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rosdyana / Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction

Repository for Going Deeper with Convolutional Neural Network for Stock Market Prediction
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trying to use it and breaks literally every step of the way #3

Open berlinguyinca opened 5 years ago

berlinguyinca commented 5 years ago

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): , Using TensorFlow backend. loading dataset train size : 3751 train size : 331 /home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py:55: UserWarning: Update your 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 main() File "/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/myDeepCNN.py", line 137, in main model.fit(X_train, Y_train, batch_size=batch_size, epochs=epochs) File "/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/venv/lib/python3.7/site-packages/keras/engine/training.py", line 952, in fit batch_size=batch_size) File "/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/venv/lib/python3.7/site-packages/keras/engine/training.py", line 751, in _standardize_user_data exception_prefix='input') File "/home/wohlgemuth/workspace/Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction/venv/lib/python3.7/site-packages/keras/engine/training_utils.py", line 128, in standardize_input_data 'with shape ' + str(data_shape)) ValueError: Error when checking input: expected input_1 to have 4 dimensions, but got array with shape (3751, 7500)

tondatto commented 4 years ago

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