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Added fake_epoch for observation

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master
lkrsnik 7 years ago
parent 592ad9b26b
commit 669aa6bbfd
2 changed files with 28 additions and 53 deletions
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63
.idea/workspace.xml
Unescape View File

@ -2,7 +2,9 @@
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/cnn.ipynb" afterPath="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/cnn.ipynb" />
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@ -32,8 +34,8 @@
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@ -135,6 +137,7 @@
<find>split_number</find>
<find>StringIO</find>
<find>shuffle_inputs</find>
<find>generator</find>
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@ -178,7 +181,7 @@
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@ -860,8 +823,8 @@
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@ -928,12 +891,6 @@
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18
prepare_data.py
Unescape View File

@ -7,6 +7,7 @@ import h5py
import gc
import math
# functions for saving, loading and shuffling whole arrays to ram
def save_inputs(file_name, X, y, other_features=[]):
h5f = h5py.File(file_name, 'w')
@ -18,6 +19,7 @@ def save_inputs(file_name, X, y, other_features=[]):
h5f.create_dataset(k, data=v)
h5f.close()
def load_inputs(file_name, other_features=False):
h5f = h5py.File(file_name,'r')
X = h5f['X'][:]
@ -42,6 +44,7 @@ def shuffle_inputs(X, y, X_pure=[]):
else:
return X, y
# functions for saving and loading partial arrays to ram
def create_and_save_inputs(file_name, part, X, y, X_pure):
# X, y, X_pure = generate_full_vowel_matrix_inputs()
@ -51,6 +54,7 @@ def create_and_save_inputs(file_name, part, X, y, X_pure):
h5f.create_dataset(k,data=v)
h5f.close()
def load_extended_inputs(file_name, obtain_range):
h5f = h5py.File(file_name,'r')
X = h5f['X'][obtain_range[0]:obtain_range[1]]
@ -70,6 +74,7 @@ def create_and_save_shuffle_vector(file_name, shuffle_vector):
h5f.create_dataset(k,data=v)
h5f.close()
def load_shuffle_vector(file_name):
h5f = h5py.File(file_name,'r')
shuffle_vector = h5f['shuffle_vector'][[179859, 385513, 893430]]
@ -452,6 +457,19 @@ def generate_X_and_y_RAM_efficient(name, split_number):
h5f.close()
# generator for inputs for tracking of data fitting
def generate_fake_epoch(orig_X, orig_X_additional, orig_y, batch_size):
size = orig_X.shape[0]
while 1:
loc = 0
while loc < size:
if loc + batch_size >= size:
yield([orig_X[loc:size], orig_X_additional[loc:size]], orig_y[loc:size])
else:
yield([orig_X[loc:loc + batch_size], orig_X_additional[loc:loc + batch_size]], orig_y[loc:loc + batch_size])
loc += batch_size
# generator for inputs
def generate_arrays_from_file(path, batch_size):
h5f = h5py.File(path, 'r')

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