Hi @violet17
I noticed that the data directory is set to /home/liumm/data/dataset/cifar-10-batches-py. Are you using the Python version of CIFAR-10 data set? You should use the binary version, downloaded from here.

I encountered the same problem. The problem was solved by re-downloading and then replacing the cifar-10-binary.tar.gz file. It seems as if the problem was caused by file corruption or using the wrong dataset.

from pocketflow.

I have met the same issue. When I change tensorfow to 1.09, it works.

from pocketflow.

I have met the same issue. When I change tensorfow to 1.09, it works.

I have met the same issue. When I change tensorfow to 1.09, it works.

I have met the same issue. When I change tensorfow to 1.09, it works.

Thanks! I will try this.

from pocketflow.

So, what tensorflow version do official publisher recommend?

from pocketflow.

hi, we recommend to use TensorFlow 1.10, as said in the installation guide:
https://pocketflow.github.io/installation/

from pocketflow.

hi, we recommend to use TensorFlow 1.10, as said in the installation guide:
https://pocketflow.github.io/installation/

I try TensorFlow 1.10, and the error is the same.

from pocketflow.

So, what tensorflow version do official publisher recommend?

The result of using TensorFlow 1.10 is the same as using TensorFlow 1.11.

from pocketflow.

Hi @violet17
I noticed that the data directory is set to /home/liumm/data/dataset/cifar-10-batches-py. Are you using the Python version of CIFAR-10 data set? You should use the binary version, downloaded from here.

from pocketflow.

Hi @violet17
I noticed that the data directory is set to /home/liumm/data/dataset/cifar-10-batches-py. Are you using the Python version of CIFAR-10 data set? You should use the binary version, downloaded from here.

thanks.

from pocketflow.

Hi @violet17
I noticed that the data directory is set to /home/liumm/data/dataset/cifar-10-batches-py. Are you using the Python version of CIFAR-10 data set? You should use the binary version, downloaded from here.

Thank you. Solved my problem.

from pocketflow.

Hi @violet17
I noticed that the data directory is set to /home/liumm/data/dataset/cifar-10-batches-py. Are you using the Python version of CIFAR-10 data set? You should use the binary version, downloaded from here.

I used binary version of CIFAR-10 data set ,but it still appears the "Segmentation fault" error.

from pocketflow.

Could you please post your latest full log and execution command? @violet17

from pocketflow.

@jiaxiang-wu
The log is listed below:
./scripts/run_local.sh nets/resnet_at_cifar10_run.py
Python script: nets/resnet_at_cifar10_run.py

of GPUs: 1

extra arguments: --model_http_url https://api.ai.tencent.com/pocketflow --data_dir_local /home/liumm/data/dataset/cifar-10-binary/
'nets/resnet_at_cifar10_run.py' -> 'main.py'
multi-GPU training disabled
[WARNING] TF-Plus & Horovod cannot be imported; multi-GPU training is unsupported
INFO:tensorflow:FLAGS:
INFO:tensorflow:data_disk: local
INFO:tensorflow:data_hdfs_host: None
INFO:tensorflow:data_dir_local: /home/liumm/data/dataset/cifar-10-binary/
INFO:tensorflow:data_dir_hdfs: None
INFO:tensorflow:cycle_length: 4
INFO:tensorflow:nb_threads: 8
INFO:tensorflow:buffer_size: 1024
INFO:tensorflow:prefetch_size: 8
INFO:tensorflow:nb_classes: 10
INFO:tensorflow:nb_smpls_train: 50000
INFO:tensorflow:nb_smpls_val: 5000
INFO:tensorflow:nb_smpls_eval: 10000
INFO:tensorflow:batch_size: 128
INFO:tensorflow:batch_size_eval: 100
INFO:tensorflow:resnet_size: 20
INFO:tensorflow:lrn_rate_init: 0.1
INFO:tensorflow:batch_size_norm: 128.0
INFO:tensorflow:momentum: 0.9
INFO:tensorflow:loss_w_dcy: 0.0002
INFO:tensorflow:model_http_url: https://api.ai.tencent.com/pocketflow
INFO:tensorflow:summ_step: 100
INFO:tensorflow:save_step: 10000
INFO:tensorflow:save_path: ./models/model.ckpt
INFO:tensorflow:save_path_eval: ./models_eval/model.ckpt
INFO:tensorflow:enbl_dst: False
INFO:tensorflow:enbl_warm_start: False
INFO:tensorflow:loss_w_dst: 4.0
INFO:tensorflow:tempr_dst: 4.0
INFO:tensorflow:save_path_dst: ./models_dst/model.ckpt
INFO:tensorflow:nb_epochs_rat: 1.0
INFO:tensorflow:ddpg_actor_depth: 2
INFO:tensorflow:ddpg_actor_width: 64
INFO:tensorflow:ddpg_critic_depth: 2
INFO:tensorflow:ddpg_critic_width: 64
INFO:tensorflow:ddpg_noise_type: param
INFO:tensorflow:ddpg_noise_prtl: tdecy
INFO:tensorflow:ddpg_noise_std_init: 1.0
INFO:tensorflow:ddpg_noise_dst_finl: 0.01
INFO:tensorflow:ddpg_noise_adpt_rat: 1.03
INFO:tensorflow:ddpg_noise_std_finl: 1e-05
INFO:tensorflow:ddpg_rms_eps: 0.0001
INFO:tensorflow:ddpg_tau: 0.01
INFO:tensorflow:ddpg_gamma: 0.9
INFO:tensorflow:ddpg_lrn_rate: 0.001
INFO:tensorflow:ddpg_loss_w_dcy: 0.0
INFO:tensorflow:ddpg_record_step: 1
INFO:tensorflow:ddpg_batch_size: 64
INFO:tensorflow:ddpg_enbl_bsln_func: True
INFO:tensorflow:ddpg_bsln_decy_rate: 0.95
INFO:tensorflow:ws_save_path: ./models_ws/model.ckpt
INFO:tensorflow:ws_prune_ratio: 0.75
INFO:tensorflow:ws_prune_ratio_prtl: optimal
INFO:tensorflow:ws_nb_rlouts: 200
INFO:tensorflow:ws_nb_rlouts_min: 50
INFO:tensorflow:ws_reward_type: single-obj
INFO:tensorflow:ws_lrn_rate_rg: 0.03
INFO:tensorflow:ws_nb_iters_rg: 20
INFO:tensorflow:ws_lrn_rate_ft: 0.0003
INFO:tensorflow:ws_nb_iters_ft: 400
INFO:tensorflow:ws_nb_iters_feval: 25
INFO:tensorflow:ws_prune_ratio_exp: 3.0
INFO:tensorflow:ws_iter_ratio_beg: 0.1
INFO:tensorflow:ws_iter_ratio_end: 0.5
INFO:tensorflow:ws_mask_update_step: 500.0
INFO:tensorflow:cp_lasso: True
INFO:tensorflow:cp_quadruple: False
INFO:tensorflow:cp_reward_policy: accuracy
INFO:tensorflow:cp_nb_points_per_layer: 10
INFO:tensorflow:cp_nb_batches: 60
INFO:tensorflow:cp_prune_option: auto
INFO:tensorflow:cp_prune_list_file: ratio.list
INFO:tensorflow:cp_best_path: ./models/best_model.ckpt
INFO:tensorflow:cp_original_path: ./models/original_model.ckpt
INFO:tensorflow:cp_preserve_ratio: 0.5
INFO:tensorflow:cp_uniform_preserve_ratio: 0.6
INFO:tensorflow:cp_noise_tolerance: 0.15
INFO:tensorflow:cp_lrn_rate_ft: 0.0001
INFO:tensorflow:cp_nb_iters_ft_ratio: 0.2
INFO:tensorflow:cp_finetune: False
INFO:tensorflow:cp_retrain: False
INFO:tensorflow:cp_list_group: 1000
INFO:tensorflow:cp_nb_rlouts: 200
INFO:tensorflow:cp_nb_rlouts_min: 50
INFO:tensorflow:dcp_save_path: ./models_dcp/model.ckpt
INFO:tensorflow:dcp_save_path_eval: ./models_dcp_eval/model.ckpt
INFO:tensorflow:dcp_prune_ratio: 0.5
INFO:tensorflow:dcp_nb_stages: 3
INFO:tensorflow:dcp_lrn_rate_adam: 0.001
INFO:tensorflow:dcp_nb_iters_block: 10000
INFO:tensorflow:dcp_nb_iters_layer: 500
INFO:tensorflow:uql_equivalent_bits: 4
INFO:tensorflow:uql_nb_rlouts: 200
INFO:tensorflow:uql_w_bit_min: 2
INFO:tensorflow:uql_w_bit_max: 8
INFO:tensorflow:uql_tune_layerwise_steps: 100
INFO:tensorflow:uql_tune_global_steps: 2000
INFO:tensorflow:uql_tune_save_path: ./rl_tune_models/model.ckpt
INFO:tensorflow:uql_tune_disp_steps: 300
INFO:tensorflow:uql_enbl_random_layers: True
INFO:tensorflow:uql_enbl_rl_agent: False
INFO:tensorflow:uql_enbl_rl_global_tune: True
INFO:tensorflow:uql_enbl_rl_layerwise_tune: False
INFO:tensorflow:uql_weight_bits: 4
INFO:tensorflow:uql_activation_bits: 32
INFO:tensorflow:uql_use_buckets: False
INFO:tensorflow:uql_bucket_size: 256
INFO:tensorflow:uql_quant_epochs: 60
INFO:tensorflow:uql_save_quant_model_path: ./uql_quant_models/uql_quant_model.ckpt
INFO:tensorflow:uql_quantize_all_layers: False
INFO:tensorflow:uql_bucket_type: channel
INFO:tensorflow:uqtf_save_path: ./models_uqtf/model.ckpt
INFO:tensorflow:uqtf_save_path_eval: ./models_uqtf_eval/model.ckpt
INFO:tensorflow:uqtf_weight_bits: 8
INFO:tensorflow:uqtf_activation_bits: 8
INFO:tensorflow:uqtf_quant_delay: 0
INFO:tensorflow:uqtf_freeze_bn_delay: None
INFO:tensorflow:uqtf_lrn_rate_dcy: 0.01
INFO:tensorflow:nuql_equivalent_bits: 4
INFO:tensorflow:nuql_nb_rlouts: 200
INFO:tensorflow:nuql_w_bit_min: 2
INFO:tensorflow:nuql_w_bit_max: 8
INFO:tensorflow:nuql_tune_layerwise_steps: 100
INFO:tensorflow:nuql_tune_global_steps: 2101
INFO:tensorflow:nuql_tune_save_path: ./rl_tune_models/model.ckpt
INFO:tensorflow:nuql_tune_disp_steps: 300
INFO:tensorflow:nuql_enbl_random_layers: True
INFO:tensorflow:nuql_enbl_rl_agent: False
INFO:tensorflow:nuql_enbl_rl_global_tune: True
INFO:tensorflow:nuql_enbl_rl_layerwise_tune: False
INFO:tensorflow:nuql_init_style: quantile
INFO:tensorflow:nuql_opt_mode: weights
INFO:tensorflow:nuql_weight_bits: 4
INFO:tensorflow:nuql_activation_bits: 32
INFO:tensorflow:nuql_use_buckets: False
INFO:tensorflow:nuql_bucket_size: 256
INFO:tensorflow:nuql_quant_epochs: 60
INFO:tensorflow:nuql_save_quant_model_path: ./nuql_quant_models/model.ckpt
INFO:tensorflow:nuql_quantize_all_layers: False
INFO:tensorflow:nuql_bucket_type: split
INFO:tensorflow:log_dir: ./logs
INFO:tensorflow:enbl_multi_gpu: False
INFO:tensorflow:learner: full-prec
INFO:tensorflow:exec_mode: train
INFO:tensorflow:debug: False
INFO:tensorflow:h: False
INFO:tensorflow:help: False
INFO:tensorflow:helpfull: False
INFO:tensorflow:helpshort: False
2018-11-06 11:03:23.085396: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-11-06 11:03:26.082618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1405] Found device 0 with properties:
name: TITAN Xp major: 6 minor: 1 memoryClockRate(GHz): 1.582
pciBusID: 0000:02:00.0
totalMemory: 11.91GiB freeMemory: 11.74GiB
2018-11-06 11:03:26.082680: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1484] Adding visible gpu devices: 0
2018-11-06 11:03:26.437942: I tensorflow/core/common_runtime/gpu/gpu_device.cc:965] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-11-06 11:03:26.438009: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0
2018-11-06 11:03:26.438018: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] 0: N
2018-11-06 11:03:26.438290: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1097] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 11361 MB memory) -> physical GPU (device: 0, name: TITAN Xp, pci bus id: 0000:02:00.0, compute capability: 6.1)
2018-11-06 11:03:29.822337: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1484] Adding visible gpu devices: 0
2018-11-06 11:03:29.822393: I tensorflow/core/common_runtime/gpu/gpu_device.cc:965] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-11-06 11:03:29.822403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0
2018-11-06 11:03:29.822425: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] 0: N
2018-11-06 11:03:29.822604: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1097] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 11361 MB memory) -> physical GPU (device: 0, name: TITAN Xp, pci bus id: 0000:02:00.0, compute capability: 6.1)
./scripts/run_local.sh: line 45: 4393 Segmentation fault (core dumped) python main.py ${extra_args}

from pocketflow.

Can you list files under this directory /home/liumm/data/dataset/cifar-10-binary/? @violet17

from pocketflow.

@jiaxiang-wu Oh, I made a mistake.
The directory /home/liumm/data/dataset/cifar-10-binary/ contained cifar-10-bin instead of the dataset files, so the scripts didn't works.
Thank you very much for your help!

from pocketflow.

You're welcome. Closing this issue.

from pocketflow.

hi @jiaxiang-wu
environment:
ubuntu 16.04
I want to compress the mobilenetv1.Here is the command used for it
./scripts/run_local.sh nets/mobilenet_at_ilsvrc12_run.py --learner weight-sparse --ws_prune_ratio_prtl uniform
Iam getting the error message " ./scripts/run_local.sh: line 48: 14402 Segmentation fault (core dumped) python main.py ${extra_args}"
here is the detailed log
./scripts/run_local.sh nets/mobilenet_at_ilsvrc12_run.py --learner weight-sparse --ws_prune_ratio_prtl uniform
Python script: nets/mobilenet_at_ilsvrc12_run.py

of GPUs: 1

extra arguments: --learner weight-sparse --ws_prune_ratio_prtl uniform --model_http_url https://api.ai.tencent.com/pocketflow --data_dir_local /home/user/PocketFlow/imagenet_tfrecord
/bin/sh: 1: nvidia-smi: not found
Traceback (most recent call last):
File "utils/get_idle_gpus.py", line 38, in
gpu_smi_output = subprocess.check_output(cmd, shell=True)
File "/usr/lib/python3.6/subprocess.py", line 336, in check_output
**kwargs).stdout
File "/usr/lib/python3.6/subprocess.py", line 418, in run
output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command 'nvidia-smi --query-gpu=index,memory.used,memory.total --format=csv,noheader,nounits' returned non-zero exit status 127.
'nets/mobilenet_at_ilsvrc12_run.py' -> 'main.py'
multi-GPU training disabled
[WARNING] TF-Plus & Horovod cannot be imported; multi-GPU training is unsupported
INFO:tensorflow:FLAGS:
INFO:tensorflow:data_disk: local
INFO:tensorflow:data_hdfs_host: None
INFO:tensorflow:data_dir_local: /home/user/PocketFlow/imagenet_tfrecord
INFO:tensorflow:data_dir_hdfs: None
INFO:tensorflow:cycle_length: 4
INFO:tensorflow:nb_threads: 8
INFO:tensorflow:buffer_size: 1024
INFO:tensorflow:prefetch_size: 8
INFO:tensorflow:nb_classes: 1001
INFO:tensorflow:nb_smpls_train: 1281167
INFO:tensorflow:nb_smpls_val: 10000
INFO:tensorflow:nb_smpls_eval: 50000
INFO:tensorflow:batch_size: 64
INFO:tensorflow:batch_size_eval: 100
INFO:tensorflow:mobilenet_version: 1
INFO:tensorflow:mobilenet_depth_mult: 1.0
INFO:tensorflow:nb_epochs_rat: 1.0
INFO:tensorflow:lrn_rate_init: 0.045
INFO:tensorflow:batch_size_norm: 96.0
INFO:tensorflow:momentum: 0.9
INFO:tensorflow:loss_w_dcy: 4e-05
INFO:tensorflow:model_http_url: https://api.ai.tencent.com/pocketflow
INFO:tensorflow:summ_step: 100
INFO:tensorflow:save_step: 10000
INFO:tensorflow:save_path: ./models/model.ckpt
INFO:tensorflow:save_path_eval: ./models_eval/model.ckpt
INFO:tensorflow:enbl_dst: False
INFO:tensorflow:enbl_warm_start: False
INFO:tensorflow:loss_w_dst: 4.0
INFO:tensorflow:tempr_dst: 4.0
INFO:tensorflow:save_path_dst: ./models_dst/model.ckpt
INFO:tensorflow:ddpg_actor_depth: 2
INFO:tensorflow:ddpg_actor_width: 64
INFO:tensorflow:ddpg_critic_depth: 2
INFO:tensorflow:ddpg_critic_width: 64
INFO:tensorflow:ddpg_noise_type: param
INFO:tensorflow:ddpg_noise_prtl: tdecy
INFO:tensorflow:ddpg_noise_std_init: 1.0
INFO:tensorflow:ddpg_noise_dst_finl: 0.01
INFO:tensorflow:ddpg_noise_adpt_rat: 1.03
INFO:tensorflow:ddpg_noise_std_finl: 1e-05
INFO:tensorflow:ddpg_rms_eps: 0.0001
INFO:tensorflow:ddpg_tau: 0.01
INFO:tensorflow:ddpg_gamma: 0.9
INFO:tensorflow:ddpg_lrn_rate: 0.001
INFO:tensorflow:ddpg_loss_w_dcy: 0.0
INFO:tensorflow:ddpg_record_step: 1
INFO:tensorflow:ddpg_batch_size: 64
INFO:tensorflow:ddpg_enbl_bsln_func: True
INFO:tensorflow:ddpg_bsln_decy_rate: 0.95
INFO:tensorflow:ws_save_path: ./models_ws/model.ckpt
INFO:tensorflow:ws_prune_ratio: 0.75
INFO:tensorflow:ws_prune_ratio_prtl: uniform
INFO:tensorflow:ws_nb_rlouts: 200
INFO:tensorflow:ws_nb_rlouts_min: 50
INFO:tensorflow:ws_reward_type: single-obj
INFO:tensorflow:ws_lrn_rate_rg: 0.03
INFO:tensorflow:ws_nb_iters_rg: 20
INFO:tensorflow:ws_lrn_rate_ft: 0.0003
INFO:tensorflow:ws_nb_iters_ft: 400
INFO:tensorflow:ws_nb_iters_feval: 25
INFO:tensorflow:ws_prune_ratio_exp: 3.0
INFO:tensorflow:ws_iter_ratio_beg: 0.1
INFO:tensorflow:ws_iter_ratio_end: 0.5
INFO:tensorflow:ws_mask_update_step: 500.0
INFO:tensorflow:cp_lasso: True
INFO:tensorflow:cp_quadruple: False
INFO:tensorflow:cp_reward_policy: accuracy
INFO:tensorflow:cp_nb_points_per_layer: 10
INFO:tensorflow:cp_nb_batches: 30
INFO:tensorflow:cp_prune_option: auto
INFO:tensorflow:cp_prune_list_file: ratio.list
INFO:tensorflow:cp_channel_pruned_path: ./models/pruned_model.ckpt
INFO:tensorflow:cp_best_path: ./models/best_model.ckpt
INFO:tensorflow:cp_original_path: ./models/original_model.ckpt
INFO:tensorflow:cp_preserve_ratio: 0.5
INFO:tensorflow:cp_uniform_preserve_ratio: 0.6
INFO:tensorflow:cp_noise_tolerance: 0.15
INFO:tensorflow:cp_lrn_rate_ft: 0.0001
INFO:tensorflow:cp_nb_iters_ft_ratio: 0.2
INFO:tensorflow:cp_finetune: False
INFO:tensorflow:cp_retrain: False
INFO:tensorflow:cp_list_group: 1000
INFO:tensorflow:cp_nb_rlouts: 200
INFO:tensorflow:cp_nb_rlouts_min: 50
INFO:tensorflow:cpg_save_path: ./models_cpg/model.ckpt
INFO:tensorflow:cpg_save_path_eval: ./models_cpg_eval/model.ckpt
INFO:tensorflow:cpg_prune_ratio_type: uniform
INFO:tensorflow:cpg_prune_ratio: 0.5
INFO:tensorflow:cpg_skip_ht_layers: True
INFO:tensorflow:cpg_prune_ratio_file: None
INFO:tensorflow:cpg_lrn_rate_pgd_init: 1e-10
INFO:tensorflow:cpg_lrn_rate_pgd_incr: 1.4
INFO:tensorflow:cpg_lrn_rate_pgd_decr: 0.7
INFO:tensorflow:cpg_lrn_rate_adam: 0.01
INFO:tensorflow:cpg_nb_iters_layer: 1000
INFO:tensorflow:cpr_save_path: ./models_cpr/model.ckpt
INFO:tensorflow:cpr_save_path_eval: ./models_cpr_eval/model.ckpt
INFO:tensorflow:cpr_save_path_ws: ./models_cpr_ws/model.ckpt
INFO:tensorflow:cpr_prune_ratio: 0.5
INFO:tensorflow:cpr_skip_frst_layer: True
INFO:tensorflow:cpr_skip_last_layer: False
INFO:tensorflow:cpr_skip_op_names: None
INFO:tensorflow:cpr_nb_smpls: 5000
INFO:tensorflow:cpr_nb_crops_per_smpl: 10
INFO:tensorflow:cpr_ista_lrn_rate: 0.01
INFO:tensorflow:cpr_ista_nb_iters: 100
INFO:tensorflow:cpr_lstsq_lrn_rate: 0.001
INFO:tensorflow:cpr_lstsq_nb_iters: 100
INFO:tensorflow:cpr_warm_start: False
INFO:tensorflow:dcp_save_path: ./models_dcp/model.ckpt
INFO:tensorflow:dcp_save_path_eval: ./models_dcp_eval/model.ckpt
INFO:tensorflow:dcp_prune_ratio: 0.5
INFO:tensorflow:dcp_nb_stages: 3
INFO:tensorflow:dcp_lrn_rate_adam: 0.001
INFO:tensorflow:dcp_nb_iters_block: 10000
INFO:tensorflow:dcp_nb_iters_layer: 500
INFO:tensorflow:uql_equivalent_bits: 4
INFO:tensorflow:uql_nb_rlouts: 200
INFO:tensorflow:uql_w_bit_min: 2
INFO:tensorflow:uql_w_bit_max: 8
INFO:tensorflow:uql_tune_layerwise_steps: 100
INFO:tensorflow:uql_tune_global_steps: 2000
INFO:tensorflow:uql_tune_save_path: ./rl_tune_models/model.ckpt
INFO:tensorflow:uql_tune_disp_steps: 300
INFO:tensorflow:uql_enbl_random_layers: True
INFO:tensorflow:uql_enbl_rl_agent: False
INFO:tensorflow:uql_enbl_rl_global_tune: True
INFO:tensorflow:uql_enbl_rl_layerwise_tune: False
INFO:tensorflow:uql_weight_bits: 4
INFO:tensorflow:uql_activation_bits: 32
INFO:tensorflow:uql_use_buckets: False
INFO:tensorflow:uql_bucket_size: 256
INFO:tensorflow:uql_quant_epochs: 60
INFO:tensorflow:uql_save_quant_model_path: ./uql_quant_models/uql_quant_model.ckpt
INFO:tensorflow:uql_quantize_all_layers: False
INFO:tensorflow:uql_bucket_type: channel
INFO:tensorflow:uqtf_save_path_probe: ./models_uqtf_probe/model.ckpt
INFO:tensorflow:uqtf_save_path_probe_eval: ./models_uqtf_probe_eval/model.ckpt
INFO:tensorflow:uqtf_save_path: ./models_uqtf/model.ckpt
INFO:tensorflow:uqtf_save_path_eval: ./models_uqtf_eval/model.ckpt
INFO:tensorflow:uqtf_weight_bits: 8
INFO:tensorflow:uqtf_activation_bits: 8
INFO:tensorflow:uqtf_quant_delay: 0
INFO:tensorflow:uqtf_freeze_bn_delay: None
INFO:tensorflow:uqtf_lrn_rate_dcy: 0.01
INFO:tensorflow:uqtf_enbl_manual_quant: False
INFO:tensorflow:nuql_equivalent_bits: 4
INFO:tensorflow:nuql_nb_rlouts: 200
INFO:tensorflow:nuql_w_bit_min: 2
INFO:tensorflow:nuql_w_bit_max: 8
INFO:tensorflow:nuql_tune_layerwise_steps: 100
INFO:tensorflow:nuql_tune_global_steps: 2101
INFO:tensorflow:nuql_tune_save_path: ./rl_tune_models/model.ckpt
INFO:tensorflow:nuql_tune_disp_steps: 300
INFO:tensorflow:nuql_enbl_random_layers: True
INFO:tensorflow:nuql_enbl_rl_agent: False
INFO:tensorflow:nuql_enbl_rl_global_tune: True
INFO:tensorflow:nuql_enbl_rl_layerwise_tune: False
INFO:tensorflow:nuql_init_style: quantile
INFO:tensorflow:nuql_opt_mode: weights
INFO:tensorflow:nuql_weight_bits: 4
INFO:tensorflow:nuql_activation_bits: 32
INFO:tensorflow:nuql_use_buckets: False
INFO:tensorflow:nuql_bucket_size: 256
INFO:tensorflow:nuql_quant_epochs: 60
INFO:tensorflow:nuql_save_quant_model_path: ./nuql_quant_models/model.ckpt
INFO:tensorflow:nuql_quantize_all_layers: False
INFO:tensorflow:nuql_bucket_type: split
INFO:tensorflow:log_dir: ./logs
INFO:tensorflow:enbl_multi_gpu: False
INFO:tensorflow:learner: weight-sparse
INFO:tensorflow:exec_mode: train
INFO:tensorflow:debug: False
INFO:tensorflow:h: False
INFO:tensorflow:help: False
INFO:tensorflow:helpfull: False
INFO:tensorflow:helpshort: False
WARNING:tensorflow:From /home/user/PocketFlow/datasets/abstract_dataset.py:85: parallel_interleave (from tensorflow.contrib.data.python.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.data.experimental.parallel_interleave(...).
WARNING:tensorflow:From /home/user/PocketFlow/datasets/abstract_dataset.py:106: shuffle_and_repeat (from tensorflow.contrib.data.python.ops.shuffle_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.data.experimental.shuffle_and_repeat(...).
INFO:tensorflow:model/MobilenetV1/Conv2d_1_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_2_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_3_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_4_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_5_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_6_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_7_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_8_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_9_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_10_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_11_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_12_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Conv2d_13_pointwise/weights:0: 0.750000
INFO:tensorflow:model/MobilenetV1/Logits/Conv2d_1c_1x1/weights:0: 0.750000
./scripts/run_local.sh: line 48: 14402 Segmentation fault (core dumped) python main.py ${extra_args}

can u please solve my problem

from pocketflow.