from utils import DEFINE_boolean
from utils import DEFINE_float
from utils import DEFINE_integer
from utils import DEFINE_string
from utils import print_user_flags
import data_utils
from micro_controller import MicroController
from micro_child import MicroChild
flags = tf.app.flags
FLAGS = flags.FLAGS
################## YOU Should write under parameter ######################
DEFINE_string("output_dir", "./output", "")
DEFINE_string("train_data_dir", "./data/train", "")
DEFINE_string("val_data_dir", "./data/valid", "")
DEFINE_string("test_data_dir", "./data/test", "")
DEFINE_integer("channel", 1, "MNIST: 1, Cifar10: 3")
DEFINE_integer("img_size", 32, "enlarge image size")
DEFINE_integer("n_aug_img", 1,
"if 2: num_img: 55000 -> aug_img: 110000, elif 1: False")
DEFINE_float("child_lr_min", 0.00005, "for lr schedule")
##########################################################################
DEFINE_boolean("reset_output_dir", True, "Delete output_dir if exists.")
DEFINE_string("data_format", "NHWC", "'NHWC or NCHW'")
DEFINE_string("search_for", "micro", "")
DEFINE_integer("batch_size", 160, "")
from path_generator import PathGenerator
from dag_executor import DagExecutor
from dag_generator import DagGenerator
from dag_controller import DagController
import data_utils
from data_utils import read_data
flags = tf.app.flags
FLAGS = flags.FLAGS
os.environ['CUDA_VISIBLE_DEVICES'] = '1'
logger = utils.logger
DEFINE_boolean("reset_output_dir", False, "Delete output_dir if exists.")
DEFINE_string("data_path", "", "")
DEFINE_string("output_dir", "", "")
DEFINE_string("summaries_dir", "", "")
DEFINE_string("data_format", "NHWC", "'NHWC' or 'NCWH'")
DEFINE_string("search_for", None, "Must be [macro|micro]")
DEFINE_integer("num_gpus", 1, "")
DEFINE_integer("num_cpus", 1, "")
DEFINE_integer("batch_size", 32, "")
DEFINE_integer("num_epochs_evolve", 3, "")
DEFINE_integer("num_epochs", 300, "")
DEFINE_integer("child_lr_dec_every", 100, "")
DEFINE_integer("child_num_layers", 5, "")
DEFINE_integer("child_num_cells", 8, "")
from utils import DEFINE_boolean
from utils import DEFINE_integer
from utils import DEFINE_string
from utils import DEFINE_float
from utils import print_user_flags
from utils import loss_function
from utils import plot_attention_map
flags = tf.app.flags
FLAGS = flags.FLAGS
DEFINE_boolean("reset_output_dir", False, "Delete output_dir if exists.")
DEFINE_boolean("restore_checkpoint", True, "Auto retrieve checkpoint or not.")
DEFINE_boolean("is_toy", False, "Toy Dataset or not, useful for debugging")
DEFINE_boolean("is_attention", False, "Using Attention for Decoder or not")
DEFINE_string("data_path", "en-es", "Path to parallel corpus data (.txt)")
DEFINE_string("output_dir", "output", "Path to log folder")
DEFINE_string("cell_type", "gru", "GRU or LSTM or naive, ...")
DEFINE_integer("n_epochs", 10, "Number of training epochs")
DEFINE_integer("n_layers", 1, "Number of stacked RNN layers")
DEFINE_integer("n_hidden", 1024, "Dimensionality of RNN output")
DEFINE_integer("emb_dim", 256, "Dimensionality of word embedding, src==tgt")
DEFINE_integer("save_every", 500, "How many batches to save once")
DEFINE_integer("eval_every", 100, "How many batches to evaluate")
DEFINE_integer("batch_size", 64, "Batch size. SET to `2` for easy debugging.")
DEFINE_integer("n_loaded_sentences", 20000, "Number of sentences to load, "
"Set to <= 0 for loading all data,"
"SET LOWER FOR DEBUGGING")
DEFINE_float("init_lr", 1e-3, "Init learning rate. This is default for Adam.")
DEFINE_float("drop_keep_prob", 1.0, "Dropout rate")
from utils import DEFINE_bool
from utils import DEFINE_float
from utils import DEFINE_integer
from utils import DEFINE_string
from utils import print_user_flags
os.environ['CUDA_VISIBLE_DEVICES'] = '1'
logger = utils.logger
flags = tf.flags
FLAGS = flags.FLAGS
## Required parameters
DEFINE_string(
"data_dir", None,
"The input data dir. Should contain the .tsv files (or other data files) "
"for the task.")
DEFINE_string(
"bert_config_file", None,
"The config json file corresponding to the pre-trained BERT model. "
"This specifies the model architecture.")
DEFINE_string("task_name", None, "The name of the task to train.")
DEFINE_string("vocab_file", None,
"The vocabulary file that the BERT model was trained on.")
DEFINE_string(
"output_dir", None,
"The output directory where the model checkpoints will be written.")