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import numpy as np
from scipy.optimize import OptimizeResult


def sgd(
    fun,
    x0,
    jac,
    args=(),
    learning_rate=0.001,

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class oset:
    """An ordered set which stores elements as the keys of a dict (ordered as 
    of python 3.6). 'A few times' slower than using a set directly for small
    sizes, but makes everything deterministic.
    """

    def __init__(self, it):
        self._d = dict.fromkeys(it)

    @classmethod

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def oinsum(eq, *arrays):
    """A ``einsum`` implementation for ``numpy`` object arrays.
    """
    import numpy as np
    import functools
    import operator

    lhs, output = eq.split('->')
    inputs = lhs.split(',')

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#!/usr/bin/env python

import subprocess

print("Finding packages conda says are installed by pip...")
conda_raw = subprocess.run(
    ['conda', 'list'],
    stdout=subprocess.PIPE,
    stderr=subprocess.PIPE,
).stdout.decode('utf-8')

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\.ipynb_checkpoints/

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import functools 
import numpy as np 
 
 
transpose = np.transpose 
einsum = np.einsum 
 
 
@functools.lru_cache(1) 
def get_hasher(): 

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import networkx as nx

reg = 3
n = 100
seed = 0

gamma0 = -0.743043
beta0 = 0.754082

# create the random graph