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"""Converts between the RGB and CIECAM02 color spaces."""

from collections import namedtuple
from functools import partial

import colour
from colour.utilities import tsplit, tstack
import numpy as np
from scipy.optimize import fmin_l_bfgs_b

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import pyparsing as pp
from pyparsing import pyparsing_common as ppc

from repl import repl


variables = {}

var = ppc.identifier.copy()
def do_var(t):

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import pyparsing as pp
from pyparsing import pyparsing_common as ppc

from repl import repl


class Node:
    def __init__(self, name, *args):
        self.name = name
        self.items = args

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import numpy as np


class EWMA:
    """An exponentially weighted moving average with initialization bias correction."""
    def __init__(self, shape=(), dtype=np.float64, beta=0.9, correct_bias=True):
        self.beta = beta
        self.beta_accum = 1 if correct_bias else 0
        self.value = np.zeros(shape, dtype)

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"""Captures and returns an argument passed to a lambda expression."""

class Capture:
    """Captures and returns an argument passed to a lambda expression.

    :param fn: The lambda expression.
    :type fn: function

    :Example:

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import inspect
import typing
from typing import get_type_hints, TypeVar, Any, AnyStr, Generic, Union

from sphinx.util import logging
from sphinx.util.inspect import Signature

try:
    from typing_extensions import Protocol
except ImportError:

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"""The prompt-toolkit utility function :func:`format_fragments`."""

from prompt_toolkit.formatted_text import FormattedText


def format_fragments(fragments, *args, **kwargs):
    """Applies :meth:`str.format` to each text fragment in `fragments`.

    Args:
        fragments (FormattedText): The input list of text fragments.

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"""A with-statement context manager to benchmark code."""

import time

__all__ = ['Benchmark']


class Benchmark:
    """A with-statement context manager to benchmark code."""
    def __init__(self, timer=time.perf_counter):

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name: "thing"
layer {
    name: "data"
    type: "Data"
    top: "big_data"
    top: "label"
    include { phase: TRAIN }
    transform_param {
       mean_value: 103.939
       mean_value: 116.779

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# This file provides configuration information about non-Python dependencies for
# numpy.distutils-using packages. Create a file like this called "site.cfg" next
# to your package's setup.py file and fill in the appropriate sections. Not all
# packages will use all sections so you should leave out sections that your
# package does not use.

# To assist automatic installation like easy_install, the user's home directory
# will also be checked for the file ~/.numpy-site.cfg .

# The format of the file is that of the standard library's ConfigParser module.