778 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_max_gradient | def _write_max_gradient(self)->None:
"Writes the maximum of the gradients to Tensorboard."
max_gradient = max(x.data.max() for x in self.gradients)
self._add_gradient_scalar('max_gradient', scalar_value=max_gradient) | python | def _write_max_gradient(self)->None:
"Writes the maximum of the gradients to Tensorboard."
max_gradient = max(x.data.max() for x in self.gradients)
self._add_gradient_scalar('max_gradient', scalar_value=max_gradient) | [
"def",
"_write_max_gradient",
"(",
"self",
")",
"->",
"None",
":",
"max_gradient",
"=",
"max",
"(",
"x",
".",
"data",
".",
"max",
"(",
")",
"for",
"x",
"in",
"self",
".",
"gradients",
")",
"self",
".",
"_add_gradient_scalar",
"(",
"'max_gradient'",
",",
... | Writes the maximum of the gradients to Tensorboard. | [
"Writes",
"the",
"maximum",
"of",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L335-L338 |
20,779 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest._write_min_gradient | def _write_min_gradient(self)->None:
"Writes the minimum of the gradients to Tensorboard."
min_gradient = min(x.data.min() for x in self.gradients)
self._add_gradient_scalar('min_gradient', scalar_value=min_gradient) | python | def _write_min_gradient(self)->None:
"Writes the minimum of the gradients to Tensorboard."
min_gradient = min(x.data.min() for x in self.gradients)
self._add_gradient_scalar('min_gradient', scalar_value=min_gradient) | [
"def",
"_write_min_gradient",
"(",
"self",
")",
"->",
"None",
":",
"min_gradient",
"=",
"min",
"(",
"x",
".",
"data",
".",
"min",
"(",
")",
"for",
"x",
"in",
"self",
".",
"gradients",
")",
"self",
".",
"_add_gradient_scalar",
"(",
"'min_gradient'",
",",
... | Writes the minimum of the gradients to Tensorboard. | [
"Writes",
"the",
"minimum",
"of",
"the",
"gradients",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L340-L343 |
20,780 | fastai/fastai | fastai/callbacks/tensorboard.py | ModelStatsTBRequest.write | def write(self)->None:
"Writes model gradient statistics to Tensorboard."
if len(self.gradients) == 0: return
norms = [x.data.norm() for x in self.gradients]
self._write_avg_norm(norms=norms)
self._write_median_norm(norms=norms)
self._write_max_norm(norms=norms)
s... | python | def write(self)->None:
"Writes model gradient statistics to Tensorboard."
if len(self.gradients) == 0: return
norms = [x.data.norm() for x in self.gradients]
self._write_avg_norm(norms=norms)
self._write_median_norm(norms=norms)
self._write_max_norm(norms=norms)
s... | [
"def",
"write",
"(",
"self",
")",
"->",
"None",
":",
"if",
"len",
"(",
"self",
".",
"gradients",
")",
"==",
"0",
":",
"return",
"norms",
"=",
"[",
"x",
".",
"data",
".",
"norm",
"(",
")",
"for",
"x",
"in",
"self",
".",
"gradients",
"]",
"self",... | Writes model gradient statistics to Tensorboard. | [
"Writes",
"model",
"gradient",
"statistics",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L345-L357 |
20,781 | fastai/fastai | fastai/callbacks/tensorboard.py | ImageTBRequest._write_images | def _write_images(self, name:str, images:[Tensor])->None:
"Writes list of images as tensors to Tensorboard."
tag = self.ds_type.name + ' ' + name
self.tbwriter.add_image(tag=tag, img_tensor=vutils.make_grid(images, normalize=True), global_step=self.iteration) | python | def _write_images(self, name:str, images:[Tensor])->None:
"Writes list of images as tensors to Tensorboard."
tag = self.ds_type.name + ' ' + name
self.tbwriter.add_image(tag=tag, img_tensor=vutils.make_grid(images, normalize=True), global_step=self.iteration) | [
"def",
"_write_images",
"(",
"self",
",",
"name",
":",
"str",
",",
"images",
":",
"[",
"Tensor",
"]",
")",
"->",
"None",
":",
"tag",
"=",
"self",
".",
"ds_type",
".",
"name",
"+",
"' '",
"+",
"name",
"self",
".",
"tbwriter",
".",
"add_image",
"(",
... | Writes list of images as tensors to Tensorboard. | [
"Writes",
"list",
"of",
"images",
"as",
"tensors",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L373-L376 |
20,782 | fastai/fastai | fastai/callbacks/tensorboard.py | ImageTBWriter.write | def write(self, learn:Learner, trn_batch:Tuple, val_batch:Tuple, iteration:int, tbwriter:SummaryWriter)->None:
"Writes training and validation batch images to Tensorboard."
self._write_for_dstype(learn=learn, batch=val_batch, iteration=iteration, tbwriter=tbwriter, ds_type=DatasetType.Valid)
sel... | python | def write(self, learn:Learner, trn_batch:Tuple, val_batch:Tuple, iteration:int, tbwriter:SummaryWriter)->None:
"Writes training and validation batch images to Tensorboard."
self._write_for_dstype(learn=learn, batch=val_batch, iteration=iteration, tbwriter=tbwriter, ds_type=DatasetType.Valid)
sel... | [
"def",
"write",
"(",
"self",
",",
"learn",
":",
"Learner",
",",
"trn_batch",
":",
"Tuple",
",",
"val_batch",
":",
"Tuple",
",",
"iteration",
":",
"int",
",",
"tbwriter",
":",
"SummaryWriter",
")",
"->",
"None",
":",
"self",
".",
"_write_for_dstype",
"(",... | Writes training and validation batch images to Tensorboard. | [
"Writes",
"training",
"and",
"validation",
"batch",
"images",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L399-L402 |
20,783 | fastai/fastai | fastai/callbacks/tensorboard.py | ImageTBWriter._write_for_dstype | def _write_for_dstype(self, learn:Learner, batch:Tuple, iteration:int, tbwriter:SummaryWriter, ds_type:DatasetType)->None:
"Writes batch images of specified DatasetType to Tensorboard."
request = ImageTBRequest(learn=learn, batch=batch, iteration=iteration, tbwriter=tbwriter, ds_type=ds_type)
as... | python | def _write_for_dstype(self, learn:Learner, batch:Tuple, iteration:int, tbwriter:SummaryWriter, ds_type:DatasetType)->None:
"Writes batch images of specified DatasetType to Tensorboard."
request = ImageTBRequest(learn=learn, batch=batch, iteration=iteration, tbwriter=tbwriter, ds_type=ds_type)
as... | [
"def",
"_write_for_dstype",
"(",
"self",
",",
"learn",
":",
"Learner",
",",
"batch",
":",
"Tuple",
",",
"iteration",
":",
"int",
",",
"tbwriter",
":",
"SummaryWriter",
",",
"ds_type",
":",
"DatasetType",
")",
"->",
"None",
":",
"request",
"=",
"ImageTBRequ... | Writes batch images of specified DatasetType to Tensorboard. | [
"Writes",
"batch",
"images",
"of",
"specified",
"DatasetType",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L404-L407 |
20,784 | fastai/fastai | fastai/callbacks/tensorboard.py | GraphTBRequest.write | def write(self)->None:
"Writes single model graph to Tensorboard."
self.tbwriter.add_graph(model=self.model, input_to_model=self.input_to_model) | python | def write(self)->None:
"Writes single model graph to Tensorboard."
self.tbwriter.add_graph(model=self.model, input_to_model=self.input_to_model) | [
"def",
"write",
"(",
"self",
")",
"->",
"None",
":",
"self",
".",
"tbwriter",
".",
"add_graph",
"(",
"model",
"=",
"self",
".",
"model",
",",
"input_to_model",
"=",
"self",
".",
"input_to_model",
")"
] | Writes single model graph to Tensorboard. | [
"Writes",
"single",
"model",
"graph",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L415-L417 |
20,785 | fastai/fastai | fastai/callbacks/tensorboard.py | GraphTBWriter.write | def write(self, model:nn.Module, tbwriter:SummaryWriter, input_to_model:torch.Tensor)->None:
"Writes model graph to Tensorboard."
request = GraphTBRequest(model=model, tbwriter=tbwriter, input_to_model=input_to_model)
asyncTBWriter.request_write(request) | python | def write(self, model:nn.Module, tbwriter:SummaryWriter, input_to_model:torch.Tensor)->None:
"Writes model graph to Tensorboard."
request = GraphTBRequest(model=model, tbwriter=tbwriter, input_to_model=input_to_model)
asyncTBWriter.request_write(request) | [
"def",
"write",
"(",
"self",
",",
"model",
":",
"nn",
".",
"Module",
",",
"tbwriter",
":",
"SummaryWriter",
",",
"input_to_model",
":",
"torch",
".",
"Tensor",
")",
"->",
"None",
":",
"request",
"=",
"GraphTBRequest",
"(",
"model",
"=",
"model",
",",
"... | Writes model graph to Tensorboard. | [
"Writes",
"model",
"graph",
"to",
"Tensorboard",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L421-L424 |
20,786 | fastai/fastai | old/fastai/lm_rnn.py | repackage_var | def repackage_var(h):
"""Wraps h in new Variables, to detach them from their history."""
if IS_TORCH_04: return h.detach() if type(h) == torch.Tensor else tuple(repackage_var(v) for v in h)
else: return Variable(h.data) if type(h) == Variable else tuple(repackage_var(v) for v in h) | python | def repackage_var(h):
"""Wraps h in new Variables, to detach them from their history."""
if IS_TORCH_04: return h.detach() if type(h) == torch.Tensor else tuple(repackage_var(v) for v in h)
else: return Variable(h.data) if type(h) == Variable else tuple(repackage_var(v) for v in h) | [
"def",
"repackage_var",
"(",
"h",
")",
":",
"if",
"IS_TORCH_04",
":",
"return",
"h",
".",
"detach",
"(",
")",
"if",
"type",
"(",
"h",
")",
"==",
"torch",
".",
"Tensor",
"else",
"tuple",
"(",
"repackage_var",
"(",
"v",
")",
"for",
"v",
"in",
"h",
... | Wraps h in new Variables, to detach them from their history. | [
"Wraps",
"h",
"in",
"new",
"Variables",
"to",
"detach",
"them",
"from",
"their",
"history",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/old/fastai/lm_rnn.py#L20-L23 |
20,787 | fastai/fastai | old/fastai/lm_rnn.py | get_language_model | def get_language_model(n_tok, emb_sz, n_hid, n_layers, pad_token,
dropout=0.4, dropouth=0.3, dropouti=0.5, dropoute=0.1, wdrop=0.5, tie_weights=True, qrnn=False, bias=False):
"""Returns a SequentialRNN model.
A RNN_Encoder layer is instantiated using the parameters provided.
This is follo... | python | def get_language_model(n_tok, emb_sz, n_hid, n_layers, pad_token,
dropout=0.4, dropouth=0.3, dropouti=0.5, dropoute=0.1, wdrop=0.5, tie_weights=True, qrnn=False, bias=False):
"""Returns a SequentialRNN model.
A RNN_Encoder layer is instantiated using the parameters provided.
This is follo... | [
"def",
"get_language_model",
"(",
"n_tok",
",",
"emb_sz",
",",
"n_hid",
",",
"n_layers",
",",
"pad_token",
",",
"dropout",
"=",
"0.4",
",",
"dropouth",
"=",
"0.3",
",",
"dropouti",
"=",
"0.5",
",",
"dropoute",
"=",
"0.1",
",",
"wdrop",
"=",
"0.5",
",",... | Returns a SequentialRNN model.
A RNN_Encoder layer is instantiated using the parameters provided.
This is followed by the creation of a LinearDecoder layer.
Also by default (i.e. tie_weights = True), the embedding matrix used in the RNN_Encoder
is used to instantiate the weights for the LinearDecode... | [
"Returns",
"a",
"SequentialRNN",
"model",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/old/fastai/lm_rnn.py#L204-L238 |
20,788 | fastai/fastai | fastai/text/transform.py | replace_rep | def replace_rep(t:str) -> str:
"Replace repetitions at the character level in `t`."
def _replace_rep(m:Collection[str]) -> str:
c,cc = m.groups()
return f' {TK_REP} {len(cc)+1} {c} '
re_rep = re.compile(r'(\S)(\1{3,})')
return re_rep.sub(_replace_rep, t) | python | def replace_rep(t:str) -> str:
"Replace repetitions at the character level in `t`."
def _replace_rep(m:Collection[str]) -> str:
c,cc = m.groups()
return f' {TK_REP} {len(cc)+1} {c} '
re_rep = re.compile(r'(\S)(\1{3,})')
return re_rep.sub(_replace_rep, t) | [
"def",
"replace_rep",
"(",
"t",
":",
"str",
")",
"->",
"str",
":",
"def",
"_replace_rep",
"(",
"m",
":",
"Collection",
"[",
"str",
"]",
")",
"->",
"str",
":",
"c",
",",
"cc",
"=",
"m",
".",
"groups",
"(",
")",
"return",
"f' {TK_REP} {len(cc)+1} {c} '... | Replace repetitions at the character level in `t`. | [
"Replace",
"repetitions",
"at",
"the",
"character",
"level",
"in",
"t",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L42-L48 |
20,789 | fastai/fastai | fastai/text/transform.py | replace_wrep | def replace_wrep(t:str) -> str:
"Replace word repetitions in `t`."
def _replace_wrep(m:Collection[str]) -> str:
c,cc = m.groups()
return f' {TK_WREP} {len(cc.split())+1} {c} '
re_wrep = re.compile(r'(\b\w+\W+)(\1{3,})')
return re_wrep.sub(_replace_wrep, t) | python | def replace_wrep(t:str) -> str:
"Replace word repetitions in `t`."
def _replace_wrep(m:Collection[str]) -> str:
c,cc = m.groups()
return f' {TK_WREP} {len(cc.split())+1} {c} '
re_wrep = re.compile(r'(\b\w+\W+)(\1{3,})')
return re_wrep.sub(_replace_wrep, t) | [
"def",
"replace_wrep",
"(",
"t",
":",
"str",
")",
"->",
"str",
":",
"def",
"_replace_wrep",
"(",
"m",
":",
"Collection",
"[",
"str",
"]",
")",
"->",
"str",
":",
"c",
",",
"cc",
"=",
"m",
".",
"groups",
"(",
")",
"return",
"f' {TK_WREP} {len(cc.split(... | Replace word repetitions in `t`. | [
"Replace",
"word",
"repetitions",
"in",
"t",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L50-L56 |
20,790 | fastai/fastai | fastai/text/transform.py | fix_html | def fix_html(x:str) -> str:
"List of replacements from html strings in `x`."
re1 = re.compile(r' +')
x = x.replace('#39;', "'").replace('amp;', '&').replace('#146;', "'").replace(
'nbsp;', ' ').replace('#36;', '$').replace('\\n', "\n").replace('quot;', "'").replace(
'<br />', "\n").replace(... | python | def fix_html(x:str) -> str:
"List of replacements from html strings in `x`."
re1 = re.compile(r' +')
x = x.replace('#39;', "'").replace('amp;', '&').replace('#146;', "'").replace(
'nbsp;', ' ').replace('#36;', '$').replace('\\n', "\n").replace('quot;', "'").replace(
'<br />', "\n").replace(... | [
"def",
"fix_html",
"(",
"x",
":",
"str",
")",
"->",
"str",
":",
"re1",
"=",
"re",
".",
"compile",
"(",
"r' +'",
")",
"x",
"=",
"x",
".",
"replace",
"(",
"'#39;'",
",",
"\"'\"",
")",
".",
"replace",
"(",
"'amp;'",
",",
"'&'",
")",
".",
"replace... | List of replacements from html strings in `x`. | [
"List",
"of",
"replacements",
"from",
"html",
"strings",
"in",
"x",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L58-L65 |
20,791 | fastai/fastai | fastai/text/transform.py | replace_all_caps | def replace_all_caps(x:Collection[str]) -> Collection[str]:
"Replace tokens in ALL CAPS in `x` by their lower version and add `TK_UP` before."
res = []
for t in x:
if t.isupper() and len(t) > 1: res.append(TK_UP); res.append(t.lower())
else: res.append(t)
return res | python | def replace_all_caps(x:Collection[str]) -> Collection[str]:
"Replace tokens in ALL CAPS in `x` by their lower version and add `TK_UP` before."
res = []
for t in x:
if t.isupper() and len(t) > 1: res.append(TK_UP); res.append(t.lower())
else: res.append(t)
return res | [
"def",
"replace_all_caps",
"(",
"x",
":",
"Collection",
"[",
"str",
"]",
")",
"->",
"Collection",
"[",
"str",
"]",
":",
"res",
"=",
"[",
"]",
"for",
"t",
"in",
"x",
":",
"if",
"t",
".",
"isupper",
"(",
")",
"and",
"len",
"(",
"t",
")",
">",
"... | Replace tokens in ALL CAPS in `x` by their lower version and add `TK_UP` before. | [
"Replace",
"tokens",
"in",
"ALL",
"CAPS",
"in",
"x",
"by",
"their",
"lower",
"version",
"and",
"add",
"TK_UP",
"before",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L67-L73 |
20,792 | fastai/fastai | fastai/text/transform.py | deal_caps | def deal_caps(x:Collection[str]) -> Collection[str]:
"Replace all Capitalized tokens in `x` by their lower version and add `TK_MAJ` before."
res = []
for t in x:
if t == '': continue
if t[0].isupper() and len(t) > 1 and t[1:].islower(): res.append(TK_MAJ)
res.append(t.lower())
re... | python | def deal_caps(x:Collection[str]) -> Collection[str]:
"Replace all Capitalized tokens in `x` by their lower version and add `TK_MAJ` before."
res = []
for t in x:
if t == '': continue
if t[0].isupper() and len(t) > 1 and t[1:].islower(): res.append(TK_MAJ)
res.append(t.lower())
re... | [
"def",
"deal_caps",
"(",
"x",
":",
"Collection",
"[",
"str",
"]",
")",
"->",
"Collection",
"[",
"str",
"]",
":",
"res",
"=",
"[",
"]",
"for",
"t",
"in",
"x",
":",
"if",
"t",
"==",
"''",
":",
"continue",
"if",
"t",
"[",
"0",
"]",
".",
"isupper... | Replace all Capitalized tokens in `x` by their lower version and add `TK_MAJ` before. | [
"Replace",
"all",
"Capitalized",
"tokens",
"in",
"x",
"by",
"their",
"lower",
"version",
"and",
"add",
"TK_MAJ",
"before",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L75-L82 |
20,793 | fastai/fastai | fastai/text/transform.py | Tokenizer.process_text | def process_text(self, t:str, tok:BaseTokenizer) -> List[str]:
"Process one text `t` with tokenizer `tok`."
for rule in self.pre_rules: t = rule(t)
toks = tok.tokenizer(t)
for rule in self.post_rules: toks = rule(toks)
return toks | python | def process_text(self, t:str, tok:BaseTokenizer) -> List[str]:
"Process one text `t` with tokenizer `tok`."
for rule in self.pre_rules: t = rule(t)
toks = tok.tokenizer(t)
for rule in self.post_rules: toks = rule(toks)
return toks | [
"def",
"process_text",
"(",
"self",
",",
"t",
":",
"str",
",",
"tok",
":",
"BaseTokenizer",
")",
"->",
"List",
"[",
"str",
"]",
":",
"for",
"rule",
"in",
"self",
".",
"pre_rules",
":",
"t",
"=",
"rule",
"(",
"t",
")",
"toks",
"=",
"tok",
".",
"... | Process one text `t` with tokenizer `tok`. | [
"Process",
"one",
"text",
"t",
"with",
"tokenizer",
"tok",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L103-L108 |
20,794 | fastai/fastai | fastai/text/transform.py | Tokenizer._process_all_1 | def _process_all_1(self, texts:Collection[str]) -> List[List[str]]:
"Process a list of `texts` in one process."
tok = self.tok_func(self.lang)
if self.special_cases: tok.add_special_cases(self.special_cases)
return [self.process_text(str(t), tok) for t in texts] | python | def _process_all_1(self, texts:Collection[str]) -> List[List[str]]:
"Process a list of `texts` in one process."
tok = self.tok_func(self.lang)
if self.special_cases: tok.add_special_cases(self.special_cases)
return [self.process_text(str(t), tok) for t in texts] | [
"def",
"_process_all_1",
"(",
"self",
",",
"texts",
":",
"Collection",
"[",
"str",
"]",
")",
"->",
"List",
"[",
"List",
"[",
"str",
"]",
"]",
":",
"tok",
"=",
"self",
".",
"tok_func",
"(",
"self",
".",
"lang",
")",
"if",
"self",
".",
"special_cases... | Process a list of `texts` in one process. | [
"Process",
"a",
"list",
"of",
"texts",
"in",
"one",
"process",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L110-L114 |
20,795 | fastai/fastai | fastai/text/transform.py | Tokenizer.process_all | def process_all(self, texts:Collection[str]) -> List[List[str]]:
"Process a list of `texts`."
if self.n_cpus <= 1: return self._process_all_1(texts)
with ProcessPoolExecutor(self.n_cpus) as e:
return sum(e.map(self._process_all_1, partition_by_cores(texts, self.n_cpus)), []) | python | def process_all(self, texts:Collection[str]) -> List[List[str]]:
"Process a list of `texts`."
if self.n_cpus <= 1: return self._process_all_1(texts)
with ProcessPoolExecutor(self.n_cpus) as e:
return sum(e.map(self._process_all_1, partition_by_cores(texts, self.n_cpus)), []) | [
"def",
"process_all",
"(",
"self",
",",
"texts",
":",
"Collection",
"[",
"str",
"]",
")",
"->",
"List",
"[",
"List",
"[",
"str",
"]",
"]",
":",
"if",
"self",
".",
"n_cpus",
"<=",
"1",
":",
"return",
"self",
".",
"_process_all_1",
"(",
"texts",
")",... | Process a list of `texts`. | [
"Process",
"a",
"list",
"of",
"texts",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L116-L120 |
20,796 | fastai/fastai | fastai/text/transform.py | Vocab.numericalize | def numericalize(self, t:Collection[str]) -> List[int]:
"Convert a list of tokens `t` to their ids."
return [self.stoi[w] for w in t] | python | def numericalize(self, t:Collection[str]) -> List[int]:
"Convert a list of tokens `t` to their ids."
return [self.stoi[w] for w in t] | [
"def",
"numericalize",
"(",
"self",
",",
"t",
":",
"Collection",
"[",
"str",
"]",
")",
"->",
"List",
"[",
"int",
"]",
":",
"return",
"[",
"self",
".",
"stoi",
"[",
"w",
"]",
"for",
"w",
"in",
"t",
"]"
] | Convert a list of tokens `t` to their ids. | [
"Convert",
"a",
"list",
"of",
"tokens",
"t",
"to",
"their",
"ids",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L128-L130 |
20,797 | fastai/fastai | fastai/text/transform.py | Vocab.textify | def textify(self, nums:Collection[int], sep=' ') -> List[str]:
"Convert a list of `nums` to their tokens."
return sep.join([self.itos[i] for i in nums]) if sep is not None else [self.itos[i] for i in nums] | python | def textify(self, nums:Collection[int], sep=' ') -> List[str]:
"Convert a list of `nums` to their tokens."
return sep.join([self.itos[i] for i in nums]) if sep is not None else [self.itos[i] for i in nums] | [
"def",
"textify",
"(",
"self",
",",
"nums",
":",
"Collection",
"[",
"int",
"]",
",",
"sep",
"=",
"' '",
")",
"->",
"List",
"[",
"str",
"]",
":",
"return",
"sep",
".",
"join",
"(",
"[",
"self",
".",
"itos",
"[",
"i",
"]",
"for",
"i",
"in",
"nu... | Convert a list of `nums` to their tokens. | [
"Convert",
"a",
"list",
"of",
"nums",
"to",
"their",
"tokens",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L132-L134 |
20,798 | fastai/fastai | fastai/text/transform.py | Vocab.create | def create(cls, tokens:Tokens, max_vocab:int, min_freq:int) -> 'Vocab':
"Create a vocabulary from a set of `tokens`."
freq = Counter(p for o in tokens for p in o)
itos = [o for o,c in freq.most_common(max_vocab) if c >= min_freq]
for o in reversed(defaults.text_spec_tok):
if ... | python | def create(cls, tokens:Tokens, max_vocab:int, min_freq:int) -> 'Vocab':
"Create a vocabulary from a set of `tokens`."
freq = Counter(p for o in tokens for p in o)
itos = [o for o,c in freq.most_common(max_vocab) if c >= min_freq]
for o in reversed(defaults.text_spec_tok):
if ... | [
"def",
"create",
"(",
"cls",
",",
"tokens",
":",
"Tokens",
",",
"max_vocab",
":",
"int",
",",
"min_freq",
":",
"int",
")",
"->",
"'Vocab'",
":",
"freq",
"=",
"Counter",
"(",
"p",
"for",
"o",
"in",
"tokens",
"for",
"p",
"in",
"o",
")",
"itos",
"="... | Create a vocabulary from a set of `tokens`. | [
"Create",
"a",
"vocabulary",
"from",
"a",
"set",
"of",
"tokens",
"."
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L148-L155 |
20,799 | fastai/fastai | fastai/text/transform.py | Vocab.load | def load(cls, path):
"Load the `Vocab` contained in `path`"
itos = pickle.load(open(path, 'rb'))
return cls(itos) | python | def load(cls, path):
"Load the `Vocab` contained in `path`"
itos = pickle.load(open(path, 'rb'))
return cls(itos) | [
"def",
"load",
"(",
"cls",
",",
"path",
")",
":",
"itos",
"=",
"pickle",
".",
"load",
"(",
"open",
"(",
"path",
",",
"'rb'",
")",
")",
"return",
"cls",
"(",
"itos",
")"
] | Load the `Vocab` contained in `path` | [
"Load",
"the",
"Vocab",
"contained",
"in",
"path"
] | 9fb84a5cdefe5a766cdb792b8f5d8971737b7e67 | https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/text/transform.py#L158-L161 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.