#############################################################################
# Model Setup #
#############################################################################
logging.info("MODEL SETUP - Tensorflow version".format(tf.__version__))
logging.info("MODEL SETUP - Validation Script - train_full.py")
from tensorflow.python.client import device_lib
logging.info("MODEL SETUP - CUDA VISIBLE DEVICES {}".format(
device_lib.list_local_devices()))
# tf.compat.v1.debugging.assert_equal(True, tf.test.is_gpu_available())
# tf.compat.v1.debugging.assert_equal(True, tf.test.is_built_with_cuda())
image2seq = EDAXUMLP()
logging.info("MODEL SETUP - image2seq model {} instantiated".format(
image2seq.get_model_name()))
logging.info("MODEL SETUP - log file = "
"image2seq/logs/evaluate_log_{}_{}{}.txt".format(
date, hour, minute))
# Parameter options #########################################################
# CSV file of images to import
# images_seqs_csv = "/graphs/0816_retinanet_1x1_demo/cropped/stage2_train.txt"
# train_info_csv = "/graphs/0816_retinanet_1x1_demo/cropped/stage2_train.txt"
images_seqs_csv = "/graphs/0828_retinanet_1x1_demo/cropped/stage2_train.txt"
train_info_csv = "/graphs/0828_retinanet_1x1_demo/cropped/stage2_train.txt"
# Data config
batch_size = 22
logging.info("MODEL SETUP - Batch size {}".format(batch_size))
#############################################################################
# Model Setup #
#############################################################################
logging.info("MODEL SETUP - Training Script - train.py")
from tensorflow.python.client import device_lib
logging.info("MODEL SETUP - CUDA VISIBLE DEVICES {}".format(
device_lib.list_local_devices()))
tf.compat.v1.debugging.assert_equal(True, tf.test.is_gpu_available())
tf.compat.v1.debugging.assert_equal(True, tf.test.is_built_with_cuda())
image2seq = EDAXUMLP(image_embedding_dim=256,
token_embedding_dim=8,
decoder_hidden_dim=512,
mlp_hidden_dim=256)
logging.info("MODEL SETUP - image2seq model {} instantiated".format(
image2seq.get_model_name()))
logging.info(
"MODEL SETUP - log file = image2seq/logs/train_log_{}_{}{}.txt".format(
date, hour, minute))
# Parameter options #########################################################
# CSV file of images to import
# images_seqs_csv = "/test_data/stage2_data_train/stage2_train.txt"
images_seqs_csv = "/stage2_data_train_1x1/stage2_train.txt"
train_info_csv = "/stage2_data_train_1x1/stage2_train_info.txt"
# Data config
batch_size = 256
logging.info("MODEL SETUP - Batch size {}".format(batch_size))
# Optimizer selection