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DL_CFAR_model_summary.txt
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DL_CFAR_model_summary.txt
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Using TensorFlow backend.
2022-05-18 13:47:09.658251: I C:\tf_jenkins\workspace\rel-win\M\windows\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:140]
Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) (None, 16, 16, 1) 0
__________________________________________________________________________________________________
conv2d_1 (Conv2D) (None, 16, 16, 32) 288 input_1[0][0]
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 16, 16, 32) 128 conv2d_1[0][0]
__________________________________________________________________________________________________
p_re_lu_1 (PReLU) (None, 16, 16, 32) 8192 batch_normalization_1[0][0]
__________________________________________________________________________________________________
conv2d_2 (Conv2D) (None, 16, 16, 16) 4608 p_re_lu_1[0][0]
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 16, 16, 16) 64 conv2d_2[0][0]
__________________________________________________________________________________________________
p_re_lu_2 (PReLU) (None, 16, 16, 16) 4096 batch_normalization_2[0][0]
__________________________________________________________________________________________________
conv2d_3 (Conv2D) (None, 16, 16, 8) 1152 p_re_lu_2[0][0]
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 16, 16, 8) 32 conv2d_3[0][0]
__________________________________________________________________________________________________
p_re_lu_3 (PReLU) (None, 16, 16, 8) 2048 batch_normalization_3[0][0]
__________________________________________________________________________________________________
conv2d_4 (Conv2D) (None, 16, 16, 1) 72 p_re_lu_3[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 16, 16, 1) 4 conv2d_4[0][0]
__________________________________________________________________________________________________
p_re_lu_4 (PReLU) (None, 16, 16, 1) 256 batch_normalization_4[0][0]
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 16, 16, 1) 4 p_re_lu_4[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, 16, 16, 1) 0 input_1[0][0]
batch_normalization_5[0][0]
__________________________________________________________________________________________________
p_re_lu_5 (PReLU) (None, 16, 16, 1) 256 add_1[0][0]
__________________________________________________________________________________________________
conv2d_5 (Conv2D) (None, 16, 16, 32) 288 p_re_lu_5[0][0]
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 16, 16, 32) 128 conv2d_5[0][0]
__________________________________________________________________________________________________
p_re_lu_6 (PReLU) (None, 16, 16, 32) 8192 batch_normalization_6[0][0]
__________________________________________________________________________________________________
conv2d_6 (Conv2D) (None, 16, 16, 16) 4608 p_re_lu_6[0][0]
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 16, 16, 16) 64 conv2d_6[0][0]
__________________________________________________________________________________________________
p_re_lu_7 (PReLU) (None, 16, 16, 16) 4096 batch_normalization_7[0][0]
__________________________________________________________________________________________________
conv2d_7 (Conv2D) (None, 16, 16, 8) 1152 p_re_lu_7[0][0]
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 16, 16, 8) 32 conv2d_7[0][0]
__________________________________________________________________________________________________
p_re_lu_8 (PReLU) (None, 16, 16, 8) 2048 batch_normalization_8[0][0]
__________________________________________________________________________________________________
conv2d_8 (Conv2D) (None, 16, 16, 1) 72 p_re_lu_8[0][0]
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, 16, 16, 1) 4 conv2d_8[0][0]
__________________________________________________________________________________________________
p_re_lu_9 (PReLU) (None, 16, 16, 1) 256 batch_normalization_9[0][0]
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, 16, 16, 1) 4 p_re_lu_9[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, 16, 16, 1) 0 p_re_lu_5[0][0]
batch_normalization_10[0][0]
__________________________________________________________________________________________________
p_re_lu_10 (PReLU) (None, 16, 16, 1) 256 add_2[0][0]
__________________________________________________________________________________________________
flatten_1 (Flatten) (None, 256) 0 p_re_lu_10[0][0]
__________________________________________________________________________________________________
dense_1 (Dense) (None, 512) 131584 flatten_1[0][0]
__________________________________________________________________________________________________
dense_2 (Dense) (None, 256) 131328 dense_1[0][0]
==================================================================================================
Total params: 305,312
Trainable params: 305,080
Non-trainable params: 232
__________________________________________________________________________________________________