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`