Created
August 3, 2020 20:22
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from tensorflow import keras | |
import numpy as np | |
from IPython import embed | |
INPUT_SHAPE = (3, 3, 1) | |
CONV_SIZE = 3 | |
model_name = 'test_model' | |
def create_model(): | |
sub_image = keras.layers.Input(shape=INPUT_SHAPE, name="image") | |
c2d=keras.layers.Conv2D(1, (CONV_SIZE, CONV_SIZE), use_bias=False, name="C2D")(sub_image) | |
output = keras.layers.Dense(1, name="action",use_bias=False,trainable=False)(c2d) | |
model = keras.models.Model(inputs=sub_image, outputs=output, name=model_name) | |
return model | |
input = np.ones((1, 3, 3, 1), dtype=np.float) | |
embed() | |
model = create_model() | |
result = model(input) | |
hl1_weights = model.layers[1].get_weights() | |
print(np.sum(hl1_weights)) | |
hl2_weights = model.layers[2].get_weights() | |
print(np.sum(hl2_weights)) | |
print(np.sum(hl1_weights) * np.sum(hl2_weights)) | |
print(f'tf run sum={result}') |
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