在安装Google驱动器后，我正在使用colab在cifar10上训练resnet 我克隆了存储库，并能够运行脚本。 但是，已加载Tensorflow并将数据文件传递到网络，但我的结尾是：
tensorflow.python.framework.errors_impl.NotFoundError： / content / drive /我的；没有这样的文件或目录
我的路径似乎有问题，因为它包含一个空格“ / content / gdrive /我的驱动器/ apps / PocketFlow”。如何更改gdrive的安装方式，换句话说，我可以将“我的驱动器”更改为其他名称以再次运行测试吗？
下面您可以找到代码和日志文件：
from google.colab import drive
drive.mount('/content/gdrive')
import os
os.chdir("/content/gdrive/My Drive/apps/PocketFlow")
!chmod 755 ./scripts/run_local.sh
!./scripts/run_local.sh nets/resnet_at_cifar10_run.py
日志：
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 /content/drive/My Drive/apps/datasets/cifar10
'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: /content/drive/My
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: 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: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
2018-11-16 12:53:20.147847: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:964] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-11-16 12:53:20.148287: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:00:04.0
totalMemory: 11.17GiB freeMemory: 11.10GiB
2018-11-16 12:53:20.148358: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2018-11-16 12:53:20.565167: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-11-16 12:53:20.565235: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2018-11-16 12:53:20.565262: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2018-11-16 12:53:20.565561: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:42] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.
2018-11-16 12:53:20.565637: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10758 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7)
WARNING:tensorflow:From /content/gdrive/My Drive/apps/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 /content/gdrive/My Drive/apps/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(...)`.
2018-11-16 12:53:23.066723: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2018-11-16 12:53:23.066814: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-11-16 12:53:23.066857: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2018-11-16 12:53:23.066882: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2018-11-16 12:53:23.067168: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10758 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7)
2018-11-16 12:53:24.963790: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at matching_files_op.cc:49 : Not found: /content/drive/My; No such file or directory
2018-11-16 12:53:24.964542: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at matching_files_op.cc:49 : Not found: /content/drive/My; No such file or directory
2018-11-16 12:53:24.964744: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at iterator_ops.cc:947 : Not found: /content/drive/My; No such file or directory
[[{{node ShuffleDataset/data/list_files/MatchingFiles}} = MatchingFiles[](ShuffleDataset/data/list_files/file_pattern)]]
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py", line 1334, in _do_call
return fn(*args)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.NotFoundError: /content/drive/My; No such file or directory
[[{{node ShuffleDataset/data/list_files/MatchingFiles}} = MatchingFiles[](ShuffleDataset/data/list_files/file_pattern)]]
[[{{node data/OneShotIterator}} = OneShotIterator[container="", dataset_factory=_make_dataset_E02JEaYNEAE[], output_shapes=[[?,32,32,3], [?,10]], output_types=[DT_FLOAT, DT_FLOAT], shared_name="", _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
[[{{node data/IteratorGetNext/_3}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_107_data/IteratorGetNext", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "main.py", line 69, in <module>
tf.app.run()
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "main.py", line 55, in main
learner.train()
File "/content/gdrive/My Drive/apps/PocketFlow/learners/full_precision/learner.py", line 71, in train
self.sess_train.run(self.train_op)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py", line 929, in run
run_metadata_ptr)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py", line 1328, in _do_run
run_metadata)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: /content/drive/My; No such file or directory
[[{{node ShuffleDataset/data/list_files/MatchingFiles}} = MatchingFiles[](ShuffleDataset/data/list_files/file_pattern)]]
[[node data/OneShotIterator (defined at /content/gdrive/My Drive/apps/PocketFlow/datasets/abstract_dataset.py:109) = OneShotIterator[container="", dataset_factory=_make_dataset_E02JEaYNEAE[], output_shapes=[[?,32,32,3], [?,10]], output_types=[DT_FLOAT, DT_FLOAT], shared_name="", _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
[[{{node data/IteratorGetNext/_3}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_107_data/IteratorGetNext", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
答案 0 :(得分：3)
似乎./scripts/run_local.sh或nets/resnet_at_cifar10_run.py正在将$PWD的等效项传递给报价不足的子流程。您可以修复它或解决它，例如与：
from google.colab import drive
drive.mount('/content/gdrive')
!ln -s "/content/gdrive/My Drive" "/content/mydrive"
import os
os.chdir("/content/mydrive/apps/PocketFlow")
!chmod 755 ./scripts/run_local.sh
!./scripts/run_local.sh nets/resnet_at_cifar10_run.py