_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_27300 | See torch.renorm() | |
doc_27301 | A non-callable version of MagicMock. The constructor parameters have the same meaning as for MagicMock, with the exception of return_value and side_effect which have no meaning on a non-callable mock. | |
doc_27302 |
Convert coefficient matrix to sparse format. Converts the coef_ member to a scipy.sparse matrix, which for L1-regularized models can be much more memory- and storage-efficient than the usual numpy.ndarray representation. The intercept_ member is not converted. Returns
self
Fitted estimator. Notes For non-spar... | |
doc_27303 |
Initialize a graph with edges, name, or graph attributes. Parameters
incoming_graph_datainput graph (optional, default: None)
Data to initialize graph. If None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python packages are insta... | |
doc_27304 |
Evaluate a 3-D polynomial at points (x, y, z). This function returns the values: \[p(x,y,z) = \sum_{i,j,k} c_{i,j,k} * x^i * y^j * z^k\] The parameters x, y, and z are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars and they must have the same shape after conversion. I... | |
doc_27305 | See Migration guide for more details. tf.compat.v1.io.decode_proto
tf.io.decode_proto(
bytes, message_type, field_names, output_types,
descriptor_source='local://', message_format='binary',
sanitize=False, name=None
)
The decode_proto op extracts fields from a serialized protocol buffers message into ten... | |
doc_27306 | repository revision of the build rev = 'a6f89747b551+' The Mercurial node identifier of the repository checkout from which this package was built. If the identifier ends with a plus sign '+' then the package contains uncommitted changes. Please include this revision number in bug reports, especially for non-release p... | |
doc_27307 | tf.experimental.numpy.divmod(
x1, x2
)
Unsupported arguments: out1, out2, out, where, casting, order, dtype, subok, signature, extobj. See the NumPy documentation for numpy.divmod. | |
doc_27308 |
Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each hour. Mark every hour in byhour; byhour can be an int or sequence. Default is to tick every hour: byhour=range(24) interval is the interval between each iteration. For example, if interval=2, mark every second occurrence. | |
doc_27309 |
Fit a model to data with the RANSAC (random sample consensus) algorithm. RANSAC is an iterative algorithm for the robust estimation of parameters from a subset of inliers from the complete data set. Each iteration performs the following tasks: Select min_samples random samples from the original data and check whethe... | |
doc_27310 |
Check whether an array-like or dtype is of a DatetimeTZDtype 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 a DatetimeTZDtype dtype. Examples
>>> is_datetime64tz_dtype(object)
False
>>> is_datetime64tz_... | |
doc_27311 | Escape a string. Calls escape() and ensures that for subclasses the correct type is returned. Parameters
s (Any) – Return type
markupsafe.Markup | |
doc_27312 | Set the character stream (a text file) for this input source. If there is a character stream specified, the SAX parser will ignore any byte stream and will not attempt to open a URI connection to the system identifier. | |
doc_27313 |
Find the unique elements of an array. Returns the sorted unique elements of an array. There are three optional outputs in addition to the unique elements: the indices of the input array that give the unique values the indices of the unique array that reconstruct the input array the number of times each unique value ... | |
doc_27314 | Return base to the power exp; if mod is present, return base to the power exp, modulo mod (computed more efficiently than pow(base, exp) % mod). The two-argument form pow(base, exp) is equivalent to using the power operator: base**exp. The arguments must have numeric types. With mixed operand types, the coercion rules ... | |
doc_27315 | See Migration guide for more details. tf.compat.v1.raw_ops.Abs
tf.raw_ops.Abs(
x, name=None
)
Given a tensor x, this operation returns a tensor containing the absolute value of each element in x. For example, if x is an input element and y is an output element, this operation computes \(y = |x|\).
Args
x ... | |
doc_27316 | Does basic configuration for the logging system by creating a StreamHandler with a default Formatter and adding it to the root logger. The functions debug(), info(), warning(), error() and critical() will call basicConfig() automatically if no handlers are defined for the root logger. This function does nothing if the ... | |
doc_27317 | Return a new hmac object. key is a bytes or bytearray object giving the secret key. If msg is present, the method call update(msg) is made. digestmod is the digest name, digest constructor or module for the HMAC object to use. It may be any name suitable to hashlib.new(). Despite its argument position, it is required. ... | |
doc_27318 |
Check whether the provided array or dtype is of the datetime64[ns] dtype. Parameters
arr_or_dtype:array-like or dtype
The array or dtype to check. Returns
bool
Whether or not the array or dtype is of the datetime64[ns] dtype. Examples
>>> is_datetime64_ns_dtype(str)
False
>>> is_datetime64_ns_dtype(i... | |
doc_27319 | tf.compat.v1.metrics.precision_at_top_k(
labels, predictions_idx, k=None, class_id=None, weights=None,
metrics_collections=None, updates_collections=None, name=None
)
Differs from sparse_precision_at_k in that predictions must be in the form of top k class indices, whereas sparse_precision_at_k expects logits.... | |
doc_27320 | Create a new Font instance from a supported font file. Font(file, size=0, font_index=0, resolution=0, ucs4=False) -> Font Argument file can be either a string representing the font's filename, a file-like object containing the font, or None; if None, a default, Pygame, font is used. Optionally, a size argument may be... | |
doc_27321 | Creates a class object dynamically using the appropriate metaclass. The first three arguments are the components that make up a class definition header: the class name, the base classes (in order), the keyword arguments (such as metaclass). The exec_body argument is a callback that is used to populate the freshly creat... | |
doc_27322 |
Return the frequency object if it is set, otherwise None. | |
doc_27323 | Class derived from Error. Contains no additional instance variables. | |
doc_27324 |
Apply func(self, *args, **kwargs), and return the result. Parameters
func:function
Function to apply to the Styler. Alternatively, a (callable, keyword) tuple where keyword is a string indicating the keyword of callable that expects the Styler.
*args:optional
Arguments passed to func.
**kwargs:optional
... | |
doc_27325 | See Migration guide for more details. tf.compat.v1.math.segment_min, tf.compat.v1.segment_min
tf.math.segment_min(
data, segment_ids, name=None
)
Read the section on segmentation for an explanation of segments. Computes a tensor such that \(output_i = \min_j(data_j)\) where min is over j such that segment_ids[j]... | |
doc_27326 | Assert the mock has been awaited with the specified calls. The await_args_list list is checked for the awaits. If any_order is false then the awaits must be sequential. There can be extra calls before or after the specified awaits. If any_order is true then the awaits can be in any order, but they must all appear in aw... | |
doc_27327 |
This criterion combines log_softmax and nll_loss in a single function. See CrossEntropyLoss for details. Parameters
input (Tensor) – (N,C)(N, C) where C = number of classes or (N,C,H,W)(N, C, H, W) in case of 2D Loss, or (N,C,d1,d2,...,dK)(N, C, d_1, d_2, ..., d_K) where K≥1K \geq 1 in the case of K-dimension... | |
doc_27328 | Returns a tensor filled with the scalar value 1, with the same size as input. torch.ones_like(input) is equivalent to torch.ones(input.size(), dtype=input.dtype, layout=input.layout, device=input.device). Warning As of 0.4, this function does not support an out keyword. As an alternative, the old torch.ones_like(input... | |
doc_27329 |
Raised when encountering a timedelta value that cannot be represented as a timedelta64[ns]. | |
doc_27330 |
Initializes RPC primitives such as the local RPC agent and distributed autograd, which immediately makes the current process ready to send and receive RPCs. Parameters
name (str) – a globally unique name of this node. (e.g., Trainer3, ParameterServer2, Master, Worker1) Name can only contain number, alphabet, unde... | |
doc_27331 |
Applies a 2D convolution over a quantized input signal composed of several quantized input planes. For details on input arguments, parameters, and implementation see Conv2d. Note Only zeros is supported for the padding_mode argument. Note Only torch.quint8 is supported for the input data type. Variables
~Conv... | |
doc_27332 | The multipart headers as Headers object. This usually contains irrelevant information but in combination with custom multipart requests the raw headers might be interesting. Changelog New in version 0.6. | |
doc_27333 | A context manager that temporarily changes the current working directory to path and yields the directory. If quiet is False, the context manager raises an exception on error. Otherwise, it issues only a warning and keeps the current working directory the same. | |
doc_27334 |
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_27335 |
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op. Parameters
valuesarray
The input v... | |
doc_27336 | Returns the variance of all elements in the input tensor. If unbiased is False, then the variance will be calculated via the biased estimator. Otherwise, Bessel’s correction will be used. Parameters
input (Tensor) – the input tensor.
unbiased (bool) – whether to use the unbiased estimation or not Example: >>> a... | |
doc_27337 | Size in bytes. | |
doc_27338 | tkinter.filedialog.askopenfilenames(**options)
The above two functions create an Open dialog and return the selected filename(s) that correspond to existing file(s). | |
doc_27339 |
Array mapping from feature integer indices to feature name. Returns
feature_nameslist
A list of feature names. | |
doc_27340 | tf.sparse.split(
sp_input=None, num_split=None, axis=None, name=None
)
If the sp_input.dense_shape[axis] is not an integer multiple of num_split each slice starting from 0:shape[axis] % num_split gets extra one dimension. For example:
indices = [[0, 2], [0, 4], [0, 5], [1, 0], [1, 1]]
values = [1, 2, 3, 4, 5]
t =... | |
doc_27341 |
Return whether event should be ignored. This method should be called at the beginning of any event callback. | |
doc_27342 | In-place version of lerp() | |
doc_27343 |
Return True if this Future is done. A Future is done if it has a result or an exception. | |
doc_27344 | New in Django 3.2. Set this attribute to False to prevent Django from selecting a configuration class automatically. This is useful when apps.py defines only one AppConfig subclass but you don’t want Django to use it by default. Set this attribute to True to tell Django to select a configuration class automatically. ... | |
doc_27345 | See Migration guide for more details. tf.compat.v1.nondifferentiable_batch_function
tf.nondifferentiable_batch_function(
num_batch_threads, max_batch_size, batch_timeout_micros,
allowed_batch_sizes=None, max_enqueued_batches=10, autograph=True,
enable_large_batch_splitting=True
)
So, for example, in the ... | |
doc_27346 | Execute the coroutine coro and return the result. This function runs the passed coroutine, taking care of managing the asyncio event loop, finalizing asynchronous generators, and closing the threadpool. This function cannot be called when another asyncio event loop is running in the same thread. If debug is True, the e... | |
doc_27347 |
Returns the unique elements of the input tensor. See torch.unique() | |
doc_27348 | int goal_reached(int index, float cumcost) This method is called each iteration after popping an index from the heap, before examining the neighbours. This method can be overloaded to modify the behavior of the MCP algorithm. An example might be to stop the algorithm when a certain cumulative cost is reached, or when t... | |
doc_27349 | See Migration guide for more details. tf.compat.v1.tpu.experimental.TPUSystemMetadata
tf.tpu.experimental.TPUSystemMetadata(
num_cores, num_hosts, num_of_cores_per_host, topology, devices
)
Attributes
num_cores interger. Total number of TPU cores in the TPU system.
num_hosts interger. Total number... | |
doc_27350 | Shift the surface image in place scroll(dx=0, dy=0) -> None Move the image by dx pixels right and dy pixels down. dx and dy may be negative for left and up scrolls respectively. Areas of the surface that are not overwritten retain their original pixel values. Scrolling is contained by the Surface clip area. It is saf... | |
doc_27351 | remove Sprites from the Group remove(*sprites) -> None Remove any number of Sprites from the Group. This will only remove Sprites that are already members of the Group. Each sprite argument can also be a iterator containing Sprites. | |
doc_27352 |
Fit the model from data in X. Parameters
Xarray-like of shape (n_samples, n_features)
Training vector, where n_samples in the number of samples and n_features is the number of features.
yIgnored
Returns
selfobject
Returns the instance itself. | |
doc_27353 |
Add a centered supylabel to the figure. Parameters
tstr
The supylabel text.
xfloat, default: 0.02
The x location of the text in figure coordinates.
yfloat, default: 0.5
The y location of the text in figure coordinates.
horizontalalignment, ha{'center', 'left', 'right'}, default: left
The horizontal ... | |
doc_27354 |
Return alpha to be applied to all ContourSet artists. | |
doc_27355 |
Set the label2 text. Parameters
sstr | |
doc_27356 |
Return a Path representing a circle of a given radius and center. Parameters
center(float, float), default: (0, 0)
The center of the circle.
radiusfloat, default: 1
The radius of the circle.
readonlybool
Whether the created path should have the "readonly" argument set when creating the Path instance. ... | |
doc_27357 | See Migration guide for more details. tf.compat.v1.raw_ops.TridiagonalMatMul
tf.raw_ops.TridiagonalMatMul(
superdiag, maindiag, subdiag, rhs, name=None
)
Calculates product of two matrices, where left matrix is a tridiagonal matrix.
Args
superdiag A Tensor. Must be one of the following types: float64, f... | |
doc_27358 | Computes the singular value decomposition of either a matrix or batch of matrices input. The singular value decomposition is represented as a namedtuple (U,S,V), such that input = U diag(S) Vᴴ, where Vᴴ is the transpose of V for the real-valued inputs, or the conjugate transpose of V for the complex-valued inputs. If i... | |
doc_27359 | See Migration guide for more details. tf.compat.v1.data.experimental.DistributeOptions
tf.data.experimental.DistributeOptions()
You can set the distribution options of a dataset through the experimental_distribute property of tf.data.Options; the property is an instance of tf.data.experimental.DistributeOptions. opt... | |
doc_27360 | Raised when an attempt is made to use an object that is not defined or is no longer usable. | |
doc_27361 |
Drawing function for box and whisker plots. Make a box and whisker plot for each column of x or each vector in sequence x. The box extends from the lower to upper quartile values of the data, with a line at the median. The whiskers extend from the box to show the range of the data. Flier points are those past the end... | |
doc_27362 |
Draw samples from a standard Cauchy distribution with mode = 0. Also known as the Lorentz distribution. Note New code should use the standard_cauchy method of a default_rng() instance instead; please see the Quick Start. Parameters
sizeint or tuple of ints, optional
Output shape. If the given shape is, e.g., ... | |
doc_27363 |
Returns
list
List of segments in the LineCollection. Each list item contains an array of vertices. | |
doc_27364 |
Transform X. This is implemented by linking the points X into the graph of geodesic distances of the training data. First the n_neighbors nearest neighbors of X are found in the training data, and from these the shortest geodesic distances from each point in X to each point in the training data are computed in order ... | |
doc_27365 | This method adapts obj to a ctypes type. It is called with the actual object used in a foreign function call when the type is present in the foreign function’s argtypes tuple; it must return an object that can be used as a function call parameter. All ctypes data types have a default implementation of this classmethod ... | |
doc_27366 |
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_27367 | Represents an RSS enclosure | |
doc_27368 | tf.compat.v1.gfile.Stat(
filename
)
Args
filename string, path to a file
Returns FileStatistics struct that contains information about the path
Raises
errors.OpError If the operation fails. | |
doc_27369 | Returns a GEOSGeometry combining the points in this geometry not in other, and the points in other not in this geometry. | |
doc_27370 | uu.encode(in_file, out_file, name=None, mode=None, *, backtick=False)
Uuencode file in_file into file out_file. The uuencoded file will have the header specifying name and mode as the defaults for the results of decoding the file. The default defaults are taken from in_file, or '-' and 0o666 respectively. If backtick... | |
doc_27371 | See Migration guide for more details. tf.compat.v1.raw_ops.Floor
tf.raw_ops.Floor(
x, name=None
)
Args
x A Tensor. Must be one of the following types: bfloat16, half, float32, float64.
name A name for the operation (optional).
Returns A Tensor. Has the same type as x. | |
doc_27372 | Alias for field number 1 | |
doc_27373 | class frozenset([iterable])
Return a new set or frozenset object whose elements are taken from iterable. The elements of a set must be hashable. To represent sets of sets, the inner sets must be frozenset objects. If iterable is not specified, a new empty set is returned. Sets can be created by several means: Use a ... | |
doc_27374 | See Migration guide for more details. tf.compat.v1.keras.applications.densenet.decode_predictions
tf.keras.applications.densenet.decode_predictions(
preds, top=5
)
Arguments
preds Numpy array encoding a batch of predictions.
top Integer, how many top-guesses to return. Defaults to 5.
Retur... | |
doc_27375 |
Build a text report showing the main classification metrics. Read more in the User Guide. Parameters
y_true1d array-like, or label indicator array / sparse matrix
Ground truth (correct) target values.
y_pred1d array-like, or label indicator array / sparse matrix
Estimated targets as returned by a classifier... | |
doc_27376 | Based on IntegerField and translates its input into NumericRange. Default for IntegerRangeField and BigIntegerRangeField. | |
doc_27377 |
Raw scoring function of the samples. Parameters
Xarray-like of shape (n_samples, n_features)
The data matrix. Returns
score_samplesndarray of shape (n_samples,)
Returns the (unshifted) scoring function of the samples. | |
doc_27378 | Instance of the TestLoader class intended to be shared. If no customization of the TestLoader is needed, this instance can be used instead of repeatedly creating new instances. | |
doc_27379 | New in Django 4.0. Override empty_result_set_value to None since most aggregate functions result in NULL when applied to an empty result set. | |
doc_27380 | operator.invert(obj)
operator.__inv__(obj)
operator.__invert__(obj)
Return the bitwise inverse of the number obj. This is equivalent to ~obj. | |
doc_27381 | Gets or sets the CMY representation of the Color. cmy -> tuple The CMY representation of the Color. The CMY components are in the ranges C = [0, 1], M = [0, 1], Y = [0, 1]. Note that this will not return the absolutely exact CMY values for the set RGB values in all cases. Due to the RGB mapping from 0-255 and the CMY... | |
doc_27382 | Takes a single “compressed” value of a field, for example a DateRangeField, and returns a tuple representing a lower and upper bound. | |
doc_27383 |
Check if coefficients match. New in version 1.6.0. Parameters
otherclass instance
The other class must have the coef attribute. Returns
boolboolean
True if the coefficients are the same, False otherwise. | |
doc_27384 | Possible value for SSLContext.verify_mode, or the cert_reqs parameter to wrap_socket(). Except for PROTOCOL_TLS_CLIENT, it is the default mode. With client-side sockets, just about any cert is accepted. Validation errors, such as untrusted or expired cert, are ignored and do not abort the TLS/SSL handshake. In server m... | |
doc_27385 |
Alias for set_edgecolor. | |
doc_27386 | >>> cache.get('my_key')
'hello, world!' | |
doc_27387 |
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_27388 | A generic version of collections.abc.AsyncIterable. New in version 3.5.2. Deprecated since version 3.9: collections.abc.AsyncIterable now supports []. See PEP 585 and Generic Alias Type. | |
doc_27389 | tf.profiler.experimental.Profile(
logdir, options=None
)
Profiling will start when entering the scope, and stop and save the results to the logdir when exits the scope. Open TensorBoard profile tab to view results. Example usage: with tf.profiler.experimental.Profile("/path/to/logdir"):
# do some work
Args... | |
doc_27390 |
Set the parameters of this kernel. The method works on simple kernels as well as on nested kernels. The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object. Returns
self | |
doc_27391 | tf.compat.v1.keras.backend.set_session(
session
)
Arguments
session A TF Session. | |
doc_27392 |
Return real and imaginary responses to Gabor filter. The real and imaginary parts of the Gabor filter kernel are applied to the image and the response is returned as a pair of arrays. Gabor filter is a linear filter with a Gaussian kernel which is modulated by a sinusoidal plane wave. Frequency and orientation repres... | |
doc_27393 |
Perform total-variation denoising on n-dimensional images. Parameters
imagendarray of ints, uints or floats
Input data to be denoised. image can be of any numeric type, but it is cast into an ndarray of floats for the computation of the denoised image.
weightfloat, optional
Denoising weight. The greater wei... | |
doc_27394 | Converts a float tensor to a per-channel quantized tensor with given scales and zero points. Parameters
input (Tensor) – float tensor to quantize
scales (Tensor) – float 1D tensor of scales to use, size should match input.size(axis)
zero_points (int) – integer 1D tensor of offset to use, size should match input.... | |
doc_27395 |
Add the coordinates of an event to the list of clicks. Parameters
eventMouseEvent | |
doc_27396 | Base class for other signals and a subclass of ArithmeticError. | |
doc_27397 | Encode the bytes-like object b using base85 (as used in e.g. git-style binary diffs) and return the encoded bytes. If pad is true, the input is padded with b'\0' so its length is a multiple of 4 bytes before encoding. New in version 3.4. | |
doc_27398 | Set or remove the completion display function. If function is specified, it will be used as the new completion display function; if omitted or None, any completion display function already installed is removed. This sets or clears the rl_completion_display_matches_hook callback in the underlying library. The completion... | |
doc_27399 | Assert that the mock was awaited at least once. Note that this is separate from the object having been called, the await keyword must be used: >>> mock = AsyncMock()
>>> async def main(coroutine_mock):
... await coroutine_mock
...
>>> coroutine_mock = mock()
>>> mock.called
True
>>> mock.assert_awaited()
Traceback ... |
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