_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_18800 | Open fullurl using the appropriate protocol. This method sets up cache and proxy information, then calls the appropriate open method with its input arguments. If the scheme is not recognized, open_unknown() is called. The data argument has the same meaning as the data argument of urlopen(). This method always quotes fu... | |
doc_18801 | The origin or ‘*’ for any origin that may make cross origin requests. | |
doc_18802 | See Migration guide for more details. tf.compat.v1.FixedLenFeature, tf.compat.v1.io.FixedLenFeature
tf.io.FixedLenFeature(
shape, dtype, default_value=None
)
To treat sparse input as dense, provide a default_value; otherwise, the parse functions will fail on any examples missing this feature. Fields:
shape: Sh... | |
doc_18803 |
Calculate the expanding count of non NaN observations. Returns
Series or DataFrame
Return type is the same as the original object with np.float64 dtype. See also pandas.Series.expanding
Calling expanding with Series data. pandas.DataFrame.expanding
Calling expanding with DataFrames. pandas.Series.count
... | |
doc_18804 | Make an iterator that returns elements from the iterable as long as the predicate is true. Roughly equivalent to: def takewhile(predicate, iterable):
# takewhile(lambda x: x<5, [1,4,6,4,1]) --> 1 4
for x in iterable:
if predicate(x):
yield x
else:
break | |
doc_18805 | The version number of this module, as a string. This is not the version of the SQLite library. | |
doc_18806 | The height of the band in pixels (Y-axis). | |
doc_18807 | This is a list of all the awaits made to the mock object in sequence (so the length of the list is the number of times it has been awaited). Before any awaits have been made it is an empty list. >>> mock = AsyncMock()
>>> async def main(*args):
... await mock(*args)
...
>>> mock.await_args_list
[]
>>> asyncio.run(m... | |
doc_18808 |
Set the linewidth(s) for the collection. lw can be a scalar or a sequence; if it is a sequence the patches will cycle through the sequence Parameters
lwfloat or list of floats | |
doc_18809 | This method for the Stats class prints out a report as described in the profile.run() definition. The order of the printing is based on the last sort_stats() operation done on the object (subject to caveats in add() and strip_dirs()). The arguments provided (if any) can be used to limit the list down to the significant... | |
doc_18810 |
Set the parameters of this estimator. The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object. Parameters
**paramsdict
Estimator parameters. Returns... | |
doc_18811 | tf.compat.v1.summary.scalar(
name, tensor, collections=None, family=None
)
The generated Summary has a Tensor.proto containing the input Tensor.
Args
name A name for the generated node. Will also serve as the series name in TensorBoard.
tensor A real numeric Tensor containing a single value.
col... | |
doc_18812 | class sklearn.decomposition.FactorAnalysis(n_components=None, *, tol=0.01, copy=True, max_iter=1000, noise_variance_init=None, svd_method='randomized', iterated_power=3, rotation=None, random_state=0) [source]
Factor Analysis (FA). A simple linear generative model with Gaussian latent variables. The observations are ... | |
doc_18813 |
A long short-term memory (LSTM) cell. i=σ(Wiix+bii+Whih+bhi)f=σ(Wifx+bif+Whfh+bhf)g=tanh(Wigx+big+Whgh+bhg)o=σ(Wiox+bio+Whoh+bho)c′=f∗c+i∗gh′=o∗tanh(c′)\begin{array}{ll} i = \sigma(W_{ii} x + b_{ii} + W_{hi} h + b_{hi}) \\ f = \sigma(W_{if} x + b_{if} + W_{hf} h + b_{hf}) \\ g = \tanh(W_{ig} x + b_{ig} + W_{hg} h ... | |
doc_18814 | The constructor takes a single argument which is the template string.
substitute(mapping={}, /, **kwds)
Performs the template substitution, returning a new string. mapping is any dictionary-like object with keys that match the placeholders in the template. Alternatively, you can provide keyword arguments, where the... | |
doc_18815 | sklearn.metrics.plot_confusion_matrix(estimator, X, y_true, *, labels=None, sample_weight=None, normalize=None, display_labels=None, include_values=True, xticks_rotation='horizontal', values_format=None, cmap='viridis', ax=None, colorbar=True) [source]
Plot Confusion Matrix. Read more in the User Guide. Parameters
... | |
doc_18816 | Abstract base class for generic types. A generic type is typically declared by inheriting from an instantiation of this class with one or more type variables. For example, a generic mapping type might be defined as: class Mapping(Generic[KT, VT]):
def __getitem__(self, key: KT) -> VT:
...
# Etc.
Th... | |
doc_18817 | Adds (or updates) the Vary header in the given HttpResponse object. newheaders is a list of header names that should be in Vary. If headers contains an asterisk, then Vary header will consist of a single asterisk '*', according to RFC 7231#section-7.1.4. Otherwise, existing headers in Vary aren’t removed. | |
doc_18818 |
Set how to draw connections between line segments. Parameters
jsJoinStyle or {'miter', 'round', 'bevel'} | |
doc_18819 |
Returns the number of splitting iterations in the cross-validator Parameters
Xobject
Always ignored, exists for compatibility.
yobject
Always ignored, exists for compatibility.
groupsobject
Always ignored, exists for compatibility. Returns
n_splitsint
Returns the number of splitting iterations i... | |
doc_18820 |
Return an array with the elements of self right-justified in a string of length width. See also char.rjust | |
doc_18821 | sklearn.utils.sparsefuncs_fast.inplace_csr_row_normalize_l2()
Inplace row normalize using the l2 norm | |
doc_18822 |
Creates a setuptools.Extension for CUDA/C++. Convenience method that creates a setuptools.Extension with the bare minimum (but often sufficient) arguments to build a CUDA/C++ extension. This includes the CUDA include path, library path and runtime library. All arguments are forwarded to the setuptools.Extension const... | |
doc_18823 | Fills elements of self tensor with value where mask is True. The shape of mask must be broadcastable with the shape of the underlying tensor. Parameters
mask (BoolTensor) – the boolean mask
value (float) – the value to fill in with | |
doc_18824 | Generates a Vandermonde matrix. The columns of the output matrix are elementwise powers of the input vector x(N−1),x(N−2),...,x0x^{(N-1)}, x^{(N-2)}, ..., x^0 . If increasing is True, the order of the columns is reversed x0,x1,...,x(N−1)x^0, x^1, ..., x^{(N-1)} . Such a matrix with a geometric progression in each row i... | |
doc_18825 |
Set the label position (left or right) Parameters
position{'left', 'right'} | |
doc_18826 | See Migration guide for more details. tf.compat.v1.identity_n
tf.identity_n(
input, name=None
)
tensors. This op can be used to override the gradient for complicated functions. For example, suppose y = f(x) and we wish to apply a custom function g for backprop such that dx = g(dy). In Python, with tf.get_default... | |
doc_18827 | Initiate a transfer over the data connection. If the transfer is active, send an EPRT or PORT command and the transfer command specified by cmd, and accept the connection. If the server is passive, send an EPSV or PASV command, connect to it, and start the transfer command. Either way, return the socket for the connect... | |
doc_18828 | Return the current exception handler, or None if no custom exception handler was set. New in version 3.5.2. | |
doc_18829 |
Stack the prescribed level(s) from columns to index. Return a reshaped DataFrame or Series having a multi-level index with one or more new inner-most levels compared to the current DataFrame. The new inner-most levels are created by pivoting the columns of the current dataframe:
if the columns have a single level,... | |
doc_18830 |
Perform classification on test vectors X. Parameters
Xarray-like of shape (n_samples, n_features)
Test data.
return_stdbool, default=False
Whether to return the standard deviation of posterior prediction. All zeros in this case. New in version 0.20. Returns
yarray-like of shape (n_samples,) or (n_sa... | |
doc_18831 | See Migration guide for more details. tf.compat.v1.sets.intersection, tf.compat.v1.sets.set_intersection
tf.sets.intersection(
a, b, validate_indices=True
)
All but the last dimension of a and b must match. Example: import tensorflow as tf
import collections
# Represent the following array of sets as a sparse t... | |
doc_18832 |
Format a floating-point scalar as a decimal string in positional notation. Provides control over rounding, trimming and padding. Uses and assumes IEEE unbiased rounding. Uses the “Dragon4” algorithm. Parameters
xpython float or numpy floating scalar
Value to format.
precisionnon-negative integer or None, opti... | |
doc_18833 |
Fit the model using X, y as training data. Parameters
Xarray-like of shape (n_samples, n_features)
Training data.
yarray-like of shape (n_samples,)
Target values. Returns
selfobject
returns an instance of self. | |
doc_18834 | See Migration guide for more details. tf.compat.v1.log_sigmoid, tf.compat.v1.math.log_sigmoid
tf.math.log_sigmoid(
x, name=None
)
Specifically, y = log(1 / (1 + exp(-x))). For numerical stability, we use y = -tf.nn.softplus(-x).
Args
x A Tensor with type float32 or float64.
name A name for the ope... | |
doc_18835 | tf.compat.v1.metrics.auc(
labels, predictions, weights=None, num_thresholds=200, metrics_collections=None,
updates_collections=None, curve='ROC', name=None,
summation_method='trapezoidal', thresholds=None
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updat... | |
doc_18836 | tf.experimental.numpy.fix(
x
)
Unsupported arguments: out. See the NumPy documentation for numpy.fix. | |
doc_18837 | In some cases, it is desirable not to parse an input source at once, but to feed chunks of the document as they get available. Note that the reader will normally not read the entire file, but read it in chunks as well; still parse() won’t return until the entire document is processed. So these interfaces should be used... | |
doc_18838 |
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_18839 |
Alias for get_linestyle. | |
doc_18840 | Class method that makes a new instance from an existing sequence or iterable. >>> t = [11, 22]
>>> Point._make(t)
Point(x=11, y=22) | |
doc_18841 | tf.experimental.numpy.var(
a, axis=None, dtype=None, out=None, ddof=0, keepdims=None
)
See the NumPy documentation for numpy.var. | |
doc_18842 |
Set the parameters of this estimator. The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object. Parameters
**paramsdict
Estimator parameters. Returns... | |
doc_18843 | class sklearn.svm.NuSVR(*, nu=0.5, C=1.0, kernel='rbf', degree=3, gamma='scale', coef0=0.0, shrinking=True, tol=0.001, cache_size=200, verbose=False, max_iter=- 1) [source]
Nu Support Vector Regression. Similar to NuSVC, for regression, uses a parameter nu to control the number of support vectors. However, unlike NuS... | |
doc_18844 | Initialize the underlying FreeType library. init(cache_size=64, resolution=72) This function initializes the underlying FreeType library and must be called before trying to use any of the functionality of the freetype module. However, pygame.init() will automatically call this function if the freetype module is alrea... | |
doc_18845 | The default asyncio policy. Uses SelectorEventLoop on Unix and ProactorEventLoop on Windows. There is no need to install the default policy manually. asyncio is configured to use the default policy automatically. Changed in version 3.8: On Windows, ProactorEventLoop is now used by default. | |
doc_18846 | tf.compat.v1.keras.experimental.load_from_saved_model(
saved_model_path, custom_objects=None
)
This function reinstantiates model state by: 1) loading model topology from json (this will eventually come from metagraph). 2) loading model weights from checkpoint. Example: import tensorflow as tf
# Create a tf.keras... | |
doc_18847 | sklearn.cluster.estimate_bandwidth(X, *, quantile=0.3, n_samples=None, random_state=0, n_jobs=None) [source]
Estimate the bandwidth to use with the mean-shift algorithm. That this function takes time at least quadratic in n_samples. For large datasets, it’s wise to set that parameter to a small value. Parameters
... | |
doc_18848 |
Abstract base class of all numeric scalar types. | |
doc_18849 |
Set the zorder for the artist. Artists with lower zorder values are drawn first. Parameters
levelfloat | |
doc_18850 | tf.dtypes.cast Compat aliases for migration See Migration guide for more details. tf.compat.v1.cast, tf.compat.v1.dtypes.cast
tf.cast(
x, dtype, name=None
)
The operation casts x (in case of Tensor) or x.values (in case of SparseTensor or IndexedSlices) to dtype. For example:
x = tf.constant([1.8, 2.2], dtype=t... | |
doc_18851 |
Applies element-wise, SELU(x)=scale∗(max(0,x)+min(0,α∗(exp(x)−1)))\text{SELU}(x) = scale * (\max(0,x) + \min(0, \alpha * (\exp(x) - 1))) , with α=1.6732632423543772848170429916717\alpha=1.6732632423543772848170429916717 and scale=1.0507009873554804934193349852946scale=1.0507009873554804934193349852946 . See SELU ... | |
doc_18852 | Create a file at this given path. If mode is given, it is combined with the process’ umask value to determine the file mode and access flags. If the file already exists, the function succeeds if exist_ok is true (and its modification time is updated to the current time), otherwise FileExistsError is raised. | |
doc_18853 | Special value that can be used as the stderr argument to Popen and indicates that standard error should go into the same handle as standard output. | |
doc_18854 | This method is called unconditionally after tearDownClass(), or after setUpClass() if setUpClass() raises an exception. It is responsible for calling all the cleanup functions added by addClassCleanup(). If you need cleanup functions to be called prior to tearDownClass() then you can call doClassCleanups() yourself. do... | |
doc_18855 | sklearn.metrics.confusion_matrix(y_true, y_pred, *, labels=None, sample_weight=None, normalize=None) [source]
Compute confusion matrix to evaluate the accuracy of a classification. By definition a confusion matrix \(C\) is such that \(C_{i, j}\) is equal to the number of observations known to be in group \(i\) and pr... | |
doc_18856 | Attempt to read and parse an iterable of filenames, returning a list of filenames which were successfully parsed. If filenames is a string, a bytes object or a path-like object, it is treated as a single filename. If a file named in filenames cannot be opened, that file will be ignored. This is designed so that you can... | |
doc_18857 | In-place version of logical_not() | |
doc_18858 | Leave newline mode. Disable translation of return into newline on input, and disable low-level translation of newline into newline/return on output (but this does not change the behavior of addch('\n'), which always does the equivalent of return and line feed on the virtual screen). With translation off, curses can som... | |
doc_18859 |
Return an array formed from the elements of a at the given indices. Refer to numpy.take for full documentation. See also numpy.take
equivalent function | |
doc_18860 |
Show libraries in the system on which NumPy was built. Print information about various resources (libraries, library directories, include directories, etc.) in the system on which NumPy was built. See also get_include
Returns the directory containing NumPy C header files. Notes
Classes specifying the informat... | |
doc_18861 | This will be "SimpleHTTP/" + __version__, where __version__ is defined at the module level. | |
doc_18862 |
Set whether and how tight_layout is called when drawing. Parameters
tightbool or dict with keys "pad", "w_pad", "h_pad", "rect" or None
If a bool, sets whether to call tight_layout upon drawing. If None, use rcParams["figure.autolayout"] (default: False) instead. If a dict, pass it as kwargs to tight_layout, ov... | |
doc_18863 | This is the same function as sequence2st(). This entry point is maintained for backward compatibility. | |
doc_18864 | returns the bottom layer get_bottom_layer() -> layer | |
doc_18865 | include(pattern_list)
include((pattern_list, app_namespace), namespace=None)
A function that takes a full Python import path to another URLconf module that should be “included” in this place. Optionally, the application namespace and instance namespace where the entries will be included into can also be specified. ... | |
doc_18866 |
Return local median of an image. Parameters
image([P,] M, N) ndarray (uint8, uint16)
Input image.
selemndarray
The neighborhood expressed as an ndarray of 1’s and 0’s. If None, a full square of size 3 is used.
out([P,] M, N) array (same dtype as input)
If None, a new array is allocated.
maskndarray (i... | |
doc_18867 | When save_as=True, the default redirect after saving the new object is to the change view for that object. If you set save_as_continue=False, the redirect will be to the changelist view. By default, save_as_continue is set to True. | |
doc_18868 | A parallel equivalent of the map() built-in function (it supports only one iterable argument though, for multiple iterables see starmap()). It blocks until the result is ready. This method chops the iterable into a number of chunks which it submits to the process pool as separate tasks. The (approximate) size of these ... | |
doc_18869 |
Swaps the module if it has a quantized counterpart and it has an observer attached. Parameters
mod – input module
mapping – a dictionary that maps from nn module to nnq module Returns
The corresponding quantized module of mod | |
doc_18870 |
Set whether the artist uses clipping. When False artists will be visible outside of the axes which can lead to unexpected results. Parameters
bbool | |
doc_18871 |
Save several arrays into a single file in uncompressed .npz format. Provide arrays as keyword arguments to store them under the corresponding name in the output file: savez(fn, x=x, y=y). If arrays are specified as positional arguments, i.e., savez(fn,
x, y), their names will be arr_0, arr_1, etc. Parameters
file... | |
doc_18872 |
Plot a 3D wireframe. Note The rcount and ccount kwargs, which both default to 50, determine the maximum number of samples used in each direction. If the input data is larger, it will be downsampled (by slicing) to these numbers of points. Parameters
X, Y, Z2D arrays
Data values.
rcount, ccountint
Maximum ... | |
doc_18873 | Return the attribute value for displaying text in the specified color pair. Only the first 256 color pairs are supported. This attribute value can be combined with A_STANDOUT, A_REVERSE, and the other A_* attributes. pair_number() is the counterpart to this function. | |
doc_18874 | resume paused music unpause() -> None This will resume the playback of a music stream after it has been paused. | |
doc_18875 |
Get a mask, or integer index, of the features selected Parameters
indicesbool, default=False
If True, the return value will be an array of integers, rather than a boolean mask. Returns
supportarray
An index that selects the retained features from a feature vector. If indices is False, this is a boolean ... | |
doc_18876 | See Migration guide for more details. tf.compat.v1.random.stateless_binomial
tf.random.stateless_binomial(
shape, seed, counts, probs, output_dtype=tf.dtypes.int32, name=None
)
The generated values follow a binomial distribution with specified count and probability of success parameters. This is a stateless vers... | |
doc_18877 |
Write array to a file as text or binary (default). Data is always written in ‘C’ order, independent of the order of a. The data produced by this method can be recovered using the function fromfile(). Parameters
fidfile or str or Path
An open file object, or a string containing a filename. Changed in version 1.... | |
doc_18878 | class uuid.SafeUUID
New in version 3.7.
safe
The UUID was generated by the platform in a multiprocessing-safe way.
unsafe
The UUID was not generated in a multiprocessing-safe way.
unknown
The platform does not provide information on whether the UUID was generated safely or not.
class uuid.UUID... | |
doc_18879 |
Bases: object Representation of a kernel-density estimate using Gaussian kernels. Parameters
datasetarray-like
Datapoints to estimate from. In case of univariate data this is a 1-D array, otherwise a 2D array with shape (# of dims, # of data).
bw_methodstr, scalar or callable, optional
The method used to ca... | |
doc_18880 | A dictionary of context data that will be added to the default context data passed to the template. | |
doc_18881 | sklearn.set_config(assume_finite=None, working_memory=None, print_changed_only=None, display=None) [source]
Set global scikit-learn configuration New in version 0.19. Parameters
assume_finitebool, default=None
If True, validation for finiteness will be skipped, saving time, but leading to potential crashes. I... | |
doc_18882 | The name to use for the reverse filter name from the target model. It defaults to the value of related_name or default_related_name if set, otherwise it defaults to the name of the model: # Declare the ForeignKey with related_query_name
class Tag(models.Model):
article = models.ForeignKey(
Article,
... | |
doc_18883 | See torch.copysign() | |
doc_18884 | operator.__ifloordiv__(a, b)
a = ifloordiv(a, b) is equivalent to a //= b. | |
doc_18885 | tf.estimator.DNNLinearCombinedRegressor(
model_dir=None, linear_feature_columns=None, linear_optimizer='Ftrl',
dnn_feature_columns=None, dnn_optimizer='Adagrad',
dnn_hidden_units=None, dnn_activation_fn=tf.nn.relu, dnn_dropout=None,
label_dimension=1, weight_column=None, config=None, warm_start_from=Non... | |
doc_18886 | Get a string with the name of the character encoding used in the selected locale. | |
doc_18887 | See Migration guide for more details. tf.compat.v1.keras.datasets.fashion_mnist.load_data
tf.keras.datasets.fashion_mnist.load_data()
This is a dataset of 60,000 28x28 grayscale images of 10 fashion categories, along with a test set of 10,000 images. This dataset can be used as a drop-in replacement for MNIST. The c... | |
doc_18888 |
Alias for get_xlim3d. | |
doc_18889 | class tkinter.filedialog.SaveAs(master=None, **options)
The above two classes provide native dialog windows for saving and loading files. | |
doc_18890 | An ABC with one abstract method __int__. | |
doc_18891 |
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 float or 2D array-like or None
animated bool
array unknown
clim (vmin: float, vmax: float)
clip_box Bbox... | |
doc_18892 |
Resample by using the nearest value. When resampling data, missing values may appear (e.g., when the resampling frequency is higher than the original frequency). The nearest method will replace NaN values that appeared in the resampled data with the value from the nearest member of the sequence, based on the index va... | |
doc_18893 |
Get a mask, or integer index, of the features selected Parameters
indicesbool, default=False
If True, the return value will be an array of integers, rather than a boolean mask. Returns
supportarray
An index that selects the retained features from a feature vector. If indices is False, this is a boolean ... | |
doc_18894 | runeval(expression, globals=None, locals=None)
runcall(function, *args, **kwds)
set_trace()
See the documentation for the functions explained above. | |
doc_18895 |
Roll provided date backward to next offset only if not on offset. Returns
TimeStamp
Rolled timestamp if not on offset, otherwise unchanged timestamp. | |
doc_18896 | The class CAB represents a CAB file. During MSI construction, files will be added simultaneously to the Files table, and to a CAB file. Then, when all files have been added, the CAB file can be written, then added to the MSI file. name is the name of the CAB file in the MSI file.
append(full, file, logical)
Add the... | |
doc_18897 |
Draw samples from the Dirichlet distribution. Draw size samples of dimension k from a Dirichlet distribution. A Dirichlet-distributed random variable can be seen as a multivariate generalization of a Beta distribution. The Dirichlet distribution is a conjugate prior of a multinomial distribution in Bayesian inference... | |
doc_18898 | Character device. | |
doc_18899 |
Apply trees in the forest to X, return leaf indices. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The 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 csr_matrix. Returns
X_leavesndarr... |
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