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mobilenet_model.txt
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mobilenet_model.txt
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Model: "model_10"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_11 (InputLayer) [(None, 32, 32, 3)] 0
quantize_layer_9 (QuantizeL (None, 32, 32, 3) 3
ayer)
quant_conv1 (QuantizeWrappe (None, 16, 16, 32) 929
rV2)
quant_conv1_bn (QuantizeWra (None, 16, 16, 32) 129
pperV2)
quant_conv1_relu (QuantizeW (None, 16, 16, 32) 3
rapperV2)
quant_conv_dw_1 (QuantizeWr (None, 16, 16, 32) 291
apperV2)
quant_conv_dw_1_bn (Quantiz (None, 16, 16, 32) 129
eWrapperV2)
quant_conv_dw_1_relu (Quant (None, 16, 16, 32) 3
izeWrapperV2)
quant_conv_pw_1 (QuantizeWr (None, 16, 16, 64) 2177
apperV2)
quant_conv_pw_1_bn (Quantiz (None, 16, 16, 64) 257
eWrapperV2)
quant_conv_pw_1_relu (Quant (None, 16, 16, 64) 3
izeWrapperV2)
quant_conv_pad_2 (QuantizeW (None, 17, 17, 64) 1
rapperV2)
quant_conv_dw_2 (QuantizeWr (None, 8, 8, 64) 579
apperV2)
quant_conv_dw_2_bn (Quantiz (None, 8, 8, 64) 257
eWrapperV2)
quant_conv_dw_2_relu (Quant (None, 8, 8, 64) 3
izeWrapperV2)
quant_conv_pw_2 (QuantizeWr (None, 8, 8, 128) 8449
apperV2)
quant_conv_pw_2_bn (Quantiz (None, 8, 8, 128) 513
eWrapperV2)
quant_conv_pw_2_relu (Quant (None, 8, 8, 128) 3
izeWrapperV2)
quant_conv_dw_3 (QuantizeWr (None, 8, 8, 128) 1155
apperV2)
quant_conv_dw_3_bn (Quantiz (None, 8, 8, 128) 513
eWrapperV2)
quant_conv_dw_3_relu (Quant (None, 8, 8, 128) 3
izeWrapperV2)
quant_conv_pw_3 (QuantizeWr (None, 8, 8, 128) 16641
apperV2)
quant_conv_pw_3_bn (Quantiz (None, 8, 8, 128) 513
eWrapperV2)
quant_conv_pw_3_relu (Quant (None, 8, 8, 128) 3
izeWrapperV2)
quant_conv_pad_4 (QuantizeW (None, 9, 9, 128) 1
rapperV2)
quant_conv_dw_4 (QuantizeWr (None, 4, 4, 128) 1155
apperV2)
quant_conv_dw_4_bn (Quantiz (None, 4, 4, 128) 513
eWrapperV2)
quant_conv_dw_4_relu (Quant (None, 4, 4, 128) 3
izeWrapperV2)
quant_conv_pw_4 (QuantizeWr (None, 4, 4, 256) 33281
apperV2)
quant_conv_pw_4_bn (Quantiz (None, 4, 4, 256) 1025
eWrapperV2)
quant_conv_pw_4_relu (Quant (None, 4, 4, 256) 3
izeWrapperV2)
quant_conv_dw_5 (QuantizeWr (None, 4, 4, 256) 2307
apperV2)
quant_conv_dw_5_bn (Quantiz (None, 4, 4, 256) 1025
eWrapperV2)
quant_conv_dw_5_relu (Quant (None, 4, 4, 256) 3
izeWrapperV2)
quant_conv_pw_5 (QuantizeWr (None, 4, 4, 256) 66049
apperV2)
quant_conv_pw_5_bn (Quantiz (None, 4, 4, 256) 1025
eWrapperV2)
quant_conv_pw_5_relu (Quant (None, 4, 4, 256) 3
izeWrapperV2)
quant_conv_pad_6 (QuantizeW (None, 5, 5, 256) 1
rapperV2)
quant_conv_dw_6 (QuantizeWr (None, 2, 2, 256) 2307
apperV2)
quant_conv_dw_6_bn (Quantiz (None, 2, 2, 256) 1025
eWrapperV2)
quant_conv_dw_6_relu (Quant (None, 2, 2, 256) 3
izeWrapperV2)
quant_conv_pw_6 (QuantizeWr (None, 2, 2, 512) 132097
apperV2)
quant_conv_pw_6_bn (Quantiz (None, 2, 2, 512) 2049
eWrapperV2)
quant_conv_pw_6_relu (Quant (None, 2, 2, 512) 3
izeWrapperV2)
quant_conv_dw_7 (QuantizeWr (None, 2, 2, 512) 4611
apperV2)
quant_conv_dw_7_bn (Quantiz (None, 2, 2, 512) 2049
eWrapperV2)
quant_conv_dw_7_relu (Quant (None, 2, 2, 512) 3
izeWrapperV2)
quant_conv_pw_7 (QuantizeWr (None, 2, 2, 512) 263169
apperV2)
quant_conv_pw_7_bn (Quantiz (None, 2, 2, 512) 2049
eWrapperV2)
quant_conv_pw_7_relu (Quant (None, 2, 2, 512) 3
izeWrapperV2)
quant_conv_dw_8 (QuantizeWr (None, 2, 2, 512) 4611
apperV2)
quant_conv_dw_8_bn (Quantiz (None, 2, 2, 512) 2049
eWrapperV2)
quant_conv_dw_8_relu (Quant (None, 2, 2, 512) 3
izeWrapperV2)
quant_conv_pw_8 (QuantizeWr (None, 2, 2, 512) 263169
apperV2)
quant_conv_pw_8_bn (Quantiz (None, 2, 2, 512) 2049
eWrapperV2)
quant_conv_pw_8_relu (Quant (None, 2, 2, 512) 3
izeWrapperV2)
quant_conv_dw_9 (QuantizeWr (None, 2, 2, 512) 4611
apperV2)
quant_conv_dw_9_bn (Quantiz (None, 2, 2, 512) 2049
eWrapperV2)
quant_conv_dw_9_relu (Quant (None, 2, 2, 512) 3
izeWrapperV2)
quant_conv_pw_9 (QuantizeWr (None, 2, 2, 512) 263169
apperV2)
quant_conv_pw_9_bn (Quantiz (None, 2, 2, 512) 2049
eWrapperV2)
quant_conv_pw_9_relu (Quant (None, 2, 2, 512) 3
izeWrapperV2)
quant_conv_dw_10 (QuantizeW (None, 2, 2, 512) 4611
rapperV2)
quant_conv_dw_10_bn (Quanti (None, 2, 2, 512) 2049
zeWrapperV2)
quant_conv_dw_10_relu (Quan (None, 2, 2, 512) 3
tizeWrapperV2)
quant_conv_pw_10 (QuantizeW (None, 2, 2, 512) 263169
rapperV2)
quant_conv_pw_10_bn (Quanti (None, 2, 2, 512) 2049
zeWrapperV2)
quant_conv_pw_10_relu (Quan (None, 2, 2, 512) 3
tizeWrapperV2)
quant_conv_dw_11 (QuantizeW (None, 2, 2, 512) 4611
rapperV2)
quant_conv_dw_11_bn (Quanti (None, 2, 2, 512) 2049
zeWrapperV2)
quant_conv_dw_11_relu (Quan (None, 2, 2, 512) 3
tizeWrapperV2)
quant_conv_pw_11 (QuantizeW (None, 2, 2, 512) 263169
rapperV2)
quant_conv_pw_11_bn (Quanti (None, 2, 2, 512) 2049
zeWrapperV2)
quant_conv_pw_11_relu (Quan (None, 2, 2, 512) 3
tizeWrapperV2)
quant_conv_pad_12 (Quantize (None, 3, 3, 512) 1
WrapperV2)
quant_conv_dw_12 (QuantizeW (None, 1, 1, 512) 4611
rapperV2)
quant_conv_dw_12_bn (Quanti (None, 1, 1, 512) 2049
zeWrapperV2)
quant_conv_dw_12_relu (Quan (None, 1, 1, 512) 3
tizeWrapperV2)
quant_conv_pw_12 (QuantizeW (None, 1, 1, 1024) 526337
rapperV2)
quant_conv_pw_12_bn (Quanti (None, 1, 1, 1024) 4097
zeWrapperV2)
quant_conv_pw_12_relu (Quan (None, 1, 1, 1024) 3
tizeWrapperV2)
quant_conv_dw_13 (QuantizeW (None, 1, 1, 1024) 9219
rapperV2)
quant_conv_dw_13_bn (Quanti (None, 1, 1, 1024) 4097
zeWrapperV2)
quant_conv_dw_13_relu (Quan (None, 1, 1, 1024) 3
tizeWrapperV2)
quant_conv_pw_13 (QuantizeW (None, 1, 1, 1024) 1050625
rapperV2)
quant_conv_pw_13_bn (Quanti (None, 1, 1, 1024) 4097
zeWrapperV2)
quant_conv_pw_13_relu (Quan (None, 1, 1, 1024) 3
tizeWrapperV2)
quant_global_average_poolin (None, 1024) 3
g2d_10 (QuantizeWrapperV2)
quant_dropout_10 (QuantizeW (None, 1024) 1
rapperV2)
quant_dense_11 (QuantizeWra (None, 10) 10255
pperV2)
=================================================================
Total params: 3,251,259
Trainable params: 3,217,226
Non-trainable params: 34,033
_________________________________________________________________