_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_200 | Deprecated since version 3.9: Deprecated in favor of url. | |
doc_201 |
Project data to maximize class separation. Parameters
Xarray-like of shape (n_samples, n_features)
Input data. Returns
X_newndarray of shape (n_samples, n_components)
Transformed data. | |
doc_202 |
Return an array with the elements of self right-justified in a string of length width. See also char.rjust | |
doc_203 |
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_204 |
Compute standard deviation of groups, excluding missing values. Parameters
ddof:int, default 1
Degrees of freedom. Returns
DataFrame or Series
Standard deviation of values within each group. | |
doc_205 |
Initialize self. See help(type(self)) for accurate signature. | |
doc_206 | This decorator adds a Cache-Control: max-age=0, no-cache, no-store,
must-revalidate, private header to a response to indicate that a page should never be cached. | |
doc_207 | This class implements semaphore objects. A semaphore manages an atomic counter representing the number of release() calls minus the number of acquire() calls, plus an initial value. The acquire() method blocks if necessary until it can return without making the counter negative. If not given, value defaults to 1. The o... | |
doc_208 |
Set parameters within this locator. | |
doc_209 | See Migration guide for more details. tf.compat.v1.raw_ops.ResourceAccumulatorNumAccumulated
tf.raw_ops.ResourceAccumulatorNumAccumulated(
handle, name=None
)
Args
handle A Tensor of type resource. The handle to an accumulator.
name A name for the operation (optional).
Returns A Tensor o... | |
doc_210 |
Return self|value. | |
doc_211 | tf.compat.v1.train.Scaffold(
init_op=None, init_feed_dict=None, init_fn=None, ready_op=None,
ready_for_local_init_op=None, local_init_op=None, summary_op=None, saver=None,
copy_from_scaffold=None, local_init_feed_dict=None
)
When you build a model for training you usually need ops to initialize variables, ... | |
doc_212 | Files and subdirectories only in a. | |
doc_213 |
Set the position of the spine. Spine position is specified by a 2 tuple of (position type, amount). The position types are: 'outward': place the spine out from the data area by the specified number of points. (Negative values place the spine inwards.) 'axes': place the spine at the specified Axes coordinate (0 to 1)... | |
doc_214 | Use BoundField.initial to retrieve initial data for a form field. It retrieves the data from Form.initial if present, otherwise trying Field.initial. Callable values are evaluated. See Initial form values for more examples. BoundField.initial caches its return value, which is useful especially when dealing with callabl... | |
doc_215 | Same as ModelChoiceField.to_field_name. | |
doc_216 |
Set the artist transform. Parameters
tTransform | |
doc_217 | Access the fitted transformer by name. Read-only attribute to access any transformer by given name. Keys are transformer names and values are the fitted transformer objects. | |
doc_218 |
Create color map from linear mapping segments segmentdata argument is a dictionary with a red, green and blue entries. Each entry should be a list of x, y0, y1 tuples, forming rows in a table. Entries for alpha are optional. Example: suppose you want red to increase from 0 to 1 over the bottom half, green to do the s... | |
doc_219 | tf.compat.v1.feature_column.categorical_column_with_vocabulary_file(
key, vocabulary_file, vocabulary_size=None, num_oov_buckets=0,
default_value=None, dtype=tf.dtypes.string
)
Use this when your inputs are in string or integer format, and you have a vocabulary file that maps each value to an integer ID. By de... | |
doc_220 | Return the thread stack size used when creating new threads. The optional size argument specifies the stack size to be used for subsequently created threads, and must be 0 (use platform or configured default) or a positive integer value of at least 32,768 (32 KiB). If size is not specified, 0 is used. If changing the t... | |
doc_221 | from django.utils.translation import gettext_lazy as _
def validate_even(value):
if value % 2 != 0:
raise ValidationError(
_('%(value)s is not an even number'),
params={'value': value},
)
You can add this to a model field via the field’s validators argument: from django.db ... | |
doc_222 | os.O_DIRECT
os.O_DIRECTORY
os.O_NOFOLLOW
os.O_NOATIME
os.O_PATH
os.O_TMPFILE
os.O_SHLOCK
os.O_EXLOCK
The above constants are extensions and not present if they are not defined by the C library. Changed in version 3.4: Add O_PATH on systems that support it. Add O_TMPFILE, only available on Linux Kernel ... | |
doc_223 |
Broadcast any number of arrays against each other. Parameters
`*args`array_likes
The arrays to broadcast.
subokbool, optional
If True, then sub-classes will be passed-through, otherwise the returned arrays will be forced to be a base-class array (default). Returns
broadcastedlist of arrays
These arr... | |
doc_224 | sklearn.linear_model.ridge_regression(X, y, alpha, *, sample_weight=None, solver='auto', max_iter=None, tol=0.001, verbose=0, random_state=None, return_n_iter=False, return_intercept=False, check_input=True) [source]
Solve the ridge equation by the method of normal equations. Read more in the User Guide. Parameters ... | |
doc_225 |
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 a... | |
doc_226 |
Iterate over DataFrame rows as (index, Series) pairs. Yields
index:label or tuple of label
The index of the row. A tuple for a MultiIndex.
data:Series
The data of the row as a Series. See also DataFrame.itertuples
Iterate over DataFrame rows as namedtuples of the values. DataFrame.items
Iterate ove... | |
doc_227 |
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_228 | Implements the 'backslashreplace' error handling (for text encodings only): malformed data is replaced by a backslashed escape sequence. | |
doc_229 |
Truncate series to length size. Reduce the series to length size by discarding the high degree terms. The value of size must be a positive integer. This can be useful in least squares where the coefficients of the high degree terms may be very small. Parameters
sizepositive int
The series is reduced to length s... | |
doc_230 | Unescape '&', '<', and '>' in a string of data. You can unescape other strings of data by passing a dictionary as the optional entities parameter. The keys and values must all be strings; each key will be replaced with its corresponding value. '&', '<', and '>' are always unescaped, even if entities ... | |
doc_231 |
Autoscale the scalar limits on the norm instance using the current array | |
doc_232 | Gathers values along an axis specified by dim. For a 3-D tensor the output is specified by: out[i][j][k] = input[index[i][j][k]][j][k] # if dim == 0
out[i][j][k] = input[i][index[i][j][k]][k] # if dim == 1
out[i][j][k] = input[i][j][index[i][j][k]] # if dim == 2
input and index must have the same number of dimensio... | |
doc_233 |
Compute the histogram of a dataset. Parameters
aarray_like
Input data. The histogram is computed over the flattened array.
binsint or sequence of scalars or str, optional
If bins is an int, it defines the number of equal-width bins in the given range (10, by default). If bins is a sequence, it defines a mon... | |
doc_234 |
Attributes
key int32 key
value TensorShapeProto value | |
doc_235 |
Return variable labels as a dict, associating each variable name with corresponding label. Returns
dict | |
doc_236 | The part of the name preceding the colon if there is one, else the empty string. | |
doc_237 |
Marks a middleware as synchronous-only. (The default in Django, but this allows you to future-proof if the default ever changes in a future release.) | |
doc_238 | from django.utils.translation import gettext as _
def my_view(request):
output = _("Welcome to my site.")
return HttpResponse(output)
You could code this without using the alias. This example is identical to the previous one: from django.http import HttpResponse
from django.utils.translation import gettext
d... | |
doc_239 | See Migration guide for more details. tf.compat.v1.raw_ops.QuantizedReluX
tf.raw_ops.QuantizedReluX(
features, max_value, min_features, max_features, out_type=tf.dtypes.quint8,
name=None
)
Args
features A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16.
max_val... | |
doc_240 |
Set the locator of the major ticker. Parameters
locatorLocator
Examples using matplotlib.axis.Axis.set_major_locator
Hatch-filled histograms
Creating a timeline with lines, dates, and text
Date tick labels
Anatomy of a figure
3D surface (colormap)
3D surface (checker... | |
doc_241 | See Migration guide for more details. tf.compat.v1.train.Features.FeatureEntry
Attributes
key string key
value Feature value | |
doc_242 | tf.nn.embedding_lookup_sparse(
params, sp_ids, sp_weights, combiner=None, max_norm=None, name=None
)
This op assumes that there is at least one id for each row in the dense tensor represented by sp_ids (i.e. there are no rows with empty features), and that all the indices of sp_ids are in canonical row-major order... | |
doc_243 |
Resume the animation. | |
doc_244 | A string containing the format (in struct module style) for each element in the view. A memoryview can be created from exporters with arbitrary format strings, but some methods (e.g. tolist()) are restricted to native single element formats. Changed in version 3.3: format 'B' is now handled according to the struct mod... | |
doc_245 |
Return the SubplotParams for the GridSpec. In order of precedence the values are taken from non-None attributes of the GridSpec the provided figure
rcParams["figure.subplot.*"] | |
doc_246 | See Migration guide for more details. tf.compat.v1.raw_ops.ReaderNumWorkUnitsCompleted
tf.raw_ops.ReaderNumWorkUnitsCompleted(
reader_handle, name=None
)
Args
reader_handle A Tensor of type mutable string. Handle to a Reader.
name A name for the operation (optional).
Returns A Tensor of ... | |
doc_247 | sklearn.metrics.label_ranking_loss(y_true, y_score, *, sample_weight=None) [source]
Compute Ranking loss measure. Compute the average number of label pairs that are incorrectly ordered given y_score weighted by the size of the label set and the number of labels not in the label set. This is similar to the error set s... | |
doc_248 | A subclass of HTTPException. | |
doc_249 |
Parameters:
regex – If not None, overrides regex. Can be a regular expression string or a pre-compiled regular expression.
message – If not None, overrides message.
code – If not None, overrides code.
inverse_match – If not None, overrides inverse_match.
flags – If not None, overrides flags. In that case, re... | |
doc_250 |
Predict class log-probabilities for X. Parameters
Xarray of shape [n_samples, n_features]
The input samples. Returns
parray of shape (n_samples, n_classes)
The class log-probabilities of the input samples. The order of the classes corresponds to that in the attribute classes_. | |
doc_251 |
Return the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation. | |
doc_252 |
Return the coefficient of determination \(R^2\) of the prediction. The coefficient \(R^2\) is defined as \((1 - \frac{u}{v})\), where \(u\) is the residual sum of squares ((y_true - y_pred)
** 2).sum() and \(v\) is the total sum of squares ((y_true -
y_true.mean()) ** 2).sum(). The best possible score is 1.0 and it c... | |
doc_253 |
Return whether rotations of the transform affect the text direction. | |
doc_254 |
Transform self.module and return the transformed GraphModule. | |
doc_255 | tf.experimental.numpy.fabs(
x
)
Unsupported arguments: out, where, casting, order, dtype, subok, signature, extobj. See the NumPy documentation for numpy.fabs. | |
doc_256 |
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_257 | Logs a message with level ERROR on the root logger. The arguments are interpreted as for debug(). | |
doc_258 | Return a result record of the query, through calling MsiViewFetch(). | |
doc_259 | class sklearn.neural_network.MLPClassifier(hidden_layer_sizes=100, activation='relu', *, solver='adam', alpha=0.0001, batch_size='auto', learning_rate='constant', learning_rate_init=0.001, power_t=0.5, max_iter=200, shuffle=True, random_state=None, tol=0.0001, verbose=False, warm_start=False, momentum=0.9, nesterovs_mo... | |
doc_260 | tf.experimental.numpy.kron(
a, b
)
See the NumPy documentation for numpy.kron. | |
doc_261 |
Fills the input Tensor with values drawn from the normal distribution N(mean,std2)\mathcal{N}(\text{mean}, \text{std}^2) . Parameters
tensor – an n-dimensional torch.Tensor
mean – the mean of the normal distribution
std – the standard deviation of the normal distribution Examples >>> w = torch.empty(3, 5)
>... | |
doc_262 | Is raised by TarInfo.frombuf() if the buffer it gets is invalid. | |
doc_263 |
Draw the Artist (and its children) using the given renderer. This has no effect if the artist is not visible (Artist.get_visible returns False). Parameters
rendererRendererBase subclass.
Notes This method is overridden in the Artist subclasses. | |
doc_264 | tf.experimental.numpy.cbrt(
x
)
Unsupported arguments: out, where, casting, order, dtype, subok, signature, extobj. See the NumPy documentation for numpy.cbrt. | |
doc_265 |
Alias for get_edgecolor. | |
doc_266 | See Migration guide for more details. tf.compat.v1.raw_ops.MaxPool3D
tf.raw_ops.MaxPool3D(
input, ksize, strides, padding, data_format='NDHWC', name=None
)
Args
input A Tensor. Must be one of the following types: half, bfloat16, float32. Shape [batch, depth, rows, cols, channels] tensor to pool over.
... | |
doc_267 | End the scope of a prefix-URI mapping. See startPrefixMapping() for details. This event will always occur after the corresponding endElement() event, but the order of endPrefixMapping() events is not otherwise guaranteed. | |
doc_268 |
Remove a callback based on its observer id. See also add_callback | |
doc_269 | Creates the loader for the Jinja2 environment. Can be used to override just the loader and keeping the rest unchanged. It’s discouraged to override this function. Instead one should override the jinja_loader() function instead. The global loader dispatches between the loaders of the application and the individual bluep... | |
doc_270 | Fork a child process, using a new pseudo-terminal as the child’s controlling terminal. Return a pair of (pid, fd), where pid is 0 in the child, the new child’s process id in the parent, and fd is the file descriptor of the master end of the pseudo-terminal. For a more portable approach, use the pty module. If an error ... | |
doc_271 | Sets the public identifier of this InputSource. | |
doc_272 |
[Deprecated] Notes Deprecated since version 3.4: | |
doc_273 |
Returns the diagonal of the kernel k(X, X). The result of this method is identical to np.diag(self(X)); however, it can be evaluated more efficiently since only the diagonal is evaluated. Parameters
Xndarray of shape (n_samples_X, n_features)
Left argument of the returned kernel k(X, Y) Returns
K_diagndar... | |
doc_274 |
Bases: mpl_toolkits.axes_grid1.axes_divider.Divider The Divider class whose rectangle area is specified as a subplot geometry. Parameters
figmatplotlib.figure.Figure
*argstuple (nrows, ncols, index) or int
The array of subplots in the figure has dimensions (nrows,
ncols), and index is the index of the subplot... | |
doc_275 | Return True if the stream supports writing. If False, write() and truncate() will raise OSError. | |
doc_276 |
Test whether the mouse event occurred in the collection. Returns bool, dict(ind=itemlist), where every item in itemlist contains the event. | |
doc_277 | turtle.rt(angle)
Parameters
angle – a number (integer or float) Turn turtle right by angle units. (Units are by default degrees, but can be set via the degrees() and radians() functions.) Angle orientation depends on the turtle mode, see mode(). >>> turtle.heading()
22.0
>>> turtle.right(45)
>>> turtle.heading()
... | |
doc_278 | Returns the current position of the file pointer. | |
doc_279 | See torch.allclose() | |
doc_280 |
Return whether the colormap is grayscale. | |
doc_281 |
Calculate the expanding rank. New in version 1.4.0. Parameters
method:{‘average’, ‘min’, ‘max’}, default ‘average’
How to rank the group of records that have the same value (i.e. ties): average: average rank of the group min: lowest rank in the group max: highest rank in the group
ascending:bool, default ... | |
doc_282 |
Empty the stack. | |
doc_283 | Logs a message with level ERROR on the root logger. The arguments are interpreted as for debug(). Exception info is added to the logging message. This function should only be called from an exception handler. | |
doc_284 |
Stack arrays in sequence vertically (row wise). This is equivalent to concatenation along the first axis after 1-D arrays of shape (N,) have been reshaped to (1,N). Rebuilds arrays divided by vsplit. This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first a... | |
doc_285 | These decorators can be used to generate ETag and Last-Modified headers; see conditional view processing. | |
doc_286 |
Perform clustering on X and returns cluster labels. Parameters
Xarray-like of shape (n_samples, n_features)
Input data.
yIgnored
Not used, present for API consistency by convention. Returns
labelsndarray of shape (n_samples,), dtype=np.int64
Cluster labels. | |
doc_287 | Get the position of an entry or raise ValueError. Parameters
key – The key to be looked up. Changelog Changed in version 0.5: This used to raise IndexError, which was inconsistent with the list API. | |
doc_288 | See Migration guide for more details. tf.compat.v1.app.flags.EnumClassFlag
tf.compat.v1.flags.EnumClassFlag(
name, default, help, enum_class, short_name=None, case_sensitive=False, **args
)
Attributes
value
Methods flag_type
flag_type()
Returns a str that describes the type of the flag.
Note: we u... | |
doc_289 |
relation_name
The name of the field on which you’d like to filter the relation.
condition
A Q object to control the filtering. | |
doc_290 | See Migration guide for more details. tf.compat.v1.raw_ops.UnicodeScript
tf.raw_ops.UnicodeScript(
input, name=None
)
This operation converts Unicode code points to script codes corresponding to each code point. Script codes correspond to International Components for Unicode (ICU) UScriptCode values. See ICU pro... | |
doc_291 |
Set the locators and formatters of axis to instances suitable for this scale. | |
doc_292 |
Aggregate using one or more operations over the specified axis. Parameters
func:function, str, list or dict
Function to use for aggregating the data. If a function, must either work when passed a DataFrame or when passed to DataFrame.apply. Accepted combinations are: function string function name list of funct... | |
doc_293 |
Generates an octagon shaped structuring element. For a given size of (m) horizontal and vertical sides and a given (n) height or width of slanted sides octagon is generated. The slanted sides are 45 or 135 degrees to the horizontal axis and hence the widths and heights are equal. Parameters
mint
The size of the... | |
doc_294 |
Return the array of values, that are mapped to colors. The base class ScalarMappable does not make any assumptions on the dimensionality and shape of the array. | |
doc_295 | tf.compat.v1.test.compute_gradient(
x, x_shape, y, y_shape, x_init_value=None, delta=0.001, init_targets=None,
extra_feed_dict=None
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.test.compute_gradient in 2.0, which has better support for functi... | |
doc_296 |
Draw samples from a negative binomial distribution. Samples are drawn from a negative binomial distribution with specified parameters, n successes and p probability of success where n is > 0 and p is in the interval [0, 1]. Note New code should use the negative_binomial method of a default_rng() instance instead; pl... | |
doc_297 | The Max-Forwards request-header field provides a mechanism with the TRACE and OPTIONS methods to limit the number of proxies or gateways that can forward the request to the next inbound server. | |
doc_298 | See torch.log10() | |
doc_299 | See Migration guide for more details. tf.compat.v1.raw_ops.FusedBatchNorm
tf.raw_ops.FusedBatchNorm(
x, scale, offset, mean, variance, epsilon=0.0001, exponential_avg_factor=1,
data_format='NHWC', is_training=True, name=None
)
Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". The size ... |
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