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Python pp.pprint方法代码示例

本文整理汇总了Python中utils.pp.pprint方法的典型用法代码示例。如果您正苦于以下问题：Python pp.pprint方法的具体用法？Python pp.pprint怎么用？Python pp.pprint使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类utils.pp的用法示例。


在下文中一共展示了pp.pprint方法的13个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
    pp.pprint(flags.FLAGS.__flags)

    if not os.path.exists(FLAGS.checkpoint_dir):
        os.makedirs(FLAGS.checkpoint_dir)
    if not os.path.exists(FLAGS.sample_dir):
        os.makedirs(FLAGS.sample_dir)

    gpu_options = tf.GPUOptions(
        per_process_gpu_memory_fraction=FLAGS.gpu_frac)

    config = tf.ConfigProto()
    config.gpu_options.allow_growth = True
    
    with tf.Session(config = tf.ConfigProto(gpu_options=gpu_options)) as sess:
        dcgan = ECGAN(sess)
        dcgan.train()
开发者ID:arnavkj1995，项目名称:face_inpainting，代码行数:19，代码来源:main.py

示例2: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
	pp.pprint(flags.FLAGS.__flags)

	if not os.path.exists(FLAGS.checkpoint_dir):
		os.makedirs(FLAGS.checkpoint_dir)
	if not os.path.exists(FLAGS.sample_dir):
		os.makedirs(FLAGS.sample_dir)

	gpu_options = tf.GPUOptions(
		per_process_gpu_memory_fraction=FLAGS.gpu_frac)
	
	with tf.Session(config=tf.ConfigProto(gpu_options=gpu_options)) as sess:
		
		# with tf.Session() as sess:
		dcgan = ECGAN(sess)
		dcgan.temporal_consistency()
开发者ID:arnavkj1995，项目名称:face_inpainting，代码行数:18，代码来源:temporal.py

示例3: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
  pp.pprint(flags.FLAGS.__flags)

  if not os.path.exists(FLAGS.checkpoint_dir):
    os.makedirs(FLAGS.checkpoint_dir)

  Analogy = model_dict[FLAGS.dataset]

  with tf.Session() as sess:
    analogy = Analogy(sess, image_size=FLAGS.image_size, model_type=FLAGS.model_type,
                      batch_size=FLAGS.batch_size, dataset=FLAGS.dataset)

    if FLAGS.is_train:
      analogy.train(max_iter=FLAGS.max_iter, alpha=FLAGS.alpha,
                    learning_rate=FLAGS.learning_rate, checkpoint_dir=FLAGS.checkpoint_dir)
    else:
      analogy.load(FLAGS.checkpoint_dir)

    analogy.test()
开发者ID:carpedm20，项目名称:visual-analogy-tensorflow，代码行数:21，代码来源:main.py

示例4: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
    pp.pprint(flags.FLAGS.__flags)

    config = Config(FLAGS)
    config.print_config()
    config.make_dirs()

    config_proto = tf.ConfigProto(allow_soft_placement=FLAGS.is_train, log_device_placement=False)
    config_proto.gpu_options.allow_growth = True

    with tf.Session(config=config_proto) as sess:
        model = globals()[FLAGS.model](config)

        if not FLAGS.is_train:
            test_generation(model, sess)
        else:
            train(model, sess)
开发者ID:whyjay，项目名称:memoryGAN，代码行数:19，代码来源:run.py

示例5: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
  pp.pprint(flags.FLAGS.__flags)

  data_path = "./data/%s" % FLAGS.dataset
  reader = TextReader(data_path)

  with tf.Session() as sess:
    m = MODELS[FLAGS.model]
    model = m(sess, reader, dataset=FLAGS.dataset,
              embed_dim=FLAGS.embed_dim, h_dim=FLAGS.h_dim,
              learning_rate=FLAGS.learning_rate, max_iter=FLAGS.max_iter,
              checkpoint_dir=FLAGS.checkpoint_dir)

    if FLAGS.forward_only:
      model.load(FLAGS.checkpoint_dir)
    else:
      model.train(FLAGS)

    while True:
      text = raw_input(" [*] Enter text to test: ")
      model.sample(5, text)
开发者ID:carpedm20，项目名称:variational-text-tensorflow，代码行数:23，代码来源:main.py

示例6: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
    pp.pprint(flags.FLAGS.__flags)
    sample_dir_ = os.path.join(FLAGS.sample_dir, FLAGS.name)
    checkpoint_dir_ = os.path.join(FLAGS.checkpoint_dir, FLAGS.name)
    log_dir_ = os.path.join(FLAGS.log_dir, FLAGS.name)
    if not os.path.exists(checkpoint_dir_):
        os.makedirs(checkpoint_dir_)
    if not os.path.exists(sample_dir_):
        os.makedirs(sample_dir_)
    if not os.path.exists(log_dir_):
        os.makedirs(log_dir_)

    with tf.Session() as sess:
        if FLAGS.dataset == 'mnist':
            dcgan = DCGAN(sess, config=FLAGS, batch_size=FLAGS.batch_size, output_size=28, c_dim=1,
                    dataset_name=FLAGS.dataset, is_crop=FLAGS.is_crop, checkpoint_dir=checkpoint_dir_, sample_dir=sample_dir_, log_dir=log_dir_)
        else:
            dcgan = DCGAN(sess, image_size=FLAGS.image_size, batch_size=FLAGS.batch_size, output_size=FLAGS.output_size, c_dim=FLAGS.c_dim,
                    dataset_name=FLAGS.dataset, is_crop=FLAGS.is_crop, checkpoint_dir=FLAGS.checkpoint_dir, sample_dir=FLAGS.sample_dir)

        if FLAGS.is_train:
            dcgan.train(FLAGS)
        else:
            dcgan.sampling(FLAGS)

        if FLAGS.visualize:
            to_json("./web/js/layers.js", [dcgan.h0_w, dcgan.h0_b, dcgan.g_bn0],
                                          [dcgan.h1_w, dcgan.h1_b, dcgan.g_bn1],
                                          [dcgan.h2_w, dcgan.h2_b, dcgan.g_bn2],
                                          [dcgan.h3_w, dcgan.h3_b, dcgan.g_bn3],
                                          [dcgan.h4_w, dcgan.h4_b, None])

            # Below is codes for visualization
            OPTION = 2
            visualize(sess, dcgan, FLAGS, OPTION)
开发者ID:djsutherland，项目名称:opt-mmd，代码行数:37，代码来源:main_mmd.py

示例7: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
    pp.pprint(flags.FLAGS.__flags)
    sample_dir_ = os.path.join(FLAGS.sample_dir, FLAGS.name)
    checkpoint_dir_ = os.path.join(FLAGS.checkpoint_dir, FLAGS.name)
    log_dir_ = os.path.join(FLAGS.log_dir, FLAGS.name)
    if not os.path.exists(checkpoint_dir_):
        os.makedirs(checkpoint_dir_)
    if not os.path.exists(sample_dir_):
        os.makedirs(sample_dir_)
    if not os.path.exists(log_dir_):
        os.makedirs(log_dir_)

    with tf.Session() as sess:
        if FLAGS.dataset == 'mnist':
            dcgan = DCGAN(sess, config=FLAGS, batch_size=FLAGS.batch_size, output_size=28, c_dim=1,
                    dataset_name=FLAGS.dataset, is_crop=FLAGS.is_crop, checkpoint_dir=checkpoint_dir_, sample_dir=sample_dir_, log_dir=log_dir_)
        else:
            dcgan = DCGAN(sess, image_size=FLAGS.image_size, batch_size=FLAGS.batch_size, output_size=FLAGS.output_size, c_dim=FLAGS.c_dim,
                    dataset_name=FLAGS.dataset, is_crop=FLAGS.is_crop, checkpoint_dir=FLAGS.checkpoint_dir, sample_dir=FLAGS.sample_dir)

        if FLAGS.is_train:
            dcgan.train(FLAGS)
        else:
            dcgan.sampling(FLAGS)
            #dcgan.load(FLAGS.checkpoint_dir)

        if FLAGS.visualize:
            to_json("./web/js/layers.js", [dcgan.h0_w, dcgan.h0_b, dcgan.g_bn0],
                                          [dcgan.h1_w, dcgan.h1_b, dcgan.g_bn1],
                                          [dcgan.h2_w, dcgan.h2_b, dcgan.g_bn2],
                                          [dcgan.h3_w, dcgan.h3_b, dcgan.g_bn3],
                                          [dcgan.h4_w, dcgan.h4_b, None])

            # Below is codes for visualization
            OPTION = 2
            visualize(sess, dcgan, FLAGS, OPTION)
开发者ID:djsutherland，项目名称:opt-mmd，代码行数:38，代码来源:main_mmd_fm.py

示例8: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
    #pp.pprint(FLAGS.__flags)
    pp.pprint(tf.app.flags.FLAGS.flag_values_dict())


    if not os.path.exists(FLAGS.checkpoint_dir):
        os.makedirs(FLAGS.checkpoint_dir)
    if not os.path.exists(FLAGS.samples_dir):
        os.makedirs(FLAGS.samples_dir)

    gpu_options = tf.GPUOptions(visible_device_list =FLAGS.gpu, per_process_gpu_memory_fraction = 0.8, allow_growth = True)

    with tf.Session(config=tf.ConfigProto(allow_soft_placement=True, log_device_placement=False, gpu_options=gpu_options)) as sess:
        dcgan = DCGAN(sess, FLAGS)
            
        if FLAGS.is_train:
            dcgan.train(FLAGS)
        else:
            dcgan.load(FLAGS.checkpoint_dir)
            dcgan.test(FLAGS, True)
        '''
        if FLAGS.visualize:
            to_json("./web/js/layers.js", [dcgan.h0_w, dcgan.h0_b, dcgan.g_bn0],
                                          [dcgan.h1_w, dcgan.h1_b, dcgan.g_bn1],
                                          [dcgan.h2_w, dcgan.h2_b, dcgan.g_bn2],
                                          [dcgan.h3_w, dcgan.h3_b, dcgan.g_bn3],
                                          [dcgan.h4_w, dcgan.h4_b, None])

                # Below is codes for visualization
            OPTION = 2
            visualize(sess, dcgan, FLAGS, OPTION)'''
开发者ID:tranluan，项目名称:Nonlinear_Face_3DMM，代码行数:33，代码来源:main_non_linear_3DMM.py

示例9: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
	pp.pprint(flags.FLAGS.__flags)

	if not os.path.exists(FLAGS.checkpoint_dir):
		os.makedirs(FLAGS.checkpoint_dir)
	if not os.path.exists(FLAGS.sample_dir):
		os.makedirs(FLAGS.sample_dir)

	gpu_options = tf.GPUOptions(
		per_process_gpu_memory_fraction=FLAGS.gpu_frac)

	with tf.Session(config=tf.ConfigProto(gpu_options=gpu_options)) as sess:
		dcgan = ECGAN(sess)
		dcgan.complete()
开发者ID:arnavkj1995，项目名称:face_inpainting，代码行数:16，代码来源:complete.py

示例10: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
  pp.pprint(flags.FLAGS.__flags)

  if not os.path.exists(FLAGS.checkpoint_dir):
    print(" [*] Creating checkpoint directory...")
    os.makedirs(FLAGS.checkpoint_dir)

  with tf.Session() as sess:
    model = model_dict[FLAGS.model](sess, checkpoint_dir=FLAGS.checkpoint_dir,
                                    seq_length=FLAGS.seq_length,
                                    word_embed_dim=FLAGS.word_embed_dim,
                                    char_embed_dim=FLAGS.char_embed_dim,
                                    feature_maps=eval(FLAGS.feature_maps),
                                    kernels=eval(FLAGS.kernels),
                                    batch_size=FLAGS.batch_size,
                                    dropout_prob=FLAGS.dropout_prob,
                                    max_word_length=FLAGS.max_word_length,
                                    forward_only=FLAGS.forward_only,
                                    dataset_name=FLAGS.dataset,
                                    use_char=FLAGS.use_char,
                                    use_word=FLAGS.use_word,
                                    data_dir=FLAGS.data_dir)

    if not FLAGS.forward_only:
      model.run(FLAGS.epoch, FLAGS.learning_rate, FLAGS.decay)
    else:
      test_loss = model.test(2)
      print(" [*] Test loss: %2.6f, perplexity: %2.6f" % (test_loss, np.exp(test_loss)))
开发者ID:carpedm20，项目名称:lstm-char-cnn-tensorflow，代码行数:30，代码来源:main.py

示例11: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
  pp.pprint(flags.FLAGS.__flags)

  if FLAGS.input_width is None:
    FLAGS.input_width = FLAGS.input_height
  if FLAGS.output_width is None:
    FLAGS.output_width = FLAGS.output_height

  if not os.path.exists(FLAGS.checkpoint_dir):
    os.makedirs(FLAGS.checkpoint_dir)
  if not os.path.exists(FLAGS.sample_dir):
    os.makedirs(FLAGS.sample_dir)

  run_config = tf.ConfigProto()
  run_config.gpu_options.allow_growth=True
  with tf.Session(config=run_config) as sess:
    wgan = WGAN(
      sess,
      input_width=FLAGS.input_width,
      input_height=FLAGS.input_height,
      input_water_width=FLAGS.input_water_width,
      input_water_height=FLAGS.input_water_height,
      output_width=FLAGS.output_width,
      output_height=FLAGS.output_height,
      batch_size=FLAGS.batch_size,
      c_dim=FLAGS.c_dim,
      max_depth = FLAGS.max_depth,
      save_epoch=FLAGS.save_epoch,
      water_dataset_name=FLAGS.water_dataset,
      air_dataset_name = FLAGS.air_dataset,
      depth_dataset_name = FLAGS.depth_dataset,
      input_fname_pattern=FLAGS.input_fname_pattern,
      is_crop=FLAGS.is_crop,
      checkpoint_dir=FLAGS.checkpoint_dir,
      results_dir = FLAGS.results_dir,
      sample_dir=FLAGS.sample_dir,
      num_samples = FLAGS.num_samples)

    if FLAGS.is_train:
      wgan.train(FLAGS)
    else:
      if not wgan.load(FLAGS.checkpoint_dir):
        raise Exception("[!] Train a model first, then run test mode")
      wgan.test(FLAGS)

    # to_json("./web/js/layers.js", [wgan.h0_w, wgan.h0_b, wgan.g_bn0],
    #                 [wgan.h1_w, wgan.h1_b, wgan.g_bn1],
    #                 [wgan.h2_w, wgan.h2_b, wgan.g_bn2],
    #                 [wgan.h3_w, wgan.h3_b, wgan.g_bn3],
    #                 [wgan.h4_w, wgan.h4_b, None])

    # Below is codes for visualization
    #OPTION = 1
    #visualize(sess, wgan, FLAGS, OPTION)
开发者ID:kskin，项目名称:WaterGAN，代码行数:56，代码来源:mainmhl.py

示例12: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
  np.random.seed(0)
  tf.set_random_seed(0)
  pp.pprint(flags.FLAGS.__flags)

  if FLAGS.input_width is None:
    FLAGS.input_width = FLAGS.input_height

  if not os.path.exists(FLAGS.checkpoint_dir):
    os.makedirs(FLAGS.checkpoint_dir)
  if not os.path.exists(FLAGS.sample_dir):
    os.makedirs(FLAGS.sample_dir)

  run_config = tf.ConfigProto()
  run_config.gpu_options.allow_growth=True
  run_config.allow_soft_placement=True
  sess = None
  with tf.Session(config=run_config) as sess:
    dcgan = DCGAN(
        sess,
        input_width=FLAGS.input_width,
        input_height=FLAGS.input_height,
        batch_size=FLAGS.batch_size,
        sample_num=FLAGS.batch_size,
        c_dim=FLAGS.c_dim,
        z_dim=FLAGS.c_dim * FLAGS.input_height * FLAGS.input_width,
        dataset_name=FLAGS.dataset,
        checkpoint_dir=FLAGS.checkpoint_dir,
        f_div=FLAGS.f_div,
        prior=FLAGS.prior,
        lr_decay=FLAGS.lr_decay,
        min_lr=FLAGS.min_lr,
        model_type=FLAGS.model_type,
        log_dir=FLAGS.log_dir,
        alpha=FLAGS.alpha,
        batch_norm_adaptive=FLAGS.batch_norm_adaptive,
        init_type=FLAGS.init_type,
        reg=FLAGS.reg,
        n_critic=FLAGS.n_critic,
        hidden_layers=FLAGS.hidden_layers,
        no_of_layers=FLAGS.no_of_layers,
        like_reg=FLAGS.like_reg,
        df_dim=FLAGS.df_dim)

  dcgan.train(FLAGS)
开发者ID:ermongroup，项目名称:flow-gan，代码行数:47，代码来源:main.py

示例13: main

# 需要导入模块: from utils import pp [as 别名]
# 或者: from utils.pp import pprint [as 别名]
def main(_):
	pp.pprint(flags.FLAGS.__flags)

#	run_config = tf.ConfigProto()
#	run_config.gpu_options.allow_growth=True

#	with tf.Session(config=run_config) as sess:
	with tf.Session() as sess:
		wgan = WGAN(sess,
				input_height=FLAGS.input_height,
				input_width=FLAGS.input_width,
				crop=FLAGS.crop,
				batch_size=FLAGS.batch_size,
				output_height=FLAGS.output_height,
				output_width=FLAGS.output_width,
				z_dim=FLAGS.z_dim,
				g_dim=FLAGS.g_dim,
				d_dim=FLAGS.d_dim,
				dataset_name=FLAGS.dataset,
				input_fname_pattern=FLAGS.data_pattern,
				log_dir=FLAGS.log_dir,
				sample_dir=FLAGS.sample_dir,
				max_epoch=FLAGS.max_epoch,
				n_critic=FLAGS.n_critic,
				lr=FLAGS.learning_rate,
				beta1=FLAGS.beta1,
				beta2=FLAGS.beta2)


		show_all_variables()

		if FLAGS.train:
			wgan.train()
		else:
			if not wgan.load(FLAGS.log_dir):
				raise Exception("[!] Train a model first, then run test mode")



		if FLAGS.forward_test:
			forward_test(sess,wgan,FLAGS, FLAGS.test_num)
		OPTION = 1
		visualize(sess,wgan, FLAGS, OPTION)
开发者ID:changwoolee，项目名称:WGAN-GP-tensorflow，代码行数:45，代码来源:main.py


注：本文中的utils.pp.pprint方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。