_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_1200 | See Migration guide for more details. tf.compat.v1.app.flags.FloatParser
tf.compat.v1.flags.FloatParser(
lower_bound=None, upper_bound=None
)
Parsed value may be bounded to a given upper and lower bound. Methods convert
convert(
argument
)
Returns the float value of argument. flag_type
flag_type()
See ba... | |
doc_1201 |
Returns the score on the given data, if the estimator has been refit. This uses the score defined by scoring where provided, and the best_estimator_.score method otherwise. Parameters
Xarray-like of shape (n_samples, n_features)
Input data, where n_samples is the number of samples and n_features is the number o... | |
doc_1202 |
Return whether the Artist has an explicitly set transform. This is True after set_transform has been called. | |
doc_1203 |
Warning used to notify implicit data conversions happening in the code. This warning occurs when some input data needs to be converted or interpreted in a way that may not match the user’s expectations. For example, this warning may occur when the user
passes an integer array to a function which expects float inpu... | |
doc_1204 | See Migration guide for more details. tf.compat.v1.keras.layers.StackedRNNCells
tf.keras.layers.StackedRNNCells(
cells, **kwargs
)
Used to implement efficient stacked RNNs.
Arguments
cells List of RNN cell instances. Examples: batch_size = 3
sentence_max_length = 5
n_features = 2
new_shape = (batch_s... | |
doc_1205 | A dictionary mapping from option flags to True or False, which is used to override default options for this example. Any option flags not contained in this dictionary are left at their default value (as specified by the DocTestRunner’s optionflags). By default, no options are set. | |
doc_1206 | Contains information about the current hardware profile of the local computer system. | |
doc_1207 |
Set the (group) id for the artist. Parameters
gidstr | |
doc_1208 | Listing subdirectories: >>> p = Path('.')
>>> [x for x in p.iterdir() if x.is_dir()]
[PosixPath('.hg'), PosixPath('docs'), PosixPath('dist'),
PosixPath('__pycache__'), PosixPath('build')]
Listing Python source files in this directory tree: >>> list(p.glob('**/*.py'))
[PosixPath('test_pathlib.py'), PosixPath('setup.p... | |
doc_1209 |
Plot a triangulated surface. The (optional) triangulation can be specified in one of two ways; either: plot_trisurf(triangulation, ...)
where triangulation is a Triangulation object, or: plot_trisurf(X, Y, ...)
plot_trisurf(X, Y, triangles, ...)
plot_trisurf(X, Y, triangles=triangles, ...)
in which case a Triangula... | |
doc_1210 |
Predict regression target at each stage for X. This method allows monitoring (i.e. determine error on testing set) after each stage. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The input samples. Internally, it will be converted to dtype=np.float32 and if a sparse matrix is provided... | |
doc_1211 |
Determine if an image is low contrast. Parameters
imagearray-like
The image under test.
fraction_thresholdfloat, optional
The low contrast fraction threshold. An image is considered low- contrast when its range of brightness spans less than this fraction of its data type’s full range. [1]
lower_percentile... | |
doc_1212 |
Fit the model according to the given training data. Parameters
Xarray-like of shape (n_samples, n_features)
The training samples.
yarray-like of shape (n_samples,)
The corresponding training labels. Returns
selfobject
returns a trained NeighborhoodComponentsAnalysis model. | |
doc_1213 |
Applies the element-wise function: ReLU6(x)=min(max(x0,x),q(6))\text{ReLU6}(x) = \min(\max(x_0, x), q(6)) , where x0x_0 is the zero_point, and q(6)q(6) is the quantized representation of number 6. Parameters
inplace – can optionally do the operation in-place. Default: False Shape:
Input: (N,∗)(N, *) where... | |
doc_1214 |
Returns the number of splitting iterations in the cross-validator Parameters
Xobject
Always ignored, exists for compatibility. np.zeros(n_samples) may be used as a placeholder.
yobject
Always ignored, exists for compatibility. np.zeros(n_samples) may be used as a placeholder.
groupsarray-like of shape (n_... | |
doc_1215 |
Remove axes of length one from a. Parameters
aarray_like
Input data.
axisNone or int or tuple of ints, optional
New in version 1.7.0. Selects a subset of the entries of length one in the shape. If an axis is selected with shape entry greater than one, an error is raised. Returns
squeezedMaskedArray
... | |
doc_1216 |
Return the visibility. | |
doc_1217 | Send an HTTP request, which can be either GET or POST, depending on req.has_data(). | |
doc_1218 |
Return peaks in a circle Hough transform. Identifies most prominent circles separated by certain distances in given Hough spaces. Non-maximum suppression with different sizes is applied separately in the first and second dimension of the Hough space to identify peaks. For circles with different radius but close in di... | |
doc_1219 |
Return the mapping parameters. The returned values define a linear map off + scl*x that is applied to the input arguments before the series is evaluated. The map depends on the domain and window; if the current domain is equal to the window the resulting map is the identity. If the coefficients of the series instance... | |
doc_1220 |
Return the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation. | |
doc_1221 | Pattern Meaning
* matches everything
? matches any single character
[seq] matches any character in seq
[!seq] matches any character not in seq For a literal match, wrap the meta-characters in brackets. For example, '[?]' matches the character '?'. Note that the filename separator ('/' on Unix) is not special... | |
doc_1222 |
Return the visibility. | |
doc_1223 |
Return the values (min, max) that are mapped to the colormap limits. | |
doc_1224 |
Warp an image according to a given coordinate transformation. Parameters
imagendarray
Input image.
inverse_maptransformation object, callable cr = f(cr, **kwargs), or ndarray
Inverse coordinate map, which transforms coordinates in the output images into their corresponding coordinates in the input image. Th... | |
doc_1225 |
Determine if two Index object are equal. The things that are being compared are: The elements inside the Index object. The order of the elements inside the Index object. Parameters
other:Any
The other object to compare against. Returns
bool
True if “other” is an Index and it has the same elements and or... | |
doc_1226 |
Return the roots of the series polynomial. Compute the roots for the series. Note that the accuracy of the roots decrease the further outside the domain they lie. Returns
rootsndarray
Array containing the roots of the series. | |
doc_1227 | Return the encoding used for text data, according to user preferences. User preferences are expressed differently on different systems, and might not be available programmatically on some systems, so this function only returns a guess. On some systems, it is necessary to invoke setlocale() to obtain the user preference... | |
doc_1228 |
Fit the model according to the given training data. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
Training vector, where n_samples is the number of samples and n_features is the number of features.
yarray-like of shape (n_samples,)
Target vector relative to X.
sample_weightarray... | |
doc_1229 | turtle.st()
Make the turtle visible. >>> turtle.showturtle() | |
doc_1230 |
Given the location and size of the box, return the path of the box around it. Parameters
x0, y0, width, heightfloat
Location and size of the box.
mutation_sizefloat
A reference scale for the mutation. Returns
Path | |
doc_1231 | Returns the variance and mean of all elements in the input tensor. If unbiased is False, then the variance will be calculated via the biased estimator. Otherwise, Bessel’s correction will be used. Parameters
input (Tensor) – the input tensor.
unbiased (bool) – whether to use the unbiased estimation or not Examp... | |
doc_1232 | tf.compat.v1.all_variables()
Warning: THIS FUNCTION IS DEPRECATED. It will be removed after 2017-03-02. Instructions for updating: Please use tf.global_variables instead. | |
doc_1233 | See Migration guide for more details. tf.compat.v1.distribute.cluster_resolver.UnionResolver
tf.distribute.cluster_resolver.UnionResolver(
*args, **kwargs
)
This class performs a union given two or more existing ClusterResolvers. It merges the underlying ClusterResolvers, and returns one unified ClusterSpec when... | |
doc_1234 |
Initialize self. See help(type(self)) for accurate signature. | |
doc_1235 | See torch.subtract(). | |
doc_1236 |
Perform classification on an array of test vectors X. The predicted class C for each sample in X is returned. Parameters
Xarray-like of shape (n_samples, n_features)
Returns
Cndarray of shape (n_samples,) | |
doc_1237 | Dictionary mapping filename extensions to MIME types. | |
doc_1238 |
Remove “small” “trailing” coefficients from a polynomial. “Small” means “small in absolute value” and is controlled by the parameter tol; “trailing” means highest order coefficient(s), e.g., in [0, 1, 1, 0, 0] (which represents 0 + x + x**2 + 0*x**3 + 0*x**4) both the 3-rd and 4-th order coefficients would be “trimme... | |
doc_1239 | See Migration guide for more details. tf.compat.v1.raw_ops.Conv3DBackpropInputV2
tf.raw_ops.Conv3DBackpropInputV2(
input_sizes, filter, out_backprop, strides, padding,
data_format='NDHWC', dilations=[1, 1, 1, 1, 1], name=None
)
Args
input_sizes A Tensor. Must be one of the following types: int32, in... | |
doc_1240 |
Return True if year is a leap year. Examples
>>> ts = pd.Timestamp(2020, 3, 14)
>>> ts.is_leap_year
True | |
doc_1241 |
Set the (group) id for the artist. Parameters
gidstr | |
doc_1242 |
Stack arrays in sequence vertically (row wise). This is equivalent to concatenation along the first axis after 1-D arrays of shape (N,) have been reshaped to (1,N). Rebuilds arrays divided by vsplit. This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first a... | |
doc_1243 |
Logistic Regression (aka logit, MaxEnt) classifier. In the multiclass case, the training algorithm uses the one-vs-rest (OvR) scheme if the ‘multi_class’ option is set to ‘ovr’, and uses the cross-entropy loss if the ‘multi_class’ option is set to ‘multinomial’. (Currently the ‘multinomial’ option is supported only b... | |
doc_1244 |
Add new categories. new_categories will be included at the last/highest place in the categories and will be unused directly after this call. Parameters
new_categories:category or list-like of category
The new categories to be included.
inplace:bool, default False
Whether or not to add the categories inplace... | |
doc_1245 |
Bases: matplotlib.cm.ScalarMappable, matplotlib.contour.ContourLabeler Store a set of contour lines or filled regions. User-callable method: clabel Parameters
axAxes
levels[level0, level1, ..., leveln]
A list of floating point numbers indicating the contour levels.
allsegs[level0segs, level1segs, ...]
Lis... | |
doc_1246 | Return (bytes, is_cryptographic): bytes are num pseudo-random bytes, is_cryptographic is True if the bytes generated are cryptographically strong. Raises an SSLError if the operation is not supported by the current RAND method. Generated pseudo-random byte sequences will be unique if they are of sufficient length, but ... | |
doc_1247 | In-place version of frac() | |
doc_1248 |
Get the artist's bounding box in display space. The bounding box' width and height are nonnegative. Subclasses should override for inclusion in the bounding box "tight" calculation. Default is to return an empty bounding box at 0, 0. Be careful when using this function, the results will not update if the artist windo... | |
doc_1249 |
Return a parametrized wrapper around the number type. New in version 1.22. Returns
aliastypes.GenericAlias
A parametrized number type. See also PEP 585
Type hinting generics in standard collections. Notes This method is only available for python 3.9 and later. Examples >>> from typing import Any
>>>... | |
doc_1250 |
Make a box plot of the DataFrame columns. A box plot is a method for graphically depicting groups of numerical data through their quartiles. The box extends from the Q1 to Q3 quartile values of the data, with a line at the median (Q2). The whiskers extend from the edges of box to show the range of the data. The posit... | |
doc_1251 |
Return list of slices corresponding to the unmasked clumps of a 1-D array. (A “clump” is defined as a contiguous region of the array). Parameters
andarray
A one-dimensional masked array. Returns
sliceslist of slice
The list of slices, one for each continuous region of unmasked elements in a. See al... | |
doc_1252 | tf.compat.v1.nn.fused_batch_norm(
x, scale, offset, mean=None, variance=None, epsilon=0.001,
data_format='NHWC', is_training=True, name=None,
exponential_avg_factor=1.0
)
See Source: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift; S. Ioffe, C. Szegedy.
Arg... | |
doc_1253 |
Return the width ratios. This is None if no width ratios have been set explicitly. | |
doc_1254 | See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalStatsAggregatorHandle
tf.raw_ops.ExperimentalStatsAggregatorHandle(
container='', shared_name='', name=None
)
Args
container An optional string. Defaults to "".
shared_name An optional string. Defaults to "".
name A name ... | |
doc_1255 |
Autoscale the scalar limits on the norm instance using the current array | |
doc_1256 | Compress data, returning a bytes object containing compressed data for at least part of the data in data. This data should be concatenated to the output produced by any preceding calls to the compress() method. Some input may be kept in internal buffers for later processing. | |
doc_1257 | sys.ps2
Strings specifying the primary and secondary prompt of the interpreter. These are only defined if the interpreter is in interactive mode. Their initial values in this case are '>>> ' and '... '. If a non-string object is assigned to either variable, its str() is re-evaluated each time the interpreter prepares... | |
doc_1258 | See torch.ger() | |
doc_1259 | Locale category for the formatting of time. The function time.strftime() follows these conventions. | |
doc_1260 |
router = routers.SimpleRouter()
router.register(r'users', UserViewSet)
router.register(r'accounts', AccountViewSet)
urlpatterns = router.urls
There are two mandatory arguments to the register() method:
prefix - The URL prefix to use for this set of routes.
viewset - The viewset class. Optionally, you may also spe... | |
doc_1261 |
Call self as a function. | |
doc_1262 | See Migration guide for more details. tf.compat.v1.app.flags.flag_dict_to_args
tf.compat.v1.flags.flag_dict_to_args(
flag_map, multi_flags=None
)
This method is used to convert a dictionary into a sequence of parameters for a binary that parses arguments using this module.
Args
flag_map dict, a mapping ... | |
doc_1263 | Decorator for skipping tests if bz2 doesn’t exist. | |
doc_1264 |
For base class, this just appends an event to events. | |
doc_1265 |
Identity function. If p is the returned series, then p(x) == x for all values of x. Parameters
domain{None, array_like}, optional
If given, the array must be of the form [beg, end], where beg and end are the endpoints of the domain. If None is given then the class domain is used. The default is None.
window{N... | |
doc_1266 | See Migration guide for more details. tf.compat.v1.distribute.ReduceOp
SUM: Add all the values.
MEAN: Take the arithmetic mean ("average") of the values.
Class Variables
MEAN tf.distribute.ReduceOp
SUM tf.distribute.ReduceOp | |
doc_1267 |
Attributes
element_spec The type specification of an element of tf.distribute.DistributedIterator.
global_batch_size = 16
strategy = tf.distribute.MirroredStrategy(["GPU:0", "GPU:1"])
dataset = tf.data.Dataset.from_tensors(([1.],[2])).repeat(100).batch(global_batch_size)
distributed_iterator = iter(strategy.e... | |
doc_1268 |
Computes the Mean Squared Error between two covariance estimators. (In the sense of the Frobenius norm). Parameters
comp_covarray-like of shape (n_features, n_features)
The covariance to compare with.
norm{“frobenius”, “spectral”}, default=”frobenius”
The type of norm used to compute the error. Available er... | |
doc_1269 | See Migration guide for more details. tf.compat.v1.keras.applications.vgg16.decode_predictions
tf.keras.applications.vgg16.decode_predictions(
preds, top=5
)
Arguments
preds Numpy array encoding a batch of predictions.
top Integer, how many top-guesses to return. Defaults to 5.
Returns A... | |
doc_1270 |
Alias for get_edgecolor. | |
doc_1271 | Holds the SMTPServer that spawned this channel. | |
doc_1272 | This method is called from dispatch_return() when stop_here() yields True. | |
doc_1273 |
Set the default font weight. The initial value is 'normal'. | |
doc_1274 |
Update k means estimate on a single mini-batch X. Parameters
Xarray-like of shape (n_samples, n_features)
Coordinates of the data points to cluster. It must be noted that X will be copied if it is not C-contiguous.
yIgnored
Not used, present here for API consistency by convention.
sample_weightarray-like ... | |
doc_1275 | See Migration guide for more details. tf.compat.v1.function
tf.function(
func=None, input_signature=None, autograph=True, experimental_implements=None,
experimental_autograph_options=None, experimental_relax_shapes=False,
experimental_compile=None, experimental_follow_type_hints=None
)
tf.function constr... | |
doc_1276 | stat.FILE_ATTRIBUTE_COMPRESSED
stat.FILE_ATTRIBUTE_DEVICE
stat.FILE_ATTRIBUTE_DIRECTORY
stat.FILE_ATTRIBUTE_ENCRYPTED
stat.FILE_ATTRIBUTE_HIDDEN
stat.FILE_ATTRIBUTE_INTEGRITY_STREAM
stat.FILE_ATTRIBUTE_NORMAL
stat.FILE_ATTRIBUTE_NOT_CONTENT_INDEXED
stat.FILE_ATTRIBUTE_NO_SCRUB_DATA
stat.FILE_ATTRIBUTE... | |
doc_1277 | See Migration guide for more details. tf.compat.v1.raw_ops.VarHandleOp
tf.raw_ops.VarHandleOp(
dtype, shape, container='', shared_name='',
allowed_devices=[], name=None
)
Args
dtype A tf.DType. the type of this variable. Must agree with the dtypes of all ops using this variable.
shape A tf.Ten... | |
doc_1278 |
Load a FontManager from the JSON file named filename. See also json_dump | |
doc_1279 | The response object that is used by default in Flask. Works like the response object from Werkzeug but is set to have an HTML mimetype by default. Quite often you don’t have to create this object yourself because make_response() will take care of that for you. If you want to replace the response object used you can sub... | |
doc_1280 | Returns an InlineFormSet using modelformset_factory() with defaults of formset=BaseInlineFormSet, can_delete=True, and extra=3. If your model has more than one ForeignKey to the parent_model, you must specify a fk_name. See Inline formsets for example usage. Changed in Django 3.2: The absolute_max and can_delete_extra... | |
doc_1281 | Returns a list of all hyperparameter. | |
doc_1282 |
Applies the hard shrinkage function element-wise: HardShrink(x)={x, if x>λx, if x<−λ0, otherwise \text{HardShrink}(x) = \begin{cases} x, & \text{ if } x > \lambda \\ x, & \text{ if } x < -\lambda \\ 0, & \text{ otherwise } \end{cases}
Parameters
lambd – the λ\lambda value for the Hardshrink formulation. Default... | |
doc_1283 | Return non-zero if the mode is from a socket. | |
doc_1284 | Returns a date object containing the previous valid day. This function can also return None or raise an Http404 exception, depending on the values of allow_empty and allow_future. | |
doc_1285 | Returns the GEOS geometry type identification number. The following table shows the value for each geometry type:
Geometry ID
Point 0
LineString 1
LinearRing 2
Polygon 3
MultiPoint 4
MultiLineString 5
MultiPolygon 6
GeometryCollection 7 | |
doc_1286 | tf.compat.v1.train.natural_exp_decay(
learning_rate, global_step, decay_steps, decay_rate, staircase=False, name=None
)
When training a model, it is often recommended to lower the learning rate as the training progresses. This function applies an exponential decay function to a provided initial learning rate. It r... | |
doc_1287 | '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_1288 |
Add new fields to an existing array. The names of the fields are given with the names arguments, the corresponding values with the data arguments. If a single field is appended, names, data and dtypes do not have to be lists but just values. Parameters
basearray
Input array to extend.
namesstring, sequence
... | |
doc_1289 |
Indicator whether Series/DataFrame is empty. True if Series/DataFrame is entirely empty (no items), meaning any of the axes are of length 0. Returns
bool
If Series/DataFrame is empty, return True, if not return False. See also Series.dropna
Return series without null values. DataFrame.dropna
Return DataF... | |
doc_1290 | Return True if x is a positive or negative infinity, and False otherwise. | |
doc_1291 |
Alias for set_linewidth. | |
doc_1292 | Returns a new tensor with the elements of input at the given indices. The input tensor is treated as if it were viewed as a 1-D tensor. The result takes the same shape as the indices. Parameters
input (Tensor) – the input tensor.
indices (LongTensor) – the indices into tensor Example: >>> src = torch.tensor([[4... | |
doc_1293 |
Convert argument to datetime. This function converts a scalar, array-like, Series or DataFrame/dict-like to a pandas datetime object. Parameters
arg:int, float, str, datetime, list, tuple, 1-d array, Series, DataFrame/dict-like
The object to convert to a datetime. If a DataFrame is provided, the method expects ... | |
doc_1294 | See Migration guide for more details. tf.compat.v1.raw_ops.BoostedTreesSparseAggregateStats
tf.raw_ops.BoostedTreesSparseAggregateStats(
node_ids, gradients, hessians, feature_indices, feature_values, feature_shape,
max_splits, num_buckets, name=None
)
The summary stats contains gradients and hessians accumu... | |
doc_1295 |
Least squares polynomial fit. Note This forms part of the old polynomial API. Since version 1.4, the new polynomial API defined in numpy.polynomial is preferred. A summary of the differences can be found in the transition guide. Fit a polynomial p(x) = p[0] * x**deg + ... + p[deg] of degree deg to points (x, y). Re... | |
doc_1296 | See Migration guide for more details. tf.compat.v1.raw_ops.SegmentProd
tf.raw_ops.SegmentProd(
data, segment_ids, name=None
)
Read the section on segmentation for an explanation of segments. Computes a tensor such that \(output_i = \prod_j data_j\) where the product is over j such that segment_ids[j] == i. If th... | |
doc_1297 | See Migration guide for more details. tf.compat.v1.raw_ops.LoadTPUEmbeddingCenteredRMSPropParameters
tf.raw_ops.LoadTPUEmbeddingCenteredRMSPropParameters(
parameters, ms, mom, mg, num_shards, shard_id, table_id=-1,
table_name='', config='', name=None
)
An op that loads optimization parameters into HBM for em... | |
doc_1298 | Given field_name as returned by parse() (see above), convert it to an object to be formatted. Returns a tuple (obj, used_key). The default version takes strings of the form defined in PEP 3101, such as “0[name]” or “label.title”. args and kwargs are as passed in to vformat(). The return value used_key has the same mean... | |
doc_1299 | ABC for sized iterable container classes. New in version 3.6. |
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