Epoch limit reached

[rakibhasan48]

I am running the following :
python train.py --slices 55 --width 12 --stride 1 --Bwidth 350 --vocabulary_size 29
--height 25 --train_data_pattern ./tf-data/handwritten-test-{}.tfrecords --train_dir models-feds
--test_data_pattern ./tf-data/handwritten-test-{}.tfrecords --max_steps 20 --batch_size 20 --beam_size 1
--input_chanels 1 --start_new_model --rnn_cell LSTM --model LSTMCTCModel --num_epochs 6000

Ouput
FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters
INFO:tensorflow:/job:master/task:0: Tensorflow version: 1.1.0.
(8750, '', 25, 350, 1)
[20, 25, 350, 1]
0
[20, 25, None, 1]
INFO:tensorflow:/job:master/task:0: Removing existing train directory.
INFO:tensorflow:/job:master/task:0: Flag 'start_new_model' is set. Building a new model.
INFO:tensorflow:Using batch size of 20 for training.
tf-data/handwritten-test-{}.tfrecords
INFO:tensorflow:Number of training files: 3.
(8750, '', 25, 350, 1)
(8750, '', 25, 350, 1)
INFO:tensorflow:Using batch size of 20 for testing.
tf-data/handwritten-test-{}.tfrecords
INFO:tensorflow:Number of testing files: 3.
(8750, '', 25, 350, 1)
(8750, '********************', 25, 350, 1)
Tensor("Reshape:0", shape=(20, 25, 350, 1), dtype=float32)
[20, 25, 350, 1]
0
[20, 25, None, 1]
INFO:tensorflow:/job:master/task:0: Starting managed session.
2018-03-19 18:25:13.630111: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-03-19 18:25:13.630151: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-03-19 18:25:13.630159: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-03-19 18:25:13.630174: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2instructions, but these are available on your machine and could speed up CPU computations.
2018-03-19 18:25:13.630180: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
2018-03-19 18:25:16.371931: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-03-19 18:25:16.372284: I tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 with properties:
name: Tesla K80
major: 3 minor: 7 memoryClockRate (GHz) 0.8235
pciBusID 0000:00:1e.0
Total memory: 11.17GiB
Free memory: 11.10GiB
2018-03-19 18:25:16.372318: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0
2018-03-19 18:25:16.372332: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y
2018-03-19 18:25:16.372347: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla K80, pci bus id: 0000:00:1e.0)
INFO:tensorflow:/job:master/task:0: Entering training loop.
INFO:tensorflow:global_step/sec: 0
INFO:tensorflow:models-feds/model.ckpt-0 is not in all_model_checkpoint_paths. Manually adding it.
2018-03-19 18:25:19.788531: W tensorflow/core/kernels/queue_base.cc:302] _3_test_input/shuffle_batch_join/random_shuffle_queue: Skipping cancelled dequeue attempt with queue not closed
2018-03-19 18:25:19.789465: W tensorflow/core/kernels/queue_base.cc:302] _3_test_input/shuffle_batch_join/random_shuffle_queue: Skipping cancelled dequeue attempt with queue not closed
INFO:tensorflow:/job:master/task:0: Done training -- epoch limit reached.
INFO:tensorflow:/job:master/task:0: Exited training loop.

@rakibhasan48 what is your os, and how many GB of ram do you have?

[JiteshPshah]

I am also getting the same error. What is the solution?

[rakibhasan48]

I tested on aws. With a titan xp, so specs shouldn't be a problem.

[johnsmithm]

check out the files = [data_pattern.format(j) for j in range(3)] if nameT=='train' else [data_pattern.format(j) for j in range(3,6)] line from train.py to specify the number of training and testing tfrecords. check if tfrecord has images and labels.