In [1]:
import numpy as np
from keras.models import Model
from keras.layers import Input
from keras.layers.core import Dense
from keras.layers.convolutional import Conv2D
from keras.layers.wrappers import TimeDistributed
from keras import backend as K
import json
from collections import OrderedDict
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def format_decimal(arr, places=6):
return [round(x * 10**places) / 10**places for x in arr]
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DATA = OrderedDict()
[wrappers.TimeDistributed.0] wrap a Dense layer with units 4 (input: 3 x 6)
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random_seed = 2000
data_in_shape = (3, 6)
layer_0 = Input(shape=data_in_shape)
layer_1 = TimeDistributed(Dense(4))(layer_0)
model = Model(inputs=layer_0, outputs=layer_1)
np.random.seed(random_seed)
data_in = 2 * np.random.random(data_in_shape) - 1
# set weights to random (use seed for reproducibility)
weights = []
for i, w in enumerate(model.get_weights()):
np.random.seed(random_seed + i)
weights.append(2 * np.random.random(w.shape) - 1)
model.set_weights(weights)
result = model.predict(np.array([data_in]))
data_out_shape = result[0].shape
data_in_formatted = format_decimal(data_in.ravel().tolist())
data_out_formatted = format_decimal(result[0].ravel().tolist())
DATA['wrappers.TimeDistributed.0'] = {
'input': {'data': data_in_formatted, 'shape': data_in_shape},
'weights': [{'data': format_decimal(w.ravel().tolist()), 'shape': w.shape} for w in weights],
'expected': {'data': data_out_formatted, 'shape': data_out_shape}
}
[wrappers.TimeDistributed.1] wrap a Conv2D layer with 6 3x3 filters (input: 5x4x4x2)
In [5]:
random_seed = 2000
data_in_shape = (5, 4, 4, 2)
layer_0 = Input(shape=data_in_shape)
layer_1 = TimeDistributed(Conv2D(6, (3,3), data_format='channels_last'))(layer_0)
model = Model(inputs=layer_0, outputs=layer_1)
np.random.seed(random_seed)
data_in = 2 * np.random.random(data_in_shape) - 1
# set weights to random (use seed for reproducibility)
weights = []
for i, w in enumerate(model.get_weights()):
np.random.seed(random_seed + i)
weights.append(2 * np.random.random(w.shape) - 1)
model.set_weights(weights)
result = model.predict(np.array([data_in]))
data_out_shape = result[0].shape
data_in_formatted = format_decimal(data_in.ravel().tolist())
data_out_formatted = format_decimal(result[0].ravel().tolist())
DATA['wrappers.TimeDistributed.1'] = {
'input': {'data': data_in_formatted, 'shape': data_in_shape},
'weights': [{'data': format_decimal(w.ravel().tolist()), 'shape': w.shape} for w in weights],
'expected': {'data': data_out_formatted, 'shape': data_out_shape}
}
In [6]:
import os
filename = '../../../test/data/layers/wrappers/TimeDistributed.json'
if not os.path.exists(os.path.dirname(filename)):
os.makedirs(os.path.dirname(filename))
with open(filename, 'w') as f:
json.dump(DATA, f)
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print(json.dumps(DATA))
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