_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_13300 | play the original aliens example oldalien.main() -> None This more closely resembles a port of the SDL Aliens demo. The code is a lot simpler, so it makes a better starting point for people looking at code for the first times. These blitting routines are not as optimized as they should/could be, but the code is easie... | |
doc_13301 |
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. | |
doc_13302 | If session.permanent is true, the cookie’s expiration will be set this number of seconds in the future. Can either be a datetime.timedelta or an int. Flask’s default cookie implementation validates that the cryptographic signature is not older than this value. Default: timedelta(days=31) (2678400 seconds) | |
doc_13303 | Read up to len bytes of data from the SSL socket and return the result as a bytes instance. If buffer is specified, then read into the buffer instead, and return the number of bytes read. Raise SSLWantReadError or SSLWantWriteError if the socket is non-blocking and the read would block. As at any time a re-negotiation ... | |
doc_13304 | tf.compat.v1.data.experimental.TensorStructure(
dtype, shape
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.TensorSpec instead. | |
doc_13305 | Sums start and the items of an iterable from left to right and returns the total. The iterable’s items are normally numbers, and the start value is not allowed to be a string. For some use cases, there are good alternatives to sum(). The preferred, fast way to concatenate a sequence of strings is by calling ''.join(seq... | |
doc_13306 | get the line space of the font text get_linesize() -> int Return the height in pixels for a line of text with the font. When rendering multiple lines of text this is the recommended amount of space between lines. | |
doc_13307 |
Set the (group) id for the artist. Parameters
gidstr | |
doc_13308 | Asserts that the template with the given name was used in rendering the response. response must be a response instance returned by the test client. template_name should be a string such as 'admin/index.html'. The count argument is an integer indicating the number of times the template should be rendered. Default is Non... | |
doc_13309 | sklearn.utils.multiclass.unique_labels(*ys) [source]
Extract an ordered array of unique labels. We don’t allow:
mix of multilabel and multiclass (single label) targets mix of label indicator matrix and anything else, because there are no explicit labels) mix of label indicator matrices of different sizes mix of st... | |
doc_13310 | See Migration guide for more details. tf.compat.v1.raw_ops.LMDBReader
tf.raw_ops.LMDBReader(
container='', shared_name='', name=None
)
Args
container An optional string. Defaults to "". If non-empty, this reader is placed in the given container. Otherwise, a default container is used.
shared_name ... | |
doc_13311 | Limits valid inputs to the specified protocol. Accepted values are both (default), IPv4 or IPv6. Matching is case insensitive. | |
doc_13312 | Returns a signer which uses key to generate signatures and sep to separate values. sep cannot be in the URL safe base64 alphabet. This alphabet contains alphanumeric characters, hyphens, and underscores. algorithm must be an algorithm supported by hashlib, it defaults to 'sha256'. | |
doc_13313 |
Turn the x- and y-axis on. This affects the axis lines, ticks, ticklabels, grid and axis labels. | |
doc_13314 | tf.test.assert_equal_graph_def(
expected, actual
)
Compares two GraphDef protos for equality, ignoring versions and ordering of nodes, attrs, and control inputs. Node names are used to match up nodes between the graphs, so the naming of nodes must be consistent. This function ignores randomized attribute values th... | |
doc_13315 | fft(a[, n, axis, norm]) Compute the one-dimensional discrete Fourier Transform.
ifft(a[, n, axis, norm]) Compute the one-dimensional inverse discrete Fourier Transform.
fft2(a[, s, axes, norm]) Compute the 2-dimensional discrete Fourier Transform.
ifft2(a[, s, axes, norm]) Compute the 2-dimensional inverse discre... | |
doc_13316 |
Convert x using the unit type of the xaxis. If the artist is not in contained in an Axes or if the xaxis does not have units, x itself is returned. | |
doc_13317 | Alias for torch.trunc() | |
doc_13318 | This function returns the solution to the system of linear equations represented by AX=BAX = B and the LU factorization of A, in order as a namedtuple solution, LU. LU contains L and U factors for LU factorization of A. torch.solve(B, A) can take in 2D inputs B, A or inputs that are batches of 2D matrices. If the inpu... | |
doc_13319 | Copy the permission bits, last access time, last modification time, and flags from src to dst. On Linux, copystat() also copies the “extended attributes” where possible. The file contents, owner, and group are unaffected. src and dst are path-like objects or path names given as strings. If follow_symlinks is false, and... | |
doc_13320 |
Return a backend-specific tuple to return to the backend after all processing is done. | |
doc_13321 | Limit on the number of characters in the representation of the string. Note that the “normal” representation of the string is used as the character source: if escape sequences are needed in the representation, these may be mangled when the representation is shortened. The default is 30. | |
doc_13322 | See Migration guide for more details. tf.compat.v1.raw_ops.StringSplit
tf.raw_ops.StringSplit(
input, delimiter, skip_empty=True, name=None
)
Let N be the size of source (typically N will be the batch size). Split each element of input based on delimiter and return a SparseTensor containing the splitted tokens. ... | |
doc_13323 | sklearn.metrics.mean_gamma_deviance(y_true, y_pred, *, sample_weight=None) [source]
Mean Gamma deviance regression loss. Gamma deviance is equivalent to the Tweedie deviance with the power parameter power=2. It is invariant to scaling of the target variable, and measures relative errors. Read more in the User Guide. ... | |
doc_13324 |
Release the canvas and disconnect press/release events. | |
doc_13325 |
Fit the radius neighbors regressor from the training dataset. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features) or (n_samples, n_samples) if metric=’precomputed’
Training data.
y{array-like, sparse matrix} of shape (n_samples,) or (n_samples, n_outputs)
Target values. Returns
se... | |
doc_13326 | Close the transport immediately, without waiting for pending operations to complete. Buffered data will be lost. No more data will be received. The protocol’s protocol.connection_lost() method will eventually be called with None as its argument. | |
doc_13327 | See Migration guide for more details. tf.compat.v1.raw_ops.LearnedUnigramCandidateSampler
tf.raw_ops.LearnedUnigramCandidateSampler(
true_classes, num_true, num_sampled, unique, range_max, seed=0, seed2=0,
name=None
)
See explanations of candidate sampling and the data formats at go/candidate-sampling. For e... | |
doc_13328 | A helper class that has ABCMeta as its metaclass. With this class, an abstract base class can be created by simply deriving from ABC avoiding sometimes confusing metaclass usage, for example: from abc import ABC
class MyABC(ABC):
pass
Note that the type of ABC is still ABCMeta, therefore inheriting from ABC requi... | |
doc_13329 |
Scale back the data to the original representation Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The data used to scale along the features axis.
copybool, default=None
Copy the input X or not. Returns
X_tr{ndarray, sparse matrix} of shape (n_samples, n_features)
Transforme... | |
doc_13330 | operator.__truediv__(a, b)
Return a / b where 2/3 is .66 rather than 0. This is also known as “true” division. | |
doc_13331 | Remove (delete) the file path. This function is semantically identical to remove(); the unlink name is its traditional Unix name. Please see the documentation for remove() for further information. Raises an auditing event os.remove with arguments path, dir_fd. New in version 3.3: The dir_fd parameter. Changed in ver... | |
doc_13332 |
Element-wise minimum of array elements. Compare two arrays and returns a new array containing the element-wise minima. If one of the elements being compared is a NaN, then the non-nan element is returned. If both elements are NaNs then the first is returned. The latter distinction is important for complex NaNs, which... | |
doc_13333 |
Get the week of the year on the given Period. Returns
int
See also Period.dayofweek
Get the day component of the Period. Period.weekday
Get the day component of the Period. Examples
>>> p = pd.Period("2018-03-11", "H")
>>> p.week
10
>>> p = pd.Period("2018-02-01", "D")
>>> p.week
5
>>> p = pd.Per... | |
doc_13334 | Returns the strftime() format to use when parsing the week. Returns week_format by default. | |
doc_13335 |
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_13336 |
Return the indices of the maximum values in the specified axis ignoring NaNs. For all-NaN slices ValueError is raised. Warning: the results cannot be trusted if a slice contains only NaNs and -Infs. Parameters
aarray_like
Input data.
axisint, optional
Axis along which to operate. By default flattened input ... | |
doc_13337 |
Lewiner marching cubes algorithm to find surfaces in 3d volumetric data. In contrast to marching_cubes_classic(), this algorithm is faster, resolves ambiguities, and guarantees topologically correct results. Therefore, this algorithm generally a better choice, unless there is a specific need for the classic algorithm... | |
doc_13338 | See Migration guide for more details. tf.compat.v1.raw_ops.RetrieveTPUEmbeddingProximalYogiParameters
tf.raw_ops.RetrieveTPUEmbeddingProximalYogiParameters(
num_shards, shard_id, table_id=-1, table_name='', config='',
name=None
)
Args
num_shards An int.
shard_id An int.
table_id An optio... | |
doc_13339 |
Convenience method to set or retrieve autoscaling margins. Call signatures: margins()
returns xmargin, ymargin, zmargin margins(margin)
margins(xmargin, ymargin, zmargin)
margins(x=xmargin, y=ymargin, z=zmargin)
margins(..., tight=False)
All forms above set the xmargin, ymargin and zmargin parameters. All keywor... | |
doc_13340 |
A sequential container. Modules will be added to it in the order they are passed in the constructor. Alternatively, an ordered dict of modules can also be passed in. To make it easier to understand, here is a small example: # Example of using Sequential
model = nn.Sequential(
nn.Conv2d(1,20,5),
nn... | |
doc_13341 | See Migration guide for more details. tf.compat.v1.raw_ops.RandomShuffleQueueV2
tf.raw_ops.RandomShuffleQueueV2(
component_types, shapes=[], capacity=-1, min_after_dequeue=0, seed=0, seed2=0,
container='', shared_name='', name=None
)
Args
component_types A list of tf.DTypes that has length >= 1. The... | |
doc_13342 | See Migration guide for more details. tf.compat.v1.raw_ops.QuantizedMatMulWithBiasAndDequantize
tf.raw_ops.QuantizedMatMulWithBiasAndDequantize(
a, b, bias, min_a, max_a, min_b, max_b, min_freezed_output, max_freezed_output,
Toutput, transpose_a=False, transpose_b=False,
input_quant_mode='MIN_FIRST', name... | |
doc_13343 | Indicates if a message of severity level would be processed by this logger. This method checks first the module-level level set by logging.disable(level) and then the logger’s effective level as determined by getEffectiveLevel(). | |
doc_13344 |
Chebyshev points of the first kind. The Chebyshev points of the first kind are the points cos(x), where x = [pi*(k + .5)/npts for k in range(npts)]. Parameters
nptsint
Number of sample points desired. Returns
ptsndarray
The Chebyshev points of the first kind. See also chebpts2
Notes New in vers... | |
doc_13345 |
Convert this path to a list of polygons or polylines. Each polygon/polyline is an Nx2 array of vertices. In other words, each polygon has no MOVETO instructions or curves. This is useful for displaying in backends that do not support compound paths or Bezier curves. If width and height are both non-zero then the line... | |
doc_13346 |
Return a dictionary of all the properties of the artist. | |
doc_13347 |
Return self>=value. | |
doc_13348 | Return a string object containing two hexadecimal digits for each byte in the buffer. >>> m = memoryview(b"abc")
>>> m.hex()
'616263'
New in version 3.5. Changed in version 3.8: Similar to bytes.hex(), memoryview.hex() now supports optional sep and bytes_per_sep parameters to insert separators between bytes in the ... | |
doc_13349 | Setting this disables or force-enables the automatic options handling. | |
doc_13350 |
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_13351 |
Warning used when the metric is invalid Changed in version 0.18: Moved from sklearn.base. Attributes
args
Methods
with_traceback Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self. | |
doc_13352 |
pygame module to control the display window and screen This module offers control over the pygame display. Pygame has a single display Surface that is either contained in a window or runs full screen. Once you create the display you treat it as a regular Surface. Changes are not immediately visible onscreen; you m... | |
doc_13353 | Optional. Either a method or attribute. If it’s a method, it should take one argument – an object as returned by items() – and return that object’s last-modified date/time as a datetime. If it’s an attribute, its value should be a datetime representing the last-modified date/time for every object returned by items(). I... | |
doc_13354 | Returns the log-transformed bounds on the theta. Returns
boundsndarray of shape (n_dims, 2)
The log-transformed bounds on the kernel’s hyperparameters theta | |
doc_13355 | sklearn.cluster.cluster_optics_xi(*, reachability, predecessor, ordering, min_samples, min_cluster_size=None, xi=0.05, predecessor_correction=True) [source]
Automatically extract clusters according to the Xi-steep method. Parameters
reachabilityndarray of shape (n_samples,)
Reachability distances calculated by ... | |
doc_13356 |
Logarithm of the sum of exponentiations of the inputs. Calculates log(exp(x1) + exp(x2)). This function is useful in statistics where the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases the logarithm of the calculated probability is stored. Thi... | |
doc_13357 | Return the column number where the current event begins. | |
doc_13358 |
Return the artist's zorder. | |
doc_13359 | Abstract base class for structures in little endian byte order. | |
doc_13360 |
Used for moving to next business day. | |
doc_13361 | Returns a list of values for the given key and removes them from the dictionary. Raises KeyError if the key does not exist. For example: >>> q = QueryDict('a=1&a=2&a=3', mutable=True)
>>> q.pop('a')
['1', '2', '3'] | |
doc_13362 | See Migration guide for more details. tf.compat.v1.keras.mixed_precision.LossScaleOptimizer
tf.keras.mixed_precision.LossScaleOptimizer(
inner_optimizer, dynamic=True, initial_scale=None, dynamic_growth_steps=None
)
Loss scaling is a technique to prevent numeric underflow in intermediate gradients when float16 i... | |
doc_13363 |
Return list of grid lines as a list of paths (list of points). which : "major" or "minor" axis : "both", "x" or "y" | |
doc_13364 |
get_backoff_factor() [source]
Returns a Python float containing the scale backoff factor.
get_growth_factor() [source]
Returns a Python float containing the scale growth factor.
get_growth_interval() [source]
Returns a Python int containing the growth interval.
get_scale() [source]
Returns a Pyt... | |
doc_13365 | The Content-Security-Policy header adds an additional layer of security to help detect and mitigate certain types of attacks. | |
doc_13366 | Return an item if one is immediately available, else raise QueueEmpty. | |
doc_13367 |
Scalar method identical to the corresponding array attribute. Please see ndarray.all. | |
doc_13368 | Base class for all transports. Contains methods that all asyncio transports share. | |
doc_13369 |
Gathers tensors from the whole group in a list. Complex tensors are supported. Parameters
tensor_list (list[Tensor]) – Output list. It should contain correctly-sized tensors to be used for output of the collective.
tensor (Tensor) – Tensor to be broadcast from current process.
group (ProcessGroup, optional) – T... | |
doc_13370 | Packs a variable length list of homogeneous items. First, the length of the list is packed as an unsigned integer, then each element is packed as in pack_farray() above. | |
doc_13371 | Returns the expression ready to be sorted in descending order. nulls_first and nulls_last define how null values are sorted. See Using F() to sort null values for example usage. | |
doc_13372 |
Return probability estimates for the test data X. Parameters
Xarray-like of shape (n_queries, n_features), or (n_queries, n_indexed) if metric == ‘precomputed’
Test samples. Returns
pndarray of shape (n_queries, n_classes), or a list of n_outputs
of such arrays if n_outputs > 1. The class probabilities ... | |
doc_13373 |
Call self as a function. | |
doc_13374 |
Move ticks and ticklabels (if present) to the bottom of the axes.
Examples using matplotlib.axis.XAxis.tick_bottom
Broken Axis
Bachelor's degrees by gender | |
doc_13375 | See Migration guide for more details. tf.compat.v1.raw_ops.MultiDeviceIteratorFromStringHandle
tf.raw_ops.MultiDeviceIteratorFromStringHandle(
string_handle, output_types=[], output_shapes=[], name=None
)
Args
string_handle A Tensor of type string. String representing the resource.
output_types An... | |
doc_13376 |
A str subclass that has been specifically marked as “safe” (requires no further escaping) for HTML output purposes. | |
doc_13377 | The regex flags used when compiling the regular expression string regex. If regex is a pre-compiled regular expression, and flags is overridden, TypeError is raised. Defaults to 0. | |
doc_13378 | tf.compat.v1.metrics.average_precision_at_k(
labels, predictions, k, weights=None, metrics_collections=None,
updates_collections=None, name=None
)
average_precision_at_k creates two local variables, average_precision_at_<k>/total and average_precision_at_<k>/max, that are used to compute the frequency. This fr... | |
doc_13379 | See Migration guide for more details. tf.compat.v1.raw_ops.PyFunc
tf.raw_ops.PyFunc(
input, token, Tout, name=None
)
This operation is considered stateful. For a stateless version, see PyFuncStateless.
Args
input A list of Tensor objects. List of Tensors that will provide input to the Op.
token A ... | |
doc_13380 | Removes the item with the index i from the array and returns it. The optional argument defaults to -1, so that by default the last item is removed and returned. | |
doc_13381 |
Clips gradient of an iterable of parameters at specified value. Gradients are modified in-place. Parameters
parameters (Iterable[Tensor] or Tensor) – an iterable of Tensors or a single Tensor that will have gradients normalized
clip_value (float or int) – maximum allowed value of the gradients. The gradients are... | |
doc_13382 |
Default "do nothing" implementation of the process_selected method. Parameters
indlist of int
The indices of the selected vertices.
xs, ysarray-like
The coordinates of the selected vertices. | |
doc_13383 | the maximum content length. This is forwarded to the form data parsing function (parse_form_data()). When set and the form or files attribute is accessed and the parsing fails because more than the specified value is transmitted a RequestEntityTooLarge exception is raised. Have a look at Dealing with Request Data for m... | |
doc_13384 | Add another header to the request. Headers are currently ignored by all handlers except HTTP handlers, where they are added to the list of headers sent to the server. Note that there cannot be more than one header with the same name, and later calls will overwrite previous calls in case the key collides. Currently, thi... | |
doc_13385 |
Return a normalized rgba array corresponding to x. In the normal case, x is a 1D or 2D sequence of scalars, and the corresponding ndarray of rgba values will be returned, based on the norm and colormap set for this ScalarMappable. There is one special case, for handling images that are already rgb or rgba, such as mi... | |
doc_13386 | tf.experimental.numpy.int32(
*args, **kwargs
)
Character code: 'i'. Canonical name: np.intc. Alias on this platform: np.int32: 32-bit signed integer (-2147483648 to 2147483647). Methods all
all()
Not implemented (virtual attribute) Class generic exists solely to derive numpy scalars from, and possesses, albeit u... | |
doc_13387 |
Stop the current blocking event loop. Interactive backends need to reimplement this to match start_event_loop | |
doc_13388 | operator.__imatmul__(a, b)
a = imatmul(a, b) is equivalent to a @= b. New in version 3.5. | |
doc_13389 | Like gettext(), but look the message up in the specified domain. | |
doc_13390 | Creates a check constraint in the database. | |
doc_13391 | Adds a parameter to the module. The parameter can be accessed as an attribute using given name. Parameters
name (string) – name of the parameter. The parameter can be accessed from this module using the given name
param (Parameter) – parameter to be added to the module. | |
doc_13392 | tf.compat.v1.logging.info(
msg, *args, **kwargs
) | |
doc_13393 | tf.nn.softmax_cross_entropy_with_logits(
labels, logits, axis=-1, name=None
)
Measures the probability error in discrete classification tasks in which the classes are mutually exclusive (each entry is in exactly one class). For example, each CIFAR-10 image is labeled with one and only one label: an image can be a ... | |
doc_13394 | Like substitute(), except that if placeholders are missing from mapping and kwds, instead of raising a KeyError exception, the original placeholder will appear in the resulting string intact. Also, unlike with substitute(), any other appearances of the $ will simply return $ instead of raising ValueError. While other e... | |
doc_13395 | Transform an old-style comparison function to a key function. Used with tools that accept key functions (such as sorted(), min(), max(), heapq.nlargest(), heapq.nsmallest(), itertools.groupby()). This function is primarily used as a transition tool for programs being converted from Python 2 which supported the use of c... | |
doc_13396 | tf.nn.separable_conv2d(
input, depthwise_filter, pointwise_filter, strides, padding, data_format=None,
dilations=None, name=None
)
Performs a depthwise convolution that acts separately on channels followed by a pointwise convolution that mixes channels. Note that this is separability between dimensions [1, 2] ... | |
doc_13397 | Group id of the owner. | |
doc_13398 | See Migration guide for more details. tf.compat.v1.nn.atrous_conv2d_transpose
tf.nn.atrous_conv2d_transpose(
value, filters, output_shape, rate, padding, name=None
)
This operation is sometimes called "deconvolution" after (Zeiler et al., 2010), but is really the transpose (gradient) of atrous_conv2d rather than... | |
doc_13399 |
Evaluate a 3-D Chebyshev series on the Cartesian product of x, y, and z. This function returns the values: \[p(a,b,c) = \sum_{i,j,k} c_{i,j,k} * T_i(a) * T_j(b) * T_k(c)\] where the points (a, b, c) consist of all triples formed by taking a from x, b from y, and c from z. The resulting points form a grid with x in t... |
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