forked from M-Labs/artiq
240 lines
7.8 KiB
Python
240 lines
7.8 KiB
Python
"""
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Implementation and management of scan objects.
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A scan object (e.g. :class:`artiq.language.scan.RangeScan`) represents a
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one-dimensional sweep of a numerical range. Multi-dimensional scans are
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constructed by combining several scan objects, for example using
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:class:`artiq.language.scan.MultiScanManager`.
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Iterate on a scan object to scan it, e.g. ::
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for variable in self.scan:
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do_something(variable)
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Iterating multiple times on the same scan object is possible, with the scan
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yielding the same values each time. Iterating concurrently on the
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same scan object (e.g. via nested loops) is also supported, and the
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iterators are independent from each other.
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"""
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import random
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import inspect
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from itertools import product
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from artiq.language.core import *
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from artiq.language.environment import NoDefault, DefaultMissing
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from artiq.language import units
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__all__ = ["ScanObject",
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"NoScan", "RangeScan", "ExplicitScan",
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"Scannable", "MultiScanManager"]
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class ScanObject:
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pass
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class NoScan(ScanObject):
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"""A scan object that yields a single value for a specified number
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of repetitions."""
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def __init__(self, value, repetitions=1):
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self.value = value
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self.repetitions = repetitions
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def _gen(self):
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for i in range(self.repetitions):
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yield self.value
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def __iter__(self):
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return self._gen()
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def __len__(self):
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return self.repetitions
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def describe(self):
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return {"ty": "NoScan", "value": self.value,
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"repetitions": self.repetitions}
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class RangeScan(ScanObject):
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"""A scan object that yields a fixed number of evenly spaced values in a
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range. If ``randomize`` is True the points are randomly ordered."""
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def __init__(self, start, stop, npoints, randomize=False, seed=None):
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self.start = start
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self.stop = stop
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self.npoints = npoints
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self.randomize = randomize
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self.seed = seed
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if npoints == 0:
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self.sequence = []
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if npoints == 1:
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self.sequence = [self.start]
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else:
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dx = (stop - start)/(npoints - 1)
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self.sequence = [i*dx + start for i in range(npoints)]
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if randomize:
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rng = random.Random(seed)
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random.shuffle(self.sequence, rng.random)
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def __iter__(self):
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return iter(self.sequence)
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def __len__(self):
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return self.npoints
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def describe(self):
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return {"ty": "RangeScan",
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"start": self.start, "stop": self.stop,
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"npoints": self.npoints,
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"randomize": self.randomize,
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"seed": self.seed}
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class ExplicitScan(ScanObject):
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"""A scan object that yields values from an explicitly defined sequence."""
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def __init__(self, sequence):
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self.sequence = sequence
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def __iter__(self):
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return iter(self.sequence)
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def __len__(self):
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return len(self.sequence)
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def describe(self):
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return {"ty": "ExplicitScan", "sequence": self.sequence}
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_ty_to_scan = {
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"NoScan": NoScan,
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"RangeScan": RangeScan,
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"ExplicitScan": ExplicitScan
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}
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class Scannable:
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"""An argument (as defined in :class:`artiq.language.environment`) that
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takes a scan object.
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When ``scale`` is not specified, and the unit is a common one (i.e.
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defined in ``artiq.language.units``), then the scale is obtained from
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the unit using a simple string match. For example, milliseconds (``"ms"``)
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units set the scale to 0.001. No unit (default) corresponds to a scale of
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1.0.
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For arguments with uncommon or complex units, use both the unit parameter
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(a string for display) and the scale parameter (a numerical scale for
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experiments).
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For example, a scan shown between 1 xyz and 10 xyz in the GUI with
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``scale=0.001`` and ``unit="xyz"`` results in values between 0.001 and
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0.01 being scanned.
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:param default: The default scan object. This parameter can be a list of
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scan objects, in which case the first one is used as default and the
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others are used to configure the default values of scan types that are
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not initially selected in the GUI.
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:param global_min: The minimum value taken by the scanned variable, common
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to all scan modes. The user interface takes this value to set the
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range of its input widgets.
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:param global_max: Same as global_min, but for the maximum value.
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:param global_step: The step with which the value should be modified by
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up/down buttons in a user interface. The default is the scale divided
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by 10.
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:param unit: A string representing the unit of the scanned variable.
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:param scale: A numerical scaling factor by which the displayed values
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are multiplied when referenced in the experiment.
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:param ndecimals: The number of decimals a UI should use.
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"""
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def __init__(self, default=NoDefault, unit="", scale=None,
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global_step=None, global_min=None, global_max=None,
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ndecimals=2):
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if scale is None:
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if unit == "":
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scale = 1.0
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else:
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try:
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scale = getattr(units, unit)
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except AttributeError:
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raise KeyError("Unit {} is unknown, you must specify "
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"the scale manually".format(unit))
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if global_step is None:
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global_step = scale/10.0
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if default is not NoDefault:
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if not isinstance(default, list):
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default = [default]
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self.default_values = default
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self.unit = unit
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self.scale = scale
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self.global_step = global_step
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self.global_min = global_min
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self.global_max = global_max
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self.ndecimals = ndecimals
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def default(self):
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if not hasattr(self, "default_values"):
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raise DefaultMissing
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return self.default_values[0]
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def process(self, x):
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cls = _ty_to_scan[x["ty"]]
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args = dict()
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for arg in inspect.getargspec(cls).args[1:]:
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if arg in x:
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args[arg] = x[arg]
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return cls(**args)
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def describe(self):
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d = {"ty": "Scannable"}
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if hasattr(self, "default_values"):
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d["default"] = [d.describe() for d in self.default_values]
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d["unit"] = self.unit
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d["scale"] = self.scale
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d["global_step"] = self.global_step
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d["global_min"] = self.global_min
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d["global_max"] = self.global_max
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d["ndecimals"] = self.ndecimals
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return d
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class MultiScanManager:
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"""
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Makes an iterator that returns elements from the first scan object until
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it is exhausted, then proceeds to the next iterable, until all of the
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scan objects are exhausted. Used for treating consecutive scans as a
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single scan.
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Scan objects must be passed as a list of tuples (name, scan_object).
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Íteration produces scan points that have attributes that correspond
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to the names of the scan objects, and have the last value yielded by
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that scan object.
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"""
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def __init__(self, *args):
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self.names = [a[0] for a in args]
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self.scan_objects = [a[1] for a in args]
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class ScanPoint:
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def __init__(self, **kwargs):
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self.attr = set()
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for k, v in kwargs.items():
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setattr(self, k, v)
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self.attr.add(k)
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def __repr__(self):
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return ("<ScanPoint " +
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" ".join("{}={}".format(k, getattr(self, k))
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for k in self.attr) +
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">")
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self.scan_point_cls = ScanPoint
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def _gen(self):
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for values in product(*self.scan_objects):
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d = {k: v for k, v in zip(self.names, values)}
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yield self.scan_point_cls(**d)
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def __iter__(self):
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return self._gen()
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