_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
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|---|---|---|
doc_5100 | See Migration guide for more details. tf.compat.v1.raw_ops.SparseTensorDenseAdd
tf.raw_ops.SparseTensorDenseAdd(
a_indices, a_values, a_shape, b, name=None
)
This Op does not require a_indices be sorted in standard lexicographic order.
Args
a_indices A Tensor. Must be one of the following types: int32, ... | |
doc_5101 | An override to the verbose_name from the model’s inner Meta class. | |
doc_5102 | tf.compat.v1.quantize_v2(
input, min_range, max_range, T, mode='MIN_COMBINED', name=None,
round_mode='HALF_AWAY_FROM_ZERO', narrow_range=False, axis=None,
ensure_minimum_range=0.01
) | |
doc_5103 | Base class for warnings about dubious runtime behavior. | |
doc_5104 | Return the match for key in map mapname, or raise an error (nis.error) if there is none. Both should be strings, key is 8-bit clean. Return value is an arbitrary array of bytes (may contain NULL and other joys). Note that mapname is first checked if it is an alias to another name. The domain argument allows overriding ... | |
doc_5105 | See Migration guide for more details. tf.compat.v1.keras.preprocessing.image.random_rotation
tf.keras.preprocessing.image.random_rotation(
x, rg, row_axis=1, col_axis=2, channel_axis=0, fill_mode='nearest',
cval=0.0, interpolation_order=1
)
Arguments
x Input tensor. Must be 3D.
rg Rotation ran... | |
doc_5106 |
Predict regression target for X. The predicted regression target of an input sample is computed as the mean predicted regression targets of the estimators in the ensemble. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The training input samples. Sparse matrices are accepted only if th... | |
doc_5107 | Returns a pretty-printed representation (as valid Python syntax) of the internal graph for the forward method. See Inspecting Code for details. | |
doc_5108 | Return the smallest number representable in the given context (or in the current thread’s context if no context is given) that is larger than the given operand. | |
doc_5109 | This optional argument is used to specify the field to use as the value of the choices in the field’s widget. Be sure it’s a unique field for the model, otherwise the selected value could match more than one object. By default it is set to None, in which case the primary key of each object will be used. For example: # ... | |
doc_5110 |
Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using figure(). (To test whether there is currently a figure on the pyplot figure stack, check whether get_fignums() is empty.) | |
doc_5111 | Others have execute permission. | |
doc_5112 | Send an XHDR command. The hdr argument is a header keyword, e.g. 'subject'. The str argument should have the form 'first-last' where first and last are the first and last article numbers to search. Return a pair (response, list), where list is a list of pairs (id,
text), where id is an article number (as a string) and ... | |
doc_5113 | Unpacks IPv4 mapped addresses like ::ffff:192.0.2.1. If this option is enabled that address would be unpacked to 192.0.2.1. Default is disabled. Can only be used when protocol is set to 'both'. | |
doc_5114 |
Mask an array where a condition is met. Return a as an array masked where condition is True. Any masked values of a or condition are also masked in the output. Parameters
conditionarray_like
Masking condition. When condition tests floating point values for equality, consider using masked_values instead.
aarra... | |
doc_5115 |
True if this transform has a corresponding inverse transform. | |
doc_5116 |
Calculates the radon transform of an image given specified projection angles. Parameters
imagearray_like
Input image. The rotation axis will be located in the pixel with indices (image.shape[0] // 2, image.shape[1] // 2).
thetaarray_like, optional
Projection angles (in degrees). If None, the value is set to... | |
doc_5117 | The name or description of the band, if any. | |
doc_5118 |
Define the picking behavior of the artist. Parameters
pickerNone or bool or float or callable
This can be one of the following:
None: Picking is disabled for this artist (default). A boolean: If True then picking will be enabled and the artist will fire a pick event if the mouse event is over the artist. A fl... | |
doc_5119 |
Return whether locale settings are used for formatting. See also ScalarFormatter.set_useLocale | |
doc_5120 | In-place version of arctanh() | |
doc_5121 | A combination of starmap() and map_async() that iterates over iterable of iterables and calls func with the iterables unpacked. Returns a result object. New in version 3.3. | |
doc_5122 |
Autoscale the scalar limits on the norm instance using the current array, changing only limits that are None | |
doc_5123 | The document encoding is not supported by Expat. | |
doc_5124 | '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_5125 | See Migration guide for more details. tf.compat.v1.data.experimental.ignore_errors
tf.data.experimental.ignore_errors(
log_warning=False
)
Use this transformation to produce a dataset that contains the same elements as the input, but silently drops any elements that caused an error. For example: dataset = tf.dat... | |
doc_5126 | Set blocking or non-blocking read behavior for the window. If delay is negative, blocking read is used (which will wait indefinitely for input). If delay is zero, then non-blocking read is used, and getch() will return -1 if no input is waiting. If delay is positive, then getch() will block for delay milliseconds, and ... | |
doc_5127 |
Load data from Google BigQuery. This function requires the pandas-gbq package. See the How to authenticate with Google BigQuery guide for authentication instructions. Parameters
query:str
SQL-Like Query to return data values.
project_id:str, optional
Google BigQuery Account project ID. Optional when availab... | |
doc_5128 |
Compute the Matthews correlation coefficient (MCC). The Matthews correlation coefficient is used in machine learning as a measure of the quality of binary and multiclass classifications. It takes into account true and false positives and negatives and is generally regarded as a balanced measure which can be used even... | |
doc_5129 | An entry in a SymbolTable corresponding to an identifier in the source. The constructor is not public.
get_name()
Return the symbol’s name.
is_referenced()
Return True if the symbol is used in its block.
is_imported()
Return True if the symbol is created from an import statement.
is_parameter()
Re... | |
doc_5130 | A subclass of OSError, this exception is raised for address-related errors by getaddrinfo() and getnameinfo(). The accompanying value is a pair (error, string) representing an error returned by a library call. string represents the description of error, as returned by the gai_strerror() C function. The numeric error va... | |
doc_5131 | Exactly like Parser, except that headersonly defaults to True. | |
doc_5132 | See Migration guide for more details. tf.compat.v1.data.experimental.prefetch_to_device
tf.data.experimental.prefetch_to_device(
device, buffer_size=None
)
Note: Although the transformation creates a tf.data.Dataset, the transformation must be the final Dataset in the input pipeline.
Args
device A str... | |
doc_5133 | Human-readable version of getcomptype(). Usually 'not compressed' parallels 'NONE'. | |
doc_5134 |
Fit linear model with coordinate descent. Fit is on grid of alphas and best alpha estimated by cross-validation. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
Training data. Pass directly as Fortran-contiguous data to avoid unnecessary memory duplication. If y is mono-output, X can be... | |
doc_5135 | '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_5136 | A “handler of last resort” is available through this attribute. This is a StreamHandler writing to sys.stderr with a level of WARNING, and is used to handle logging events in the absence of any logging configuration. The end result is to just print the message to sys.stderr. This replaces the earlier error message sayi... | |
doc_5137 |
Fit the model with X. Samples random projection according to n_features. Parameters
Xarray-like, shape (n_samples, n_features)
Training data, where n_samples in the number of samples and n_features is the number of features. Returns
selfobject
Returns the transformer. | |
doc_5138 | socket.BDADDR_LOCAL
These are string constants containing Bluetooth addresses with special meanings. For example, BDADDR_ANY can be used to indicate any address when specifying the binding socket with BTPROTO_RFCOMM. | |
doc_5139 | Returns the current date and time, formatted for logging. | |
doc_5140 | tf.compat.v1.graph_util.tensor_shape_from_node_def_name(
graph, input_name
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.compat.v1.graph_util.tensor_shape_from_node_def_name | |
doc_5141 | Update the current file selection to file. | |
doc_5142 | Returns a view of input as a complex tensor. For an input complex tensor of size m1,m2,…,mi,2m1, m2, \dots, mi, 2 , this function returns a new complex tensor of size m1,m2,…,mim1, m2, \dots, mi where the last dimension of the input tensor is expected to represent the real and imaginary components of complex numbers. ... | |
doc_5143 |
Set the minimum theta limit in degrees. | |
doc_5144 | tf.experimental.numpy.log(
x
)
Unsupported arguments: out, where, casting, order, dtype, subok, signature, extobj. See the NumPy documentation for numpy.log. | |
doc_5145 | tf.initializers Classes class Constant: Initializer that generates tensors with constant values. class GlorotNormal: The Glorot normal initializer, also called Xavier normal initializer. class GlorotUniform: The Glorot uniform initializer, also called Xavier uniform initializer. class HeNormal: He normal initializer. ... | |
doc_5146 | A Finder for sys.path and package __path__ attributes. This class implements the importlib.abc.MetaPathFinder ABC. Only class methods are defined by this class to alleviate the need for instantiation.
classmethod find_spec(fullname, path=None, target=None)
Class method that attempts to find a spec for the module sp... | |
doc_5147 | sndhdr.what(filename)
Determines the type of sound data stored in the file filename using whathdr(). If it succeeds, returns a namedtuple as described above, otherwise None is returned. Changed in version 3.5: Result changed from a tuple to a namedtuple.
sndhdr.whathdr(filename)
Determines the type of sound d... | |
doc_5148 |
Call predict on the estimator with the best found parameters. Only available if refit=True and the underlying estimator supports predict. Parameters
Xindexable, length n_samples
Must fulfill the input assumptions of the underlying estimator. | |
doc_5149 | tf.experimental.numpy.diff(
a, n=1, axis=-1
)
Unsupported arguments: prepend, append. See the NumPy documentation for numpy.diff. | |
doc_5150 | Allow simple extension commands notified by server in CAPABILITY response. | |
doc_5151 |
Build a forest of trees from the training set (X, y). Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The training input samples. Internally, its dtype will be converted to dtype=np.float32. If a sparse matrix is provided, it will be converted into a sparse csc_matrix.
yarray-like of ... | |
doc_5152 | The impurity-based feature importances. The higher, the more important the feature. The importance of a feature is computed as the (normalized) total reduction of the criterion brought by that feature. It is also known as the Gini importance. Warning: impurity-based feature importances can be misleading for high cardin... | |
doc_5153 |
Bases: object Callable for retrieving events in a blocking way. add_event(event)[source]
For base class, this just appends an event to events.
cleanup()[source]
Disconnect all callbacks.
on_event(event)[source]
Event handler; will be passed to the current figure to retrieve events.
pop(index=- 1)[... | |
doc_5154 | Return the default value if the requested data doesn’t exist. If type is provided and is a callable it should convert the value, return it or raise a ValueError if that is not possible. In this case the function will return the default as if the value was not found: >>> d = TypeConversionDict(foo='42', bar='blub')
>>> ... | |
doc_5155 | A Popen creationflags parameter to specify that a new process will have a below average priority. New in version 3.7. | |
doc_5156 |
Convert x using the unit type of the xaxis. If the artist is not in contained in an Axes or if the xaxis does not have units, x itself is returned. | |
doc_5157 | Returns the number of non-fixed hyperparameters of the kernel. | |
doc_5158 | Called for notation declarations. notationName, base, and systemId, and publicId are strings if given. If the public identifier is omitted, publicId will be None. | |
doc_5159 | A namespace object that can store data during an application context. This is an instance of Flask.app_ctx_globals_class, which defaults to ctx._AppCtxGlobals. This is a good place to store resources during a request. During testing, you can use the Faking Resources and Context pattern to pre-configure such resources. ... | |
doc_5160 |
A generic data source file (file, http, ftp, …). DataSources can be local files or remote files/URLs. The files may also be compressed or uncompressed. DataSource hides some of the low-level details of downloading the file, allowing you to simply pass in a valid file path (or URL) and obtain a file object. Parameter... | |
doc_5161 |
Bases: matplotlib.ticker.Locator Used to locate radius ticks. Ensures that all ticks are strictly positive. For all other tasks, it delegates to the base Locator (which may be different depending on the scale of the r-axis). nonsingular(vmin, vmax)[source]
Adjust a range as needed to avoid singularities. This met... | |
doc_5162 | sklearn.datasets.load_breast_cancer(*, return_X_y=False, as_frame=False) [source]
Load and return the breast cancer wisconsin dataset (classification). The breast cancer dataset is a classic and very easy binary classification dataset.
Classes 2
Samples per class 212(M),357(B)
Samples total 569
Dimensionality... | |
doc_5163 |
Histogram-based Gradient Boosting Regression Tree. This estimator is much faster than GradientBoostingRegressor for big datasets (n_samples >= 10 000). This estimator has native support for missing values (NaNs). During training, the tree grower learns at each split point whether samples with missing values should go... | |
doc_5164 | initialize a cdrom drive for use init() -> None Initialize the cdrom drive for use. The drive must be initialized for most CD methods to work. Even if the rest of pygame has been initialized. There may be a brief pause while the drive is initialized. Avoid CD.init() if the program should not stop for a second or two. | |
doc_5165 | See Migration guide for more details. tf.compat.v1.train.FloatList
Attributes
value repeated float value | |
doc_5166 |
Fit the model to the data X. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
Training data. Returns
selfBernoulliRBM
The fitted model. | |
doc_5167 | See Migration guide for more details. tf.compat.v1.errors.CancelledError
tf.errors.CancelledError(
node_def, op, message
)
For example, a long-running operation (e.g. tf.QueueBase.enqueue may be cancelled by running another operation (e.g. tf.QueueBase.close, or by tf.Session.close. A step that is running such a... | |
doc_5168 |
True if this transform has a corresponding inverse transform. | |
doc_5169 | The error code used by ValidationError if validation fails. Defaults to "null_characters_not_allowed". | |
doc_5170 | Return True if the message’s payload is a list of sub-EmailMessage objects, otherwise return False. When is_multipart() returns False, the payload should be a string object (which might be a CTE encoded binary payload). Note that is_multipart() returning True does not necessarily mean that “msg.get_content_maintype() =... | |
doc_5171 | This method creates a ctypes instance, copying the buffer from the source object buffer which must be readable. The optional offset parameter specifies an offset into the source buffer in bytes; the default is zero. If the source buffer is not large enough a ValueError is raised. Raises an auditing event ctypes.cdata/b... | |
doc_5172 |
Gauss-Hermite quadrature. Computes the sample points and weights for Gauss-Hermite quadrature. These sample points and weights will correctly integrate polynomials of degree \(2*deg - 1\) or less over the interval \([-\inf, \inf]\) with the weight function \(f(x) = \exp(-x^2)\). Parameters
degint
Number of samp... | |
doc_5173 |
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 array-like or scalar or None
animated bool
antialiased or aa or antialiaseds bool or list of bools
array (... | |
doc_5174 |
Synonym for DataFrame.fillna() with method='bfill'. Returns
Series/DataFrame or None
Object with missing values filled or None if inplace=True. | |
doc_5175 | JoinableQueue, a Queue subclass, is a queue which additionally has task_done() and join() methods.
task_done()
Indicate that a formerly enqueued task is complete. Used by queue consumers. For each get() used to fetch a task, a subsequent call to task_done() tells the queue that the processing on the task is complet... | |
doc_5176 |
Place a legend on the figure. 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 automatical... | |
doc_5177 |
Return the snap setting. See set_snap for details. | |
doc_5178 | Absolute path to the package on the filesystem. Used to look up resources contained in the package. | |
doc_5179 |
Move ticks and ticklabels (if present) to the left of the axes.
Examples using matplotlib.axis.YAxis.tick_left
Bachelor's degrees by gender
Set default y-axis tick labels on the right | |
doc_5180 | exception dbm.error
A tuple containing the exceptions that can be raised by each of the supported modules, with a unique exception also named dbm.error as the first item — the latter is used when dbm.error is raised.
dbm.whichdb(filename)
This function attempts to guess which of the several simple database modu... | |
doc_5181 | Return the absolute value of the argument. This operation is unaffected by the context and is quiet: no flags are changed and no rounding is performed. | |
doc_5182 | tf.sin Compat aliases for migration See Migration guide for more details. tf.compat.v1.math.sin, tf.compat.v1.sin
tf.math.sin(
x, name=None
)
Given an input tensor, this function computes sine of every element in the tensor. Input range is (-inf, inf) and output range is [-1,1]. x = tf.constant([-float("inf"), -... | |
doc_5183 | '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_5184 |
Compute an uniformly refined triangulation refi_triangulation of the encapsulated triangulation. This function refines the encapsulated triangulation by splitting each father triangle into 4 child sub-triangles built on the edges midside nodes, recursing subdiv times. In the end, each triangle is hence divided into 4... | |
doc_5185 | Unparse an ast.AST object and generate a string with code that would produce an equivalent ast.AST object if parsed back with ast.parse(). Warning The produced code string will not necessarily be equal to the original code that generated the ast.AST object (without any compiler optimizations, such as constant tuples/f... | |
doc_5186 | tf.linalg.tensordot Compat aliases for migration See Migration guide for more details. tf.compat.v1.linalg.tensordot, tf.compat.v1.tensordot
tf.tensordot(
a, b, axes, name=None
)
Tensordot (also known as tensor contraction) sums the product of elements from a and b over the indices specified by a_axes and b_axes... | |
doc_5187 | A python serializer for the payload. The default is a compact JSON derived serializer with support for some extra Python types such as datetime objects or tuples. | |
doc_5188 |
alias of mpl_toolkits.axisartist.axisline_style._FancyAxislineStyle.FilledArrow | |
doc_5189 | The abstract base session model.
session_key
Primary key. The field itself may contain up to 40 characters. The current implementation generates a 32-character string (a random sequence of digits and lowercase ASCII letters).
session_data
A string containing an encoded and serialized session dictionary.
e... | |
doc_5190 | The smallest possible difference between non-equal date objects, timedelta(days=1). | |
doc_5191 | Asserts that a form field behaves correctly with various inputs.
Parameters:
fieldclass – the class of the field to be tested.
valid – a dictionary mapping valid inputs to their expected cleaned values.
invalid – a dictionary mapping invalid inputs to one or more raised error messages.
field_args – the args p... | |
doc_5192 | See Migration guide for more details. tf.compat.v1.app.flags.disclaim_key_flags
tf.compat.v1.flags.disclaim_key_flags()
Normally, the module that calls the DEFINE_xxx functions claims the flag to be its key flag. This is undesirable for modules that define additional DEFINE_yyy functions with its own flag parsers an... | |
doc_5193 |
Bases: matplotlib.scale.ScaleBase The default linear scale. get_transform()[source]
Return the transform for linear scaling, which is just the IdentityTransform.
name='linear'
set_default_locators_and_formatters(axis)[source]
Set the locators and formatters of axis to instances suitable for this scale. | |
doc_5194 | draw a rectangle rectangle(surface, rect, color) -> None Draws an unfilled rectangle on the given surface. For a filled rectangle use box().
Parameters:
surface (Surface) -- surface to draw on
rect (Rect) -- rectangle to draw, position and dimensions
color (Color or tuple(int, int, int, [int])) -- color to ... | |
doc_5195 |
Draw samples from a multinomial distribution. The multinomial distribution is a multivariate generalization of the binomial distribution. Take an experiment with one of p possible outcomes. An example of such an experiment is throwing a dice, where the outcome can be 1 through 6. Each sample drawn from the distributi... | |
doc_5196 |
Translate slice objects to concatenation along the first axis. This is the masked array version of lib.index_tricks.RClass. See also lib.index_tricks.RClass
Examples >>> np.ma.mr_[np.ma.array([1,2,3]), 0, 0, np.ma.array([4,5,6])]
masked_array(data=[1, 2, 3, ..., 4, 5, 6],
mask=False,
fill_valu... | |
doc_5197 | Equivalent to as_bytes(). Allows bytes(msg) to produce a bytes object containing the formatted message. New in version 3.4. | |
doc_5198 |
Compute the total log probability density under the model. Parameters
Xarray-like of shape (n_samples, n_features)
List of n_features-dimensional data points. Each row corresponds to a single data point.
yNone
Ignored. This parameter exists only for compatibility with Pipeline. Returns
logprobfloat
... | |
doc_5199 |
Inpaint masked points in image with biharmonic equations. Parameters
image(M[, N[, …, P]][, C]) ndarray
Input image.
mask(M[, N[, …, P]]) ndarray
Array of pixels to be inpainted. Have to be the same shape as one of the ‘image’ channels. Unknown pixels have to be represented with 1, known pixels - with 0.
... |
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