_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_17000 |
Bind the given figure to the tools. Parameters
figureFigure
update_toolsbool, default: True
Force tools to update figure. | |
doc_17001 |
Bases: torch.distributions.distribution.Distribution Creates a multivariate normal (also called Gaussian) distribution parameterized by a mean vector and a covariance matrix. The multivariate normal distribution can be parameterized either in terms of a positive definite covariance matrix Σ\mathbf{\Sigma} or a posit... | |
doc_17002 | Create a Timer instance with the given statement, setup code and timer function and run its timeit() method with number executions. The optional globals argument specifies a namespace in which to execute the code. Changed in version 3.5: The optional globals parameter was added. | |
doc_17003 |
Inner product of two arrays. Ordinary inner product of vectors for 1-D arrays (without complex conjugation), in higher dimensions a sum product over the last axes. Parameters
a, barray_like
If a and b are nonscalar, their last dimensions must match. Returns
outndarray
If a and b are both scalars or both... | |
doc_17004 | See Migration guide for more details. tf.compat.v1.test.gpu_device_name
tf.test.gpu_device_name() | |
doc_17005 |
Set whether to use antialiased rendering. Parameters
bbool | |
doc_17006 | Insert nlines lines into the specified window above the current line. The nlines bottom lines are lost. For negative nlines, delete nlines lines starting with the one under the cursor, and move the remaining lines up. The bottom nlines lines are cleared. The current cursor position remains the same. | |
doc_17007 |
Build a layout of Axes based on ASCII art or nested lists. This is a helper function to build complex GridSpec layouts visually. Note This API is provisional and may be revised in the future based on early user feedback. Parameters
mosaiclist of list of {hashable or nested} or str
A visual layout of how you w... | |
doc_17008 | Releases the thread lock acquired with acquire(). | |
doc_17009 | See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayGather
tf.raw_ops.TensorArrayGather(
handle, indices, flow_in, dtype, element_shape=None, name=None
)
Args
handle A Tensor of type mutable string.
indices A Tensor of type int32.
flow_in A Tensor of type float32.
dtype... | |
doc_17010 | Find longest matching block in a[alo:ahi] and b[blo:bhi]. If isjunk was omitted or None, find_longest_match() returns (i, j, k) such that a[i:i+k] is equal to b[j:j+k], where alo
<= i <= i+k <= ahi and blo <= j <= j+k <= bhi. For all (i', j',
k') meeting those conditions, the additional conditions k >= k', i
<= i', and... | |
doc_17011 | class argparse.RawTextHelpFormatter
class argparse.ArgumentDefaultsHelpFormatter
class argparse.MetavarTypeHelpFormatter | |
doc_17012 |
Set multiple properties at once. Supported properties are
Property Description
3d_properties unknown
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
antialiased or aa bool or None
capstyle CapStyle or {... | |
doc_17013 | Separate the underlying binary buffer from the TextIOBase and return it. After the underlying buffer has been detached, the TextIOBase is in an unusable state. Some TextIOBase implementations, like StringIO, may not have the concept of an underlying buffer and calling this method will raise UnsupportedOperation. New i... | |
doc_17014 | See Migration guide for more details. tf.compat.v1.raw_ops.TensorListConcatLists
tf.raw_ops.TensorListConcatLists(
input_a, input_b, element_dtype, name=None
)
Args
input_a A Tensor of type variant.
input_b A Tensor of type variant.
element_dtype A tf.DType.
name A name for the operati... | |
doc_17015 |
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_17016 |
Bootstrap plot on mean, median and mid-range statistics. The bootstrap plot is used to estimate the uncertainty of a statistic by relaying on random sampling with replacement [1]. This function will generate bootstrapping plots for mean, median and mid-range statistics for the given number of samples of the given siz... | |
doc_17017 | Returns the root element for this tree. | |
doc_17018 |
Return the clipbox. | |
doc_17019 |
Alias for set_linestyle. | |
doc_17020 |
List functions that are overridable via __torch_function__ Returns
A dictionary that maps namespaces that contain overridable functions to functions in that namespace that can be overridden. Return type
Dict[Any, List[Callable]] | |
doc_17021 |
Permutation importance for feature evaluation [BRE]. The estimator is required to be a fitted estimator. X can be the data set used to train the estimator or a hold-out set. The permutation importance of a feature is calculated as follows. First, a baseline metric, defined by scoring, is evaluated on a (potentially d... | |
doc_17022 | Create a new socket using the given address family, socket type and protocol number. The address family should be AF_INET (the default), AF_INET6, AF_UNIX, AF_CAN, AF_PACKET, or AF_RDS. The socket type should be SOCK_STREAM (the default), SOCK_DGRAM, SOCK_RAW or perhaps one of the other SOCK_ constants. The protocol nu... | |
doc_17023 | tf.linalg.einsum Compat aliases for migration See Migration guide for more details. tf.compat.v1.einsum, tf.compat.v1.linalg.einsum
tf.einsum(
equation, *inputs, **kwargs
)
Einsum allows defining Tensors by defining their element-wise computation. This computation is defined by equation, a shorthand form based o... | |
doc_17024 |
The Exponentiation kernel takes one base kernel and a scalar parameter \(p\) and combines them via \[k_{exp}(X, Y) = k(X, Y) ^p\] Note that the __pow__ magic method is overridden, so Exponentiation(RBF(), 2) is equivalent to using the ** operator with RBF() ** 2. Read more in the User Guide. New in version 0.18. ... | |
doc_17025 | codecs.BOM_BE
codecs.BOM_LE
codecs.BOM_UTF8
codecs.BOM_UTF16
codecs.BOM_UTF16_BE
codecs.BOM_UTF16_LE
codecs.BOM_UTF32
codecs.BOM_UTF32_BE
codecs.BOM_UTF32_LE
These constants define various byte sequences, being Unicode byte order marks (BOMs) for several encodings. They are used in UTF-16 and UTF-32 d... | |
doc_17026 | In-place version of xlogy() | |
doc_17027 |
Dict {group name -> group labels}. | |
doc_17028 | See Migration guide for more details. tf.compat.v1.rank
tf.rank(
input, name=None
)
See also tf.shape. Returns a 0-D int32 Tensor representing the rank of input. For example: # shape of tensor 't' is [2, 2, 3]
t = tf.constant([[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]])
tf.rank(t) # 3
Note: The rank of a... | |
doc_17029 |
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_17030 | sklearn.utils.check_scalar(x, name, target_type, *, min_val=None, max_val=None) [source]
Validate scalar parameters type and value. Parameters
xobject
The scalar parameter to validate.
namestr
The name of the parameter to be printed in error messages.
target_typetype or tuple
Acceptable data types for t... | |
doc_17031 |
Returns
transformTransform
The transform used for drawing y-axis labels, which will add pad_points of padding (in points) between the axis and the label. The x-direction is in axis coordinates and the y-direction is in data coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}
The tex... | |
doc_17032 |
Return the capstyle. | |
doc_17033 | tf.compat.v1.losses.log_loss(
labels, predictions, weights=1.0, epsilon=1e-07, scope=None,
loss_collection=tf.GraphKeys.LOSSES, reduction=Reduction.SUM_BY_NONZERO_WEIGHTS
)
weights acts as a coefficient for the loss. If a scalar is provided, then the loss is simply scaled by the given value. If weights is a te... | |
doc_17034 | Search fragment for a slice of length length samples (not bytes!) with maximum energy, i.e., return i for which rms(fragment[i*2:(i+length)*2]) is maximal. The fragments should both contain 2-byte samples. The routine takes time proportional to len(fragment). | |
doc_17035 | This function must do all the work required to service a request. The default implementation does nothing. Several instance attributes are available to it; the request is available as self.request; the client address as self.client_address; and the server instance as self.server, in case it needs access to per-server i... | |
doc_17036 |
Create a new composite transform that is the result of applying Affine2DBase a then Affine2DBase b. You will generally not call this constructor directly but write a +
b instead, which will automatically choose the best kind of composite transform instance to create. | |
doc_17037 |
Create a new "blended" transform using x_transform to transform the x-axis and y_transform to transform the y-axis. Both x_transform and y_transform must be 2D affine transforms. You will generally not call this constructor directly but use the blended_transform_factory function instead, which can determine automatic... | |
doc_17038 |
Alias for set_edgecolor. | |
doc_17039 | itertools.islice(iterable, start, stop[, step])
Make an iterator that returns selected elements from the iterable. If start is non-zero, then elements from the iterable are skipped until start is reached. Afterward, elements are returned consecutively unless step is set higher than one which results in items being sk... | |
doc_17040 | Remove the payload and all of the Content- headers, leaving all other headers intact and in their original order. | |
doc_17041 |
Set the edgecolor(s) of the LineCollection. Parameters
ccolor or list of colors
Single color (all lines have same color), or a sequence of rgba tuples; if it is a sequence the lines will cycle through the sequence. | |
doc_17042 |
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
antialiased or aa bool or None
capstyle CapStyle or {'butt', 'projecting', 'r... | |
doc_17043 | Return the MAJOR.MINOR Python version number as a string. Similar to '%d.%d' % sys.version_info[:2]. | |
doc_17044 |
Insert a get_attr node into the Graph. A get_attr Node represents the fetch of an attribute from the Module hierarchy. Parameters
qualified_name (str) – the fully-qualified name of the attribute to be retrieved. For example, if the traced Module has a submodule named foo, which has a submodule named bar, which ha... | |
doc_17045 | Simply handles the multiplication between the parameter being pruned and the generated mask. Fetches the mask and the original tensor from the module and returns the pruned version of the tensor. Parameters
module (nn.Module) – module containing the tensor to prune Returns
pruned version of the input tensor Return... | |
doc_17046 | Use this at the end of test_main whenever sub-processes are started. This will help ensure that no extra children (zombies) stick around to hog resources and create problems when looking for refleaks. | |
doc_17047 |
Returns a clone of self with given hyperparameters theta. Parameters
thetandarray of shape (n_dims,)
The hyperparameters | |
doc_17048 | Converts the dataclass instance to a tuple (by using the factory function tuple_factory). Each dataclass is converted to a tuple of its field values. dataclasses, dicts, lists, and tuples are recursed into. Continuing from the previous example: assert astuple(p) == (10, 20)
assert astuple(c) == ([(0, 0), (10, 4)],)
Ra... | |
doc_17049 |
Returns the indices that would partition this array. Refer to numpy.argpartition for full documentation. New in version 1.8.0. See also numpy.argpartition
equivalent function | |
doc_17050 | Return True if it is one of character device, block device or FIFO. | |
doc_17051 | See Migration guide for more details. tf.compat.v1.raw_ops.IteratorFromStringHandle
tf.raw_ops.IteratorFromStringHandle(
string_handle, output_types=[], output_shapes=[], name=None
)
Args
string_handle A Tensor of type string. A string representation of the given handle.
output_types An optional l... | |
doc_17052 | Token value for "|=". | |
doc_17053 | This function returns the C string starting at memory address address as a bytes object. If size is specified, it is used as size, otherwise the string is assumed to be zero-terminated. Raises an auditing event ctypes.string_at with arguments address, size. | |
doc_17054 | Send an ARTICLE command, where message_spec has the same meaning as for stat(). Return a tuple (response, info) where info is a namedtuple with three attributes number, message_id and lines (in that order). number is the article number in the group (or 0 if the information is not available), message_id the message id a... | |
doc_17055 | numpy.int16
numpy.int32
numpy.int64
Aliases for the signed integer types (one of numpy.byte, numpy.short, numpy.intc, numpy.int_ and numpy.longlong) with the specified number of bits. Compatible with the C99 int8_t, int16_t, int32_t, and int64_t, respectively. | |
doc_17056 | Applies a 1D transposed convolution operator over an input signal composed of several input planes, sometimes also called “deconvolution”. This operator supports TensorFloat32. See ConvTranspose1d for details and output shape. Note In some circumstances when given tensors on a CUDA device and using CuDNN, this operato... | |
doc_17057 |
Set the edgecolor(s) of the collection. Parameters
ccolor or list of colors or 'face'
The collection edgecolor(s). If a sequence, the patches cycle through it. If 'face', match the facecolor. | |
doc_17058 |
Leave P Group(s) Out cross-validator Provides train/test indices to split data according to a third-party provided group. This group information can be used to encode arbitrary domain specific stratifications of the samples as integers. For instance the groups could be the year of collection of the samples and thus a... | |
doc_17059 | The backends are not expected to handle non-affine transformations themselves. classmatplotlib.transforms.Affine2D(matrix=None, **kwargs)[source]
Bases: matplotlib.transforms.Affine2DBase A mutable 2D affine transformation. Initialize an Affine transform from a 3x3 numpy float array: a c e
b d f
0 0 1
If matrix i... | |
doc_17060 | Insert CGI variables for the current request into the environ attribute. | |
doc_17061 | See Migration guide for more details. tf.compat.v1.raw_ops.MatrixBandPart
tf.raw_ops.MatrixBandPart(
input, num_lower, num_upper, name=None
)
The band part is computed as follows: Assume input has k dimensions [I, J, K, ..., M, N], then the output is a tensor with the same shape where band[i, j, k, ..., m, n] = ... | |
doc_17062 | The frame which surrounds the text and scroll bar widgets. | |
doc_17063 |
Set the pick radius used for containment tests. Parameters
prfloat
Pick radius, in points. | |
doc_17064 | The content type to use for the response. content_type is passed as a keyword argument to response_class. Default is None – meaning that Django uses 'text/html'. | |
doc_17065 |
Writer for JavaScript-based HTML movies. 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 seco... | |
doc_17066 | Return the list of stack frames for this Task. If the wrapped coroutine is not done, this returns the stack where it is suspended. If the coroutine has completed successfully or was cancelled, this returns an empty list. If the coroutine was terminated by an exception, this returns the list of traceback frames. The fra... | |
doc_17067 | See Migration guide for more details. tf.compat.v1.raw_ops.DeserializeManySparse
tf.raw_ops.DeserializeManySparse(
serialized_sparse, dtype, name=None
)
The input serialized_sparse must be a string matrix of shape [N x 3] where N is the minibatch size and the rows correspond to packed outputs of SerializeSparse.... | |
doc_17068 | Pass it a filename and it will return a secure version of it. This filename can then safely be stored on a regular file system and passed to os.path.join(). The filename returned is an ASCII only string for maximum portability. On windows systems the function also makes sure that the file is not named after one of the ... | |
doc_17069 |
Return the minimum along a given axis. Refer to numpy.amin for full documentation. See also numpy.amin
equivalent function | |
doc_17070 | '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_17071 | '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_17072 | This method checks if the frame is somewhere below botframe in the call stack. botframe is the frame in which debugging started. | |
doc_17073 | The abstract base class for all I/O classes, acting on streams of bytes. There is no public constructor. This class provides empty abstract implementations for many methods that derived classes can override selectively; the default implementations represent a file that cannot be read, written or seeked. Even though IOB... | |
doc_17074 |
Bases: matplotlib.backend_bases.Event An event triggered by a figure being closed. | |
doc_17075 | Returns the number of samples that are in the hardware buffer yet to be played. | |
doc_17076 | Dump the tracebacks of all threads into file. If all_threads is False, dump only the current thread. Changed in version 3.5: Added support for passing file descriptor to this function. | |
doc_17077 | Checks for a non-ASCII character (ordinal values 0x80 and above). | |
doc_17078 | Register the read end of pipe in the event loop. protocol_factory must be a callable returning an asyncio protocol implementation. pipe is a file-like object. Return pair (transport, protocol), where transport supports the ReadTransport interface and protocol is an object instantiated by the protocol_factory. With Sele... | |
doc_17079 |
Base object if memory is from some other object. Examples The base of an array that owns its memory is None: >>> x = np.array([1,2,3,4])
>>> x.base is None
True
Slicing creates a view, whose memory is shared with x: >>> y = x[2:]
>>> y.base is x
True | |
doc_17080 |
LabelSpreading model for semi-supervised learning This model is similar to the basic Label Propagation algorithm, but uses affinity matrix based on the normalized graph Laplacian and soft clamping across the labels. Read more in the User Guide. Parameters
kernel{‘knn’, ‘rbf’} or callable, default=’rbf’
String i... | |
doc_17081 | In order to use another client-side library to handle translations, you may want to take advantage of the JSONCatalog view. It’s similar to JavaScriptCatalog but returns a JSON response. See the documentation for JavaScriptCatalog to learn about possible values and use of the domain and packages attributes. The respons... | |
doc_17082 |
Return threshold value based on minimum method. The histogram of the input image is computed if not provided and smoothed until there are only two maxima. Then the minimum in between is the threshold value. Either image or hist must be provided. In case hist is given, the actual histogram of the image is ignored. Pa... | |
doc_17083 | Cartesian product of input iterables. Roughly equivalent to nested for-loops in a generator expression. For example, product(A, B) returns the same as ((x,y) for x in A for y in B). The nested loops cycle like an odometer with the rightmost element advancing on every iteration. This pattern creates a lexicographic orde... | |
doc_17084 |
Alias for set_drawstyle. | |
doc_17085 |
Create an RGB representation of a gray-level image. Parameters
imagearray_like
Input image.
alphabool, optional
Ensure that the output image has an alpha layer. If None, alpha layers are passed through but not created. Returns
rgb(…, 3) ndarray
RGB image. A new dimension of length 3 is added to inpu... | |
doc_17086 |
Bases: object A helper class to implement a renderer that switches between vector and raster drawing. An example may be a PDF writer, where most things are drawn with PDF vector commands, but some very complex objects, such as quad meshes, are rasterised and then output as images. Parameters
figurematplotlib.figu... | |
doc_17087 | Alias for torch.clamp(). | |
doc_17088 | Logging options of subsequent syslog() calls can be set by calling openlog(). syslog() will call openlog() with no arguments if the log is not currently open. The optional ident keyword argument is a string which is prepended to every message, and defaults to sys.argv[0] with leading path components stripped. The optio... | |
doc_17089 | See Migration guide for more details. tf.compat.v1.raw_ops.ExtractVolumePatches
tf.raw_ops.ExtractVolumePatches(
input, ksizes, strides, padding, name=None
)
Args
input A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint6... | |
doc_17090 | In-place version of fix() | |
doc_17091 |
Performs a single optimization step. Parameters
closure (callable, optional) – A closure that reevaluates the model and returns the loss. | |
doc_17092 | Timeout in seconds for tests using a network server listening on the network local loopback interface like 127.0.0.1. The timeout is long enough to prevent test failure: it takes into account that the client and the server can run in different threads or even different processes. The timeout should be long enough for c... | |
doc_17093 |
Predict new data by linear interpolation. Parameters
Tarray-like of shape (n_samples,) or (n_samples, 1)
Data to transform. Returns
y_predndarray of shape (n_samples,)
Transformed data. | |
doc_17094 | This is the counterpart of getattr(). The arguments are an object, a string and an arbitrary value. The string may name an existing attribute or a new attribute. The function assigns the value to the attribute, provided the object allows it. For example, setattr(x, 'foobar', 123) is equivalent to x.foobar = 123. | |
doc_17095 |
Check whether an array-like or dtype is of the Categorical 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 Categorical dtype. Examples
>>> is_categorical_dtype(object)
False
>>> is_categorical_dtype(... | |
doc_17096 |
Return the picking behavior of the artist. The possible values are described in set_picker. See also
set_picker, pickable, pick | |
doc_17097 | Reserved for future definition. | |
doc_17098 | Return the representation of x in polar coordinates. Returns a pair (r, phi) where r is the modulus of x and phi is the phase of x. polar(x) is equivalent to (abs(x),
phase(x)). | |
doc_17099 |
Return the value of an Artist's property, or print all of them. Parameters
objArtist
The queried artist; e.g., a Line2D, a Text, or an Axes.
propertystr or None, default: None
If property is 'somename', this function returns obj.get_somename(). If it's None (or unset), it prints all gettable properties from... |
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