_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_2600 | See Migration guide for more details. tf.compat.v1.raw_ops.MatrixLogarithm
tf.raw_ops.MatrixLogarithm(
input, name=None
)
\(log(exp(A)) = A\) This op is only defined for complex matrices. If A is positive-definite and real, then casting to a complex matrix, taking the logarithm and casting back to a real matrix ... | |
doc_2601 |
Draw a collection of paths selecting drawing properties from the lists facecolors, edgecolors, linewidths, linestyles and antialiaseds. offsets is a list of offsets to apply to each of the paths. The offsets in offsets are first transformed by offsetTrans before being applied. offset_position is unused now, but the a... | |
doc_2602 | tf.compat.v1.train.ChiefSessionCreator(
scaffold=None, master='', config=None, checkpoint_dir=None,
checkpoint_filename_with_path=None
)
Args
scaffold A Scaffold used for gathering or building supportive ops. If not specified a default one is created. It's used to finalize the graph.
master Stri... | |
doc_2603 | Add a new attribute node to the element, replacing an existing attribute if necessary if the name attribute matches. If a replacement occurs, the old attribute node will be returned. If newAttr is already in use, InuseAttributeErr will be raised. | |
doc_2604 |
Return the list of minor Ticks. | |
doc_2605 |
Bases: matplotlib.ticker.Formatter Use a user-defined function for formatting. The function should take in two inputs (a tick value x and a position pos), and return a string containing the corresponding tick label. get_offset()[source]
set_offset_string(ofs)[source] | |
doc_2606 |
Computes the position of the points in the embedding space. Parameters
Xarray-like of shape (n_samples, n_features) or (n_samples, n_samples)
Input data. If dissimilarity=='precomputed', the input should be the dissimilarity matrix.
yIgnored
initndarray of shape (n_samples,), default=None
Starting configu... | |
doc_2607 | The URL to redirect to when the form is successfully processed. success_url may contain dictionary string formatting, which will be interpolated against the object’s field attributes. For example, you could use success_url="/polls/{slug}/" to redirect to a URL composed out of the slug field on a model. | |
doc_2608 |
Return a sequence of equally spaced Matplotlib dates. The dates start at dstart and reach up to, but not including dend. They are spaced by delta. Parameters
dstart, denddatetime
The date limits.
deltadatetime.timedelta
Spacing of the dates. Returns
numpy.array
A list floats representing Matplotlib da... | |
doc_2609 |
Alias for set_markersize. | |
doc_2610 |
Predict probability for each possible outcome. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
Array representing the data. Returns
yndarray of shape (n_samples, n_features)
Array with prediction probabilities. | |
doc_2611 | tf.experimental.numpy.expm1(
x
)
Unsupported arguments: out, where, casting, order, dtype, subok, signature, extobj. See the NumPy documentation for numpy.expm1. | |
doc_2612 |
An array object represents a multidimensional, homogeneous array of fixed-size items. An associated data-type object describes the format of each element in the array (its byte-order, how many bytes it occupies in memory, whether it is an integer, a floating point number, or something else, etc.) Arrays should be con... | |
doc_2613 | sklearn.utils.validation.check_symmetric(array, *, tol=1e-10, raise_warning=True, raise_exception=False) [source]
Make sure that array is 2D, square and symmetric. If the array is not symmetric, then a symmetrized version is returned. Optionally, a warning or exception is raised if the matrix is not symmetric. Param... | |
doc_2614 | Indicates the format that the module uses. Version 0 is the historical format, version 1 shares interned strings and version 2 uses a binary format for floating point numbers. Version 3 adds support for object instancing and recursion. The current version is 4. | |
doc_2615 |
Process an button-2 event (end blocking input). Parameters
eventMouseEvent | |
doc_2616 |
Bases: matplotlib.widgets.Widget Widget connected to a single Axes. To guarantee that the widget remains responsive and not garbage-collected, a reference to the object should be maintained by the user. This is necessary because the callback registry maintains only weak-refs to the functions, which are member functio... | |
doc_2617 | Name of the ndbm implementation library used. | |
doc_2618 |
Construct a Bbox by padding this one on all four sides by p. | |
doc_2619 |
Abstract base class of all scalar types without predefined length. The actual size of these types depends on the specific np.dtype instantiation. | |
doc_2620 |
Context-manager that sets gradient calculation to on or off. set_grad_enabled will enable or disable grads based on its argument mode. It can be used as a context-manager or as a function. This context manager is thread local; it will not affect computation in other threads. Parameters
mode (bool) – Flag whether to... | |
doc_2621 | Is raised when a compression method is not supported or when the data cannot be decoded properly. | |
doc_2622 | See Migration guide for more details. tf.compat.v1.keras.layers.SpatialDropout1D
tf.keras.layers.SpatialDropout1D(
rate, **kwargs
)
This version performs the same function as Dropout, however, it drops entire 1D feature maps instead of individual elements. If adjacent frames within feature maps are strongly corr... | |
doc_2623 | tf.initializers.VarianceScaling, tf.initializers.variance_scaling, tf.keras.initializers.variance_scaling
tf.keras.initializers.VarianceScaling(
scale=1.0, mode='fan_in', distribution='truncated_normal',
seed=None
)
Also available via the shortcut function tf.keras.initializers.variance_scaling. With distrib... | |
doc_2624 |
The number of types. The number of numerical NumPy types - of which there are 18 total - on which the ufunc can operate. See also numpy.ufunc.types
Examples >>> np.add.ntypes
18
>>> np.multiply.ntypes
18
>>> np.power.ntypes
17
>>> np.exp.ntypes
7
>>> np.remainder.ntypes
14 | |
doc_2625 |
Place a legend on the Axes. Call signatures: legend()
legend(handles, labels)
legend(handles=handles)
legend(labels)
The call signatures correspond to the following different ways to use this method: 1. Automatic detection of elements to be shown in the legend The elements to be added to the legend are automatically... | |
doc_2626 | If the two operands are unequal, return the number closest to the first operand in the direction of the second operand. If both operands are numerically equal, return a copy of the first operand with the sign set to be the same as the sign of the second operand. | |
doc_2627 | A data structure of functions to call to modify the keyword arguments when generating URLs, in the format {scope: [functions]}. The scope key is the name of a blueprint the functions are active for, or None for all requests. To register a function, use the url_defaults() decorator. This data structure is internal. It s... | |
doc_2628 |
Fill NA/NaN values using the specified method. Parameters
value:scalar, dict, Series, or DataFrame
Value to use to fill holes (e.g. 0), alternately a dict/Series/DataFrame of values specifying which value to use for each index (for a Series) or column (for a DataFrame). Values not in the dict/Series/DataFrame w... | |
doc_2629 | High-resolution per-process timer from the CPU. Availability: Unix. New in version 3.3. | |
doc_2630 | See torch.nan_to_num(). | |
doc_2631 |
Return the sum of the array elements over the given axis. Refer to numpy.sum for full documentation. See also numpy.sum
equivalent function | |
doc_2632 | ABC for coroutine compatible classes. These implement the following methods, defined in Coroutine Objects: send(), throw(), and close(). Custom implementations must also implement __await__(). All Coroutine instances are also instances of Awaitable. See also the definition of coroutine. Note In CPython, generator-base... | |
doc_2633 |
Get feature names from all transformers. Returns
feature_nameslist of strings
Names of the features produced by transform. | |
doc_2634 | __iter__()
values()
Return an iterator over representations of all messages if called as itervalues() or __iter__() or return a list of such representations if called as values(). The messages are represented as instances of the appropriate format-specific Message subclass unless a custom message factory was specif... | |
doc_2635 |
Bases: matplotlib.backend_bases.FigureCanvasBase draw()[source]
Render the Figure. It is important that this method actually walk the artist tree even if not output is produced because this will trigger deferred work (like computing limits auto-limits and tick values) that users may want access to before saving t... | |
doc_2636 | As soon as you have more complex URL setups it’s a good idea to use rule factories to avoid repetitive tasks. Some of them are builtin, others can be added by subclassing RuleFactory and overriding get_rules.
get_rules(map)
Subclasses of RuleFactory have to override this method and return an iterable of rules. Par... | |
doc_2637 |
Least squares fit to data. Return a series instance that is the least squares fit to the data y sampled at x. The domain of the returned instance can be specified and this will often result in a superior fit with less chance of ill conditioning. Parameters
xarray_like, shape (M,)
x-coordinates of the M sample p... | |
doc_2638 |
Alias for set_edgecolor. | |
doc_2639 | tf.losses.Loss Compat aliases for migration See Migration guide for more details. tf.compat.v1.keras.losses.Loss
tf.keras.losses.Loss(
reduction=losses_utils.ReductionV2.AUTO, name=None
)
To be implemented by subclasses:
call(): Contains the logic for loss calculation using y_true, y_pred. Example subclass im... | |
doc_2640 | See Migration guide for more details. tf.compat.v1.keras.layers.GaussianNoise
tf.keras.layers.GaussianNoise(
stddev, **kwargs
)
This is useful to mitigate overfitting (you could see it as a form of random data augmentation). Gaussian Noise (GS) is a natural choice as corruption process for real valued inputs. As... | |
doc_2641 | Copy an array to a new surface pygame.pixelcopy.make_surface(array) -> Surface Create a new Surface that best resembles the data and format of the array. The array can be 2D or 3D with any sized integer values. | |
doc_2642 |
Return the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation. | |
doc_2643 |
Return whether the polygon is closed. | |
doc_2644 | Return a list of 2-tuples containing all the message’s field headers and values. | |
doc_2645 | self.int() is equivalent to self.to(torch.int32). See to(). Parameters
memory_format (torch.memory_format, optional) – the desired memory format of returned Tensor. Default: torch.preserve_format. | |
doc_2646 |
Creates a criterion that measures the mean absolute error (MAE) between each element in the input xx and target yy . The unreduced (i.e. with reduction set to 'none') loss can be described as: ℓ(x,y)=L={l1,…,lN}⊤,ln=∣xn−yn∣,\ell(x, y) = L = \{l_1,\dots,l_N\}^\top, \quad l_n = \left| x_n - y_n \right|,
where NN i... | |
doc_2647 | A special typing construct to indicate to type checkers that a name cannot be re-assigned or overridden in a subclass. For example: MAX_SIZE: Final = 9000
MAX_SIZE += 1 # Error reported by type checker
class Connection:
TIMEOUT: Final[int] = 10
class FastConnector(Connection):
TIMEOUT = 1 # Error reported b... | |
doc_2648 | See Migration guide for more details. tf.compat.v1.keras.activations.softplus
tf.keras.activations.softplus(
x
)
Example Usage:
a = tf.constant([-20, -1.0, 0.0, 1.0, 20], dtype = tf.float32)
b = tf.keras.activations.softplus(a)
b.numpy()
array([2.0611537e-09, 3.1326166e-01, 6.9314718e-01, 1.3132616e+00,
... | |
doc_2649 |
Return boolean flag, True if artist is included in layout calculations. E.g. Constrained Layout Guide, Figure.tight_layout(), and fig.savefig(fname, bbox_inches='tight'). | |
doc_2650 | The maximum size (in bytes) of the call stack for the current process. This only affects the stack of the main thread in a multi-threaded process. | |
doc_2651 | tf.compat.v1.data.make_initializable_iterator(
dataset, shared_name=None
)
Note: The returned iterator will be in an uninitialized state, and you must run the iterator.initializer operation before using it:
dataset = ...
iterator = tf.compat.v1.data.make_initializable_iterator(dataset)
# ...
sess.run(iterator.in... | |
doc_2652 |
Evaluate a Legendre series at points x. If c is of length n + 1, this function returns the value: \[p(x) = c_0 * L_0(x) + c_1 * L_1(x) + ... + c_n * L_n(x)\] The parameter x is converted to an array only if it is a tuple or a list, otherwise it is treated as a scalar. In either case, either x or its elements must su... | |
doc_2653 | List of socket.socket objects the server is listening on. Changed in version 3.7: Prior to Python 3.7 Server.sockets used to return an internal list of server sockets directly. In 3.7 a copy of that list is returned. | |
doc_2654 |
Description of the Tool. str: Tooltip used if the Tool is included in a Toolbar. | |
doc_2655 |
[Deprecated] dpi_cor is currently used for linewidth-related things and shrink factor. Mutation scale is affected by this. Returns
scalar
Notes Deprecated since version 3.4. | |
doc_2656 |
Print the current state of the nditer instance and debug info to stdout. | |
doc_2657 |
Add a vertical span (rectangle) across the Axes. The rectangle spans from xmin to xmax horizontally, and, by default, the whole y-axis vertically. The y-span can be set using ymin (default: 0) and ymax (default: 1) which are in axis units; e.g. ymin = 0.5 always refers to the middle of the y-axis regardless of the li... | |
doc_2658 | See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalDatasetCardinality
tf.raw_ops.ExperimentalDatasetCardinality(
input_dataset, name=None
)
Returns the cardinality of input_dataset.
Args
input_dataset A Tensor of type variant. A variant tensor representing the dataset to return cardi... | |
doc_2659 |
Insert scalar into an array (scalar is cast to array’s dtype, if possible) There must be at least 1 argument, and define the last argument as item. Then, a.itemset(*args) is equivalent to but faster than a[args] = item. The item should be a scalar value and args must select a single item in the array a. Parameters
... | |
doc_2660 |
Transform X separately by each transformer, concatenate results. Parameters
Xiterable or array-like, depending on transformers
Input data to be transformed. Returns
X_tarray-like or sparse matrix of shape (n_samples, sum_n_components)
hstack of results of transformers. sum_n_components is the sum of n_c... | |
doc_2661 | Add a file to the current component of the directory, starting a new one if there is no current component. By default, the file name in the source and the file table will be identical. If the src file is specified, it is interpreted relative to the current directory. Optionally, a version and a language can be specifie... | |
doc_2662 | See Migration guide for more details. tf.compat.v1.raw_ops.ResourceApplyAdaMax
tf.raw_ops.ResourceApplyAdaMax(
var, m, v, beta1_power, lr, beta1, beta2, epsilon, grad, use_locking=False,
name=None
)
mt <- beta1 * m{t-1} + (1 - beta1) * g vt <- max(beta2 * v{t-1}, abs(g)) variable <- variable - learning_rate ... | |
doc_2663 |
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_2664 | sklearn.metrics.pairwise.kernel_metrics() [source]
Valid metrics for pairwise_kernels. This function simply returns the valid pairwise distance metrics. It exists, however, to allow for a verbose description of the mapping for each of the valid strings. The valid distance metrics, and the function they map to, are:
... | |
doc_2665 |
Return the last row(s) without any NaNs before where. The last row (for each element in where, if list) without any NaN is taken. In case of a DataFrame, the last row without NaN considering only the subset of columns (if not None) If there is no good value, NaN is returned for a Series or a Series of NaN values for ... | |
doc_2666 |
Return the cursor data for a given event. Note This method is intended to be overridden by artist subclasses. As an end-user of Matplotlib you will most likely not call this method yourself. Cursor data can be used by Artists to provide additional context information for a given event. The default implementation ju... | |
doc_2667 | Set list_display to control which fields are displayed on the change list page of the admin. Example: list_display = ('first_name', 'last_name')
If you don’t set list_display, the admin site will display a single column that displays the __str__() representation of each object. There are four types of values that can ... | |
doc_2668 | Create a mock object using another object as a spec. Attributes on the mock will use the corresponding attribute on the spec object as their spec. Functions or methods being mocked will have their arguments checked to ensure that they are called with the correct signature. If spec_set is True then attempting to set att... | |
doc_2669 |
Update this artist's properties from the dict props. Parameters
propsdict | |
doc_2670 | See Migration guide for more details. tf.compat.v1.raw_ops.TensorListScatter
tf.raw_ops.TensorListScatter(
tensor, indices, element_shape, name=None
)
Each member of the TensorList corresponds to one row of the input tensor, specified by the given index (see tf.gather). tensor: The input tensor. indices: The ind... | |
doc_2671 |
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_2672 | A helper function that decorates a function to retain the current request context. This is useful when working with greenlets. The moment the function is decorated a copy of the request context is created and then pushed when the function is called. The current session is also included in the copied request context. Ex... | |
doc_2673 | See Migration guide for more details. tf.compat.v1.raw_ops.MaxIntraOpParallelismDataset
tf.raw_ops.MaxIntraOpParallelismDataset(
input_dataset, max_intra_op_parallelism, output_types, output_shapes, name=None
)
Args
input_dataset A Tensor of type variant.
max_intra_op_parallelism A Tensor of type ... | |
doc_2674 |
Return local geometric mean of an image. Parameters
image([P,] M, N) ndarray (uint8, uint16)
Input image.
selemndarray
The neighborhood expressed as an ndarray of 1’s and 0’s.
out([P,] M, N) array (same dtype as input)
If None, a new array is allocated.
maskndarray (integer or float), optional
Mask ... | |
doc_2675 |
Immutable index of intervals that are closed on the same side. New in version 0.20.0. Parameters
data:array-like (1-dimensional)
Array-like containing Interval objects from which to build the IntervalIndex.
closed:{‘left’, ‘right’, ‘both’, ‘neither’}, default ‘right’
Whether the intervals are closed on th... | |
doc_2676 |
Compute the pruning path during Minimal Cost-Complexity Pruning. See Minimal Cost-Complexity Pruning for details on the pruning process. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The training input samples. Internally, it will be converted to dtype=np.float32 and if a sparse matri... | |
doc_2677 | See Migration guide for more details. tf.compat.v1.raw_ops.UniqueV2
tf.raw_ops.UniqueV2(
x, axis, out_idx=tf.dtypes.int32, name=None
)
This operation either returns a tensor y containing unique elements along the axis of a tensor. The returned unique elements is sorted in the same order as they occur along axis ... | |
doc_2678 | Computes the eigenvalues and eigenvectors of a complex Hermitian (or real symmetric) matrix input, or of each such matrix in a batched input. For a single matrix input, the tensor of eigenvalues w and the tensor of eigenvectors V decompose the input such that input = V diag(w) Vᴴ, where Vᴴ is the transpose of V for rea... | |
doc_2679 | Return a list of file names as returned by the NLST command. The optional argument is a directory to list (default is the current server directory). Multiple arguments can be used to pass non-standard options to the NLST command. Note If your server supports the command, mlsd() offers a better API. | |
doc_2680 |
Bases: matplotlib.patheffects.AbstractPathEffect The "identity" PathEffect. The Normal PathEffect's sole purpose is to draw the original artist with no special path effect. Parameters
offset(float, float), default: (0, 0)
The (x, y) offset to apply to the path, measured in points. | |
doc_2681 | Wait until a predicate becomes true. The predicate must be a callable which result will be interpreted as a boolean value. The final value is the return value. | |
doc_2682 | Raise ResourceDenied if resource is not available. msg is the argument to ResourceDenied if it is raised. Always returns True if called by a function whose __name__ is '__main__'. Used when tests are executed by test.regrtest. | |
doc_2683 |
Interpolate values according to different methods. Fill NaN values using an interpolation method. Please note that only method='linear' is supported for DataFrame/Series with a MultiIndex. Parameters
method:str, default ‘linear’
Interpolation technique to use. One of: ‘linear’: Ignore the index and treat the v... | |
doc_2684 |
Get the affine part of this transform. | |
doc_2685 |
Set the line width of the Figure rectangle. Parameters
linewidthnumber | |
doc_2686 |
Scale back the data to the original representation Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The rescaled data to be transformed back. Returns
X_tr{ndarray, sparse matrix} of shape (n_samples, n_features)
Transformed array. | |
doc_2687 |
Returns a 1D version of self, as a view. Parameters
order{‘C’, ‘F’, ‘A’, ‘K’}, optional
The elements of a are read using this index order. ‘C’ means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to index the elements in... | |
doc_2688 |
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_2689 | Return True if other refers to the same node as this node. This is especially useful for DOM implementations which use any sort of proxy architecture (because more than one object can refer to the same node). Note This is based on a proposed DOM Level 3 API which is still in the “working draft” stage, but this particu... | |
doc_2690 |
Returns a bool array, where True if input element is real. If element has complex type with zero complex part, the return value for that element is True. Parameters
xarray_like
Input array. Returns
outndarray, bool
Boolean array of same shape as x. See also iscomplex
isrealobj
Return True if x is... | |
doc_2691 |
Container for colormaps that are known to Matplotlib by name. Experimental While we expect the API to be final, we formally mark it as experimental for 3.5 because we want to keep the option to still adapt the API for 3.6 should the need arise. The universal registry instance is matplotlib.colormaps. There should b... | |
doc_2692 | Convert a non-multipart or a multipart/related into a multipart/alternative, moving any existing Content- headers and payload into a (new) first part of the multipart. If boundary is specified, use it as the boundary string in the multipart, otherwise leave the boundary to be automatically created when it is needed (fo... | |
doc_2693 | Same as ForeignKey.related_name. | |
doc_2694 | turtle.addshape(name, shape=None)
There are three different ways to call this function:
name is the name of a gif-file and shape is None: Install the corresponding image shape. >>> screen.register_shape("turtle.gif")
Note Image shapes do not rotate when turning the turtle, so they do not display the heading of th... | |
doc_2695 | Return a floating point number constructed from a number or string x. If the argument is a string, it should contain a decimal number, optionally preceded by a sign, and optionally embedded in whitespace. The optional sign may be '+' or '-'; a '+' sign has no effect on the value produced. The argument may also be a str... | |
doc_2696 | turtle.resetscreen()
Reset all Turtles on the Screen to their initial state. Note This TurtleScreen method is available as a global function only under the name resetscreen. The global function reset is another one derived from the Turtle method reset. | |
doc_2697 |
Return whether the artist uses clipping. | |
doc_2698 |
Set the linestyle(s) for the collection.
linestyle description
'-' or 'solid' solid line
'--' or 'dashed' dashed line
'-.' or 'dashdot' dash-dotted line
':' or 'dotted' dotted line Alternatively a dash tuple of the following form can be provided: (offset, onoffseq),
where onoffseq is an even length tup... | |
doc_2699 | Open an LZMA-compressed file in binary mode. An LZMAFile can wrap an already-open file object, or operate directly on a named file. The filename argument specifies either the file object to wrap, or the name of the file to open (as a str, bytes or path-like object). When wrapping an existing file object, the wrapped fi... |
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