_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_6400 | Print a report to standard output that lists the modules imported by the script and their paths, as well as modules that are missing or seem to be missing. | |
doc_6401 | Tests that two sets are equal. If not, an error message is constructed that lists the differences between the sets. This method is used by default when comparing sets or frozensets with assertEqual(). Fails if either of first or second does not have a set.difference() method. New in version 3.1. | |
doc_6402 | Compares x and y numerically. | |
doc_6403 | tf.linalg.eye Compat aliases for migration See Migration guide for more details. tf.compat.v1.eye, tf.compat.v1.linalg.eye
tf.eye(
num_rows, num_columns=None, batch_shape=None, dtype=tf.dtypes.float32, name=None
)
See also tf.ones, tf.zeros, tf.fill, tf.one_hot. # Construct one identity matrix.
tf.eye(2)
==> [[1... | |
doc_6404 | Register a function to handle errors by code or exception class. A decorator that is used to register a function given an error code. Example: @app.errorhandler(404)
def page_not_found(error):
return 'This page does not exist', 404
You can also register handlers for arbitrary exceptions: @app.errorhandler(Database... | |
doc_6405 | os.CLD_KILLED
os.CLD_DUMPED
os.CLD_TRAPPED
os.CLD_STOPPED
os.CLD_CONTINUED
These are the possible values for si_code in the result returned by waitid(). Availability: Unix. New in version 3.3. Changed in version 3.9: Added CLD_KILLED and CLD_STOPPED values. | |
doc_6406 |
Plot y versus x as lines and/or markers with attached errorbars. x, y define the data locations, xerr, yerr define the errorbar sizes. By default, this draws the data markers/lines as well the errorbars. Use fmt='none' to draw errorbars without any data markers. Parameters
x, yfloat or array-like
The data posit... | |
doc_6407 |
Get number of parallel build jobs set by the –parallel command line argument of setup.py If the command did not receive a setting the environment variable NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of processors on the system, with a maximum of 8 (to prevent overloading the system if there a l... | |
doc_6408 |
Cast to PeriodArray/Index at a particular frequency. Converts DatetimeArray/Index to PeriodArray/Index. Parameters
freq:str or Offset, optional
One of pandas’ offset strings or an Offset object. Will be inferred by default. Returns
PeriodArray/Index
Raises
ValueError
When converting a DatetimeArray/In... | |
doc_6409 | See Migration guide for more details. tf.compat.v1.autograph.trace
tf.autograph.trace(
*args
)
trace is useful when debugging, and it always executes during the tracing phase, that is, when the TF graph is constructed. Example usage import tensorflow as tf
for i in tf.range(10):
tf.autograph.trace(i)
# Output... | |
doc_6410 | Specifies whether or not inline objects that can be changed in the admin have a link to the change form. Defaults to False. | |
doc_6411 | A callable that takes the value of the CheckboxInput and returns True if the checkbox should be checked for that value. | |
doc_6412 |
Default tools in the toolbar | |
doc_6413 |
Return an iterable of the ParameterDict values. | |
doc_6414 | Return number of entries in the undobuffer. >>> while undobufferentries():
... undo() | |
doc_6415 | Each concrete class has an attribute _fields which gives the names of all child nodes. Each instance of a concrete class has one attribute for each child node, of the type as defined in the grammar. For example, ast.BinOp instances have an attribute left of type ast.expr. If these attributes are marked as optional in t... | |
doc_6416 |
Return an int representing the number of axes / array dimensions. Return 1 if Series. Otherwise return 2 if DataFrame. See also ndarray.ndim
Number of array dimensions. Examples
>>> s = pd.Series({'a': 1, 'b': 2, 'c': 3})
>>> s.ndim
1
>>> df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
>>> df.ndim
2 | |
doc_6417 | Returns a filename based on the name parameter that’s suitable for use on the target storage system. | |
doc_6418 |
Run fit with all sets of parameters. Parameters
Xarray-like of shape (n_samples, n_features)
Training vector, where n_samples is the number of samples and n_features is the number of features.
yarray-like of shape (n_samples, n_output) or (n_samples,), default=None
Target relative to X for classification or... | |
doc_6419 | Create a new SSL context. You may pass protocol which must be one of the PROTOCOL_* constants defined in this module. The parameter specifies which version of the SSL protocol to use. Typically, the server chooses a particular protocol version, and the client must adapt to the server’s choice. Most of the versions are ... | |
doc_6420 | Returns True if the uploaded file is big enough to require reading in multiple chunks. By default this will be any file larger than 2.5 megabytes, but that’s configurable; see below. | |
doc_6421 |
Apply glob to paths and prepend local_path if needed. | |
doc_6422 |
Determine scorer from user options. A TypeError will be thrown if the estimator cannot be scored. Parameters
estimatorestimator object implementing ‘fit’
The object to use to fit the data.
scoringstr or callable, default=None
A string (see model evaluation documentation) or a scorer callable object / functi... | |
doc_6423 | In-place version of ge(). | |
doc_6424 |
Creates a criterion that uses a squared term if the absolute element-wise error falls below beta and an L1 term otherwise. It is less sensitive to outliers than the torch.nn.MSELoss and in some cases prevents exploding gradients (e.g. see Fast R-CNN paper by Ross Girshick). Omitting a scaling factor of beta, this los... | |
doc_6425 |
Like Artist.get_window_extent, but includes any clipping. Parameters
rendererRendererBase subclass
renderer that will be used to draw the figures (i.e. fig.canvas.get_renderer()) Returns
Bbox
The enclosing bounding box (in figure pixel coordinates). | |
doc_6426 |
Number of array dimensions. Examples >>> x = np.array([1, 2, 3])
>>> x.ndim
1
>>> y = np.zeros((2, 3, 4))
>>> y.ndim
3 | |
doc_6427 |
Get parameters for this estimator. Parameters
deepbool, default=True
If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns
paramsdict
Parameter names mapped to their values. | |
doc_6428 |
Bases: matplotlib.ticker.Locator Determine the tick locations The first time this function is called it will try to set the number of ticks to make a nice tick partitioning. Thereafter the number of ticks will be fixed so that interactive navigation will be nice Use presets to set locs based on lom. A dict mapping vm... | |
doc_6429 | '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_6430 | Connect to a host. The optional second argument is the port number, which defaults to the standard Telnet port (23). The optional timeout parameter specifies a timeout in seconds for blocking operations like the connection attempt (if not specified, the global default timeout setting will be used). Do not try to reopen... | |
doc_6431 |
Parameters
fpsint, default: 5
Movie frame rate (per second).
codecstr or None, default: rcParams["animation.codec"] (default: 'h264')
The codec to use.
bitrateint, default: rcParams["animation.bitrate"] (default: -1)
The bitrate of the movie, in kilobits per second. Higher values means higher quality mo... | |
doc_6432 | See Migration guide for more details. tf.compat.v1.keras.preprocessing.text.one_hot
tf.keras.preprocessing.text.one_hot(
input_text, n,
filters='!"#$%&()*+,-./:;<=>?@[\\]^_`{|}~\t\n',
lower=True, split=' '
)
This function receives as input a string of text and returns a list of encoded integers each corr... | |
doc_6433 | See Migration guide for more details. tf.compat.v1.raw_ops.TakeDataset
tf.raw_ops.TakeDataset(
input_dataset, count, output_types, output_shapes, name=None
)
Args
input_dataset A Tensor of type variant.
count A Tensor of type int64. A scalar representing the number of elements from the input_datas... | |
doc_6434 | Arrange for func to be called in the specified executor. The executor argument should be an concurrent.futures.Executor instance. The default executor is used if executor is None. Example: import asyncio
import concurrent.futures
def blocking_io():
# File operations (such as logging) can block the
# event loop... | |
doc_6435 | See Migration guide for more details. tf.compat.v1.raw_ops.NoOp
tf.raw_ops.NoOp(
name=None
)
Args
name A name for the operation (optional).
Returns The created Operation. | |
doc_6436 | Set the title used in the generated HTML documentation. This title will be used inside the HTML “title” element. | |
doc_6437 | Deprecated. Enable fast mode if set to a true value. The fast mode disables the usage of memo, therefore speeding the pickling process by not generating superfluous PUT opcodes. It should not be used with self-referential objects, doing otherwise will cause Pickler to recurse infinitely. Use pickletools.optimize() if y... | |
doc_6438 | See Migration guide for more details. tf.compat.v1.raw_ops.LookupTableFind
tf.raw_ops.LookupTableFind(
table_handle, keys, default_value, name=None
)
The tensor keys must of the same type as the keys of the table. The output values is of the type of the table values. The scalar default_value is the value output ... | |
doc_6439 |
Divide one Chebyshev series by another. Returns the quotient-with-remainder of two Chebyshev series c1 / c2. The arguments are sequences of coefficients from lowest order “term” to highest, e.g., [1,2,3] represents the series T_0 + 2*T_1 + 3*T_2. Parameters
c1, c2array_like
1-D arrays of Chebyshev series coeffi... | |
doc_6440 | Add sequence to the list of sequences that include this message. | |
doc_6441 | tf.compat.v1.tpu.experimental.FtrlParameters(
learning_rate: float,
learning_rate_power: float = -0.5,
initial_accumulator_value: float = 0.1,
l1_regularization_strength: float = 0.0,
l2_regularization_strength: float = 0.0,
use_gradient_accumulation: bool = True,
clip_weight_min: Optional[f... | |
doc_6442 |
Get the line width of the Figure rectangle. | |
doc_6443 | Split string by the occurrences of pattern. If capturing parentheses are used in pattern, then the text of all groups in the pattern are also returned as part of the resulting list. If maxsplit is nonzero, at most maxsplit splits occur, and the remainder of the string is returned as the final element of the list. >>> r... | |
doc_6444 |
Set the agg filter. Parameters
filter_funccallable
A filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array. | |
doc_6445 | See Migration guide for more details. tf.compat.v1.train.piecewise_constant_decay
tf.compat.v1.train.piecewise_constant(
x, boundaries, values, name=None
)
Example: use a learning rate that's 1.0 for the first 100001 steps, 0.5 for the next 10000 steps, and 0.1 for any additional steps. global_step = tf.Variable... | |
doc_6446 | See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixSolve
tf.raw_ops.BatchMatrixSolve(
matrix, rhs, adjoint=False, name=None
)
Args
matrix A Tensor. Must be one of the following types: float64, float32.
rhs A Tensor. Must have the same type as matrix.
adjoint An optional bo... | |
doc_6447 | Set the current context for the active thread to c. | |
doc_6448 |
Return feature names for output features Parameters
input_featureslist of str of shape (n_features,), default=None
String names for input features if available. By default, “x0”, “x1”, … “xn_features” is used. Returns
output_feature_nameslist of str of shape (n_output_features,) | |
doc_6449 | Returns the number of non-fixed hyperparameters of the kernel. | |
doc_6450 | tf.compat.v1.scatter_max(
ref, indices, updates, use_locking=False, name=None
)
This operation computes # Scalar indices
ref[indices, ...] = max(ref[indices, ...], updates[...])
# Vector indices (for each i)
ref[indices[i], ...] = max(ref[indices[i], ...], updates[i, ...])
# High rank indices (for each i, ..., j... | |
doc_6451 | See Migration guide for more details. tf.compat.v1.bitwise.right_shift
tf.bitwise.right_shift(
x, y, name=None
)
Performs a logical shift for unsigned integer types, and an arithmetic shift for signed integer types. If y is negative, or greater than or equal to than the width of x in bits the result is implement... | |
doc_6452 | Close the underlying file if possible. | |
doc_6453 | Return the date corresponding to the proleptic Gregorian ordinal, where January 1 of year 1 has ordinal 1. ValueError is raised unless 1 <= ordinal <=
date.max.toordinal(). For any date d, date.fromordinal(d.toordinal()) == d. | |
doc_6454 | A decorator indicating abstract methods. Using this decorator requires that the class’s metaclass is ABCMeta or is derived from it. A class that has a metaclass derived from ABCMeta cannot be instantiated unless all of its abstract methods and properties are overridden. The abstract methods can be called using any of t... | |
doc_6455 | See Migration guide for more details. tf.compat.v1.no_op
tf.no_op(
name=None
)
Args
name A name for the operation (optional).
Returns The created Operation. | |
doc_6456 |
Create a Parameter with the same properties of the uninitialized one. Given a shape, it materializes a parameter in the same device and with the same dtype as the current one or the specified ones in the arguments. Parameters
shape – (tuple): the shape for the materialized tensor.
device (torch.device) – the des... | |
doc_6457 | uses alternative additive fill to that of surface.fill blit_blends.main() -> None Fake additive blending. Using NumPy. it doesn't clamp. Press r,g,b Somewhat like blend_fill. | |
doc_6458 | Checks for an ASCII uppercase letter. | |
doc_6459 | Template engines are available in django.template.engines: from django.template import engines
django_engine = engines['django']
template = django_engine.from_string("Hello {{ name }}!")
The lookup key — 'django' in this example — is the engine’s NAME. | |
doc_6460 |
Return the elements in the given positional indices along an axis. This means that we are not indexing according to actual values in the index attribute of the object. We are indexing according to the actual position of the element in the object. Parameters
indices:array-like
An array of ints indicating which p... | |
doc_6461 |
Bases: torch.distributions.distribution.Distribution A circular von Mises distribution. This implementation uses polar coordinates. The loc and value args can be any real number (to facilitate unconstrained optimization), but are interpreted as angles modulo 2 pi. Example::
>>> m = dist.VonMises(torch.tensor([1.0])... | |
doc_6462 | Extracts the path info from the given URL (or WSGI environment) and path. The path info returned is a string. The URLs might also be IRIs. If the path info could not be determined, None is returned. Some examples: >>> extract_path_info('http://example.com/app', '/app/hello')
'/hello'
>>> extract_path_info('http://examp... | |
doc_6463 | Returns the date and time given by timestamp (which must be None or in the format returned by time.time()), formatted for a message header. If timestamp is omitted, it uses the current date and time. The result looks like 'Sun, 06 Nov 1994 08:49:37 GMT'. | |
doc_6464 |
Forward fill the values. Parameters
limit:int, optional
Limit of how many values to fill. Returns
Series or DataFrame
Object with missing values filled. See also Series.ffill
Returns Series with minimum number of char in object. DataFrame.ffill
Object with missing values filled or None if inplace... | |
doc_6465 | operator.__imod__(a, b)
a = imod(a, b) is equivalent to a %= b. | |
doc_6466 |
Return series instance that has the specified roots. Returns a series representing the product (x - r[0])*(x - r[1])*...*(x - r[n-1]), where r is a list of roots. Parameters
rootsarray_like
List of roots.
domain{[], None, array_like}, optional
Domain for the resulting series. If None the domain is the inter... | |
doc_6467 | tf.import_graph_def Compat aliases for migration See Migration guide for more details. tf.compat.v1.graph_util.import_graph_def, tf.compat.v1.import_graph_def
tf.graph_util.import_graph_def(
graph_def, input_map=None, return_elements=None, name=None, op_dict=None,
producer_op_list=None
)
Warning: SOME ARGUME... | |
doc_6468 |
Bases: matplotlib.ticker.Locator Determine the tick locations for log axes Place ticks on the locations : subs[j] * base**i Parameters
basefloat, default: 10.0
The base of the log used, so ticks are placed at base**n.
subsNone or str or sequence of float, default: (1.0,)
Gives the multiples of integer power... | |
doc_6469 |
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_6470 | Attempt to set up a connection to the listener which is using address address, returning a Connection. The type of the connection is determined by family argument, but this can generally be omitted since it can usually be inferred from the format of address. (See Address Formats) If authkey is given and not None, it sh... | |
doc_6471 |
Return an ndarray of the provided type that satisfies requirements. This function is useful to be sure that an array with the correct flags is returned for passing to compiled code (perhaps through ctypes). Parameters
aarray_like
The object to be converted to a type-and-requirement-satisfying array.
dtypedata... | |
doc_6472 |
A 1-D iterator over the array. This is a numpy.flatiter instance, which acts similarly to, but is not a subclass of, Python’s built-in iterator object. See also flatten
Return a copy of the array collapsed into one dimension. flatiter
Examples >>> x = np.arange(1, 7).reshape(2, 3)
>>> x
array([[1, 2, 3],
... | |
doc_6473 | class sklearn.multioutput.MultiOutputRegressor(estimator, *, n_jobs=None) [source]
Multi target regression This strategy consists of fitting one regressor per target. This is a simple strategy for extending regressors that do not natively support multi-target regression. New in version 0.18. Parameters
estimato... | |
doc_6474 |
Predict using GLM with feature matrix X. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
Samples. Returns
y_predarray of shape (n_samples,)
Returns predicted values. | |
doc_6475 | Set during Python startup, before site.py is run, to the same value as prefix. If not running in a virtual environment, the values will stay the same; if site.py finds that a virtual environment is in use, the values of prefix and exec_prefix will be changed to point to the virtual environment, whereas base_prefix and ... | |
doc_6476 | Works like has_request_context() but for the application context. You can also just do a boolean check on the current_app object instead. Changelog New in version 0.9. Return type
bool | |
doc_6477 | Returns this tensor cast to the type of the given tensor. This is a no-op if the tensor is already of the correct type. This is equivalent to self.type(tensor.type()) Parameters
tensor (Tensor) – the tensor which has the desired type | |
doc_6478 | See Migration guide for more details. tf.compat.v1.signal.fftshift
tf.signal.fftshift(
x, axes=None, name=None
)
This function swaps half-spaces for all axes listed (defaults to all). Note that y[0] is the Nyquist component only if len(x) is even. For example: x = tf.signal.fftshift([ 0., 1., 2., 3., 4., -5.... | |
doc_6479 | get the height of the font get_height() -> int Return the height in pixels of the actual rendered text. This is the average size for each glyph in the font. | |
doc_6480 |
Return the alpha value used for blending - not supported on all backends. | |
doc_6481 | sklearn.metrics.pairwise.cosine_distances(X, Y=None) [source]
Compute cosine distance between samples in X and Y. Cosine distance is defined as 1.0 minus the cosine similarity. Read more in the User Guide. Parameters
X{array-like, sparse matrix} of shape (n_samples_X, n_features)
Matrix X.
Y{array-like, spars... | |
doc_6482 |
Roll provided date forward to next offset only if not on offset. Returns
TimeStamp
Rolled timestamp if not on offset, otherwise unchanged timestamp. | |
doc_6483 | Computes the absolute value of each element in input. outi=∣inputi∣\text{out}_{i} = |\text{input}_{i}|
Parameters
input (Tensor) – the input tensor. Keyword Arguments
out (Tensor, optional) – the output tensor. Example: >>> torch.abs(torch.tensor([-1, -2, 3]))
tensor([ 1, 2, 3]) | |
doc_6484 | wave.open(file, mode=None)
If file is a string, open the file by that name, otherwise treat it as a file-like object. mode can be:
'rb'
Read only mode.
'wb'
Write only mode. Note that it does not allow read/write WAV files. A mode of 'rb' returns a Wave_read object, while a mode of 'wb' returns a Wave_write... | |
doc_6485 |
Find artist objects. Recursively find all Artist instances contained in the artist. Parameters
match
A filter criterion for the matches. This can be
None: Return all objects contained in artist. A function with signature def match(artist: Artist) -> bool. The result will only contain artists for which the funct... | |
doc_6486 | Return True if the terminal has insert- and delete-line capabilities, or can simulate them using scrolling regions. This function is included for historical reasons only, as all modern software terminal emulators have such capabilities. | |
doc_6487 |
Fit to data, then transform it. Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X. Parameters
Xarray-like of shape (n_samples, n_features)
Input samples.
yarray-like of shape (n_samples,) or (n_samples, n_outputs), default=None
Target values (None for uns... | |
doc_6488 | A subclass of HTTPException. Raised if an excessively long line is received in the HTTP protocol from the server. | |
doc_6489 | Similar to perf_counter(), but return time as nanoseconds. New in version 3.7. | |
doc_6490 |
Right bound for the interval. | |
doc_6491 |
Return the group id. | |
doc_6492 |
Clip (limit) the values in an array. Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1. Equivalent to but faster than np.minimum(a_max, np.maximum(a, a_min)). No check ... | |
doc_6493 |
Return whether the artist is animated. | |
doc_6494 | tf.metrics.Mean Compat aliases for migration See Migration guide for more details. tf.compat.v1.keras.metrics.Mean
tf.keras.metrics.Mean(
name='mean', dtype=None
)
For example, if values is [1, 3, 5, 7] then the mean is 4. If the weights were specified as [1, 1, 0, 0] then the mean would be 2. This metric create... | |
doc_6495 | A variable name. id holds the name as a string, and ctx is one of the following types. | |
doc_6496 |
On close disconnect all artists and events from ImageViewer. Note that artists must be appended to self.artists. | |
doc_6497 | tf.nn.sampled_softmax_loss(
weights, biases, labels, inputs, num_sampled, num_classes, num_true=1,
sampled_values=None, remove_accidental_hits=True, seed=None,
name='sampled_softmax_loss'
)
This is a faster way to train a softmax classifier over a huge number of classes. This operation is for training only... | |
doc_6498 |
Return name of an ExtGState that sets alpha to the given value. | |
doc_6499 | Create a BytesParser instance. The _class and policy arguments have the same meaning and semantics as the _factory and policy arguments of BytesFeedParser. Note: The policy keyword should always be specified; The default will change to email.policy.default in a future version of Python. Changed in version 3.3: Removed... |
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