def prepare_training_data(src_files, src_files_encoding, trg_files,
trg_files_encoding, src_output_file,
trg_output_file):
'''
for each pair of source/target files, check they have the same number of sentences;
do shuffle and save with utf-8 encodings
'''
src = chain(
*[iter_(open_(f, encoding=src_files_encoding)) for f in src_files])
trg = chain(
*[iter_(open_(f, encoding=trg_files_encoding)) for f in trg_files])
# TODO: find a way not to load all sentences into memory
logger.info("reading sentences from source files...")
src_sentences = [sent for sent in src]
logger.info("reading sentences from target files...")
trg_sentences = [sent for sent in trg]
assert len(src_sentences) == len(trg_sentences)
logger.info("number of sentences:%d" % len(src_sentences))
# '\n' has been removed from a sentence
assert src_sentences[0].endswith('\n')
# do the shuffle
ids = list(range(len(src_sentences)))
random.shuffle(ids)
with codecs.open(src_output_file, 'w', 'UTF-8') as f_src:
with codecs.open(trg_output_file, 'w', 'UTF-8') as f_trg:
for i in ids:
f_src.write(src_sentences[i])
f_trg.write(trg_sentences[i])
def get_request_iterator(self):
if self.times:
return repeat(self.batch_size, self.times)
if self.num_examples:
d, r = divmod(self.num_examples, self.batch_size)
return chain(repeat(self.batch_size, d), [r] if r else [])
return repeat(self.batch_size)
def get_request_iterator(self):
iterator_list = []
start = 0
for size, examples in self.size_dict.items():
iterator_list.append(
partition_all(self.batch_size, xrange(start,
start + examples)))
start += examples
return chain(*iterator_list)
def __init__(self, data_streams, sources):
self.data_streams = data_streams
if len(
list(
chain(
*[data_stream.sources
for data_stream in data_streams]))) != len(sources):
raise ValueError("wrong number of sources given")
self.sources = sources
def __init__(self, data_streams, sources, axis_labels=None):
super(Merge, self).__init__(iteration_scheme=None, axis_labels=axis_labels)
if not all(data_stream.produces_examples == data_streams[0].produces_examples for data_stream in data_streams):
raise ValueError("all data streams must produce the same type of " "output (batches or examples)")
self.data_streams = data_streams
self.produces_examples = self.data_streams[0].produces_examples
if len(list(chain(*[data_stream.sources for data_stream in data_streams]))) != len(sources):
raise ValueError("wrong number of sources given")
self.sources = sources
def __init__(self, data_streams, sources, axis_labels=None):
super(Merge, self).__init__(
iteration_scheme=None, axis_labels=axis_labels)
if not all(data_stream.produces_examples ==
data_streams[0].produces_examples
for data_stream in data_streams):
raise ValueError('all data streams must produce the same type of '
'output (batches or examples)')
self.data_streams = data_streams
self.produces_examples = self.data_streams[0].produces_examples
if len(list(chain(*[data_stream.sources for data_stream
in data_streams]))) != len(sources):
raise ValueError("wrong number of sources given")
self.sources = sources
def wrapper_func(*args, **kwargs):
mock_requests = args[-1]
args = args[:-1]
length = len(mock_content)
mock_response = mock.Mock()
mock_response.iter_content = mock.Mock(side_effect=lambda s: chain(
(mock_content[s * i:s * (i + 1)] for i in range(length // s)),
(mock_content[(length // s) * s:], )))
mock_response.headers = {}
if content_length:
mock_response.headers['content-length'] = length
if content_disposition:
cd = 'attachment; filename={}'.format(mock_filename)
mock_response.headers['Content-Disposition'] = cd
mock_requests.get.return_value = mock_response
return func(*args, **kwargs)
def cross_validation(scheme_class, num_examples, num_folds, strict=True,
**kwargs):
"""Return pairs of schemes to be used for cross-validation.
Parameters
----------
scheme_class : subclass of :class:`IndexScheme` or :class:`BatchScheme`
The type of the returned schemes. The constructor is called with an
iterator and `**kwargs` as arguments.
num_examples : int
The number of examples in the datastream.
num_folds : int
The number of folds to return.
strict : bool, optional
If `True`, enforce that `num_examples` is divisible by `num_folds`
and so, that all validation sets have the same size. If `False`,
the size of the validation set is returned along the iteration
schemes. Defaults to `True`.
Yields
------
fold : tuple
The generator returns `num_folds` tuples. The first two elements of
the tuple are the training and validation iteration schemes. If
`strict` is set to `False`, the tuple has a third element
corresponding to the size of the validation set.
"""
if strict and num_examples % num_folds != 0:
raise ValueError(("{} examples are not divisible in {} evenly-sized " +
"folds. To allow this, have a look at the " +
"`strict` argument.").format(num_examples,
num_folds))
for i in xrange(num_folds):
begin = num_examples * i // num_folds
end = num_examples * (i+1) // num_folds
train = scheme_class(list(chain(xrange(0, begin),
xrange(end, num_examples))),
**kwargs)
valid = scheme_class(xrange(begin, end), **kwargs)
if strict:
yield (train, valid)
else:
yield (train, valid, end - begin)
def wrapper_func(*args, **kwargs):
mock_requests = args[-1]
args = args[:-1]
length = len(mock_content)
mock_response = mock.Mock()
mock_response.iter_content = mock.Mock(
side_effect=lambda s: chain(
(mock_content[s * i: s * (i + 1)]
for i in range(length // s)),
(mock_content[(length // s) * s:],)))
mock_response.headers = {}
if content_length:
mock_response.headers['content-length'] = length
if content_disposition:
cd = 'attachment; filename={}'.format(mock_filename)
mock_response.headers['Content-Disposition'] = cd
mock_requests.get.return_value = mock_response
return func(*args, **kwargs)
def search(request):
'''
queries = request.GET['q'].split()
queryset_list = Post.objects.all() # .order_by('-timestamp')
queryset_list.extend(UserProfile.objects.all())
for query in queries:
queryset_list = queryset_list.filter(
Q(title__icontains=query) |
Q(description__icontains=query) |
Q(user__username__icontains=query) |
Q(user__full_name__icontains=query)
)
'''
queries = request.GET['q'].split()
results = []
for query in queries:
user_results = (UserProfile.objects.filter(
Q(username__icontains=query) |
Q(bio__icontains=query) |
Q(full_name__icontains=query) |
Q(location__icontains=query)))
post_results = (Post.objects.filter(
Q(title__icontains=query) |
Q(description__icontains=query) |
Q(medium__icontains=query)))
results = list(chain(results, user_results, post_results))
paginator = Paginator(results, 10) # Show 10 contacts per page
page = request.GET.get('page')
try:
queryset = paginator.page(page)
except PageNotAnInteger:
queryset = paginator.page(1)
except EmptyPage:
queryset = paginator.page(paginator.num_pages)
context = {
'object_list': queryset,
'title': 'Search Results',
'query': query,
}
return render(request, 'search_results.html', context)
def search(request):
'''
queries = request.GET['q'].split()
queryset_list = Post.objects.all() # .order_by('-timestamp')
queryset_list.extend(UserProfile.objects.all())
for query in queries:
queryset_list = queryset_list.filter(
Q(title__icontains=query) |
Q(description__icontains=query) |
Q(user__username__icontains=query) |
Q(user__full_name__icontains=query)
)
'''
queries = request.GET['q'].split()
results = []
for query in queries:
user_results = (UserProfile.objects.filter(
Q(username__icontains=query) | Q(bio__icontains=query)
| Q(full_name__icontains=query) | Q(location__icontains=query)))
post_results = (Post.objects.filter(
Q(title__icontains=query) | Q(description__icontains=query)
| Q(medium__icontains=query)))
results = list(chain(results, user_results, post_results))
paginator = Paginator(results, 10) # Show 10 contacts per page
page = request.GET.get('page')
try:
queryset = paginator.page(page)
except PageNotAnInteger:
queryset = paginator.page(1)
except EmptyPage:
queryset = paginator.page(paginator.num_pages)
context = {
'object_list': queryset,
'title': 'Search Results',
'query': query,
}
return render(request, 'search_results.html', context)
def open(self):
return chain(
*[iter_(open_(f, encoding=self.encoding)) for f in self.files])
def open(self):
return chain(
*[iter_(codecs.open(f, encoding="latin1")) for f in self.files])
def __init__(self, data_streams, sources):
self.data_streams = data_streams
if len(list(chain(*[data_stream.sources for data_stream
in data_streams]))) != len(sources):
raise ValueError("wrong number of sources given")
self.sources = sources
def open(self):
return chain(*[iter_(open_(f, encoding=self.encoding))
for f in self.files])
def open(self):
return chain(*[iter_(open(f)) for f in self.files])
def open(self):
handlers = [open(f, "rb") for f in self.files]
return chain(*[iter_(h) for h in handlers]), handlers
def get_request_iterator(self):
return chain(*[sch.get_request_iterator() for sch in self.schemes])
def open(self): return chain(*[iter_( codecs.open(f, encoding="latin1") ) for f in self.files])
def open(self):
return bAbIState(chain(*[iter_(open(f)) for f in self.files]), [], 0)
def open(self):
return chain(*[iter_(open(f)) for f in self.files])
