bayerj

In [2]: import flax
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-2-5854b141ca7d> in <module>
----> 1 import flax

~/.virtualenvs/flax2/lib/python3.7/site-packages/flax/__init__.py in <module>
     32
     33 # Allow `import flax`; `flax.nn.[...]`, and the same for `flax.optim.[...]`
---> 34 from . import nn

bayerj

import numpy as onp
import jax.numpy as jnp


class ArrayContainer:
  def __init__(self, value):
    self.value = value
  def __array__(self):
    return self.value

bayerj

import jax
import jax.experimental.optimizers
from jax.api import _check_inexact_input_vjp
from jax import tree_util as tu
import numpy as onp


def make_resilient_step(loss, sample_params, split, join, optimizer):
    sample_learn_params, non_learn_params = split(sample_params)

bayerj

import jax
import jax.experimental.optimizers
from jax.api import _check_inexact_input_vjp
from jax import tree_util as tu
import numpy as onp


def make_resilient_step(loss, sample_params, split, join, optimizer):
    sample_learn_params, non_learn_params = split(sample_params)

bayerj

"""
Usage:
    run something somewhere

Options:
    -h | --help     Show this screen.
"""

import sys

bayerj

import tensorflow as tf
import edward as ed
from collections import OrderedDict


def edges(rvs):
    rvs = [*rvs]
    edges = []
    visited = set()

bayerj

"Rules are to make you think before you break them." – Terry Pratchett

Some guidelines to follow for coding to increase collaboration efficiency.

• Name variables meaningfully.
  • It pays of to think hard about it, because coming up with names is O(1) while trying to decipher names is O(“amount of people that try to understand the code”).
  • Don’t be afraid of long variable names; it is much better to have a long obvious name than a short name that does not “flow” while reading code.
  • Avoid greek letter names such as epsilon, eta or gamma. The right variable names are often offset, step_rate or decay_factor. Even if the paper you are implementing is using certain greek names, a follow up won’t. Also, mathematical formulas in papers and source code are different things with different objectives.

bayerj

class _SequentialAutoregressive(tf.contrib.distributions.Distribution):

    def __init__(self, f_process, base_dist_cls, initial_dist,
                 n_time_steps=None,
                 dtype=tf.float32,
                 name='sequential_auto_regressive'):
        self.f_process = f_process
        self.base_dist_cls = base_dist_cls
        self.initial_dist = initial_dist
        self.n_time_steps = n_time_steps

bayerj

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-2-913092c38985> in <module>()
      1 x = tf.placeholder('float32', [None, 784])
----> 2 noised = x + tf.random_normal(x.get_shape())

/Users/bayerj/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/random_ops.pyc in random_normal(shape, mean, stddev, dtype, seed, name)
     44   """
     45   with ops.op_scope([shape, mean, stddev], name, "random_normal") as name:
---> 46     shape_tensor = _ShapeTensor(shape)

bayerj

<script src="http://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS_HTML"></script>

$$test$$