_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_2200 | Normalize a pathname by collapsing redundant separators and up-level references so that A//B, A/B/, A/./B and A/foo/../B all become A/B. This string manipulation may change the meaning of a path that contains symbolic links. On Windows, it converts forward slashes to backward slashes. To normalize case, use normcase().... | |
doc_2201 | Parses an XML document from a sequence of string fragments. sequence is a list or other sequence containing XML data fragments. parser is an optional parser instance. If not given, the standard XMLParser parser is used. Returns an Element instance. New in version 3.2. | |
doc_2202 |
Add text to figure. Parameters
x, yfloat
The position to place the text. By default, this is in figure coordinates, floats in [0, 1]. The coordinate system can be changed using the transform keyword.
sstr
The text string.
fontdictdict, optional
A dictionary to override the default text properties. If no... | |
doc_2203 | tf.compat.v1.layers.Conv3D(
filters, kernel_size, strides=(1, 1, 1), padding='valid',
data_format='channels_last', dilation_rate=(1, 1, 1), activation=None,
use_bias=True, kernel_initializer=None, bias_initializer=tf.zeros_initializer(),
kernel_regularizer=None, bias_regularizer=None, activity_regulariz... | |
doc_2204 | class sklearn.feature_extraction.text.CountVectorizer(*, input='content', encoding='utf-8', decode_error='strict', strip_accents=None, lowercase=True, preprocessor=None, tokenizer=None, stop_words=None, token_pattern='(?u)\\b\\w\\w+\\b', ngram_range=(1, 1), analyzer='word', max_df=1.0, min_df=1, max_features=None, voca... | |
doc_2205 |
Check if types match. New in version 1.7.0. Parameters
otherobject
Class instance. Returns
boolboolean
True if other is same class as self | |
doc_2206 |
Computes the Maximum likelihood covariance estimator Parameters
Xndarray of shape (n_samples, n_features)
Data from which to compute the covariance estimate
assume_centeredbool, default=False
If True, data will not be centered before computation. Useful when working with data whose mean is almost, but not e... | |
doc_2207 | bytearray.istitle()
Return True if the sequence is ASCII titlecase and the sequence is not empty, False otherwise. See bytes.title() for more details on the definition of “titlecase”. For example: >>> b'Hello World'.istitle()
True
>>> b'Hello world'.istitle()
False | |
doc_2208 |
New view of array with the same data. Note Passing None for dtype is different from omitting the parameter, since the former invokes dtype(None) which is an alias for dtype('float_'). Parameters
dtypedata-type or ndarray sub-class, optional
Data-type descriptor of the returned view, e.g., float32 or int16. Om... | |
doc_2209 |
Return the coordinate system to use for Annotation.xyann. See also xycoords in Annotation. | |
doc_2210 |
Return a dictionary of all the properties of the artist. | |
doc_2211 | See Migration guide for more details. tf.compat.v1.raw_ops.SparseSparseMaximum
tf.raw_ops.SparseSparseMaximum(
a_indices, a_values, a_shape, b_indices, b_values, b_shape, name=None
)
Assumes the two SparseTensors have the same shape, i.e., no broadcasting.
Args
a_indices A Tensor of type int64. 2-D. N x... | |
doc_2212 |
Number of dimensions of broadcasted result. Alias for nd. New in version 1.12.0. Examples >>> x = np.array([1, 2, 3])
>>> y = np.array([[4], [5], [6]])
>>> b = np.broadcast(x, y)
>>> b.ndim
2 | |
doc_2213 |
Set the length of the lines used to mark each event. | |
doc_2214 | The tix commands provide access to miscellaneous elements of Tix’s internal state and the Tix application context. Most of the information manipulated by these methods pertains to the application as a whole, or to a screen or display, rather than to a particular window. To view the current settings, the common usage is... | |
doc_2215 | operator.__and__(a, b)
Return the bitwise and of a and b. | |
doc_2216 | Remove the given parameter completely from the Content-Type header. The header will be re-written in place without the parameter or its value. All values will be quoted as necessary unless requote is False (the default is True). Optional header specifies an alternative to Content-Type. | |
doc_2217 | operator.__index__(a)
Return a converted to an integer. Equivalent to a.__index__(). | |
doc_2218 | This is an abstract base class for running WSGI applications. Each instance will handle a single HTTP request, although in principle you could create a subclass that was reusable for multiple requests. BaseHandler instances have only one method intended for external use:
run(app)
Run the specified WSGI application,... | |
doc_2219 | See Migration guide for more details. tf.compat.v1.raw_ops.IsotonicRegression
tf.raw_ops.IsotonicRegression(
input, output_dtype=tf.dtypes.float32, name=None
)
Args
input A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uin... | |
doc_2220 |
Return the ConnectionStyle used. | |
doc_2221 |
An Interpreter executes an FX graph Node-by-Node. This pattern can be useful for many things, including writing code transformations as well as analysis passes. Methods in the Interpreter class can be overridden to customize the behavior of execution. The map of overrideable methods in terms of call hierarchy: run()
... | |
doc_2222 | tkinter.filedialog.askopenfiles(mode="r", **options)
The above two functions create an Open dialog and return the opened file object(s) in read-only mode. | |
doc_2223 | See Migration guide for more details. tf.compat.v1.keras.layers.Cropping3D
tf.keras.layers.Cropping3D(
cropping=((1, 1), (1, 1), (1, 1)), data_format=None, **kwargs
)
Examples:
input_shape = (2, 28, 28, 10, 3)
x = np.arange(np.prod(input_shape)).reshape(input_shape)
y = tf.keras.layers.Cropping3D(cropping=(2, 4... | |
doc_2224 |
Return the group id. | |
doc_2225 | An abstract base class which inherits from InspectLoader that, when implemented, helps a module to be executed as a script. The ABC represents an optional PEP 302 protocol.
abstractmethod get_filename(fullname)
An abstract method that is to return the value of __file__ for the specified module. If no path is availa... | |
doc_2226 | Send a QUIT command and close the connection. Once this method has been called, no other methods of the NNTP object should be called. | |
doc_2227 |
Returns a view of the array with axes transposed. For a 1-D array this has no effect, as a transposed vector is simply the same vector. To convert a 1-D array into a 2D column vector, an additional dimension must be added. np.atleast2d(a).T achieves this, as does a[:, np.newaxis]. For a 2-D array, this is a standard ... | |
doc_2228 |
Return latex's rendering of the tex string as an rgba array. Examples >>> texmanager = TexManager()
>>> s = r"\TeX\ is $\displaystyle\sum_n\frac{-e^{i\pi}}{2^n}$!"
>>> Z = texmanager.get_rgba(s, fontsize=12, dpi=80, rgb=(1, 0, 0)) | |
doc_2229 |
Estimate class weights for unbalanced datasets. Parameters
class_weightdict, ‘balanced’ or None
If ‘balanced’, class weights will be given by n_samples / (n_classes * np.bincount(y)). If a dictionary is given, keys are classes and values are corresponding class weights. If None is given, the class weights will ... | |
doc_2230 | tf.experimental.numpy.bitwise_xor(
x1, x2
)
Unsupported arguments: out, where, casting, order, dtype, subok, signature, extobj. See the NumPy documentation for numpy.bitwise_xor. | |
doc_2231 | This is the entry point you will normally use. It accepts editing keystrokes until one of the termination keystrokes is entered. If validator is supplied, it must be a function. It will be called for each keystroke entered with the keystroke as a parameter; command dispatch is done on the result. This method returns th... | |
doc_2232 |
Reduce dimensionality through Gaussian random projection. The components of the random matrix are drawn from N(0, 1 / n_components). Read more in the User Guide. New in version 0.13. Parameters
n_componentsint or ‘auto’, default=’auto’
Dimensionality of the target projection space. n_components can be automat... | |
doc_2233 |
Emit a ToolManagerMessageEvent. | |
doc_2234 |
Parameter
A kind of Tensor that is to be considered a module parameter.
UninitializedParameter
A parameter that is not initialized. Containers
Module
Base class for all neural network modules.
Sequential
A sequential container.
ModuleList
Holds submodules in a list.
ModuleDict
Holds submodules i... | |
doc_2235 | from myapp.serializers import UserSerializer
from rest_framework import generics
from rest_framework.permissions import IsAdminUser
class UserList(generics.ListCreateAPIView):
queryset = User.objects.all()
serializer_class = UserSerializer
permission_classes = [IsAdminUser]
For more complex cases you migh... | |
doc_2236 |
Bases: mpl_toolkits.axes_grid1.axes_grid.ImageGrid Parameters
figFigure
The parent figure.
rect(float, float, float, float) or int
The axes position, as a (left, bottom, width, height) tuple or as a three-digit subplot position code (e.g., "121").
nrows_ncols(int, int)
Number of rows and columns in the ... | |
doc_2237 | Perform hexbin4 binary-to-ASCII translation and return the resulting string. The argument should already be RLE-coded, and have a length divisible by 3 (except possibly the last fragment). Deprecated since version 3.9. | |
doc_2238 | alias of ConvTranspose1d | |
doc_2239 |
Add a new suppressing filter or apply it if the state is entered. Parameters
categoryclass, optional
Warning class to filter
messagestring, optional
Regular expression matching the warning message.
modulemodule, optional
Module to filter for. Note that the module (and its file) must match exactly and ca... | |
doc_2240 | An invalid operation was performed. Indicates that an operation was requested that does not make sense. If not trapped, returns NaN. Possible causes include: Infinity - Infinity
0 * Infinity
Infinity / Infinity
x % 0
Infinity % x
sqrt(-x) and x > 0
0 ** 0
x ** (non-integer)
x ** Infinity | |
doc_2241 | class calendar.Calendar(firstweekday=0)
Creates a Calendar object. firstweekday is an integer specifying the first day of the week. 0 is Monday (the default), 6 is Sunday. A Calendar object provides several methods that can be used for preparing the calendar data for formatting. This class doesn’t do any formatting i... | |
doc_2242 |
Return the current hatching pattern. | |
doc_2243 |
Return the bottom coordinate of the rectangle. | |
doc_2244 | Return either “new” (if the message should be stored in the new subdirectory) or “cur” (if the message should be stored in the cur subdirectory). Note A message is typically moved from new to cur after its mailbox has been accessed, whether or not the message is has been read. A message msg has been read if "S" in msg... | |
doc_2245 |
Return the clipbox. | |
doc_2246 | Yield all direct child nodes of node, that is, all fields that are nodes and all items of fields that are lists of nodes. | |
doc_2247 | Sets or resets the time zone search path (TZPATH) for the module. When called with no arguments, TZPATH is set to the default value. Calling reset_tzpath will not invalidate the ZoneInfo cache, and so calls to the primary ZoneInfo constructor will only use the new TZPATH in the case of a cache miss. The to parameter mu... | |
doc_2248 | Regular slicing (on the form lower:upper or lower:upper:step). Can occur only inside the slice field of Subscript, either directly or as an element of Tuple. >>> print(ast.dump(ast.parse('l[1:2]', mode='eval'), indent=4))
Expression(
body=Subscript(
value=Name(id='l', ctx=Load()),
slice=Slice(
... | |
doc_2249 | tf.metrics.MeanSquaredError Compat aliases for migration See Migration guide for more details. tf.compat.v1.keras.metrics.MeanSquaredError
tf.keras.metrics.MeanSquaredError(
name='mean_squared_error', dtype=None
)
Args
name (Optional) string name of the metric instance.
dtype (Optional) data type ... | |
doc_2250 |
One-dimensional linear interpolation for monotonically increasing sample points. Returns the one-dimensional piecewise linear interpolant to a function with given discrete data points (xp, fp), evaluated at x. Parameters
xarray_like
The x-coordinates at which to evaluate the interpolated values.
xp1-D sequenc... | |
doc_2251 | See Migration guide for more details. tf.compat.v1.raw_ops.ClipByValue
tf.raw_ops.ClipByValue(
t, clip_value_min, clip_value_max, name=None
)
Given a tensor t, this operation returns a tensor of the same type and shape as t with its values clipped to clip_value_min and clip_value_max. Any values less than clip_v... | |
doc_2252 | Close the control file descriptor of the kqueue object. | |
doc_2253 | These control the range of values permitted in the field, and should be given as decimal.Decimal values. | |
doc_2254 | sklearn.utils.sparsefuncs.inplace_column_scale(X, scale) [source]
Inplace column scaling of a CSC/CSR matrix. Scale each feature of the data matrix by multiplying with specific scale provided by the caller assuming a (n_samples, n_features) shape. Parameters
Xsparse matrix of shape (n_samples, n_features)
Matri... | |
doc_2255 | Returns a KML (Keyhole Markup Language) representation of the geometry. This should only be used for geometries with an SRID of 4326 (WGS84), but this restriction is not enforced. | |
doc_2256 |
Alias for set_fontstyle. | |
doc_2257 | class sklearn.model_selection.TimeSeriesSplit(n_splits=5, *, max_train_size=None, test_size=None, gap=0) [source]
Time Series cross-validator Provides train/test indices to split time series data samples that are observed at fixed time intervals, in train/test sets. In each split, test indices must be higher than bef... | |
doc_2258 |
Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index. Parameters
keep_tz:optional, defaults True
Return the data keeping the timezone. If keep_tz is True:
If the timezone is not set, the resulting Series will have a datetime64[ns] dtype.... | |
doc_2259 | In-place version of exp() | |
doc_2260 |
Compute the (multiplicative) inverse of a matrix. Given a square matrix a, return the matrix ainv satisfying dot(a, ainv) = dot(ainv, a) = eye(a.shape[0]). Parameters
a(…, M, M) array_like
Matrix to be inverted. Returns
ainv(…, M, M) ndarray or matrix
(Multiplicative) inverse of the matrix a. Raises ... | |
doc_2261 | '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_2262 | Compare two operands using their abstract representation rather than their value as in compare_total(), but ignoring the sign of each operand. x.compare_total_mag(y) is equivalent to x.copy_abs().compare_total(y.copy_abs()). This operation is unaffected by context and is quiet: no flags are changed and no rounding is p... | |
doc_2263 | The largest year number allowed in a date or datetime object. MAXYEAR is 9999. | |
doc_2264 |
Returns the score of the prediction. This is a wrapper for estimator_.score(X, y). Parameters
Xnumpy array or sparse matrix of shape [n_samples, n_features]
Training data.
yarray, shape = [n_samples] or [n_samples, n_targets]
Target values. Returns
zfloat
Score of the prediction. | |
doc_2265 | Using a probability density function (pdf), compute the relative likelihood that a random variable X will be near the given value x. Mathematically, it is the limit of the ratio P(x <=
X < x+dx) / dx as dx approaches zero. The relative likelihood is computed as the probability of a sample occurring in a narrow range di... | |
doc_2266 | Returns a string identifying the Python implementation. Possible return values are: ‘CPython’, ‘IronPython’, ‘Jython’, ‘PyPy’. | |
doc_2267 | lambda is a minimal function definition that can be used inside an expression. Unlike FunctionDef, body holds a single node. >>> print(ast.dump(ast.parse('lambda x,y: ...'), indent=4))
Module(
body=[
Expr(
value=Lambda(
args=arguments(
posonlyargs=[],
... | |
doc_2268 |
Computes the log det jacobian log |dy/dx| given input and output. | |
doc_2269 | Adds a success message attribute to FormView based classes
get_success_message(cleaned_data)
cleaned_data is the cleaned data from the form which is used for string formatting | |
doc_2270 |
Select features according to a percentile of the highest scores. Read more in the User Guide. Parameters
score_funccallable, default=f_classif
Function taking two arrays X and y, and returning a pair of arrays (scores, pvalues) or a single array with scores. Default is f_classif (see below “See Also”). The defa... | |
doc_2271 |
name
Returns the name of this field: >>> city['Name'].name
'Name'
type
Returns the OGR type of this field, as an integer. The FIELD_CLASSES dictionary maps these values onto subclasses of Field: >>> city['Density'].type
2
type_name
Returns a string with the name of the data type of this field: >>> city['N... | |
doc_2272 |
Mini-batch Sparse Principal Components Analysis Finds the set of sparse components that can optimally reconstruct the data. The amount of sparseness is controllable by the coefficient of the L1 penalty, given by the parameter alpha. Read more in the User Guide. Parameters
n_componentsint, default=None
number of... | |
doc_2273 |
Add the current figure to the stack of views and positions. | |
doc_2274 | Integer value to control debugging output. The initialize value is taken from the module variable Debug. Values greater than three trace each command. | |
doc_2275 |
Reduce learning rate when a metric has stopped improving. Models often benefit from reducing the learning rate by a factor of 2-10 once learning stagnates. This scheduler reads a metrics quantity and if no improvement is seen for a ‘patience’ number of epochs, the learning rate is reduced. Parameters
optimizer (O... | |
doc_2276 | Must be a subclass of django.forms.MultiWidget. Default value is TextInput, which probably is not very useful in this case. | |
doc_2277 |
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_2278 |
Randomly zero out entire channels (a channel is a 2D feature map, e.g., the jj -th channel of the ii -th sample in the batched input is a 2D tensor input[i,j]\text{input}[i, j] ). Each channel will be zeroed out independently on every forward call with probability p using samples from a Bernoulli distribution. Usuall... | |
doc_2279 |
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_2280 | See Migration guide for more details. tf.compat.v1.keras.layers.Layer
tf.keras.layers.Layer(
trainable=True, name=None, dtype=None, dynamic=False, **kwargs
)
A layer is a callable object that takes as input one or more tensors and that outputs one or more tensors. It involves computation, defined in the call() m... | |
doc_2281 | Raised when a sequence subscript is out of range. (Slice indices are silently truncated to fall in the allowed range; if an index is not an integer, TypeError is raised.) | |
doc_2282 |
Alias for set_antialiased. | |
doc_2283 | This should be the first call after the connection to the server has been made. It sends a line to the server consisting of the method string, the url string, and the HTTP version (HTTP/1.1). To disable automatic sending of Host: or Accept-Encoding: headers (for example to accept additional content encodings), specify ... | |
doc_2284 |
Fills the input Tensor with values according to the method described in Understanding the difficulty of training deep feedforward neural networks - Glorot, X. & Bengio, Y. (2010), using a normal distribution. The resulting tensor will have values sampled from N(0,std2)\mathcal{N}(0, \text{std}^2) where std=gain×2fa... | |
doc_2285 | Install the control-c handler. When a signal.SIGINT is received (usually in response to the user pressing control-c) all registered results have stop() called. | |
doc_2286 | Returns an iterator over module parameters, yielding both the name of the parameter as well as the parameter itself. Parameters
prefix (str) – prefix to prepend to all parameter names.
recurse (bool) – if True, then yields parameters of this module and all submodules. Otherwise, yields only parameters that are dir... | |
doc_2287 | Update the template context with some commonly used variables. This injects request, session, config and g into the template context as well as everything template context processors want to inject. Note that the as of Flask 0.6, the original values in the context will not be overridden if a context processor decides t... | |
doc_2288 |
Set a label that will be displayed in the legend. Parameters
sobject
s will be converted to a string by calling str. | |
doc_2289 | sklearn.covariance.oas(X, *, assume_centered=False) [source]
Estimate covariance with the Oracle Approximating Shrinkage algorithm. Parameters
Xarray-like of shape (n_samples, n_features)
Data from which to compute the covariance estimate.
assume_centeredbool, default=False
If True, data will not be centere... | |
doc_2290 |
Call self as a function. | |
doc_2291 |
The last colorbar associated with this ScalarMappable. May be None. | |
doc_2292 | See Migration guide for more details. tf.compat.v1.log1p, tf.compat.v1.math.log1p
tf.math.log1p(
x, name=None
)
I.e., \(y = \log_e (1 + x)\). Example:
x = tf.constant([0, 0.5, 1, 5])
tf.math.log1p(x)
<tf.Tensor: shape=(4,), dtype=float32, numpy=array([0. , 0.4054651, 0.6931472, 1.7917595], dtype=float32)>... | |
doc_2293 |
Bases: matplotlib.backend_tools.ToolBase Base tool for figure saving. default_keymap=['s', 'ctrl+s']
Keymap to associate with this tool. list[str]: List of keys that will trigger this tool when a keypress event is emitted on self.figure.canvas.
description='Save the figure'
Description of the Tool. str: Too... | |
doc_2294 | See Migration guide for more details. tf.compat.v1.raw_ops.ReaderSerializeStateV2
tf.raw_ops.ReaderSerializeStateV2(
reader_handle, name=None
)
Not all Readers support being serialized, so this can produce an Unimplemented error.
Args
reader_handle A Tensor of type resource. Handle to a Reader.
name... | |
doc_2295 | See Migration guide for more details. tf.compat.v1.io.gfile.rename
tf.io.gfile.rename(
src, dst, overwrite=False
)
Args
src string, pathname for a file
dst string, pathname to which the file needs to be moved
overwrite boolean, if false it's an error for dst to be occupied by an existing fil... | |
doc_2296 | sklearn.metrics.precision_recall_curve(y_true, probas_pred, *, pos_label=None, sample_weight=None) [source]
Compute precision-recall pairs for different probability thresholds. Note: this implementation is restricted to the binary classification task. The precision is the ratio tp / (tp + fp) where tp is the number o... | |
doc_2297 |
Fills the input Tensor with the value val\text{val} . Parameters
tensor – an n-dimensional torch.Tensor
val – the value to fill the tensor with Examples >>> w = torch.empty(3, 5)
>>> nn.init.constant_(w, 0.3) | |
doc_2298 |
Computes the log-likelihood of a Gaussian data set with self.covariance_ as an estimator of its covariance matrix. Parameters
X_testarray-like of shape (n_samples, n_features)
Test data of which we compute the likelihood, where n_samples is the number of samples and n_features is the number of features. X_test ... | |
doc_2299 | Similar to contextmanager(), but creates an asynchronous context manager. This function is a decorator that can be used to define a factory function for async with statement asynchronous context managers, without needing to create a class or separate __aenter__() and __aexit__() methods. It must be applied to an asynch... |
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