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Use tf.estimator, pylint, add projector
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Use tf.estimator instead of custom functions.
Added pylint configuration file.
Added `visualize_embeddings.py` for TensorBoard projector.
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omoindrot committed Mar 20, 2018
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319 changes: 319 additions & 0 deletions .pylintrc
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[MASTER]

# Specify a configuration file.
#rcfile=

# Python code to execute, usually for sys.path manipulation such as
# pygtk.require().
#init-hook=

# Profiled execution.
profile=no

# Add files or directories to the blacklist. They should be base names, not
# paths.
ignore=CVS

# Pickle collected data for later comparisons.
persistent=yes

# List of plugins (as comma separated values of python modules names) to load,
# usually to register additional checkers.
load-plugins=


[MESSAGES CONTROL]

# Enable the message, report, category or checker with the given id(s). You can
# either give multiple identifier separated by comma (,) or put this option
# multiple time. See also the "--disable" option for examples.
enable=indexing-exception,old-raise-syntax

# Disable the message, report, category or checker with the given id(s). You
# can either give multiple identifiers separated by comma (,) or put this
# option multiple times (only on the command line, not in the configuration
# file where it should appear only once).You can also use "--disable=all" to
# disable everything first and then reenable specific checks. For example, if
# you want to run only the similarities checker, you can use "--disable=all
# --enable=similarities". If you want to run only the classes checker, but have
# no Warning level messages displayed, use"--disable=all --enable=classes
# --disable=W"
disable=design,similarities,no-self-use,attribute-defined-outside-init,locally-disabled,star-args,pointless-except,bad-option-value,global-statement,fixme,suppressed-message,useless-suppression,locally-enabled,no-member,no-name-in-module,import-error,unsubscriptable-object,unbalanced-tuple-unpacking,undefined-variable,not-context-manager,no-else-return,redefined-outer-name


# Set the cache size for astng objects.
cache-size=500


[REPORTS]

# Set the output format. Available formats are text, parseable, colorized, msvs
# (visual studio) and html. You can also give a reporter class, eg
# mypackage.mymodule.MyReporterClass.
output-format=text

# Put messages in a separate file for each module / package specified on the
# command line instead of printing them on stdout. Reports (if any) will be
# written in a file name "pylint_global.[txt|html]".
files-output=no

# Tells whether to display a full report or only the messages
reports=no

# Python expression which should return a note less than 10 (10 is the highest
# note). You have access to the variables errors warning, statement which
# respectively contain the number of errors / warnings messages and the total
# number of statements analyzed. This is used by the global evaluation report
# (RP0004).
evaluation=10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10)

# Add a comment according to your evaluation note. This is used by the global
# evaluation report (RP0004).
comment=no

# Template used to display messages. This is a python new-style format string
# used to format the message information. See doc for all details
#msg-template=


[TYPECHECK]

# Tells whether missing members accessed in mixin class should be ignored. A
# mixin class is detected if its name ends with "mixin" (case insensitive).
ignore-mixin-members=yes

# List of classes names for which member attributes should not be checked
# (useful for classes with attributes dynamically set).
ignored-classes=SQLObject

# When zope mode is activated, add a predefined set of Zope acquired attributes
# to generated-members.
zope=no

# List of members which are set dynamically and missed by pylint inference
# system, and so shouldn't trigger E0201 when accessed. Python regular
# expressions are accepted.
generated-members=REQUEST,acl_users,aq_parent

# List of decorators that create context managers from functions, such as
# contextlib.contextmanager.
contextmanager-decorators=contextlib.contextmanager,contextlib2.contextmanager


[VARIABLES]

# Tells whether we should check for unused import in __init__ files.
init-import=no

# A regular expression matching the beginning of the name of dummy variables
# (i.e. not used).
dummy-variables-rgx=^\*{0,2}(_$|unused_|dummy_)

# List of additional names supposed to be defined in builtins. Remember that
# you should avoid to define new builtins when possible.
additional-builtins=


[BASIC]

# Required attributes for module, separated by a comma
required-attributes=

# List of builtins function names that should not be used, separated by a comma
bad-functions=apply,input,reduce


# Disable the report(s) with the given id(s).
# All non-Google reports are disabled by default.
disable-report=R0001,R0002,R0003,R0004,R0101,R0102,R0201,R0202,R0220,R0401,R0402,R0701,R0801,R0901,R0902,R0903,R0904,R0911,R0912,R0913,R0914,R0915,R0921,R0922,R0923

# Regular expression which should only match correct module names
module-rgx=(([a-z_][a-z0-9_]*)|([A-Z][a-zA-Z0-9]+))$

# Regular expression which should only match correct module level names
const-rgx=^(_?[A-Z][A-Z0-9_]*|__[a-z0-9_]+__|_?[a-z][a-z0-9_]*)$

# Regular expression which should only match correct class names
class-rgx=^_?[A-Z][a-zA-Z0-9]*$

# Regular expression which should only match correct function names
function-rgx=^(?:(?P<camel_case>_?[A-Z][a-zA-Z0-9]*)|(?P<snake_case>_?[a-z][a-z0-9_]*))$

# Regular expression which should only match correct method names
method-rgx=^(?:(?P<exempt>__[a-z0-9_]+__|next)|(?P<camel_case>_{0,2}[A-Z][a-zA-Z0-9]*)|(?P<snake_case>_{0,2}[a-z][a-z0-9_]*))$

# Regular expression which should only match correct instance attribute names
attr-rgx=^_{0,2}[a-z][a-z0-9_]*$

# Regular expression which should only match correct argument names
argument-rgx=^[a-z][a-z0-9_]*$

# Regular expression which should only match correct variable names
variable-rgx=^[a-z][a-z0-9_]*$

# Regular expression which should only match correct attribute names in class
# bodies
class-attribute-rgx=^(_?[A-Z][A-Z0-9_]*|__[a-z0-9_]+__|_?[a-z][a-z0-9_]*)$

# Regular expression which should only match correct list comprehension /
# generator expression variable names
inlinevar-rgx=^[a-z][a-z0-9_]*$

# Good variable names which should always be accepted, separated by a comma
good-names=main,_

# Bad variable names which should always be refused, separated by a comma
bad-names=

# Regular expression which should only match function or class names that do
# not require a docstring.
no-docstring-rgx=(__.*__|main)

# Minimum line length for functions/classes that require docstrings, shorter
# ones are exempt.
docstring-min-length=10


[FORMAT]

# Maximum number of characters on a single line.
max-line-length=100

# Regexp for a line that is allowed to be longer than the limit.
ignore-long-lines=^\s*(# )?<?https?://\S+>?$

# Allow the body of an if to be on the same line as the test if there is no
# else.
single-line-if-stmt=y

# List of optional constructs for which whitespace checking is disabled
no-space-check=

# Maximum number of lines in a module
max-module-lines=99999

# String used as indentation unit. This is usually " " (4 spaces) or "\t" (1
# tab).
indent-string=' '


[SIMILARITIES]

# Minimum lines number of a similarity.
min-similarity-lines=4

# Ignore comments when computing similarities.
ignore-comments=yes

# Ignore docstrings when computing similarities.
ignore-docstrings=yes

# Ignore imports when computing similarities.
ignore-imports=no


[MISCELLANEOUS]

# List of note tags to take in consideration, separated by a comma.
notes=


[IMPORTS]

# Deprecated modules which should not be used, separated by a comma
deprecated-modules=regsub,TERMIOS,Bastion,rexec,sets

# Create a graph of every (i.e. internal and external) dependencies in the
# given file (report RP0402 must not be disabled)
import-graph=

# Create a graph of external dependencies in the given file (report RP0402 must
# not be disabled)
ext-import-graph=

# Create a graph of internal dependencies in the given file (report RP0402 must
# not be disabled)
int-import-graph=


[CLASSES]

# List of interface methods to ignore, separated by a comma. This is used for
# instance to not check methods defines in Zope's Interface base class.
ignore-iface-methods=isImplementedBy,deferred,extends,names,namesAndDescriptions,queryDescriptionFor,getBases,getDescriptionFor,getDoc,getName,getTaggedValue,getTaggedValueTags,isEqualOrExtendedBy,setTaggedValue,isImplementedByInstancesOf,adaptWith,is_implemented_by

# List of method names used to declare (i.e. assign) instance attributes.
defining-attr-methods=__init__,__new__,setUp

# List of valid names for the first argument in a class method.
valid-classmethod-first-arg=cls,class_

# List of valid names for the first argument in a metaclass class method.
valid-metaclass-classmethod-first-arg=mcs


[DESIGN]

# Maximum number of arguments for function / method
max-args=5

# Argument names that match this expression will be ignored. Default to name
# with leading underscore
ignored-argument-names=_.*

# Maximum number of locals for function / method body
max-locals=15

# Maximum number of return / yield for function / method body
max-returns=6

# Maximum number of branch for function / method body
max-branches=12

# Maximum number of statements in function / method body
max-statements=50

# Maximum number of parents for a class (see R0901).
max-parents=7

# Maximum number of attributes for a class (see R0902).
max-attributes=7

# Minimum number of public methods for a class (see R0903).
min-public-methods=2

# Maximum number of public methods for a class (see R0904).
max-public-methods=20


[EXCEPTIONS]

# Exceptions that will emit a warning when being caught. Defaults to
# "Exception"
overgeneral-exceptions=Exception,StandardError,BaseException


[AST]

# Maximum line length for lambdas
short-func-length=1

# List of module members that should be marked as deprecated.
# All of the string functions are listed in 4.1.4 Deprecated string functions
# in the Python 2.4 docs.
deprecated-members=string.atof,string.atoi,string.atol,string.capitalize,string.expandtabs,string.find,string.rfind,string.index,string.rindex,string.count,string.lower,string.split,string.rsplit,string.splitfields,string.join,string.joinfields,string.lstrip,string.rstrip,string.strip,string.swapcase,string.translate,string.upper,string.ljust,string.rjust,string.center,string.zfill,string.replace,sys.exitfunc


[DOCSTRING]

# List of exceptions that do not need to be mentioned in the Raises section of
# a docstring.
ignore-exceptions=AssertionError,NotImplementedError,StopIteration,TypeError



[TOKENS]

# Number of spaces of indent required when the last token on the preceding line
# is an open (, [, or {.
indent-after-paren=8
33 changes: 14 additions & 19 deletions evaluate.py
@@ -1,53 +1,48 @@
"""Evaluate the model"""

import argparse
import logging
import os

import tensorflow as tf

from model.input_fn import input_fn
from model.model_fn import model_fn
from model.evaluation import evaluate
from model.utils import Params
from model.utils import set_logger


parser = argparse.ArgumentParser()
parser.add_argument('--model_dir', default='experiments/test',
help="Experiment directory containing params.json")
parser.add_argument('--data_dir', default='data/mnist',
help="Directory containing the dataset")
parser.add_argument('--restore_from', default='last_weights',
help="Subdirectory of model dir or file containing the weights")


if __name__ == '__main__':
# Set the random seed for the whole graph
tf.set_random_seed(230)
tf.reset_default_graph()
tf.logging.set_verbosity(tf.logging.INFO)

# Load the parameters
args = parser.parse_args()
json_path = os.path.join(args.model_dir, 'params.json')
assert os.path.isfile(json_path), "No json configuration file found at {}".format(json_path)
params = Params(json_path)

# Set the logger
set_logger(os.path.join(args.model_dir, 'evaluate.log'))

# Create the input data pipeline
logging.info("Creating the datasets...")
tf.logging.info("Creating the datasets...")
data = tf.contrib.learn.datasets.mnist.load_mnist(args.data_dir)

# Specify the sizes of the dataset we train on and evaluate on
# Specify the sizes of the dataset we evaluate on
params.eval_size = data.test.num_examples

# create the iterator over the dataset
test_inputs = input_fn(False, data.test.images, data.test.labels, params)
# Create the test input function
test_input_fn = lambda: input_fn(False, data.test.images, data.test.labels, params)

# Define the model
logging.info("Creating the model...")
model_spec = model_fn('eval', test_inputs, params, reuse=False)

logging.info("Starting evaluation")
evaluate(model_spec, args.model_dir, params, args.restore_from)
tf.logging.info("Creating the model...")
estimator = tf.estimator.Estimator(model_fn, params=params, model_dir=args.model_dir)

# Evaluate the model on the test set
tf.logging.info("Evaluation on the test set.")
res = estimator.evaluate(test_input_fn)
for key in res:
print("{}: {}".format(key, res[key]))
Binary file added experiments/mnist_10k_sprite.png
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