_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_22700 |
Return the quarter of the year. Examples
>>> ts = pd.Timestamp(2020, 3, 14)
>>> ts.quarter
1 | |
doc_22701 | Display url using the default browser. If new is 0, the url is opened in the same browser window if possible. If new is 1, a new browser window is opened if possible. If new is 2, a new browser page (“tab”) is opened if possible. If autoraise is True, the window is raised if possible (note that under many window manage... | |
doc_22702 |
[Deprecated] Notes Deprecated since version 3.4: | |
doc_22703 | Test whether the given pair of screen-relative character-cell coordinates are enclosed by the given window, returning True or False. It is useful for determining what subset of the screen windows enclose the location of a mouse event. | |
doc_22704 |
Test if pattern or regex is contained within a string of a Series or Index. Return boolean Series or Index based on whether a given pattern or regex is contained within a string of a Series or Index. Parameters
pat:str
Character sequence or regular expression.
case:bool, default True
If True, case sensitive... | |
doc_22705 | Platform dependent: the time of most recent metadata change on Unix, the time of creation on Windows, expressed in seconds. | |
doc_22706 | See torch.bincount() | |
doc_22707 |
Get or set the PRNG state Returns
statedict
Dictionary containing the information required to describe the state of the PRNG | |
doc_22708 |
Alias for field number 3 | |
doc_22709 | Add character ch with attribute attr, and immediately call refresh() on the window. | |
doc_22710 | See Migration guide for more details. tf.compat.v1.raw_ops.InfeedEnqueuePrelinearizedBuffer
tf.raw_ops.InfeedEnqueuePrelinearizedBuffer(
input, device_ordinal=-1, name=None
)
Args
input A Tensor of type variant. A variant tensor representing linearized output.
device_ordinal An optional int. Defau... | |
doc_22711 | A class-based view that dispatches request methods to the corresponding class methods. For example, if you implement a get method, it will be used to handle GET requests. class CounterAPI(MethodView):
def get(self):
return session.get('counter', 0)
def post(self):
session['counter'] = session.g... | |
doc_22712 |
Context-manager that changes the current device to that of given object. You can use both tensors and storages as arguments. If a given object is not allocated on a GPU, this is a no-op. Parameters
obj (Tensor or Storage) – object allocated on the selected device. | |
doc_22713 |
Alias for get_facecolor. | |
doc_22714 | Parameters
type_ – one of the strings “polygon”, “image”, “compound” Data structure modeling shapes. The pair (type_, data) must follow this specification:
type_ data
“polygon” a polygon-tuple, i.e. a tuple of pairs of coordinates
“image” an image (in this form only used internally!)
“compound” None (a co... | |
doc_22715 | This function operates exactly as TemporaryFile() does, except that data is spooled in memory until the file size exceeds max_size, or until the file’s fileno() method is called, at which point the contents are written to disk and operation proceeds as with TemporaryFile(). The resulting file has one additional method,... | |
doc_22716 | bytearray.rindex(sub[, start[, end]])
Like rfind() but raises ValueError when the subsequence sub is not found. The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255. Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence. | |
doc_22717 | Note This is an advanced function that is not needed in everyday Python programming, unlike importlib.import_module(). This function is invoked by the import statement. It can be replaced (by importing the builtins module and assigning to builtins.__import__) in order to change semantics of the import statement, but ... | |
doc_22718 |
Set the normalization instance. Parameters
normNormalize or None
Notes If there are any colorbars using the mappable for this norm, setting the norm of the mappable will reset the norm, locator, and formatters on the colorbar to default. | |
doc_22719 | turtle.turtlesize(stretch_wid=None, stretch_len=None, outline=None)
Parameters
stretch_wid – positive number
stretch_len – positive number
outline – positive number Return or set the pen’s attributes x/y-stretchfactors and/or outline. Set resizemode to “user”. If and only if resizemode is set to “user”, the ... | |
doc_22720 | tf.keras.layers.GRUCell(
units, activation='tanh', recurrent_activation='sigmoid',
use_bias=True, kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',
bias_initializer='zeros', kernel_regularizer=None,
recurrent_regularizer=None, bias_regularizer=None, kernel_constraint=None,
... | |
doc_22721 |
The negative log likelihood loss. It is useful to train a classification problem with C classes. If provided, the optional argument weight should be a 1D Tensor assigning weight to each of the classes. This is particularly useful when you have an unbalanced training set. The input given through a forward call is expe... | |
doc_22722 |
propagate
If this attribute evaluates to true, events logged to this logger will be passed to the handlers of higher level (ancestor) loggers, in addition to any handlers attached to this logger. Messages are passed directly to the ancestor loggers’ handlers - neither the level nor filters of the ancestor loggers i... | |
doc_22723 | See Migration guide for more details. tf.compat.v1.raw_ops.SummaryWriter
tf.raw_ops.SummaryWriter(
shared_name='', container='', name=None
)
Args
shared_name An optional string. Defaults to "".
container An optional string. Defaults to "".
name A name for the operation (optional).
Re... | |
doc_22724 |
Alias for get_edgecolor. | |
doc_22725 | See Migration guide for more details. tf.compat.v1.raw_ops.ExtractGlimpseV2
tf.raw_ops.ExtractGlimpseV2(
input, size, offsets, centered=True, normalized=True, uniform_noise=True,
noise='uniform', name=None
)
Returns a set of windows called glimpses extracted at location offsets from the input tensor. If the ... | |
doc_22726 |
Remove the Axes ax from the figure; update the current Axes. | |
doc_22727 |
Clear the Axes.
Examples using matplotlib.axes.Axes.cla
pyplot animation
Data Browser | |
doc_22728 |
Perform classification on an array of test vectors X. Parameters
Xarray-like of shape (n_samples, n_features)
Returns
Cndarray of shape (n_samples,)
Predicted target values for X | |
doc_22729 | Add a new node and its predecessors to the graph. Both the node and all elements in predecessors must be hashable. If called multiple times with the same node argument, the set of dependencies will be the union of all dependencies passed in. It is possible to add a node with no dependencies (predecessors is not provide... | |
doc_22730 |
Get padding for constrained_layout. Returns a list of w_pad, h_pad in inches and wspace and hspace as fractions of the subplot. See Constrained Layout Guide. Parameters
relativebool
If True, then convert from inches to figure relative. | |
doc_22731 | Add correct Cookie header to request. If policy allows (ie. the rfc2965 and hide_cookie2 attributes of the CookieJar’s CookiePolicy instance are true and false respectively), the Cookie2 header is also added when appropriate. The request object (usually a urllib.request.Request instance) must support the methods get_fu... | |
doc_22732 |
Draw the Artist (and its children) using the given renderer. This has no effect if the artist is not visible (Artist.get_visible returns False). Parameters
rendererRendererBase subclass.
Notes This method is overridden in the Artist subclasses. | |
doc_22733 |
A ConvReLU2d module is a fused module of Conv2d and ReLU, attached with FakeQuantize modules for weight for quantization aware training. We combined the interface of Conv2d and BatchNorm2d. Variables
~ConvReLU2d.weight_fake_quant – fake quant module for weight | |
doc_22734 | tf.compat.v1.nn.conv2d_backprop_filter(
input, filter_sizes, out_backprop, strides, padding, use_cudnn_on_gpu=True,
data_format='NHWC', dilations=[1, 1, 1, 1], name=None
)
Args
input A Tensor. Must be one of the following types: half, bfloat16, float32, float64. 4-D with shape [batch, in_height, in_wi... | |
doc_22735 | A list of the non-fatal errors encountered while loading tests. Not reset by the loader at any point. Fatal errors are signalled by the relevant a method raising an exception to the caller. Non-fatal errors are also indicated by a synthetic test that will raise the original error when run. New in version 3.5. | |
doc_22736 |
Bases: matplotlib.backend_tools.AxisScaleBase Tool to toggle between linear and logarithmic scales on the X axis. default_keymap=['k', 'L']
Keymap to associate with this tool. list[str]: List of keys that will trigger this tool when a keypress event is emitted on self.figure.canvas.
description='Toggle scale ... | |
doc_22737 | This class may be initialized with seconds since the epoch, a time tuple, an ISO 8601 time/date string, or a datetime.datetime instance. It has the following methods, supported mainly for internal use by the marshalling/unmarshalling code:
decode(string)
Accept a string as the instance’s new time value.
encode(... | |
doc_22738 |
Draw a collection of paths selecting drawing properties from the lists facecolors, edgecolors, linewidths, linestyles and antialiaseds. offsets is a list of offsets to apply to each of the paths. The offsets in offsets are first transformed by offsetTrans before being applied. offset_position is unused now, but the a... | |
doc_22739 | See Migration guide for more details. tf.compat.v1.raw_ops.QuantizedAvgPool
tf.raw_ops.QuantizedAvgPool(
input, min_input, max_input, ksize, strides, padding, name=None
)
Args
input A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16. 4-D with shape [batch, height, width... | |
doc_22740 |
The Axes instance the artist resides in, or None. | |
doc_22741 | Pass the response body directly through as the WSGI iterable. This can be used when the body is a binary file or other iterator of bytes, to skip some unnecessary checks. Use send_file() instead of setting this manually. | |
doc_22742 | See Migration guide for more details. tf.compat.v1.raw_ops.PadV2
tf.raw_ops.PadV2(
input, paddings, constant_values, name=None
)
This operation pads input according to the paddings and constant_values you specify. paddings is an integer tensor with shape [Dn, 2], where n is the rank of input. For each dimension ... | |
doc_22743 |
Call self as a function. | |
doc_22744 |
Return whether antialiasing is used for drawing. | |
doc_22745 |
[Deprecated] Convert days since Matplotlib epoch to UNIX time. Parameters
dlist of floats
Time in days since Matplotlib epoch (see get_epoch()). Returns
numpy.array
Time in seconds since 1970-01-01. Notes Deprecated since version 3.5. | |
doc_22746 |
Set the colormap for luminance data. Parameters
cmapColormap or str or None | |
doc_22747 |
Return the product of the array elements over the given axis Refer to numpy.prod for full documentation. See also numpy.prod
equivalent function | |
doc_22748 | Constant used to represent the limit for an unlimited resource. | |
doc_22749 | $ python myapp.pyz
<output from myapp>
Command-Line Interface When called as a program from the command line, the following form is used: $ python -m zipapp source [options]
If source is a directory, this will create an archive from the contents of source. If source is a file, it should be an archive, and it will be ... | |
doc_22750 |
Set the Figure instance the artist belongs to. Parameters
figFigure | |
doc_22751 | A named tuple giving parameters of the numeric hash implementation. For more details about hashing of numeric types, see Hashing of numeric types.
attribute explanation
width width in bits used for hash values
modulus prime modulus P used for numeric hash scheme
inf hash value returned for a positive infinity... | |
doc_22752 |
alias of matplotlib.backends.backend_webagg.FigureCanvasWebAgg
classmatplotlib.backends.backend_webagg.FigureCanvasWebAgg(*args, **kwargs)[source]
Bases: matplotlib.backends.backend_webagg_core.FigureCanvasWebAggCore
classmatplotlib.backends.backend_webagg.ServerThread(group=None, target=None, name=None, ar... | |
doc_22753 | 'blogs.blog': lambda o: "/blogs/%s/" % o.slug,
'news.story': lambda o: "/stories/%s/%s/" % (o.pub_year, o.slug),
}
The model name used in this setting should be all lowercase, regardless of the case of the actual model class name. ADMINS Default: [] (Empty list) A list of all the people who get code error noti... | |
doc_22754 |
Fit a semi-supervised label propagation model based All the input data is provided matrix X (labeled and unlabeled) and corresponding label matrix y with a dedicated marker value for unlabeled samples. Parameters
Xarray-like of shape (n_samples, n_features)
A matrix of shape (n_samples, n_samples) will be creat... | |
doc_22755 |
Apply only the affine part of this transformation on the given array of values. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally a no-op. In affine transformations, this is equivalent to transform(values). Parameters
valuesa... | |
doc_22756 |
Evaluate a Python expression as a string using various backends. The following arithmetic operations are supported: +, -, *, /, **, %, // (python engine only) along with the following boolean operations: | (or), & (and), and ~ (not). Additionally, the 'pandas' parser allows the use of and, or, and not with the same s... | |
doc_22757 | Returns an asyncgen_hooks object, which is similar to a namedtuple of the form (firstiter, finalizer), where firstiter and finalizer are expected to be either None or functions which take an asynchronous generator iterator as an argument, and are used to schedule finalization of an asynchronous generator by an event lo... | |
doc_22758 |
Clear the cursor. | |
doc_22759 | Print information on collectable objects found. | |
doc_22760 | codecs.BOM_BE
codecs.BOM_LE
codecs.BOM_UTF8
codecs.BOM_UTF16
codecs.BOM_UTF16_BE
codecs.BOM_UTF16_LE
codecs.BOM_UTF32
codecs.BOM_UTF32_BE
codecs.BOM_UTF32_LE
These constants define various byte sequences, being Unicode byte order marks (BOMs) for several encodings. They are used in UTF-16 and UTF-32 d... | |
doc_22761 |
Context manager that makes every autograd operation emit an NVTX range. It is useful when running the program under nvprof: nvprof --profile-from-start off -o trace_name.prof -- <regular command here>
Unfortunately, there’s no way to force nvprof to flush the data it collected to disk, so for CUDA profiling one has ... | |
doc_22762 | Unpacks and returns (as a list) a fixed length array of homogeneous items. n is number of list elements to expect in the buffer. As above, unpack_item is the function used to unpack each element. | |
doc_22763 | Register a function to run before each request. For example, this can be used to open a database connection, or to load the logged in user from the session. @app.before_request
def load_user():
if "user_id" in session:
g.user = db.session.get(session["user_id"])
The function will be called without any argu... | |
doc_22764 |
Bases: matplotlib.backend_tools.ToolToggleBase Base class for ToolZoom and ToolPan. disable(event)[source]
Release the canvas and disconnect press/release events.
enable(event)[source]
Connect press/release events and lock the canvas.
scroll_zoom(event)[source]
trigger(sender, event, data=None)[sour... | |
doc_22765 |
Returns numpy array of datetime.time objects with timezone information. The time part of the Timestamps. | |
doc_22766 | os.MFD_ALLOW_SEALING
os.MFD_HUGETLB
os.MFD_HUGE_SHIFT
os.MFD_HUGE_MASK
os.MFD_HUGE_64KB
os.MFD_HUGE_512KB
os.MFD_HUGE_1MB
os.MFD_HUGE_2MB
os.MFD_HUGE_8MB
os.MFD_HUGE_16MB
os.MFD_HUGE_32MB
os.MFD_HUGE_256MB
os.MFD_HUGE_512MB
os.MFD_HUGE_1GB
os.MFD_HUGE_2GB
os.MFD_HUGE_16GB
These flags can... | |
doc_22767 |
Apply trees in the ensemble to X, return leaf indices. New in version 0.17. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The input samples. Internally, its dtype will be converted to dtype=np.float32. If a sparse matrix is provided, it will be converted to a sparse csr_matrix. R... | |
doc_22768 | The WSGI specification requires that all middlewares and gateways respect the close callback of the iterable returned by the application. Because it is useful to add another close action to a returned iterable and adding a custom iterable is a boring task this class can be used for that: return ClosingIterator(app(envi... | |
doc_22769 |
Number of array dimensions. Examples >>> x = np.array([1, 2, 3])
>>> x.ndim
1
>>> y = np.zeros((2, 3, 4))
>>> y.ndim
3 | |
doc_22770 | msilib.FCICreate(cabname, files)
Create a new CAB file named cabname. files must be a list of tuples, each containing the name of the file on disk, and the name of the file inside the CAB file. The files are added to the CAB file in the order they appear in the list. All files are added into a single CAB file, using ... | |
doc_22771 |
Alter axes labels. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don’t throw an error. See the user guide for more. Parameters
mapper:dict-like or function
Dict-like or function transformations to apply to that axis’ values. Use e... | |
doc_22772 |
Predict the labels for the data samples in X using trained model. Parameters
Xarray-like of shape (n_samples, n_features)
List of n_features-dimensional data points. Each row corresponds to a single data point. Returns
labelsarray, shape (n_samples,)
Component labels. | |
doc_22773 | Index Attribute Meaning
0 pw_name Login name
1 pw_passwd Optional encrypted password
2 pw_uid Numerical user ID
3 pw_gid Numerical group ID
4 pw_gecos User name or comment field
5 pw_dir User home directory
6 pw_shell User command interpreter The uid and gid items are integers, all others are strings. ... | |
doc_22774 | Parses a string and returns a datetime.datetime. UTC offsets are supported; if value describes one, the result’s tzinfo attribute is a datetime.timezone instance. | |
doc_22775 |
Parameters
shorthand_namestr
A string representing the "name" of the transform. The name carries no significance other than to improve the readability of str(transform) when DEBUG=True. | |
doc_22776 | Change the owner and group id of the file given by fd to the numeric uid and gid. To leave one of the ids unchanged, set it to -1. See chown(). As of Python 3.3, this is equivalent to os.chown(fd, uid,
gid). Raises an auditing event os.chown with arguments path, uid, gid, dir_fd. Availability: Unix. | |
doc_22777 |
Format a number in engineering notation, appending a letter representing the power of 1000 of the original number. Some examples: >>> format_eng(0) # for self.places = 0
'0'
>>> format_eng(1000000) # for self.places = 1
'1.0 M'
>>> format_eng("-1e-6") # for self.places = 2
'-1.00 µ' | |
doc_22778 |
Define the picking behavior of the artist. Parameters
pickerNone or bool or float or callable
This can be one of the following:
None: Picking is disabled for this artist (default). A boolean: If True then picking will be enabled and the artist will fire a pick event if the mouse event is over the artist. A fl... | |
doc_22779 |
Set the parameters of this kernel. The method works on simple kernels as well as on nested kernels. The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object. Returns
self | |
doc_22780 | See Migration guide for more details. tf.compat.v1.errors.DataLossError
tf.errors.DataLossError(
node_def, op, message
)
For example, this may be raised by running a tf.WholeFileReader.read operation, if the file is truncated while it is being read.
Attributes
error_code The integer error code that desc... | |
doc_22781 |
Bases: mpl_toolkits.axes_grid1.axes_size._Base Size whose absolute part is either the largest width or the largest height of the given artist_list. add_artist(a)[source]
get_size(renderer)[source] | |
doc_22782 | Add a list of files to the current component as specified in the glob pattern. Individual files can be excluded in the exclude list. | |
doc_22783 | Return the arc cosine of x. There are two branch cuts: One extends right from 1 along the real axis to ∞, continuous from below. The other extends left from -1 along the real axis to -∞, continuous from above. | |
doc_22784 |
Iterate over (column name, Series) pairs. Iterates over the DataFrame columns, returning a tuple with the column name and the content as a Series. Yields
label:object
The column names for the DataFrame being iterated over.
content:Series
The column entries belonging to each label, as a Series. See also... | |
doc_22785 |
Apply transforms, and score with the final estimator Parameters
Xiterable
Data to predict on. Must fulfill input requirements of first step of the pipeline.
yiterable, default=None
Targets used for scoring. Must fulfill label requirements for all steps of the pipeline.
sample_weightarray-like, default=Non... | |
doc_22786 |
Pad an array. Parameters
arrayarray_like of rank N
The array to pad.
pad_width{sequence, array_like, int}
Number of values padded to the edges of each axis. ((before_1, after_1), … (before_N, after_N)) unique pad widths for each axis. ((before, after),) yields same before and after pad for each axis. (pad,)... | |
doc_22787 |
alias of numpy.longdouble | |
doc_22788 |
Cache the properties of the font at path to make it available to the FontManager. The type of font is inferred from the path suffix. Parameters
pathstr or path-like | |
doc_22789 | Sets the number of threads used for intraop parallelism on CPU. Warning To ensure that the correct number of threads is used, set_num_threads must be called before running eager, JIT or autograd code. | |
doc_22790 | An optional json.JSONDecoder subclass to deserialize the value retrieved from the database. The value will be in the format chosen by the custom encoder (most often a string). Your deserialization may need to account for the fact that you can’t be certain of the input type. For example, you run the risk of returning a ... | |
doc_22791 |
Return a view of the array with axis1 and axis2 interchanged. Refer to numpy.swapaxes for full documentation. See also numpy.swapaxes
equivalent function | |
doc_22792 | A subclass of Shelf which exposes first(), next(), previous(), last() and set_location() which are available in the third-party bsddb module from pybsddb but not in other database modules. The dict object passed to the constructor must support those methods. This is generally accomplished by calling one of bsddb.hashop... | |
doc_22793 |
A multi-label model that arranges binary classifiers into a chain. Each model makes a prediction in the order specified by the chain using all of the available features provided to the model plus the predictions of models that are earlier in the chain. Read more in the User Guide. New in version 0.19. Parameters
... | |
doc_22794 | Returns the total number of database rows that have been modified, inserted, or deleted since the database connection was opened. | |
doc_22795 | See Migration guide for more details. tf.compat.v1.raw_ops.AudioSpectrogram
tf.raw_ops.AudioSpectrogram(
input, window_size, stride, magnitude_squared=False, name=None
)
Spectrograms are a standard way of representing audio information as a series of slices of frequency information, one slice for each window of ... | |
doc_22796 |
Add tool to ToolManager. If successful, adds a new event tool_trigger_{name} where {name} is the name of the tool; the event is fired every time the tool is triggered. Parameters
namestr
Name of the tool, treated as the ID, has to be unique.
toolclass_like, i.e. str or type
Reference to find the class of th... | |
doc_22797 |
Extract Histogram of Oriented Gradients (HOG) for a given image. Compute a Histogram of Oriented Gradients (HOG) by (optional) global image normalization computing the gradient image in row and col
computing gradient histograms normalizing across blocks flattening into a feature vector Parameters
image(M, N[, ... | |
doc_22798 | credits
Objects that when printed or called, print the text of copyright or credits, respectively. | |
doc_22799 |
Computes and returns a mask for the input tensor t. Starting from a base default_mask (which should be a mask of ones if the tensor has not been pruned yet), generate a random mask to apply on top of the default_mask by randomly zeroing out channels along the specified dim of the tensor. Parameters
t (torch.Tenso... |
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