how to train or eval?

[berli]

`u@u-VirtualBox:~/sentiment_analysis_textcnn/textcnn$ python train.py

Parameters:
ALLOW_SOFT_PLACEMENT=True
BATCH_SIZE=64
CHECKPOINT_EVERY=100
DEV_SAMPLE_PERCENTAGE=0.1
DROPOUT_KEEP_PROB=0.5
EMBEDDING_DIM=128
EVALUATE_EVERY=50
FILTER_SIZES=2,3,4
L2_REG_LAMBDA=0.0
LOG_DEVICE_PLACEMENT=False
NUM_CHECKPOINTS=5
NUM_EPOCHS=10
NUM_FILTERS=128
TRAIN_DATA_FILE=../data/cutclean_label_corpus10000.txt
TRAIN_LABEL_DATA_FILE=
W2V_FILE=../data/vectors.bin

Loading data...
Traceback (most recent call last):
File "train.py", line 226, in
train(w2v_wr.model)
File "train.py", line 93, in train
x_train, x_dev, y_train, y_dev ,vocab_size= load_data(w2v_model)
File "train.py", line 54, in load_data
x_text, y = data_helpers.load_data_and_labels(FLAGS.train_data_file)
File "/home/u/sentiment_analysis_textcnn/textcnn/data_input_helper.py", line 76, in load_data_and_labels
with open(filepath, 'r', encoding='utf-8',errors='ignore') as f:
TypeError: file() takes at most 3 arguments (4 given)`` eval
u@u-VirtualBox:~/sentiment_analysis_textcnn/textcnn$ python eval.py

Parameters:
ALLOW_SOFT_PLACEMENT=True
BATCH_SIZE=64
CHECKPOINT_DIR=./runs/1501842714/checkpoints/
EVAL_TRAIN=True
LOG_DEVICE_PLACEMENT=False
VALID_DATA_FILE=../data/cutclean_label_corpus10000.txt
W2V_FILE=../data/vectors.bin

2018-01-11 10:02:53.954545: 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.
2018-01-11 10:02:53.954615: 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.
2018-01-11 10:02:53.954634: 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.
Traceback (most recent call last):
File "eval.py", line 107, in
eval(w2v_wr.model)
File "eval.py", line 68, in eval
saver = tf.train.import_meta_graph("{}.meta".format(checkpoint_file))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 1679, in import_meta_graph
meta_graph_def = meta_graph.read_meta_graph_file(meta_graph_or_file)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/meta_graph.py", line 402, in read_meta_graph_file
raise IOError("File %s does not exist." % filename)
IOError: File None.meta does not exist.

`

[JasonLiuys]

`u@u-VirtualBox:~/sentiment_analysis_textcnn/textcnn$ python train.py

Parameters:
ALLOW_SOFT_PLACEMENT=True
BATCH_SIZE=64
CHECKPOINT_EVERY=100
DEV_SAMPLE_PERCENTAGE=0.1
DROPOUT_KEEP_PROB=0.5
EMBEDDING_DIM=128
EVALUATE_EVERY=50
FILTER_SIZES=2,3,4
L2_REG_LAMBDA=0.0
LOG_DEVICE_PLACEMENT=False
NUM_CHECKPOINTS=5
NUM_EPOCHS=10
NUM_FILTERS=128
TRAIN_DATA_FILE=../data/cutclean_label_corpus10000.txt
TRAIN_LABEL_DATA_FILE=
W2V_FILE=../data/vectors.bin

Loading data...
Traceback (most recent call last):
File "train.py", line 226, in
train(w2v_wr.model)
File "train.py", line 93, in train
x_train, x_dev, y_train, y_dev ,vocab_size= load_data(w2v_model)
File "train.py", line 54, in load_data
x_text, y = data_helpers.load_data_and_labels(FLAGS.train_data_file)
File "/home/u/sentiment_analysis_textcnn/textcnn/data_input_helper.py", line 76, in load_data_and_labels
with open(filepath, 'r', encoding='utf-8',errors='ignore') as f:
TypeError: file() takes at most 3 arguments (4 given) eval ``
u@u-VirtualBox:~/sentiment_analysis_textcnn/textcnn$ python eval.py

Parameters:
ALLOW_SOFT_PLACEMENT=True
BATCH_SIZE=64
CHECKPOINT_DIR=./runs/1501842714/checkpoints/
EVAL_TRAIN=True
LOG_DEVICE_PLACEMENT=False
VALID_DATA_FILE=../data/cutclean_label_corpus10000.txt
W2V_FILE=../data/vectors.bin

2018-01-11 10:02:53.954545: 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.
2018-01-11 10:02:53.954615: 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.
2018-01-11 10:02:53.954634: 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.
Traceback (most recent call last):
File "eval.py", line 107, in
eval(w2v_wr.model)
File "eval.py", line 68, in eval
saver = tf.train.import_meta_graph("{}.meta".format(checkpoint_file))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 1679, in import_meta_graph
meta_graph_def = meta_graph.read_meta_graph_file(meta_graph_or_file)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/meta_graph.py", line 402, in read_meta_graph_file
raise IOError("File %s does not exist." % filename)
IOError: File None.meta does not exist.

`

把第22行的
tf.flags.DEFINE_string("checkpoint_dir", "./runs/1553516157/checkpoints/", "Checkpoint directory from training run")
路径改成你自己的