Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction
Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction copied to clipboard
trying to use it and breaks literally every step of the way
would it be possible to get a complete example? I keep running in all kind of issues, from keras warnings, over methods not found errors, missing requirements, etc.
example:
/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/venv/bin/python /home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py -i dataset/20_50/2880.TW -e 50 -d 50 -b 8 -o outputresult.txt
2019-06-19 05:39:27.101687: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-06-19 05:39:27.126885: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2112000000 Hz
2019-06-19 05:39:27.127344: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x1c1c450 executing computations on platform Host. Devices:
2019-06-19 05:39:27.127362: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): Conv2D
call to the Keras 2 API: Conv2D(32, (3, 3), activation="relu", padding="same", kernel_initializer="glorot_uniform")
number of classes : 331
border_mode='same', activation='relu')(input_layer)
WARNING:tensorflow:From /home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/venv/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py:61: UserWarning: Update your Conv2D
call to the Keras 2 API: Conv2D(48, (3, 3), activation="relu", padding="same", kernel_initializer="glorot_uniform")
activation='relu')(x)
WARNING:tensorflow:From /home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/venv/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.
Instructions for updating:
Please use rate
instead of keep_prob
. Rate should be set to rate = 1 - keep_prob
.
/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py:68: UserWarning: Update your Conv2D
call to the Keras 2 API: Conv2D(64, (3, 3), activation="relu", padding="same", kernel_initializer="glorot_uniform")
activation='relu')(x)
/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py:74: UserWarning: Update your Conv2D
call to the Keras 2 API: Conv2D(96, (3, 3), activation="relu", padding="same", kernel_initializer="glorot_uniform")
activation='relu')(x)
/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py:84: UserWarning: Update your Dense
call to the Keras 2 API: Dense(activation="relu", units=256)
x = Dense(output_dim=256, activation='relu')(x)
/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py:88: UserWarning: Update your Dense
call to the Keras 2 API: Dense(activation="softmax", units=2)
x = Dense(output_dim=2, activation='softmax')(x)
Traceback (most recent call last):
File "/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py", line 195, in
That error is because the project is using util/dataset_traditional.py
instead util/dataset.py
.
I fix it by comment these lines in utils/__init__.py
from __future__ import absolute_import
from . import dataset
# from . import dataset_traditional
from .dataset import dataset
# from .dataset_traditional import dataset