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doc_27800 | tf.compat.v1.distribute.Strategy(
extended
)
See the guide for overview and examples.
Note: Not all tf.distribute.Strategy implementations currently support TensorFlow's partitioned variables (where a single variable is split across multiple devices) at this time.
Attributes
cluster_resolver Returns the... | |
doc_27801 |
Returns
transformTransform
The transform used for drawing y-axis labels, which will add pad_points of padding (in points) between the axis and the label. The x-direction is in axis coordinates and the y-direction is in data coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}
The tex... | |
doc_27802 | tf.eigvals
tf.linalg.eigvals(
tensor, name=None
)
Note: If your program backpropagates through this function, you should replace it with a call to tf.linalg.eig (possibly ignoring the second output) to avoid computing the eigen decomposition twice. This is because the eigenvectors are used to compute the gradie... | |
doc_27803 |
Univariate linear regression tests. Linear model for testing the individual effect of each of many regressors. This is a scoring function to be used in a feature selection procedure, not a free standing feature selection procedure. This is done in 2 steps: The correlation between each regressor and the target is com... | |
doc_27804 |
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_27805 |
Generate missing values indicator for X. Parameters
X{array-like, sparse matrix}, shape (n_samples, n_features)
The input data to complete. Returns
Xt{ndarray or sparse matrix}, shape (n_samples, n_features) or (n_samples, n_features_with_missing)
The missing indicator for input data. The data type of X... | |
doc_27806 |
Getter for the precision matrix. Returns
precision_array-like of shape (n_features, n_features)
The precision matrix associated to the current covariance object. | |
doc_27807 | Computes the solution x to the matrix equation matmul(input, x) = other with a square matrix, or batches of such matrices, input and one or more right-hand side vectors other. If input is batched and other is not, then other is broadcast to have the same batch dimensions as input. The resulting tensor has the same shap... | |
doc_27808 |
Align the xlabels of subplots in the same subplot column if label alignment is being done automatically (i.e. the label position is not manually set). Alignment persists for draw events after this is called. If a label is on the bottom, it is aligned with labels on Axes that also have their label on the bottom and th... | |
doc_27809 | A message with mbox-specific behaviors. Parameter message has the same meaning as with the Message constructor. Messages in an mbox mailbox are stored together in a single file. The sender’s envelope address and the time of delivery are typically stored in a line beginning with “From ” that is used to indicate the star... | |
doc_27810 | Returns a new tensor with each of the elements of input rounded to the closest integer. Parameters
input (Tensor) – the input tensor. Keyword Arguments
out (Tensor, optional) – the output tensor. Example: >>> a = torch.randn(4)
>>> a
tensor([ 0.9920, 0.6077, 0.9734, -1.0362])
>>> torch.round(a)
tensor([ 1., 1.... | |
doc_27811 | A base view for displaying a list of objects. It is not intended to be used directly, but rather as a parent class of the django.views.generic.list.ListView or other views representing lists of objects. Ancestors (MRO) This view inherits methods and attributes from the following views: django.views.generic.list.Multip... | |
doc_27812 | returns the dimensions of the images being recorded get_size() -> (width, height) Returns the current dimensions of the images being captured by the camera. This will return the actual size, which may be different than the one specified during initialization if the camera did not support that size. | |
doc_27813 |
Bases: matplotlib.patches.BoxStyle._Base A box in the shape of a left-pointing arrow. Parameters
padfloat, default: 0.3
The amount of padding around the original box. __call__(x0, y0, width, height, mutation_size, mutation_aspect=<deprecated parameter>)[source]
Given the location and size of the box, re... | |
doc_27814 | Return the hyperbolic cosine of x. | |
doc_27815 |
Predict using the linear model. Parameters
Xarray-like or sparse matrix, shape (n_samples, n_features)
Samples. Returns
Carray, shape (n_samples,)
Returns predicted values. | |
doc_27816 | Adds a response header to the headers buffer and logs the accepted request. The HTTP response line is written to the internal buffer, followed by Server and Date headers. The values for these two headers are picked up from the version_string() and date_time_string() methods, respectively. If the server does not intend ... | |
doc_27817 |
Estimate 2D geometric transformation parameters. You can determine the over-, well- and under-determined parameters with the total least-squares method. Number of source and destination coordinates must match. Parameters
ttype{‘euclidean’, similarity’, ‘affine’, ‘piecewise-affine’, ‘projective’, ‘polynomial’}
T... | |
doc_27818 | The format in which this field’s initial value will be displayed. | |
doc_27819 |
Return whether x is in the open (x0, x1) interval. | |
doc_27820 |
Return the line width in points. | |
doc_27821 |
alias of numpy.half | |
doc_27822 | tf.compat.v1.create_partitioned_variables(
shape, slicing, initializer, dtype=tf.dtypes.float32, trainable=True,
collections=None, name=None, reuse=None
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.get_variable with a partitioner set. Current... | |
doc_27823 | Returns the indices of the buckets to which each value in the input belongs, where the boundaries of the buckets are set by boundaries. Return a new tensor with the same size as input. If right is False (default), then the left boundary is closed. More formally, the returned index satisfies the following rules:
righ... | |
doc_27824 |
Get whether axis ticks and gridlines are above or below most artists. Returns
bool or 'line'
See also set_axisbelow | |
doc_27825 | Returns the log-transformed bounds on the theta. Returns
boundsndarray of shape (n_dims, 2)
The log-transformed bounds on the kernel’s hyperparameters theta | |
doc_27826 | Create and return a TarInfo object from string buffer buf. Raises HeaderError if the buffer is invalid. | |
doc_27827 | See Migration guide for more details. tf.compat.v1.io.parse_single_sequence_example, tf.compat.v1.parse_single_sequence_example
tf.io.parse_single_sequence_example(
serialized, context_features=None, sequence_features=None, example_name=None,
name=None
)
Parses a single serialized SequenceExample proto given... | |
doc_27828 | See Migration guide for more details. tf.compat.v1.raw_ops.Cos
tf.raw_ops.Cos(
x, name=None
)
Given an input tensor, this function computes cosine of every element in the tensor. Input range is (-inf, inf) and output range is [-1,1]. If input lies outside the boundary, nan is returned. x = tf.constant([-float("i... | |
doc_27829 | Return True if a core dump was generated for the process, otherwise return False. This function should be employed only if WIFSIGNALED() is true. Availability: Unix. | |
doc_27830 |
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_27831 | See Migration guide for more details. tf.compat.v1.keras.layers.Activation
tf.keras.layers.Activation(
activation, **kwargs
)
Arguments
activation Activation function, such as tf.nn.relu, or string name of built-in activation function, such as "relu". Usage:
layer = tf.keras.layers.Activation('relu'... | |
doc_27832 |
Apply a function to 1-D slices along the given axis. Execute func1d(a, *args, **kwargs) where func1d operates on 1-D arrays and a is a 1-D slice of arr along axis. This is equivalent to (but faster than) the following use of ndindex and s_, which sets each of ii, jj, and kk to a tuple of indices: Ni, Nk = a.shape[:ax... | |
doc_27833 | The maximum size (in bytes) of a core file that the current process can create. This may result in the creation of a partial core file if a larger core would be required to contain the entire process image. | |
doc_27834 |
Set the zorder threshold for rasterization for vector graphics output. All artists with a zorder below the given value will be rasterized if they support rasterization. This setting is ignored for pixel-based output. See also Rasterization for vector graphics. Parameters
zfloat or None
The zorder below which ar... | |
doc_27835 | See Migration guide for more details. tf.compat.v1.histogram_fixed_width
tf.histogram_fixed_width(
values, value_range, nbins=100, dtype=tf.dtypes.int32, name=None
)
Given the tensor values, this operation returns a rank 1 histogram counting the number of entries in values that fell into every bin. The bins are ... | |
doc_27836 | Replace &, <, >, ", and ' with HTML-safe sequences. None is escaped to an empty string. Deprecated since version 2.0: Will be removed in Werkzeug 2.1. Use MarkupSafe instead. Parameters
s (Any) – Return type
str | |
doc_27837 | tf.math.log_softmax
tf.nn.log_softmax(
logits, axis=None, name=None
)
For each batch i and class j we have logsoftmax = logits - log(reduce_sum(exp(logits), axis))
Args
logits A non-empty Tensor. Must be one of the following types: half, float32, float64.
axis The dimension softmax would be perfo... | |
doc_27838 |
Forward fill the values. Parameters
limit:int, optional
Limit of how many values to fill. Returns
Series or DataFrame
Object with missing values filled. See also Series.ffill
Returns Series with minimum number of char in object. DataFrame.ffill
Object with missing values filled or None if inplace... | |
doc_27839 | By default, Django’s admin uses a select-box interface (<select>) for fields that are ForeignKey. Sometimes you don’t want to incur the overhead of having to select all the related instances to display in the drop-down. raw_id_fields is a list of fields you would like to change into an Input widget for either a Foreign... | |
doc_27840 |
Return the mean accuracy on the given test data and labels. In multi-label classification, this is the subset accuracy which is a harsh metric since you require for each sample that each label set be correctly predicted. Parameters
Xarray-like of shape (n_samples, n_features)
Test samples.
yarray-like of shap... | |
doc_27841 |
Return the visibility. | |
doc_27842 | os.O_RSYNC
os.O_SYNC
os.O_NDELAY
os.O_NONBLOCK
os.O_NOCTTY
os.O_CLOEXEC
The above constants are only available on Unix. Changed in version 3.3: Add O_CLOEXEC constant. | |
doc_27843 |
Return local percentile of an image. Returns the value of the p0 lower percentile of the local greyvalue distribution. Only greyvalues between percentiles [p0, p1] are considered in the filter. Parameters
image2-D array (uint8, uint16)
Input image.
selem2-D array
The neighborhood expressed as a 2-D array of... | |
doc_27844 | Return the longest path prefix (taken character-by-character) that is a prefix of all paths in list. If list is empty, return the empty string (''). Note This function may return invalid paths because it works a character at a time. To obtain a valid path, see commonpath(). >>> os.path.commonprefix(['/usr/lib', '/usr/... | |
doc_27845 | See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayGradV2
tf.raw_ops.TensorArrayGradV2(
handle, flow_in, source, name=None
)
Args
handle A Tensor of type string.
flow_in A Tensor of type float32.
source A string.
name A name for the operation (optional).
Retu... | |
doc_27846 |
Return the number of leaves of the decision tree. Returns
self.tree_.n_leavesint
Number of leaves. | |
doc_27847 |
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_27848 | See Migration guide for more details. tf.compat.v1.raw_ops.DenseToSparseSetOperation
tf.raw_ops.DenseToSparseSetOperation(
set1, set2_indices, set2_values, set2_shape, set_operation,
validate_indices=True, name=None
)
See SetOperationOp::SetOperationFromContext for values of set_operation. Input set2 is a Sp... | |
doc_27849 | Returns a copy of the object using copy.deepcopy(). This copy will be mutable even if the original was not. | |
doc_27850 | Returns worker information of the node that owns this RRef. | |
doc_27851 |
Return the largest n elements. Parameters
n:int, default 5
Return this many descending sorted values.
keep:{‘first’, ‘last’, ‘all’}, default ‘first’
When there are duplicate values that cannot all fit in a Series of n elements: first : return the first n occurrences in order of appearance. last : return th... | |
doc_27852 | tf.profiler.experimental.Trace(
name, **kwargs
)
A trace event will start when entering the context, and stop and save the result to the profiler when exiting the context. Open TensorBoard Profile tab and choose trace viewer to view the trace event in the timeline. Trace events are created only when the profiler i... | |
doc_27853 |
Adds many scalar data to summary. Parameters
main_tag (string) – The parent name for the tags
tag_scalar_dict (dict) – Key-value pair storing the tag and corresponding values
global_step (int) – Global step value to record
walltime (float) – Optional override default walltime (time.time()) seconds after epoch ... | |
doc_27854 | When this namespace is specified, the name string is a URL. | |
doc_27855 | The view part of the view – the method that accepts a request argument plus arguments, and returns an HTTP response. The default implementation will inspect the HTTP method and attempt to delegate to a method that matches the HTTP method; a GET will be delegated to get(), a POST to post(), and so on. By default, a HEAD... | |
doc_27856 |
Binarize labels in a one-vs-all fashion. Several regression and binary classification algorithms are available in scikit-learn. A simple way to extend these algorithms to the multi-class classification case is to use the so-called one-vs-all scheme. This function makes it possible to compute this transformation for a... | |
doc_27857 |
Convert b to bool or raise. | |
doc_27858 | See torch.greater(). | |
doc_27859 | Informs the logging system to perform an orderly shutdown by flushing and closing all handlers. This should be called at application exit and no further use of the logging system should be made after this call. When the logging module is imported, it registers this function as an exit handler (see atexit), so normally ... | |
doc_27860 | Returns a string containing the base set by a previous call to SetBase(), or None if SetBase() hasn’t been called. | |
doc_27861 | Parameters
y – a number (integer or float) Set the turtle’s second coordinate to y, leave first coordinate unchanged. >>> turtle.position()
(0.00,40.00)
>>> turtle.sety(-10)
>>> turtle.position()
(0.00,-10.00) | |
doc_27862 | A Popen creationflags parameter to specify that a new process is not associated with the job. New in version 3.7. | |
doc_27863 |
Call image_filter with widget args and kwargs Note: display_filtered_image is automatically called. | |
doc_27864 | sklearn.metrics.median_absolute_error(y_true, y_pred, *, multioutput='uniform_average', sample_weight=None) [source]
Median absolute error regression loss. Median absolute error output is non-negative floating point. The best value is 0.0. Read more in the User Guide. Parameters
y_truearray-like of shape = (n_sam... | |
doc_27865 | See Migration guide for more details. tf.compat.v1.raw_ops.MaxPool3DGrad
tf.raw_ops.MaxPool3DGrad(
orig_input, orig_output, grad, ksize, strides, padding,
data_format='NDHWC', name=None
)
Args
orig_input A Tensor. Must be one of the following types: half, bfloat16, float32. The original input tensor... | |
doc_27866 | See Migration guide for more details. tf.compat.v1.ragged.stack_dynamic_partitions
tf.ragged.stack_dynamic_partitions(
data, partitions, num_partitions, name=None
)
Returns a RaggedTensor output with num_partitions rows, where the row output[i] is formed by stacking all slices data[j1...jN] such that partitions[... | |
doc_27867 |
Creates a criterion that measures the triplet loss given input tensors aa , pp , and nn (representing anchor, positive, and negative examples, respectively), and a nonnegative, real-valued function (“distance function”) used to compute the relationship between the anchor and positive example (“positive distance”) an... | |
doc_27868 | Return all non-overlapping matches of pattern in string, as a list of strings. The string is scanned left-to-right, and matches are returned in the order found. If one or more groups are present in the pattern, return a list of groups; this will be a list of tuples if the pattern has more than one group. Empty matches ... | |
doc_27869 |
Stack arrays in sequence depth wise (along third axis). This is equivalent to concatenation along the third axis after 2-D arrays of shape (M,N) have been reshaped to (M,N,1) and 1-D arrays of shape (N,) have been reshaped to (1,N,1). Rebuilds arrays divided by dsplit. This function makes most sense for arrays with u... | |
doc_27870 | Allow use of default values for colors on terminals supporting this feature. Use this to support transparency in your application. The default color is assigned to the color number -1. After calling this function, init_pair(x,
curses.COLOR_RED, -1) initializes, for instance, color pair x to a red foreground color on th... | |
doc_27871 | Attributes
extra_context
A dictionary to include in the context. This is a convenient way of specifying some context in as_view(). Example usage: from django.views.generic import TemplateView
TemplateView.as_view(extra_context={'title': 'Custom Title'})
Methods
get_context_data(**kwargs)
Returns a dictionary... | |
doc_27872 | See torch.ceil() | |
doc_27873 | Return the docstring of the given node (which must be a FunctionDef, AsyncFunctionDef, ClassDef, or Module node), or None if it has no docstring. If clean is true, clean up the docstring’s indentation with inspect.cleandoc(). Changed in version 3.5: AsyncFunctionDef is now supported. | |
doc_27874 |
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_27875 |
Set multiple properties at once. Supported properties are
Property Description
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha scalar or None
animated bool
antialiased or aa bool or None
capstyle CapStyle or {'butt', 'projecting', 'r... | |
doc_27876 |
Return a format string formatting the coordinate. | |
doc_27877 | Works like a regular dict but the get() method can perform type conversions. MultiDict and CombinedMultiDict are subclasses of this class and provide the same feature. Changelog New in version 0.5.
get(key, default=None, type=None)
Return the default value if the requested data doesn’t exist. If type is provided ... | |
doc_27878 | See Migration guide for more details. tf.compat.v1.estimator.LatestExporter
tf.estimator.LatestExporter(
name, serving_input_receiver_fn, assets_extra=None, as_text=False,
exports_to_keep=5
)
In addition to exporting, this class also garbage collects stale exports.
Args
name unique name of this Expo... | |
doc_27879 |
Parameters
urlslist of str or None
Notes URLs are currently only implemented by the SVG backend. They are ignored by all other backends. | |
doc_27880 | The PUT action is also handled and passes all parameters through to post(). | |
doc_27881 |
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_27882 | This behaves exactly like walk(), except that it yields a 4-tuple (dirpath, dirnames, filenames, dirfd), and it supports dir_fd. dirpath, dirnames and filenames are identical to walk() output, and dirfd is a file descriptor referring to the directory dirpath. This function always supports paths relative to directory de... | |
doc_27883 | See Migration guide for more details. tf.compat.v1.estimator.experimental.stop_if_lower_hook
tf.estimator.experimental.stop_if_lower_hook(
estimator, metric_name, threshold, eval_dir=None, min_steps=0,
run_every_secs=60, run_every_steps=None
)
Usage example: estimator = ...
# Hook to stop training if loss be... | |
doc_27884 | Returns an instance of the Filter class. If name is specified, it names a logger which, together with its children, will have its events allowed through the filter. If name is the empty string, allows every event.
filter(record)
Is the specified record to be logged? Returns zero for no, nonzero for yes. If deemed a... | |
doc_27885 | Returns the current unpack data buffer as a string. | |
doc_27886 | Creates a new item and returns the item identifier of the newly created item. parent is the item ID of the parent item, or the empty string to create a new top-level item. index is an integer, or the value “end”, specifying where in the list of parent’s children to insert the new item. If index is less than or equal to... | |
doc_27887 | class sklearn.linear_model.BayesianRidge(*, n_iter=300, tol=0.001, alpha_1=1e-06, alpha_2=1e-06, lambda_1=1e-06, lambda_2=1e-06, alpha_init=None, lambda_init=None, compute_score=False, fit_intercept=True, normalize=False, copy_X=True, verbose=False) [source]
Bayesian ridge regression. Fit a Bayesian ridge model. See ... | |
doc_27888 | Decodes a DLPack to a tensor. Parameters
dlpack – a PyCapsule object with the dltensor The tensor will share the memory with the object represented in the dlpack. Note that each dlpack can only be consumed once. | |
doc_27889 | Parameters
angle – a number Rotate the turtleshape to point in the direction specified by angle, regardless of its current tilt-angle. Do not change the turtle’s heading (direction of movement). >>> turtle.reset()
>>> turtle.shape("circle")
>>> turtle.shapesize(5,2)
>>> turtle.settiltangle(45)
>>> turtle.fd(50)
>>>... | |
doc_27890 | socket.PF_PACKET
PACKET_*
Many constants of these forms, documented in the Linux documentation, are also defined in the socket module. Availability: Linux >= 2.2. | |
doc_27891 | Returns a namedtuple() (nchannels, sampwidth,
framerate, nframes, comptype, compname), equivalent to output of the get*() methods. | |
doc_27892 | tf.experimental.numpy.swapaxes(
a, axis1, axis2
)
See the NumPy documentation for numpy.swapaxes. | |
doc_27893 |
Bases: mpl_toolkits.axisartist.axisline_style.AxislineStyle.SimpleArrow Parameters
sizefloat
Size of the arrow as a fraction of the ticklabel size. ArrowAxisClass[source]
alias of mpl_toolkits.axisartist.axisline_style._FancyAxislineStyle.FilledArrow | |
doc_27894 | See Migration guide for more details. tf.compat.v1.config.run_functions_eagerly
tf.config.run_functions_eagerly(
run_eagerly
)
Calling tf.config.run_functions_eagerly(True) will make all invocations of tf.function run eagerly instead of running as a traced graph function. This can be useful for debugging.
def m... | |
doc_27895 | Return the single most common data point from discrete or nominal data. The mode (when it exists) is the most typical value and serves as a measure of central location. If there are multiple modes with the same frequency, returns the first one encountered in the data. If the smallest or largest of those is desired inst... | |
doc_27896 | boolean that is True if the application is served by a multithreaded WSGI server. | |
doc_27897 |
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_27898 |
Return a tuple width, height, xdescent, ydescent of the box. | |
doc_27899 | Although the Cursor class of the sqlite3 module implements this attribute, the database engine’s own support for the determination of “rows affected”/”rows selected” is quirky. For executemany() statements, the number of modifications are summed up into rowcount. As required by the Python DB API Spec, the rowcount attr... |
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