_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_15800 |
Call self as a function. | |
doc_15801 | Adds a child module to the current module. The module can be accessed as an attribute using the given name. Parameters
name (string) – name of the child module. The child module can be accessed from this module using the given name
module (Module) – child module to be added to the module. | |
doc_15802 | Return the given window’s current background character/attribute pair. | |
doc_15803 | tf.experimental.numpy.eye(
N, M=None, k=0, dtype=float
)
Unsupported arguments: order. See the NumPy documentation for numpy.eye. | |
doc_15804 | torch.backends.cuda.is_built() [source]
Returns whether PyTorch is built with CUDA support. Note that this doesn’t necessarily mean CUDA is available; just that if this PyTorch binary were run a machine with working CUDA drivers and devices, we would be able to use it.
torch.backends.cuda.matmul.allow_tf32
A bo... | |
doc_15805 |
Return the zaxis' major tick labels, as a list of Text. | |
doc_15806 | Return True if the event loop was closed. | |
doc_15807 |
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_15808 |
Return a transformed copy of the path. See also matplotlib.transforms.TransformedPath
A specialized path class that will cache the transformed result and automatically update when the transform changes. | |
doc_15809 | Get a reference to the currently set display surface get_surface() -> Surface Return a reference to the currently set display Surface. If no display mode has been set this will return None. | |
doc_15810 |
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_15811 |
The sampling algorithm for the von Mises distribution is based on the following paper: Best, D. J., and Nicholas I. Fisher. “Efficient simulation of the von Mises distribution.” Applied Statistics (1979): 152-157. | |
doc_15812 | The CSS class for a weekday occurring in the previous or coming month. New in version 3.7. | |
doc_15813 |
Applies the element-wise function ReLU6(x)=min(max(0,x),6)\text{ReLU6}(x) = \min(\max(0,x), 6) . See ReLU6 for more details. | |
doc_15814 | Concrete class for urlparse() results containing str data. The encode() method returns a ParseResultBytes instance. | |
doc_15815 | The address which is being used by the Listener object. | |
doc_15816 |
Construct an IntervalArray from an array of splits. Parameters
breaks:array-like (1-dimensional)
Left and right bounds for each interval.
closed:{‘left’, ‘right’, ‘both’, ‘neither’}, default ‘right’
Whether the intervals are closed on the left-side, right-side, both or neither.
copy:bool, default False
... | |
doc_15817 | A set of hosts, in addition to request.get_host(), that are safe for redirecting after login. Defaults to an empty set. | |
doc_15818 |
Function that uses a squared term if the absolute element-wise error falls below beta and an L1 term otherwise. See SmoothL1Loss for details. | |
doc_15819 | Token value for "-=". | |
doc_15820 |
async def run(cmd):
proc = await asyncio.create_subprocess_shell(
cmd,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE)
stdout, stderr = await proc.communicate()
print(f'[{cmd!r} exited with {proc.returncode}]')
if stdout:
print(f'[stdout]\n{stdout.decod... | |
doc_15821 |
Convert angles from degrees to radians. Parameters
xarray_like
Angles in degrees.
outndarray, None, or tuple of ndarray and None, optional
A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returne... | |
doc_15822 | tf.while_loop(
cond, body, loop_vars, shape_invariants=None, parallel_iterations=10,
back_prop=True, swap_memory=False, maximum_iterations=None, name=None
)
Warning: SOME ARGUMENT VALUES ARE DEPRECATED: (back_prop=False). They will be removed in a future version. Instructions for updating: back_prop=False is d... | |
doc_15823 | Name of a supported database vendor that this model is specific to. Current built-in vendor names are: sqlite, postgresql, mysql, oracle. If this attribute is not empty and the current connection vendor doesn’t match it, the model will not be synchronized. | |
doc_15824 | Query or sets dynamic values of the specified option(s) in style. Each key in kw is an option and each value should be a list or a tuple (usually) containing statespecs grouped in tuples, lists, or some other preference. A statespec is a compound of one or more states and then a value. An example may make it more under... | |
doc_15825 | Returns the indices of the minimum value(s) of the flattened tensor or along a dimension This is the second value returned by torch.min(). See its documentation for the exact semantics of this method. Note If there are multiple minimal values then the indices of the first minimal value are returned. Parameters
in... | |
doc_15826 | Maps a logging level name to a syslog priority name. You may need to override this if you are using custom levels, or if the default algorithm is not suitable for your needs. The default algorithm maps DEBUG, INFO, WARNING, ERROR and CRITICAL to the equivalent syslog names, and all other level names to ‘warning’. | |
doc_15827 | See Migration guide for more details. tf.compat.v1.raw_ops.RaggedCountSparseOutput
tf.raw_ops.RaggedCountSparseOutput(
splits, values, weights, binary_output, minlength=-1, maxlength=-1, name=None
)
Counts the number of times each value occurs in the input.
Args
splits A Tensor of type int64. Tensor con... | |
doc_15828 | See Migration guide for more details. tf.compat.v1.raw_ops.TensorSliceDataset
tf.raw_ops.TensorSliceDataset(
components, output_shapes, name=None
)
Args
components A list of Tensor objects.
output_shapes A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.
name A na... | |
doc_15829 | Alias for torch.neg() | |
doc_15830 |
Number of elements in the array. Equal to np.prod(a.shape), i.e., the product of the array’s dimensions. Notes a.size returns a standard arbitrary precision Python integer. This may not be the case with other methods of obtaining the same value (like the suggested np.prod(a.shape), which returns an instance of np.int... | |
doc_15831 | tf.keras.models.Sequential Compat aliases for migration See Migration guide for more details. tf.compat.v1.keras.Sequential, tf.compat.v1.keras.models.Sequential
tf.keras.Sequential(
layers=None, name=None
)
Sequential provides training and inference features on this model. Examples:
# Optionally, the first lay... | |
doc_15832 |
Set the offsets for the collection. Parameters
offsets(N, 2) or (2,) array-like | |
doc_15833 |
Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y, z). If l, m, n are the given degrees in x, y, z, then The pseudo-Vandermonde matrix is defined by \[V[..., (m+1)(n+1)i + (n+1)j + k] = H_i(x)*H_j(y)*H_k(z),\] where 0 <= i <= l, 0 <= j <= m, and ... | |
doc_15834 | Return True if a keypress is waiting to be read. | |
doc_15835 |
The number of array dimensions. | |
doc_15836 | A generic version of collections.abc.Iterator. Deprecated since version 3.9: collections.abc.Iterator now supports []. See PEP 585 and Generic Alias Type. | |
doc_15837 |
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op. Parameters
valuesarray
The input v... | |
doc_15838 | Decode the path-like filename from the filesystem encoding with 'surrogateescape' error handler, or 'strict' on Windows; return str unchanged. fsencode() is the reverse function. New in version 3.2. Changed in version 3.6: Support added to accept objects implementing the os.PathLike interface. | |
doc_15839 |
Convert the data back to the original representation. In case unknown categories are encountered (all zeros in the one-hot encoding), None is used to represent this category. Parameters
Xarray-like or sparse matrix, shape [n_samples, n_encoded_features]
The transformed data. Returns
X_trarray-like, shape ... | |
doc_15840 | class sklearn.preprocessing.PolynomialFeatures(degree=2, *, interaction_only=False, include_bias=True, order='C') [source]
Generate polynomial and interaction features. Generate a new feature matrix consisting of all polynomial combinations of the features with degree less than or equal to the specified degree. For e... | |
doc_15841 |
Set the CapStyle for the collection (for all its elements). Parameters
csCapStyle or {'butt', 'projecting', 'round'} | |
doc_15842 | draw an ellipse ellipse(surface, x, y, rx, ry, color) -> None Draws an unfilled ellipse on the given surface. For a filled ellipse use filled_ellipse().
Parameters:
surface (Surface) -- surface to draw on
x (int) -- x coordinate of the center of the ellipse
y (int) -- y coordinate of the center of the ellip... | |
doc_15843 | @abc.abstractmethod
create_session() | |
doc_15844 | class sklearn.manifold.MDS(n_components=2, *, metric=True, n_init=4, max_iter=300, verbose=0, eps=0.001, n_jobs=None, random_state=None, dissimilarity='euclidean') [source]
Multidimensional scaling. Read more in the User Guide. Parameters
n_componentsint, default=2
Number of dimensions in which to immerse the d... | |
doc_15845 | See Migration guide for more details. tf.compat.v1.stack
tf.stack(
values, axis=0, name='stack'
)
See also tf.concat, tf.tile, tf.repeat. Packs the list of tensors in values into a tensor with rank one higher than each tensor in values, by packing them along the axis dimension. Given a list of length N of tensor... | |
doc_15846 |
Bases: torch.distributions.transformed_distribution.TransformedDistribution Creates a half-Cauchy distribution parameterized by scale where: X ~ Cauchy(0, scale)
Y = |X| ~ HalfCauchy(scale)
Example: >>> m = HalfCauchy(torch.tensor([1.0]))
>>> m.sample() # half-cauchy distributed with scale=1
tensor([ 2.3214])
Par... | |
doc_15847 | tf.nn.convolution(
input, filters, strides=None, padding='VALID', data_format=None,
dilations=None, name=None
)
This also supports either output striding via the optional strides parameter or atrous convolution (also known as convolution with holes or dilated convolution, based on the French word "trous" meani... | |
doc_15848 | tf.compat.v1.losses.add_loss(
loss, loss_collection=tf.GraphKeys.LOSSES
)
Args
loss A loss Tensor.
loss_collection Optional collection to add the loss to. | |
doc_15849 | Out-of-place version of torch.Tensor.masked_fill_() | |
doc_15850 | tf.keras.layers.Convolution2D Compat aliases for migration See Migration guide for more details. tf.compat.v1.keras.layers.Conv2D, tf.compat.v1.keras.layers.Convolution2D
tf.keras.layers.Conv2D(
filters, kernel_size, strides=(1, 1), padding='valid',
data_format=None, dilation_rate=(1, 1), groups=1, activation... | |
doc_15851 | sklearn.metrics.mean_tweedie_deviance(y_true, y_pred, *, sample_weight=None, power=0) [source]
Mean Tweedie deviance regression loss. Read more in the User Guide. Parameters
y_truearray-like of shape (n_samples,)
Ground truth (correct) target values.
y_predarray-like of shape (n_samples,)
Estimated target v... | |
doc_15852 |
Return a reference to the shared axes Grouper object for x axes. | |
doc_15853 |
Mask an array where equal to a given value. This function is a shortcut to masked_where, with condition = (x == value). For floating point arrays, consider using masked_values(x, value). See also masked_where
Mask where a condition is met. masked_values
Mask using floating point equality. Examples >>> import ... | |
doc_15854 | Paginator class
class Paginator(object_list, per_page, orphans=0, allow_empty_first_page=True)
A paginator acts like a sequence of Page when using len() or iterating it directly.
Paginator.object_list
Required. A list, tuple, QuerySet, or other sliceable object with a count() or __len__() method. For consiste... | |
doc_15855 | See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalSqlDataset
tf.raw_ops.ExperimentalSqlDataset(
driver_name, data_source_name, query, output_types, output_shapes, name=None
)
Args
driver_name A Tensor of type string. The database type. Currently, the only supported type is 'sqlite'.... | |
doc_15856 | Creates a StreamRecoder instance which implements a two-way conversion: encode and decode work on the frontend — the data visible to code calling read() and write(), while Reader and Writer work on the backend — the data in stream. You can use these objects to do transparent transcodings, e.g., from Latin-1 to UTF-8 an... | |
doc_15857 | tf.errors.OperatorNotAllowedInGraphError(
*args, **kwargs
)
For example, using a tf.Tensor as a Python bool in Graph execution is not allowed. | |
doc_15858 | Returns the size in bytes of a ctypes type or instance memory buffer. Does the same as the C sizeof operator. | |
doc_15859 | See Migration guide for more details. tf.compat.v1.image.flip_up_down
tf.image.flip_up_down(
image
)
Outputs the contents of image flipped along the height dimension. See also reverse(). Usage Example:
x = [[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0]],
[[7.0, 8.0, 9.0],
[10.0, 11.0, 12.0]]]
tf.image.flip_... | |
doc_15860 | Marks the user as having no password set. This isn’t the same as having a blank string for a password. check_password() for this user will never return True. Doesn’t save the AbstractBaseUser object. You may need this if authentication for your application takes place against an existing external source such as an LDAP... | |
doc_15861 |
Returns
list
List of segments in the LineCollection. Each list item contains an array of vertices. | |
doc_15862 | tf.metrics.CategoricalCrossentropy Compat aliases for migration See Migration guide for more details. tf.compat.v1.keras.metrics.CategoricalCrossentropy
tf.keras.metrics.CategoricalCrossentropy(
name='categorical_crossentropy', dtype=None, from_logits=False,
label_smoothing=0
)
This is the crossentropy metri... | |
doc_15863 | class sklearn.neighbors.KernelDensity(*, bandwidth=1.0, algorithm='auto', kernel='gaussian', metric='euclidean', atol=0, rtol=0, breadth_first=True, leaf_size=40, metric_params=None) [source]
Kernel Density Estimation. Read more in the User Guide. Parameters
bandwidthfloat, default=1.0
The bandwidth of the kern... | |
doc_15864 | Create a mapping from positional and keyword arguments to parameters. Returns BoundArguments if *args and **kwargs match the signature, or raises a TypeError. | |
doc_15865 | Similar to process_time() but return time as nanoseconds. New in version 3.7. | |
doc_15866 |
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_15867 | See Migration guide for more details. tf.compat.v1.estimator.export.build_raw_serving_input_receiver_fn
tf.estimator.export.build_raw_serving_input_receiver_fn(
features, default_batch_size=None
)
Creates an serving_input_receiver_fn that expects all features to be fed directly.
Args
features a dict of ... | |
doc_15868 |
Draw a Path instance using the given affine transform. | |
doc_15869 | Move the panel to the screen coordinates (y, x). | |
doc_15870 |
Adjust the subplot layout parameters. Unset parameters are left unmodified; initial values are given by rcParams["figure.subplot.[name]"]. Parameters
leftfloat, optional
The position of the left edge of the subplots, as a fraction of the figure width.
rightfloat, optional
The position of the right edge of t... | |
doc_15871 | The HttpResponse class that handles the redirect. Defaults to HttpResponsePermanentRedirect. | |
doc_15872 |
Return whether all elements are Truthy. Parameters
*args
Required for compatibility with numpy. **kwargs
Required for compatibility with numpy. Returns
all:bool or array-like (if axis is specified)
A single element array-like may be converted to bool. See also Index.any
Return whether any element... | |
doc_15873 |
Returns a Python float containing the scale backoff factor. | |
doc_15874 | The function provides PKCS#5 password-based key derivation function 2. It uses HMAC as pseudorandom function. The string hash_name is the desired name of the hash digest algorithm for HMAC, e.g. ‘sha1’ or ‘sha256’. password and salt are interpreted as buffers of bytes. Applications and libraries should limit password t... | |
doc_15875 | class ast.SetComp(elt, generators)
class ast.GeneratorExp(elt, generators)
class ast.DictComp(key, value, generators)
List and set comprehensions, generator expressions, and dictionary comprehensions. elt (or key and value) is a single node representing the part that will be evaluated for each item. generators is... | |
doc_15876 |
Return the label reference position in transAxes. get_label_transform() returns a transform of (transAxes+offset) | |
doc_15877 |
pygame module for cursor resources Pygame offers control over the system hardware cursor. Pygame only supports black and white cursors for the system. You control the cursor with functions inside pygame.mouse. This cursors module contains functions for loading and decoding various cursor formats. These allow you t... | |
doc_15878 |
Whether to rotate the axis label: True, False or None. If set to None the label will be rotated if longer than 4 chars. | |
doc_15879 |
Bases: matplotlib.patches.BoxStyle._Base A box with round corners. Parameters
padfloat, default: 0.3
The amount of padding around the original box.
rounding_sizefloat, default: pad
Radius of the corners. __call__(x0, y0, width, height, mutation_size, mutation_aspect=<deprecated parameter>)[source]
G... | |
doc_15880 | See Migration guide for more details. tf.compat.v1.config.LogicalDevice
tf.config.LogicalDevice(
name, device_type
)
A tf.config.LogicalDevice corresponds to an initialized logical device on a tf.config.PhysicalDevice or a remote device visible to the cluster. Tensors and operations can be placed on a specific l... | |
doc_15881 |
Check gradients computed via small finite differences against analytical gradients w.r.t. tensors in inputs that are of floating point or complex type and with requires_grad=True. The check between numerical and analytical gradients uses allclose(). For complex functions, no notion of Jacobian exists. Gradcheck verif... | |
doc_15882 | tf.experimental.numpy.nanprod(
a, axis=None, dtype=None, keepdims=False
)
Unsupported arguments: out. See the NumPy documentation for numpy.nanprod. | |
doc_15883 | Spec: RFC 4287 | |
doc_15884 | See Migration guide for more details. tf.compat.v1.raw_ops.LookupTableSizeV2
tf.raw_ops.LookupTableSizeV2(
table_handle, name=None
)
Args
table_handle A Tensor of type resource. Handle to the table.
name A name for the operation (optional).
Returns A Tensor of type int64. | |
doc_15885 | The C API version for this interpreter. Programmers may find this useful when debugging version conflicts between Python and extension modules. | |
doc_15886 | This is the superclass of all Server objects in the module. It defines the interface, given below, but does not implement most of the methods, which is done in subclasses. The two parameters are stored in the respective server_address and RequestHandlerClass attributes.
fileno()
Return an integer file descriptor fo... | |
doc_15887 |
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_15888 | __setitem__(key, message)
update(arg)
Warning These methods generate unique file names based upon the current process ID. When using multiple threads, undetected name clashes may occur and cause corruption of the mailbox unless threads are coordinated to avoid using these methods to manipulate the same mailbox sim... | |
doc_15889 | Return True if key corresponds to a message, False otherwise. | |
doc_15890 | The record’s attribute dictionary is used as the operand to a string formatting operation. Returns the resulting string. Before formatting the dictionary, a couple of preparatory steps are carried out. The message attribute of the record is computed using msg % args. If the formatting string contains '(asctime)', forma... | |
doc_15891 | This function does the actual work of formatting. It is exposed as a separate function for cases where you want to pass in a predefined dictionary of arguments, rather than unpacking and repacking the dictionary as individual arguments using the *args and **kwargs syntax. vformat() does the work of breaking up the form... | |
doc_15892 |
Set the edgecolor(s) of the collection. Parameters
ccolor or list of colors or 'face'
The collection edgecolor(s). If a sequence, the patches cycle through it. If 'face', match the facecolor. | |
doc_15893 |
Return the Colormap instance. | |
doc_15894 | Return the compression algorithm being used as a string, or None if the connection isn’t compressed. If the higher-level protocol supports its own compression mechanism, you can use OP_NO_COMPRESSION to disable SSL-level compression. New in version 3.3. | |
doc_15895 | Return the turtle’s x coordinate. >>> turtle.home()
>>> turtle.left(50)
>>> turtle.forward(100)
>>> turtle.pos()
(64.28,76.60)
>>> print(round(turtle.xcor(), 5))
64.27876 | |
doc_15896 |
Convert structured or record ndarray to DataFrame. Creates a DataFrame object from a structured ndarray, sequence of tuples or dicts, or DataFrame. Parameters
data:structured ndarray, sequence of tuples or dicts, or DataFrame
Structured input data.
index:str, list of fields, array-like
Field of array to use... | |
doc_15897 | See Migration guide for more details. tf.compat.v1.train.FeatureLists
Attributes
feature_list repeated FeatureListEntry feature_list Child Classes class FeatureListEntry | |
doc_15898 | See Migration guide for more details. tf.compat.v1.raw_ops.Angle
tf.raw_ops.Angle(
input, Tout=tf.dtypes.float32, name=None
)
Given a tensor input of complex numbers, this operation returns a tensor of type float that is the argument of each element in input. All elements in input must be complex numbers of the ... | |
doc_15899 | os.POSIX_FADV_SEQUENTIAL
os.POSIX_FADV_RANDOM
os.POSIX_FADV_NOREUSE
os.POSIX_FADV_WILLNEED
os.POSIX_FADV_DONTNEED
Flags that can be used in advice in posix_fadvise() that specify the access pattern that is likely to be used. Availability: Unix. New in version 3.3. |
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