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doc_29900
See torch.mean()
doc_29901
Returns whether the kernel is stationary.
doc_29902
tf.estimator.LinearEstimator( head, feature_columns, model_dir=None, optimizer='Ftrl', config=None, sparse_combiner='sum', warm_start_from=None ) Example: categorical_column_a = categorical_column_with_hash_bucket(...) categorical_column_b = categorical_column_with_hash_bucket(...) categorical_feature_a_x_cat...
doc_29903
Some actions are best if they’re made available to any object in the admin site – the export action defined above would be a good candidate. You can make an action globally available using AdminSite.add_action(). For example: from django.contrib import admin admin.site.add_action(export_selected_objects) This makes t...
doc_29904
The UUID variant, which determines the internal layout of the UUID. This will be one of the constants RESERVED_NCS, RFC_4122, RESERVED_MICROSOFT, or RESERVED_FUTURE.
doc_29905
os.RTLD_NOW os.RTLD_GLOBAL os.RTLD_LOCAL os.RTLD_NODELETE os.RTLD_NOLOAD os.RTLD_DEEPBIND Flags for use with the setdlopenflags() and getdlopenflags() functions. See the Unix manual page dlopen(3) for what the different flags mean. New in version 3.3.
doc_29906
Callback for dragging in zoom mode.
doc_29907
[Deprecated] Notes Deprecated since version 3.5:
doc_29908
Return complex 2D Gabor filter kernel. Gabor kernel is a Gaussian kernel modulated by a complex harmonic function. Harmonic function consists of an imaginary sine function and a real cosine function. Spatial frequency is inversely proportional to the wavelength of the harmonic and to the standard deviation of a Gauss...
doc_29909
Returns whether the kernel is defined on fixed-length feature vectors or generic objects. Defaults to True for backward compatibility.
doc_29910
Return the picking behavior of the artist. The possible values are described in set_picker. See also set_picker, pickable, pick
doc_29911
Provide the rank of values within each group. Parameters method:{‘average’, ‘min’, ‘max’, ‘first’, ‘dense’}, default ‘average’ average: average rank of group. min: lowest rank in group. max: highest rank in group. first: ranks assigned in order they appear in the array. dense: like ‘min’, but rank always incre...
doc_29912
Returns True if the user account is currently active.
doc_29913
tf.compat.v1.estimator.tpu.TPUEstimatorSpec( mode, predictions=None, loss=None, train_op=None, eval_metrics=None, export_outputs=None, scaffold_fn=None, host_call=None, training_hooks=None, evaluation_hooks=None, prediction_hooks=None ) See EstimatorSpec for mode, predictions, loss, train_op, and export_ou...
doc_29914
Class method that attempts to find a spec for the module specified by fullname on sys.path or, if defined, on path. For each path entry that is searched, sys.path_importer_cache is checked. If a non-false object is found then it is used as the path entry finder to look for the module being searched for. If no entry is ...
doc_29915
Set the parameters of this estimator. The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object. Parameters **paramsdict Estimator parameters. Returns...
doc_29916
Predict on the data matrix X using the ClassifierChain model. Parameters X{array-like, sparse matrix} of shape (n_samples, n_features) The input data. Returns Y_predarray-like of shape (n_samples, n_classes) The predicted values.
doc_29917
Return the GridSpec instance associated with the subplot.
doc_29918
Bases: matplotlib.patches.Patch An axis spine -- the line noting the data area boundaries. Spines are the lines connecting the axis tick marks and noting the boundaries of the data area. They can be placed at arbitrary positions. See set_position for more information. The default position is ('outward', 0). Spines ar...
doc_29919
Performs Logarithmic correction on the input image. This function transforms the input image pixelwise according to the equation O = gain*log(1 + I) after scaling each pixel to the range 0 to 1. For inverse logarithmic correction, the equation is O = gain*(2**I - 1). Parameters imagendarray Input image. gainf...
doc_29920
Auto-negotiate the highest protocol version like PROTOCOL_TLS, but only support server-side SSLSocket connections. New in version 3.6.
doc_29921
Signoff: commit changes, unlock mailbox, drop connection.
doc_29922
Play the SystemExclamation sound.
doc_29923
Alias for set_antialiased.
doc_29924
bytearray.removeprefix(prefix, /) If the binary data starts with the prefix string, return bytes[len(prefix):]. Otherwise, return a copy of the original binary data: >>> b'TestHook'.removeprefix(b'Test') b'Hook' >>> b'BaseTestCase'.removeprefix(b'Test') b'BaseTestCase' The prefix may be any bytes-like object. Note ...
doc_29925
pygame object for video overlay graphics Overlay(format, (width, height)) -> Overlay The Overlay objects provide support for accessing hardware video overlays. Video overlays do not use standard RGB pixel formats, and can use multiple resolutions of data to create a single image. The Overlay objects represent lowe...
doc_29926
Return whether the artist is animated.
doc_29927
Rename the fields from a flexible-datatype ndarray or recarray. Nested fields are supported. Parameters basendarray Input array whose fields must be modified. namemapperdictionary Dictionary mapping old field names to their new version. Examples >>> from numpy.lib import recfunctions as rfn >>> a = np.a...
doc_29928
Return the time in seconds since the epoch as a floating point number. The specific date of the epoch and the handling of leap seconds is platform dependent. On Windows and most Unix systems, the epoch is January 1, 1970, 00:00:00 (UTC) and leap seconds are not counted towards the time in seconds since the epoch. This ...
doc_29929
Return value as a plist-formatted bytes object. See the documentation for dump() for an explanation of the keyword arguments of this function. New in version 3.4.
doc_29930
Set the dimension of the drawing canvas.
doc_29931
Set multiple properties at once. Supported properties are Property Description agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alpha scalar or None animated bool antialiased or aa bool or None capstyle CapStyle or {'butt', 'projecting', 'r...
doc_29932
You can also override the get_test_func() method to have the mixin use a differently named function for its checks (instead of test_func()).
doc_29933
Bases: matplotlib.transforms.Transform The base polar transform. This handles projection theta and r into Cartesian coordinate space x and y, but does not perform the ultimate affine transformation into the correct position. Parameters shorthand_namestr A string representing the "name" of the transform. The nam...
doc_29934
For each element, return True if there are only numeric characters in the element. Calls unicode.isnumeric element-wise. Numeric characters include digit characters, and all characters that have the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION ONE FIFTH. Parameters aarray_like, unicode Input arr...
doc_29935
sklearn.cluster.dbscan(X, eps=0.5, *, min_samples=5, metric='minkowski', metric_params=None, algorithm='auto', leaf_size=30, p=2, sample_weight=None, n_jobs=None) [source] Perform DBSCAN clustering from vector array or distance matrix. Read more in the User Guide. Parameters X{array-like, sparse (CSR) matrix} of ...
doc_29936
Returns the information about the current DataLoader iterator worker process. When called in a worker, this returns an object guaranteed to have the following attributes: id: the current worker id. num_workers: the total number of workers. seed: the random seed set for the current worker. This value is determined...
doc_29937
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_29938
Out-of-place version of torch.Tensor.scatter_add_()
doc_29939
Encapsulate an XML error or warning. This class can contain basic error or warning information from either the XML parser or the application: it can be subclassed to provide additional functionality or to add localization. Note that although the handlers defined in the ErrorHandler interface receive instances of this e...
doc_29940
This is equivalent to self.log_pob(input).argmax(dim=1), but is more efficient in some cases. Parameters input (Tensor) – a minibatch of examples Returns a class with the highest probability for each example Return type output (Tensor) Shape: Input: (N,in_features)(N, \texttt{in\_features}) Output: (N)(N...
doc_29941
Hides the tab specified by tab_id. The tab will not be displayed, but the associated window remains managed by the notebook and its configuration remembered. Hidden tabs may be restored with the add() command.
doc_29942
The subdomain that the blueprint should be active for, None otherwise.
doc_29943
This method is called to handle an HTML doctype declaration (e.g. <!DOCTYPE html>). The decl parameter will be the entire contents of the declaration inside the <!...> markup (e.g. 'DOCTYPE html').
doc_29944
Instances of autocast serve as context managers or decorators that allow regions of your script to run in mixed precision. In these regions, CUDA ops run in an op-specific dtype chosen by autocast to improve performance while maintaining accuracy. See the Autocast Op Reference for details. When entering an autocast-e...
doc_29945
tf.distribute.OneDeviceStrategy( device ) Using this strategy will place any variables created in its scope on the specified device. Input distributed through this strategy will be prefetched to the specified device. Moreover, any functions called via strategy.run will also be placed on the specified device as wel...
doc_29946
Create a kqueue object from a given file descriptor.
doc_29947
Set the artist offset transform. Parameters transOffsetTransform
doc_29948
Applies Group Normalization over a mini-batch of inputs as described in the paper Group Normalization y=x−E[x]Var[x]+ϵ∗γ+βy = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta The input channels are separated into num_groups groups, each containing num_channels / num_groups channels. Th...
doc_29949
Applies fit_predict of last step in pipeline after transforms. Applies fit_transforms of a pipeline to the data, followed by the fit_predict method of the final estimator in the pipeline. Valid only if the final estimator implements fit_predict. Parameters Xiterable Training data. Must fulfill input requirement...
doc_29950
See Migration guide for more details. tf.compat.v1.raw_ops.PartitionedCall tf.raw_ops.PartitionedCall( args, Tout, f, config='', config_proto='', executor_type='', name=None ) Args args A list of Tensor objects. A list of input tensors. Tout A list of tf.DTypes. A list of output types. f ...
doc_29951
Return a list of (width, height, descent) tuples for ticklabels. Empty labels are left out.
doc_29952
Initializes the default distributed process group, and this will also initialize the distributed package. There are 2 main ways to initialize a process group: Specify store, rank, and world_size explicitly. Specify init_method (a URL string) which indicates where/how to discover peers. Optionally specify rank and ...
doc_29953
Acts just like HttpResponse but uses a 403 status code.
doc_29954
Close all file descriptors from fd_low (inclusive) to fd_high (exclusive), ignoring errors. Equivalent to (but much faster than): for fd in range(fd_low, fd_high): try: os.close(fd) except OSError: pass
doc_29955
Called when the test case test raises an unexpected exception. err is a tuple of the form returned by sys.exc_info(): (type, value, traceback). The default implementation appends a tuple (test, formatted_err) to the instance’s errors attribute, where formatted_err is a formatted traceback derived from err.
doc_29956
tf.compat.v1.train.polynomial_decay( learning_rate, global_step, decay_steps, end_learning_rate=0.0001, power=1.0, cycle=False, name=None ) It is commonly observed that a monotonically decreasing learning rate, whose degree of change is carefully chosen, results in a better performing model. This function appl...
doc_29957
Creates a collation with the specified name and callable. The callable will be passed two string arguments. It should return -1 if the first is ordered lower than the second, 0 if they are ordered equal and 1 if the first is ordered higher than the second. Note that this controls sorting (ORDER BY in SQL) so your compa...
doc_29958
Classifier implementing the k-nearest neighbors vote. Read more in the User Guide. Parameters n_neighborsint, default=5 Number of neighbors to use by default for kneighbors queries. weights{‘uniform’, ‘distance’} or callable, default=’uniform’ weight function used in prediction. Possible values: ‘uniform’ ...
doc_29959
ctypes interface Returns interfacenamedtuple Named tuple containing ctypes wrapper state_address - Memory address of the state struct state - pointer to the state struct next_uint64 - function pointer to produce 64 bit integers next_uint32 - function pointer to produce 32 bit integers next_double - function po...
doc_29960
tf.compat.v1.train.slice_input_producer( tensor_list, num_epochs=None, shuffle=True, seed=None, capacity=32, shared_name=None, name=None ) Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by tf.data. Use tf.d...
doc_29961
Represents the C PyObject * datatype. Calling this without an argument creates a NULL PyObject * pointer.
doc_29962
Sets the elements of the color update(r, g, b) -> None update(r, g, b, a=255) -> None update(color_value) -> None Sets the elements of the color. See parameters for pygame.Color() for the parameters of this function. If the alpha value was not set it will not change. New in pygame 2.0.1.
doc_29963
Sets a new string as response. The value must be a string or bytes. If a string is set it’s encoded to the charset of the response (utf-8 by default). Changelog New in version 0.9. Parameters value (Union[bytes, str]) – Return type None
doc_29964
Set the offsets for the collection. Parameters offsets(N, 2) or (2,) array-like
doc_29965
See Migration guide for more details. tf.compat.v1.estimator.export.RegressionOutput tf.estimator.export.RegressionOutput( value ) Args value a float Tensor giving the predicted values. Required. Raises ValueError if the value is not a Tensor with dtype tf.float32. Attributes value...
doc_29966
The file may not be changed.
doc_29967
Return a list of all available group entries, in arbitrary order.
doc_29968
Alias for get_horizontalalignment.
doc_29969
Set multiple properties at once. Supported properties are Property Description agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alpha float or 2D array-like or None animated bool array unknown clim (vmin: float, vmax: float) clip_box Bbox...
doc_29970
operator.__getitem__(a, b) Return the value of a at index b.
doc_29971
Returns the message ID for the record. If you are using your own messages, you could do this by having the msg passed to the logger being an ID rather than a format string. Then, in here, you could use a dictionary lookup to get the message ID. This version returns 1, which is the base message ID in win32service.pyd.
doc_29972
Detect all offsets in the raw compiled bytecode string code which are jump targets, and return a list of these offsets.
doc_29973
The last colorbar associated with this ScalarMappable. May be None.
doc_29974
For each element, return the lowest index in the string where substring sub is found. See also char.find
doc_29975
The code object is optimized, using fast locals.
doc_29976
type_comment is an optional string with the type annotation as a comment
doc_29977
Fills the tensor with numbers drawn from the Cauchy distribution: f(x)=1πσ(x−median)2+σ2f(x) = \dfrac{1}{\pi} \dfrac{\sigma}{(x - \text{median})^2 + \sigma^2}
doc_29978
Get data and node arrays. Returns arrays: tuple of array Arrays for storing tree data, index, node data and node bounds.
doc_29979
Disconnect all events created by this widget.
doc_29980
Open a new element. Attributes can be given as keyword arguments, or as a string/string dictionary. The method returns an opaque identifier that can be passed to the close() method, to close all open elements up to and including this one. Parameters tag Element tag. attrib Attribute dictionary. Alternatively, a...
doc_29981
A compiled regular expression used to parse section headers. The default matches [section] to the name "section". Whitespace is considered part of the section name, thus [  larch  ] will be read as a section of name "  larch  ". Override this attribute if that’s unsuitable. For example: >>> import re >>> config = """ ....
doc_29982
True if this transform has a corresponding inverse transform.
doc_29983
The day of the datetime. Examples >>> datetime_series = pd.Series( ... pd.date_range("2000-01-01", periods=3, freq="D") ... ) >>> datetime_series 0 2000-01-01 1 2000-01-02 2 2000-01-03 dtype: datetime64[ns] >>> datetime_series.dt.day 0 1 1 2 2 3 dtype: int64
doc_29984
class sklearn.ensemble.VotingRegressor(estimators, *, weights=None, n_jobs=None, verbose=False) [source] Prediction voting regressor for unfitted estimators. A voting regressor is an ensemble meta-estimator that fits several base regressors, each on the whole dataset. Then it averages the individual predictions to fo...
doc_29985
Reserved for Microsoft compatibility.
doc_29986
Move cursor to (new_y, new_x).
doc_29987
Return True if the argument is either positive or negative infinity and False otherwise.
doc_29988
Autoscale the view limits using the data limits. Parameters tightbool or None If True, only expand the axis limits using the margins. Note that unlike for autoscale, tight=True does not set the margins to zero. If False and rcParams["axes.autolimit_mode"] (default: 'data') is 'round_numbers', then after expansi...
doc_29989
Extracts sliding local blocks from a batched input tensor. Consider a batched input tensor of shape (N,C,∗)(N, C, *) , where NN is the batch dimension, CC is the channel dimension, and ∗* represent arbitrary spatial dimensions. This operation flattens each sliding kernel_size-sized block within the spatial dimensi...
doc_29990
Return HTML version of exception report. Used for HTML version of debug 500 HTTP error page.
doc_29991
In-place version of tan()
doc_29992
Returns whether the kernel is stationary.
doc_29993
Returns a view of the array with axes transposed. For a 1-D array this has no effect, as a transposed vector is simply the same vector. To convert a 1-D array into a 2D column vector, an additional dimension must be added. np.atleast2d(a).T achieves this, as does a[:, np.newaxis]. For a 2-D array, this is a standard ...
doc_29994
Return the url.
doc_29995
Simply handles the multiplication between the parameter being pruned and the generated mask. Fetches the mask and the original tensor from the module and returns the pruned version of the tensor. Parameters module (nn.Module) – module containing the tensor to prune Returns pruned version of the input tensor Return...
doc_29996
See Migration guide for more details. tf.compat.v1.config.optimizer.get_experimental_options tf.config.optimizer.get_experimental_options() Refer to tf.config.optimizer.set_experimental_options for a list of current options. Note that optimizations are only applied in graph mode, (within tf.function). In addition, a...
doc_29997
Axes(fig, rect, *[, facecolor, frameon, ...]) Build an Axes in a figure. SimpleAxisArtist(axis, axisnum, spine) SimpleChainedObjects(objects)
doc_29998
Returns the element-wise remainder of division. This is the NumPy implementation of the C library function fmod, the remainder has the same sign as the dividend x1. It is equivalent to the Matlab(TM) rem function and should not be confused with the Python modulus operator x1 % x2. Parameters x1array_like Divide...
doc_29999
Bases: matplotlib.transforms.Affine2DBase The affine part of the polar projection. Scales the output so that maximum radius rests on the edge of the axes circle. limits is the view limit of the data. The only part of its bounds that is used is the y limits (for the radius limits). The theta range is handled by the no...