from tensorlayer import decorators
from tensorlayer import files
from tensorlayer import initializers
from tensorlayer import iterate
from tensorlayer import layers
from tensorlayer import lazy_imports
from tensorlayer import logging
from tensorlayer import models
from tensorlayer import optimizers
from tensorlayer import rein
from tensorlayer import utils
from tensorlayer.lazy_imports import LazyImport
# Lazy Imports
db = LazyImport("tensorlayer.db")
distributed = LazyImport("tensorlayer.distributed")
nlp = LazyImport("tensorlayer.nlp")
prepro = LazyImport("tensorlayer.prepro")
utils = LazyImport("tensorlayer.utils")
visualize = LazyImport("tensorlayer.visualize")
# alias
act = activation
vis = visualize
alphas = array_ops.alphas
alphas_like = array_ops.alphas_like
# global vars
global_flag = {}
#! /usr/bin/python
# -*- coding: utf-8 -*-
import inspect
import pickle
import time
import uuid
from datetime import datetime
from tensorlayer.lazy_imports import LazyImport
gridfs = LazyImport("gridfs")
pymongo = LazyImport("pymongo")
def AutoFill(func):
def func_wrapper(self, *args, **kwargs):
d = inspect.getcallargs(func, self, *args, **kwargs)
d['args'].update({"studyID": self.studyID})
return func(**d)
return func_wrapper
class TensorDB(object):
"""TensorDB is a MongoDB based manager that help you to manage data, network topology, parameters and logging.
Parameters
-------------
ip : str
# -*- coding: utf-8 -*-
"""
TensorLayer provides rich layer implementations trailed for
various benchmarks and domain-specific problems. In addition, we also
support transparent access to native TensorFlow parameters.
For example, we provide not only layers for local response normalization, but also
layers that allow user to apply ``tf.nn.lrn`` on ``network.outputs``.
More functions can be found in `TensorFlow API <https://www.tensorflow.org/versions/master/api_docs/index.html>`__.
"""
from tensorlayer.lazy_imports import LazyImport
from .tl_logging import *
# Lazy Imports
contrib = LazyImport("tensorlayer.logging.contrib")
__all__ = [
# tl_logging
'DEBUG',
'debug',
'ERROR',
'error',
'FATAL',
'fatal',
'INFO',
'info',
'WARN',
'warn',
'warning',
'set_verbosity',
#! /usr/bin/python
# -*- coding: utf-8 -*-
from tensorlayer.layers.core import Layer
from tensorlayer import tl_logging as logging
from tensorlayer.decorators import deprecated_alias
from tensorlayer.lazy_imports import LazyImport
try:
roi_pooling = LazyImport(
"tensorlayer.third_party.roi_pooling.roi_pooling.roi_pooling_ops")
except Exception as e:
logging.error(e)
logging.error(
"HINT: 1. https://github.com/deepsense-ai/roi-pooling 2. tensorlayer/third_party/roi_pooling"
)
__all__ = [
'ROIPoolingLayer',
]
class ROIPoolingLayer(Layer):
"""
The region of interest pooling layer.
Parameters
-----------
import subprocess
import tempfile
import warnings
from six.moves import urllib
from six.moves import xrange
import numpy as np
import tensorflow as tf
from tensorflow.python.platform import gfile
import tensorlayer as tl
from tensorlayer.lazy_imports import LazyImport
nltk = LazyImport("nltk")
__all__ = [
'generate_skip_gram_batch',
'sample',
'sample_top',
'SimpleVocabulary',
'Vocabulary',
'process_sentence',
'create_vocab',
'simple_read_words',
'read_words',
'read_analogies_file',
'build_vocab',
'build_reverse_dictionary',
'build_words_dataset',
#! /usr/bin/python
# -*- coding: utf-8 -*-
import os
import imageio
import numpy as np
import tensorlayer as tl
from tensorlayer.lazy_imports import LazyImport
cv2 = LazyImport("cv2")
# Uncomment the following line if you got: _tkinter.TclError: no display name and no $DISPLAY environment variable
# import matplotlib
# matplotlib.use('Agg')
__all__ = [
'read_image',
'read_images',
'save_image',
'save_images',
'draw_boxes_and_labels_to_image',
'draw_mpii_people_to_image',
'frame',
'CNN2d',
'images2d',
'tsne_embedding',
'draw_weights',
'W',
]
# -*- coding: utf-8 -*-
import json
import os
import time
import math
import tensorflow as tf
from tensorflow.python.training import session_run_hook
from tensorlayer import logging
from tensorlayer.decorators import deprecated
from tensorlayer.lazy_imports import LazyImport
hvd = LazyImport('horovod.tensorflow')
__all__ = [
'TaskSpecDef', 'TaskSpec', 'DistributedSession', 'StopAtTimeHook',
'LoadCheckpoint', 'Trainer'
]
class Trainer(object):
"""Trainer for neural networks in a distributed environment.
TensorLayer Trainer is a high-level training interface built on top of TensorFlow MonitoredSession and
`Horovod <https://github.com/uber/horovod>`__. It transparently scales the training of a TensorLayer model
from a single GPU to multiple GPUs that be placed on different machines in a single cluster.
To run the trainer, you will need to install Horovod on your machine. Check the installation script at
`tensorlayer/scripts/download_and_install_openmpi3_ubuntu.sh`