_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
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|---|---|---|
doc_14300 | See Migration guide for more details. tf.compat.v1.raw_ops.RegexFullMatch
tf.raw_ops.RegexFullMatch(
input, pattern, name=None
)
The input is a string tensor of any shape. The pattern is a scalar string tensor which is applied to every element of the input tensor. The boolean values (True or False) of the output... | |
doc_14301 |
Return self<=value. | |
doc_14302 |
Check whether an array-like or dtype is of the timedelta64 dtype. Parameters
arr_or_dtype:array-like or dtype
The array-like or dtype to check. Returns
boolean
Whether or not the array-like or dtype is of the timedelta64 dtype. Examples
>>> is_timedelta64_dtype(object)
False
>>> is_timedelta64_dtype(... | |
doc_14303 |
Return a where condition is True. If condition is a MaskedArray, missing values are considered as False. Parameters
conditionvar
Boolean 1-d array selecting which entries to return. If len(condition) is less than the size of a along the axis, then output is truncated to length of condition array.
axis{None, i... | |
doc_14304 | Decodes the netloc part into a string. Return type
str | |
doc_14305 | sklearn.manifold.trustworthiness(X, X_embedded, *, n_neighbors=5, metric='euclidean') [source]
Expresses to what extent the local structure is retained. The trustworthiness is within [0, 1]. It is defined as \[T(k) = 1 - \frac{2}{nk (2n - 3k - 1)} \sum^n_{i=1} \sum_{j \in \mathcal{N}_{i}^{k}} \max(0, (r(i, j) - k))\... | |
doc_14306 | Applies 2D average-pooling operation in kH×kWkH \times kW regions by step size sH×sWsH \times sW steps. The number of output features is equal to the number of input planes. See AvgPool2d for details and output shape. Parameters
input – input tensor (minibatch,in_channels,iH,iW)(\text{minibatch} , \text{in\_chann... | |
doc_14307 |
Transformer mixin that performs feature selection given a support mask This mixin provides a feature selector implementation with transform and inverse_transform functionality given an implementation of _get_support_mask. Methods
fit_transform(X[, y]) Fit to data, then transform it.
get_support([indices]) Get a m... | |
doc_14308 | tf.compat.v1.estimator.inputs.numpy_input_fn(
x, y=None, batch_size=128, num_epochs=1, shuffle=None, queue_capacity=1000,
num_threads=1
)
This returns a function outputting features and targets based on the dict of numpy arrays. The dict features has the same keys as the x. The dict targets has the same keys a... | |
doc_14309 | See torch.rot90() | |
doc_14310 | Registers a type-specific method called by assertEqual() to check if two objects of exactly the same typeobj (not subclasses) compare equal. function must take two positional arguments and a third msg=None keyword argument just as assertEqual() does. It must raise self.failureException(msg) when inequality between the ... | |
doc_14311 | Return all Nodes that are inputs to this Node. This is equivalent to iterating over args and kwargs and only collecting the values that are Nodes. Returns
List of Nodes that appear in the args and kwargs of this Node, in that order. | |
doc_14312 |
Stack of estimators with a final regressor. Stacked generalization consists in stacking the output of individual estimator and use a regressor to compute the final prediction. Stacking allows to use the strength of each individual estimator by using their output as input of a final estimator. Note that estimators_ ar... | |
doc_14313 |
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour. | |
doc_14314 | Guess the extension for a file based on its MIME type, given by type. The return value is a string giving a filename extension, including the leading dot ('.'). The extension is not guaranteed to have been associated with any particular data stream, but would be mapped to the MIME type type by guess_type(). If no exten... | |
doc_14315 |
Fit X into an embedded space and return that transformed output. Parameters
Xndarray of shape (n_samples, n_features) or (n_samples, n_samples)
If the metric is ‘precomputed’ X must be a square distance matrix. Otherwise it contains a sample per row. If the method is ‘exact’, X may be a sparse matrix of type ‘c... | |
doc_14316 |
Get a list of available MovieWriters. | |
doc_14317 |
The Axes instance the artist resides in, or None. | |
doc_14318 | Tests if each element of input is negative infinity or not. Parameters
input (Tensor) – the input tensor. Keyword Arguments
out (Tensor, optional) – the output tensor. Example::
>>> a = torch.tensor([-float('inf'), float('inf'), 1.2])
>>> torch.isneginf(a)
tensor([ True, False, False]) | |
doc_14319 | See Migration guide for more details. tf.compat.v1.keras.layers.Dense
tf.keras.layers.Dense(
units, activation=None, use_bias=True,
kernel_initializer='glorot_uniform',
bias_initializer='zeros', kernel_regularizer=None,
bias_regularizer=None, activity_regularizer=None, kernel_constraint=None,
bias... | |
doc_14320 | tf.keras.layers.AvgPool1D Compat aliases for migration See Migration guide for more details. tf.compat.v1.keras.layers.AveragePooling1D, tf.compat.v1.keras.layers.AvgPool1D
tf.keras.layers.AveragePooling1D(
pool_size=2, strides=None, padding='valid',
data_format='channels_last', **kwargs
)
Arguments
p... | |
doc_14321 | Dictionary mapping filename extensions to encoding types. This is initially a copy of the global encodings_map defined in the module. | |
doc_14322 |
Set 3D z limits. See matplotlib.axes.Axes.set_ylim() for full documentation | |
doc_14323 | Returns a tensor of random numbers drawn from separate normal distributions whose mean and standard deviation are given. The mean is a tensor with the mean of each output element’s normal distribution The std is a tensor with the standard deviation of each output element’s normal distribution The shapes of mean and std... | |
doc_14324 | Get the hardware address as a 48-bit positive integer. The first time this runs, it may launch a separate program, which could be quite slow. If all attempts to obtain the hardware address fail, we choose a random 48-bit number with the multicast bit (least significant bit of the first octet) set to 1 as recommended in... | |
doc_14325 | Undo (repeatedly) the last turtle action(s). Number of available undo actions is determined by the size of the undobuffer. >>> for i in range(4):
... turtle.fd(50); turtle.lt(80)
...
>>> for i in range(8):
... turtle.undo() | |
doc_14326 |
alias of matplotlib._api.deprecation.MatplotlibDeprecationWarning | |
doc_14327 |
Return if the index is monotonic increasing (only equal or increasing) values. Examples
>>> Index([1, 2, 3]).is_monotonic_increasing
True
>>> Index([1, 2, 2]).is_monotonic_increasing
True
>>> Index([1, 3, 2]).is_monotonic_increasing
False | |
doc_14328 | Assert the mock has ever been awaited with the specified arguments. >>> mock = AsyncMock()
>>> async def main(*args, **kwargs):
... await mock(*args, **kwargs)
...
>>> asyncio.run(main('foo', bar='bar'))
>>> asyncio.run(main('hello'))
>>> mock.assert_any_await('foo', bar='bar')
>>> mock.assert_any_await('other')
Tr... | |
doc_14329 |
Stack of estimators with a final classifier. Stacked generalization consists in stacking the output of individual estimator and use a classifier to compute the final prediction. Stacking allows to use the strength of each individual estimator by using their output as input of a final estimator. Note that estimators_ ... | |
doc_14330 | Raised when a Unicode-related error occurs during translating. It is a subclass of UnicodeError. | |
doc_14331 | Marks the user as having no password set. This isn’t the same as having a blank string for a password. check_password() for this user will never return True. Doesn’t save the User object. You may need this if authentication for your application takes place against an existing external source such as an LDAP directory. | |
doc_14332 |
Makes an animation by repeatedly calling a function func. Note You must store the created Animation in a variable that lives as long as the animation should run. Otherwise, the Animation object will be garbage-collected and the animation stops. Parameters
figFigure
The figure object used to get needed events,... | |
doc_14333 |
Helper class for measuring execution time of PyTorch statements. For a full tutorial on how to use this class, see: https://pytorch.org/tutorials/recipes/recipes/benchmark.html The PyTorch Timer is based on timeit.Timer (and in fact uses timeit.Timer internally), but with several key differences:
Runtime aware:
T... | |
doc_14334 | tf.nn.conv3d_transpose(
input, filters, output_shape, strides, padding='SAME',
data_format='NDHWC', dilations=None, name=None
)
This operation is sometimes called "deconvolution" after (Zeiler et al., 2010), but is really the transpose (gradient) of conv3d rather than an actual deconvolution.
Args
input... | |
doc_14335 | tf.compat.v1.fixed_size_partitioner(
num_shards, axis=0
)
Args
num_shards int, number of shards to partition variable.
axis int, axis to partition on.
Returns A partition function usable as the partitioner argument to variable_scope and get_variable. | |
doc_14336 | Return the underlying asyncio transport. | |
doc_14337 |
Return whether units are set on any axis. | |
doc_14338 | Returns a response object (a WSGI application) that, if called, redirects the client to the target location. Supported codes are 301, 302, 303, 305, 307, and 308. 300 is not supported because it’s not a real redirect and 304 because it’s the answer for a request with a request with defined If-Modified-Since headers. C... | |
doc_14339 | Encode the string s according to RFC 2231. Optional charset and language, if given is the character set name and language name to use. If neither is given, s is returned as-is. If charset is given but language is not, the string is encoded using the empty string for language. | |
doc_14340 | Performs a batch matrix-matrix product of matrices stored in input and mat2. input and mat2 must be 3-D tensors each containing the same number of matrices. If input is a (b×n×m)(b \times n \times m) tensor, mat2 is a (b×m×p)(b \times m \times p) tensor, out will be a (b×n×p)(b \times n \times p) tensor. outi=input... | |
doc_14341 |
Normalize, rescale, and colormap this image's data for rendering using renderer, with the given magnification. If unsampled is True, the image will not be scaled, but an appropriate affine transformation will be returned instead. Returns
image(M, N, 4) uint8 array
The RGBA image, resampled unless unsampled is T... | |
doc_14342 |
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_14343 | See Migration guide for more details. tf.compat.v1.raw_ops.OptionalGetValue
tf.raw_ops.OptionalGetValue(
optional, output_types, output_shapes, name=None
)
Args
optional A Tensor of type variant.
output_types A list of tf.DTypes that has length >= 1.
output_shapes A list of shapes (each a tf... | |
doc_14344 | draw a horizontal line hline(surface, x1, x2, y, color) -> None Draws a straight horizontal line ((x1, y) to (x2, y)) on the given surface. There are no endcaps.
Parameters:
surface (Surface) -- surface to draw on
x1 (int) -- x coordinate of one end of the line
x2 (int) -- x coordinate of the other end of t... | |
doc_14345 | An Executor subclass that executes calls asynchronously using a pool of at most max_workers processes. If max_workers is None or not given, it will default to the number of processors on the machine. If max_workers is less than or equal to 0, then a ValueError will be raised. On Windows, max_workers must be less than o... | |
doc_14346 | Casts this storage to complex float type | |
doc_14347 | See Migration guide for more details. tf.compat.v1.raw_ops.SleepDataset
tf.raw_ops.SleepDataset(
input_dataset, sleep_microseconds, output_types, output_shapes, name=None
)
Args
input_dataset A Tensor of type variant.
sleep_microseconds A Tensor of type int64.
output_types A list of tf.DType... | |
doc_14348 |
Set the units for axis. Parameters
uunits tag
Notes The units of any shared axis will also be updated.
Examples using matplotlib.axis.Axis.set_units
Artist tests
Group barchart with units
Unit handling | |
doc_14349 | Works like BytesFeedParser except that the input to the feed() method must be a string. This is of limited utility, since the only way for such a message to be valid is for it to contain only ASCII text or, if utf8 is True, no binary attachments. Changed in version 3.3: Added the policy keyword. | |
doc_14350 | Set the chunk’s current position. The whence argument is optional and defaults to 0 (absolute file positioning); other values are 1 (seek relative to the current position) and 2 (seek relative to the file’s end). There is no return value. If the underlying file does not allow seek, only forward seeks are allowed. | |
doc_14351 | assertRaises(exception, *, msg=None)
Test that an exception is raised when callable is called with any positional or keyword arguments that are also passed to assertRaises(). The test passes if exception is raised, is an error if another exception is raised, or fails if no exception is raised. To catch any of a group... | |
doc_14352 |
Set the figure size in inches. Call signatures: fig.set_size_inches(w, h) # OR
fig.set_size_inches((w, h))
Parameters
w(float, float) or float
Width and height in inches (if height not specified as a separate argument) or width.
hfloat
Height in inches.
forwardbool, default: True
If True, the canvas s... | |
doc_14353 |
Return a flattened array. Refer to numpy.ravel for full documentation. See also numpy.ravel
equivalent function ndarray.flat
a flat iterator on the array. | |
doc_14354 |
Create a two-dimensional array with the flattened input as a diagonal. Parameters
varray_like
Input data, which is flattened and set as the k-th diagonal of the output.
kint, optional
Diagonal to set; 0, the default, corresponds to the “main” diagonal, a positive (negative) k giving the number of the diagon... | |
doc_14355 |
Reconstruct an event from an IPC handle on the given device. | |
doc_14356 | Decode bytes-like object or ASCII string s using the standard Base64 alphabet and return the decoded bytes. | |
doc_14357 |
[Deprecated] Notes Deprecated since version 3.4: | |
doc_14358 | Sets new limits of consumption of resource. The limits argument must be a tuple (soft, hard) of two integers describing the new limits. A value of RLIM_INFINITY can be used to request a limit that is unlimited. Raises ValueError if an invalid resource is specified, if the new soft limit exceeds the hard limit, or if a ... | |
doc_14359 |
Compute numerical data ranks (1 through n) along axis. By default, equal values are assigned a rank that is the average of the ranks of those values. Parameters
axis:{0 or ‘index’, 1 or ‘columns’}, default 0
Index to direct ranking.
method:{‘average’, ‘min’, ‘max’, ‘first’, ‘dense’}, default ‘average’
How t... | |
doc_14360 | Called when a subtest finishes. test is the test case corresponding to the test method. subtest is a custom TestCase instance describing the subtest. If outcome is None, the subtest succeeded. Otherwise, it failed with an exception where outcome is a tuple of the form returned by sys.exc_info(): (type, value, traceback... | |
doc_14361 |
Set the colormap for luminance data. Parameters
cmapColormap or str or None | |
doc_14362 | See Migration guide for more details. tf.compat.v1.raw_ops.SegmentMax
tf.raw_ops.SegmentMax(
data, segment_ids, name=None
)
Read the section on segmentation for an explanation of segments. Computes a tensor such that \(output_i = \max_j(data_j)\) where max is over j such that segment_ids[j] == i. If the max is e... | |
doc_14363 | The date in parsed format or None. | |
doc_14364 | Assign a Python function or another callable to this attribute. The callable will be called with three or more arguments:
callable(result, func, arguments)
result is what the foreign function returns, as specified by the restype attribute. func is the foreign function object itself, this allows reusing the same cal... | |
doc_14365 | In [0, 1]. Used to disambiguate wall times during a repeated interval. (A repeated interval occurs when clocks are rolled back at the end of daylight saving time or when the UTC offset for the current zone is decreased for political reasons.) The value 0 (1) represents the earlier (later) of the two moments with the sa... | |
doc_14366 |
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
clip_box Bbox
clip_on bool
clip_path Patch or (Path, Transform) or None
f... | |
doc_14367 | See Migration guide for more details. tf.compat.v1.signal.rfft, tf.compat.v1.spectral.rfft
tf.signal.rfft(
input_tensor, fft_length=None, name=None
)
Computes the 1-dimensional discrete Fourier transform of a real-valued signal over the inner-most dimension of input. Since the DFT of a real signal is Hermitian-s... | |
doc_14368 | Returns the shape of a single sample (without batching). | |
doc_14369 | sklearn.metrics.cohen_kappa_score(y1, y2, *, labels=None, weights=None, sample_weight=None) [source]
Cohen’s kappa: a statistic that measures inter-annotator agreement. This function computes Cohen’s kappa [1], a score that expresses the level of agreement between two annotators on a classification problem. It is def... | |
doc_14370 |
Create a pseudocolor plot with a non-regular rectangular grid. Call signature: pcolormesh([X, Y,] C, **kwargs)
X and Y can be used to specify the corners of the quadrilaterals. Hint pcolormesh is similar to pcolor. It is much faster and preferred in most cases. For a detailed discussion on the differences see Diffe... | |
doc_14371 |
Transform data back to its original space. Parameters
Xarray-like of shape (n_samples, n_components)
New data, where n_samples is the number of samples and n_components is the number of pls components. Returns
x_reconstructedarray-like of shape (n_samples, n_features)
Notes This transformation will on... | |
doc_14372 | Returns True if there’s a next or previous page. | |
doc_14373 |
Return index and pixel distance to closest handle. Parameters
x, yfloat
x, y position from which the distance will be calculated to determinate the closest handle Returns
index, distanceindex of the handle and its distance from
position x, y | |
doc_14374 | Pass the barrier. When all the threads party to the barrier have called this function, they are all released simultaneously. If a timeout is provided, it is used in preference to any that was supplied to the class constructor. The return value is an integer in the range 0 to parties – 1, different for each thread. This... | |
doc_14375 |
Return Series of codes as well as the index. | |
doc_14376 | Read and return all the bytes from the stream until EOF, using multiple calls to the stream if necessary. | |
doc_14377 |
Compute the anomalies (deviations from the arithmetic mean) along the given axis. Returns an array of anomalies, with the same shape as the input and where the arithmetic mean is computed along the given axis. Parameters
axisint, optional
Axis over which the anomalies are taken. The default is to use the mean o... | |
doc_14378 | Push panel to the top of the stack. | |
doc_14379 |
Total seconds in the duration. | |
doc_14380 | Read bytes into a pre-allocated, writable bytes-like object b, and return the number of bytes read. For example, b might be a bytearray. If the object is in non-blocking mode and no bytes are available, None is returned. | |
doc_14381 |
Return a fixed frequency TimedeltaIndex, with day as the default frequency. Parameters
start:str or timedelta-like, default None
Left bound for generating timedeltas.
end:str or timedelta-like, default None
Right bound for generating timedeltas.
periods:int, default None
Number of periods to generate. ... | |
doc_14382 | Optional The value for the year, as a string. By default, set to None, which means the year will be determined using other means. | |
doc_14383 |
Autoscale the scalar limits on the norm instance using the current array | |
doc_14384 |
Create a Fixed unit when the first argument is a float, or a Fraction unit if that is a string that ends with %. The second argument is only meaningful when Fraction unit is created. >>> a = Size.from_any(1.2) # => Size.Fixed(1.2)
>>> Size.from_any("50%", a) # => Size.Fraction(0.5, a) | |
doc_14385 | alias of flask.config.Config | |
doc_14386 | This class is an abstraction of a URL request. url should be a string containing a valid URL. data must be an object specifying additional data to send to the server, or None if no such data is needed. Currently HTTP requests are the only ones that use data. The supported object types include bytes, file-like objects, ... | |
doc_14387 |
[Deprecated] Return the title text of the window containing the figure, or None if there is no window (e.g., a PS backend). Notes Deprecated since version 3.4. | |
doc_14388 |
Vectorized string functions for Series and Index. NAs stay NA unless handled otherwise by a particular method. Patterned after Python’s string methods, with some inspiration from R’s stringr package. Examples
>>> s = pd.Series(["A_Str_Series"])
>>> s
0 A_Str_Series
dtype: object
>>> s.str.split("_")
0 [A, S... | |
doc_14389 |
Return the mean accuracy on the given test data and labels. In multi-label classification, this is the subset accuracy which is a harsh metric since you require for each sample that each label set be correctly predicted. Parameters
Xarray-like of shape (n_samples, n_features)
Test samples.
yarray-like of shap... | |
doc_14390 |
Alias for get_facecolor. | |
doc_14391 | This function returns eigenvalues and eigenvectors of a real symmetric matrix input or a batch of real symmetric matrices, represented by a namedtuple (eigenvalues, eigenvectors). This function calculates all eigenvalues (and vectors) of input such that input=Vdiag(e)VT\text{input} = V \text{diag}(e) V^T . The boolean ... | |
doc_14392 | Update the values in the config from a file that is loaded using the load parameter. The loaded data is passed to the from_mapping() method. import toml
app.config.from_file("config.toml", load=toml.load)
Parameters
filename (str) – The path to the data file. This can be an absolute path or relative to the config ... | |
doc_14393 | Return the number of audio channels (1 for mono, 2 for stereo). | |
doc_14394 | This has a different meaning for each node type; see the DOM specification for details. The situation is similar to that with nodeName. The value is a string or None. | |
doc_14395 |
Return the current print options. Returns
print_optsdict
Dictionary of current print options with keys precision : int threshold : int edgeitems : int linewidth : int suppress : bool nanstr : str infstr : str formatter : dict of callables sign : str For a full description of these options, see set_printoption... | |
doc_14396 | sklearn.metrics.max_error(y_true, y_pred) [source]
max_error metric calculates the maximum residual error. Read more in the User Guide. Parameters
y_truearray-like of shape (n_samples,)
Ground truth (correct) target values.
y_predarray-like of shape (n_samples,)
Estimated target values. Returns
max_er... | |
doc_14397 |
Return whether the artist is pickable. See also
set_picker, get_picker, pick | |
doc_14398 |
Return whether the artist is to be rasterized. | |
doc_14399 |
Draw samples from a Pareto II or Lomax distribution with specified shape. The Lomax or Pareto II distribution is a shifted Pareto distribution. The classical Pareto distribution can be obtained from the Lomax distribution by adding 1 and multiplying by the scale parameter m (see Notes). The smallest value of the Loma... |
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