FLOPs全称是floating point operations的缩写，翻译过来是浮点运算数，理解为计算量，常用来衡量算法或深度学习模型的计算复杂度。
关于计算FLOPs值的函数，网上相关的博客很多，但是能用的很少，下面这个函数是我实际使用过可行的函数，用来计算keras模型的FLOPs值。
方法一：
import tensorflow as tf
tf. compat. v1. disable_eager_execution( )
print ( tf. __version__)
def get_flops_params ( ) :
sess = tf. compat. v1. Session( )
graph = sess. graph
flops = tf. compat. v1. profiler. profile( graph, options= tf. compat. v1. profiler. ProfileOptionBuilder. float_operation( ) )
params = tf. compat. v1. profiler. profile( graph, options= tf. compat. v1. profiler. ProfileOptionBuilder. trainable_variables_parameter( ) )
print ( 'FLOPs: {}; Trainable params: {}' . format ( flops. total_float_ops, params. total_parameters) )
def stats_graph ( graph) :
flops = tf. compat. v1. profiler. profile( graph, options= tf. compat. v1. profiler. ProfileOptionBuilder. float_operation( ) )
params = tf. compat. v1. profiler. profile( graph, options= tf. compat. v1. profiler. ProfileOptionBuilder. trainable_variables_parameter( ) )
print ( 'FLOPs: {}; Trainable params: {}' . format ( flops. total_float_ops, params. total_parameters) )
def get_flops ( model) :
run_meta = tf. compat. v1. RunMetadata( )
opts = tf. compat. v1. profiler. ProfileOptionBuilder. float_operation( )
flops = tf. compat. v1. profiler. profile( graph= tf. compat. v1. keras. backend. get_session( ) . graph, run_meta= run_meta, cmd= 'op' , options= opts)
return flops. total_float_ops
from tensorflow. keras. layers import Conv2D, MaxPooling2D, Flatten, Dense
from tensorflow. keras. models import Sequential
model = Sequential( )
model. add( Conv2D( filters= 64 , kernel_size= ( 3 , 3 ) , input_shape= ( 28 , 28 , 1 ) , activation= 'relu' ) )
model. add( MaxPooling2D( pool_size= ( 2 , 2 ) ) )
model. add( Flatten( ) )
model. add( Dense( units= 100 , activation= 'relu' ) )
model. add( Dense( units= 10 , activation= 'softmax' ) )
model. summary( )
get_flops_params( )
此代码情况下，实测MobileNetv2计算量误差较大：
2021 - 04 - 18 21 : 17 : 58.053772 : I tensorflow/ core/ platform/ cpu_feature_guard. cc: 142 ] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library ( oneDNN) to use the following CPU instructions in performance- critical operations: AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021 - 04 - 18 21 : 17 : 58.054691 : I tensorflow/ core/ common_runtime/ gpu/ gpu_device. cc: 1261 ] Device interconnect StreamExecutor with strength 1 edge matrix:
2021 - 04 - 18 21 : 17 : 58.054932 : I tensorflow/ core/ common_runtime/ gpu/ gpu_device. cc: 1267 ]
2021 - 04 - 18 21 : 17 : 58.055070 : I tensorflow/ compiler/ jit/ xla_gpu_device. cc: 99 ] Not creating XLA devices, tf_xla_enable_xla_devices not set
WARNING: tensorflow: From D: \Anaconda3\envs\wen\lib\site- packages\tensorflow\python\profiler\internal\flops_registry. py: 142 : tensor_shape_from_node_def_name ( from tensorflow. python. framework. graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf. compat. v1. graph_util. tensor_shape_from_node_def_name`
[ 0418 21 : 17 : 58 ] From D: \Anaconda3\envs\wen\lib\site- packages\tensorflow\python\profiler\internal\flops_registry. py: 142 : tensor_shape_from_node_def_name ( from tensorflow. python. framework. graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf. compat. v1. graph_util. tensor_shape_from_node_def_name`
62 ops no flops stats due to incomplete shapes.
Incomplete shape.
Incomplete shape.
Incomplete shape.
Incomplete shape.
== == == == == == == == == == == == = Options== == == == == == == == == == == == == == =
- max_depth 10000
- min_bytes 0
- min_peak_bytes 0
- min_residual_bytes 0
- min_output_bytes 0
- min_micros 0
- min_accelerator_micros 0
- min_cpu_micros 0
- min_params 0
- min_float_ops 1
- min_occurrence 0
- step - 1
- order_by float_ops
- account_type_regexes . *
- start_name_regexes . *
- trim_name_regexes
- show_name_regexes . *
- hide_name_regexes
- account_displayed_op_only true
- select float_ops
- output stdout:
== == == == == == == == == Model Analysis Report== == == == == == == == == == ==
Doc:
scope: The nodes in the model graph are organized by their names, which is hierarchical like filesystem.
flops: Number of float operations. Note: Please read the implementation for the math behind it.
Profile:
node name | # float_ops
_TFProfRoot ( -- / 7.01 m flops)
predictions/ kernel/ Initializer/ random_uniform ( 1.28 m/ 2.56 m flops)
predictions/ kernel/ Initializer/ random_uniform/ mul ( 1.28 m/ 1.28 m flops)
predictions/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
Conv_1/ kernel/ Initializer/ random_uniform ( 409.60 k/ 819.20 k flops)
Conv_1/ kernel/ Initializer/ random_uniform/ mul ( 409.60 k/ 409.60 k flops)
Conv_1/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_16_project/ kernel/ Initializer/ random_uniform ( 307.20 k/ 614.40 k flops)
block_16_project/ kernel/ Initializer/ random_uniform/ mul ( 307.20 k/ 307.20 k flops)
block_16_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_14_project/ kernel/ Initializer/ random_uniform ( 153.60 k/ 307.20 k flops)
block_14_project/ kernel/ Initializer/ random_uniform/ mul ( 153.60 k/ 153.60 k flops)
block_14_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_14_expand/ kernel/ Initializer/ random_uniform ( 153.60 k/ 307.20 k flops)
block_14_expand/ kernel/ Initializer/ random_uniform/ mul ( 153.60 k/ 153.60 k flops)
block_14_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_15_project/ kernel/ Initializer/ random_uniform ( 153.60 k/ 307.20 k flops)
block_15_project/ kernel/ Initializer/ random_uniform/ mul ( 153.60 k/ 153.60 k flops)
block_15_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_15_expand/ kernel/ Initializer/ random_uniform ( 153.60 k/ 307.20 k flops)
block_15_expand/ kernel/ Initializer/ random_uniform/ mul ( 153.60 k/ 153.60 k flops)
block_15_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_16_expand/ kernel/ Initializer/ random_uniform ( 153.60 k/ 307.20 k flops)
block_16_expand/ kernel/ Initializer/ random_uniform/ mul ( 153.60 k/ 153.60 k flops)
block_16_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_13_project/ kernel/ Initializer/ random_uniform ( 92.16 k/ 184.32 k flops)
block_13_project/ kernel/ Initializer/ random_uniform/ mul ( 92.16 k/ 92.16 k flops)
block_13_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_12_project/ kernel/ Initializer/ random_uniform ( 55.30 k/ 110.59 k flops)
block_12_project/ kernel/ Initializer/ random_uniform/ mul ( 55.30 k/ 55.30 k flops)
block_12_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_13_expand/ kernel/ Initializer/ random_uniform ( 55.30 k/ 110.59 k flops)
block_13_expand/ kernel/ Initializer/ random_uniform/ mul ( 55.30 k/ 55.30 k flops)
block_13_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_12_expand/ kernel/ Initializer/ random_uniform ( 55.30 k/ 110.59 k flops)
block_12_expand/ kernel/ Initializer/ random_uniform/ mul ( 55.30 k/ 55.30 k flops)
block_12_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_11_expand/ kernel/ Initializer/ random_uniform ( 55.30 k/ 110.59 k flops)
block_11_expand/ kernel/ Initializer/ random_uniform/ mul ( 55.30 k/ 55.30 k flops)
block_11_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_11_project/ kernel/ Initializer/ random_uniform ( 55.30 k/ 110.59 k flops)
block_11_project/ kernel/ Initializer/ random_uniform/ mul ( 55.30 k/ 55.30 k flops)
block_11_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_10_project/ kernel/ Initializer/ random_uniform ( 36.86 k/ 73.73 k flops)
block_10_project/ kernel/ Initializer/ random_uniform/ mul ( 36.86 k/ 36.86 k flops)
block_10_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_8_expand/ kernel/ Initializer/ random_uniform ( 24.58 k/ 49.15 k flops)
block_8_expand/ kernel/ Initializer/ random_uniform/ mul ( 24.58 k/ 24.58 k flops)
block_8_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_8_project/ kernel/ Initializer/ random_uniform ( 24.58 k/ 49.15 k flops)
block_8_project/ kernel/ Initializer/ random_uniform/ mul ( 24.58 k/ 24.58 k flops)
block_8_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_9_expand/ kernel/ Initializer/ random_uniform ( 24.58 k/ 49.15 k flops)
block_9_expand/ kernel/ Initializer/ random_uniform/ mul ( 24.58 k/ 24.58 k flops)
block_9_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_7_project/ kernel/ Initializer/ random_uniform ( 24.58 k/ 49.15 k flops)
block_7_project/ kernel/ Initializer/ random_uniform/ mul ( 24.58 k/ 24.58 k flops)
block_7_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_9_project/ kernel/ Initializer/ random_uniform ( 24.58 k/ 49.15 k flops)
block_9_project/ kernel/ Initializer/ random_uniform/ mul ( 24.58 k/ 24.58 k flops)
block_9_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_7_expand/ kernel/ Initializer/ random_uniform ( 24.58 k/ 49.15 k flops)
block_7_expand/ kernel/ Initializer/ random_uniform/ mul ( 24.58 k/ 24.58 k flops)
block_7_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_10_expand/ kernel/ Initializer/ random_uniform ( 24.58 k/ 49.15 k flops)
block_10_expand/ kernel/ Initializer/ random_uniform/ mul ( 24.58 k/ 24.58 k flops)
block_10_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_6_project/ kernel/ Initializer/ random_uniform ( 12.29 k/ 24.58 k flops)
block_6_project/ kernel/ Initializer/ random_uniform/ mul ( 12.29 k/ 12.29 k flops)
block_6_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_15_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 8.64 k/ 17.28 k flops)
block_15_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 8.64 k/ 8.64 k flops)
block_15_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_16_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 8.64 k/ 17.28 k flops)
block_16_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 8.64 k/ 8.64 k flops)
block_16_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_14_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 8.64 k/ 17.28 k flops)
block_14_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 8.64 k/ 8.64 k flops)
block_14_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_6_expand/ kernel/ Initializer/ random_uniform ( 6.14 k/ 12.29 k flops)
block_6_expand/ kernel/ Initializer/ random_uniform/ mul ( 6.14 k/ 6.14 k flops)
block_6_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_4_project/ kernel/ Initializer/ random_uniform ( 6.14 k/ 12.29 k flops)
block_4_project/ kernel/ Initializer/ random_uniform/ mul ( 6.14 k/ 6.14 k flops)
block_4_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_5_expand/ kernel/ Initializer/ random_uniform ( 6.14 k/ 12.29 k flops)
block_5_expand/ kernel/ Initializer/ random_uniform/ mul ( 6.14 k/ 6.14 k flops)
block_5_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_5_project/ kernel/ Initializer/ random_uniform ( 6.14 k/ 12.29 k flops)
block_5_project/ kernel/ Initializer/ random_uniform/ mul ( 6.14 k/ 6.14 k flops)
block_5_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_4_expand/ kernel/ Initializer/ random_uniform ( 6.14 k/ 12.29 k flops)
block_4_expand/ kernel/ Initializer/ random_uniform/ mul ( 6.14 k/ 6.14 k flops)
block_4_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_12_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 5.18 k/ 10.37 k flops)
block_12_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 5.18 k/ 5.18 k flops)
block_12_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_11_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 5.18 k/ 10.37 k flops)
block_11_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 5.18 k/ 5.18 k flops)
block_11_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_13_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 5.18 k/ 10.37 k flops)
block_13_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 5.18 k/ 5.18 k flops)
block_13_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_3_project/ kernel/ Initializer/ random_uniform ( 4.61 k/ 9.22 k flops)
block_3_project/ kernel/ Initializer/ random_uniform/ mul ( 4.61 k/ 4.61 k flops)
block_3_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_2_expand/ kernel/ Initializer/ random_uniform ( 3.46 k/ 6.91 k flops)
block_2_expand/ kernel/ Initializer/ random_uniform/ mul ( 3.46 k/ 3.46 k flops)
block_2_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_10_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 3.46 k/ 6.91 k flops)
block_10_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 3.46 k/ 3.46 k flops)
block_10_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_2_project/ kernel/ Initializer/ random_uniform ( 3.46 k/ 6.91 k flops)
block_2_project/ kernel/ Initializer/ random_uniform/ mul ( 3.46 k/ 3.46 k flops)
block_2_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_7_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 3.46 k/ 6.91 k flops)
block_7_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 3.46 k/ 3.46 k flops)
block_7_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_8_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 3.46 k/ 6.91 k flops)
block_8_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 3.46 k/ 3.46 k flops)
block_8_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_3_expand/ kernel/ Initializer/ random_uniform ( 3.46 k/ 6.91 k flops)
block_3_expand/ kernel/ Initializer/ random_uniform/ mul ( 3.46 k/ 3.46 k flops)
block_3_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_9_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 3.46 k/ 6.91 k flops)
block_9_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 3.46 k/ 3.46 k flops)
block_9_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_1_project/ kernel/ Initializer/ random_uniform ( 2.30 k/ 4.61 k flops)
block_1_project/ kernel/ Initializer/ random_uniform/ mul ( 2.30 k/ 2.30 k flops)
block_1_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_5_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1.73 k/ 3.46 k flops)
block_5_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1.73 k/ 1.73 k flops)
block_5_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_4_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1.73 k/ 3.46 k flops)
block_4_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1.73 k/ 1.73 k flops)
block_4_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_6_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1.73 k/ 3.46 k flops)
block_6_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1.73 k/ 1.73 k flops)
block_6_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_1_expand/ kernel/ Initializer/ random_uniform ( 1.54 k/ 3.07 k flops)
block_1_expand/ kernel/ Initializer/ random_uniform/ mul ( 1.54 k/ 1.54 k flops)
block_1_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_2_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1.30 k/ 2.59 k flops)
block_2_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1.30 k/ 1.30 k flops)
block_2_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_3_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1.30 k/ 2.59 k flops)
block_3_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1.30 k/ 1.30 k flops)
block_3_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
Conv1/ kernel/ Initializer/ random_uniform ( 864 / 1.73 k flops)
Conv1/ kernel/ Initializer/ random_uniform/ mul ( 864 / 864 flops)
Conv1/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_1_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 864 / 1.73 k flops)
block_1_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 864 / 864 flops)
block_1_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
Conv_1_bn/ AssignMovingAvg/ mul ( 1.28 k/ 1.28 k flops)
Conv_1_bn/ AssignMovingAvg/ sub_1 ( 1.28 k/ 1.28 k flops)
Conv_1_bn/ AssignMovingAvg_1/ mul ( 1.28 k/ 1.28 k flops)
Conv_1_bn/ AssignMovingAvg_1/ sub_1 ( 1.28 k/ 1.28 k flops)
expanded_conv_project/ kernel/ Initializer/ random_uniform ( 512 / 1.02 k flops)
expanded_conv_project/ kernel/ Initializer/ random_uniform/ mul ( 512 / 512 flops)
expanded_conv_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_15_depthwise_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_15_expand_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_15_depthwise_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_14_depthwise_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_15_expand_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_14_depthwise_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_14_depthwise_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_14_expand_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_14_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_15_depthwise_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_14_expand_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_14_expand_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_15_expand_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_14_expand_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_15_expand_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_15_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_16_expand_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_16_depthwise_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_16_depthwise_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_16_depthwise_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_16_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_16_expand_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_16_expand_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_16_expand_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
expanded_conv_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 288 / 577 flops)
expanded_conv_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 288 / 288 flops)
expanded_conv_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_13_expand_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_13_expand_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_13_expand_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_12_depthwise_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_12_depthwise_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_12_depthwise_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_11_depthwise_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_12_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_13_depthwise_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_11_depthwise_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_11_depthwise_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_11_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_11_expand_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_11_expand_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_13_depthwise_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_11_expand_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_13_depthwise_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_11_expand_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_13_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_13_expand_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_12_expand_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_12_expand_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_12_expand_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_12_expand_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_8_expand_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_8_expand_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_8_expand_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_8_expand_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_8_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_7_depthwise_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_7_depthwise_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_7_depthwise_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_9_expand_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_7_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_10_depthwise_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_10_depthwise_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_7_expand_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_10_depthwise_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_10_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_10_expand_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_10_expand_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_10_expand_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_10_expand_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_9_expand_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_9_expand_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_7_expand_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_7_expand_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_9_expand_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_7_expand_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_8_depthwise_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_9_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_8_depthwise_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_9_depthwise_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_9_depthwise_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_8_depthwise_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_9_depthwise_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_16_project_BN/ AssignMovingAvg_1/ sub_1 ( 320 / 320 flops)
block_16_project_BN/ AssignMovingAvg_1/ mul ( 320 / 320 flops)
block_16_project_BN/ AssignMovingAvg/ sub_1 ( 320 / 320 flops)
block_16_project_BN/ AssignMovingAvg/ mul ( 320 / 320 flops)
block_4_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_5_expand_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_6_expand_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_4_depthwise_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_6_depthwise_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_5_expand_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_6_expand_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_6_expand_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_5_expand_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_6_depthwise_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_4_depthwise_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_5_expand_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_4_depthwise_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_6_expand_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_5_depthwise_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_5_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_6_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_5_depthwise_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_5_depthwise_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_6_depthwise_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_4_expand_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_4_expand_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_4_expand_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_4_expand_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_14_project_BN/ AssignMovingAvg/ sub_1 ( 160 / 160 flops)
block_14_project_BN/ AssignMovingAvg/ mul ( 160 / 160 flops)
block_13_project_BN/ AssignMovingAvg/ mul ( 160 / 160 flops)
block_13_project_BN/ AssignMovingAvg_1/ sub_1 ( 160 / 160 flops)
block_13_project_BN/ AssignMovingAvg/ sub_1 ( 160 / 160 flops)
block_15_project_BN/ AssignMovingAvg/ mul ( 160 / 160 flops)
block_13_project_BN/ AssignMovingAvg_1/ mul ( 160 / 160 flops)
block_15_project_BN/ AssignMovingAvg/ sub_1 ( 160 / 160 flops)
block_14_project_BN/ AssignMovingAvg_1/ sub_1 ( 160 / 160 flops)
block_15_project_BN/ AssignMovingAvg_1/ sub_1 ( 160 / 160 flops)
block_14_project_BN/ AssignMovingAvg_1/ mul ( 160 / 160 flops)
block_15_project_BN/ AssignMovingAvg_1/ mul ( 160 / 160 flops)
block_3_expand_BN/ AssignMovingAvg/ sub_1 ( 144 / 144 flops)
block_3_expand_BN/ AssignMovingAvg_1/ mul ( 144 / 144 flops)
block_3_expand_BN/ AssignMovingAvg_1/ sub_1 ( 144 / 144 flops)
block_2_depthwise_BN/ AssignMovingAvg/ mul ( 144 / 144 flops)
block_2_depthwise_BN/ AssignMovingAvg/ sub_1 ( 144 / 144 flops)
block_2_depthwise_BN/ AssignMovingAvg_1/ mul ( 144 / 144 flops)
block_2_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 144 / 144 flops)
block_2_expand_BN/ AssignMovingAvg/ mul ( 144 / 144 flops)
block_2_expand_BN/ AssignMovingAvg/ sub_1 ( 144 / 144 flops)
block_2_expand_BN/ AssignMovingAvg_1/ mul ( 144 / 144 flops)
block_2_expand_BN/ AssignMovingAvg_1/ sub_1 ( 144 / 144 flops)
block_3_depthwise_BN/ AssignMovingAvg/ mul ( 144 / 144 flops)
block_3_depthwise_BN/ AssignMovingAvg/ sub_1 ( 144 / 144 flops)
block_3_depthwise_BN/ AssignMovingAvg_1/ mul ( 144 / 144 flops)
block_3_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 144 / 144 flops)
block_3_expand_BN/ AssignMovingAvg/ mul ( 144 / 144 flops)
block_1_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_1_expand_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_1_depthwise_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_11_project_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_1_expand_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_12_project_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_11_project_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_1_expand_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_11_project_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_1_depthwise_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_11_project_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_12_project_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_12_project_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_1_expand_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_12_project_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_1_depthwise_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_10_project_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_10_project_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_10_project_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_10_project_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_6_project_BN/ AssignMovingAvg/ mul ( 64 / 64 flops)
block_6_project_BN/ AssignMovingAvg/ sub_1 ( 64 / 64 flops)
block_7_project_BN/ AssignMovingAvg/ mul ( 64 / 64 flops)
block_7_project_BN/ AssignMovingAvg_1/ sub_1 ( 64 / 64 flops)
block_8_project_BN/ AssignMovingAvg/ mul ( 64 / 64 flops)
block_8_project_BN/ AssignMovingAvg/ sub_1 ( 64 / 64 flops)
block_8_project_BN/ AssignMovingAvg_1/ mul ( 64 / 64 flops)
block_8_project_BN/ AssignMovingAvg_1/ sub_1 ( 64 / 64 flops)
block_7_project_BN/ AssignMovingAvg_1/ mul ( 64 / 64 flops)
block_7_project_BN/ AssignMovingAvg/ sub_1 ( 64 / 64 flops)
block_6_project_BN/ AssignMovingAvg_1/ sub_1 ( 64 / 64 flops)
block_6_project_BN/ AssignMovingAvg_1/ mul ( 64 / 64 flops)
block_9_project_BN/ AssignMovingAvg/ mul ( 64 / 64 flops)
block_9_project_BN/ AssignMovingAvg/ sub_1 ( 64 / 64 flops)
block_9_project_BN/ AssignMovingAvg_1/ mul ( 64 / 64 flops)
block_9_project_BN/ AssignMovingAvg_1/ sub_1 ( 64 / 64 flops)
block_5_project_BN/ AssignMovingAvg/ mul ( 32 / 32 flops)
block_4_project_BN/ AssignMovingAvg/ mul ( 32 / 32 flops)
block_5_project_BN/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
block_4_project_BN/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
bn_Conv1/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
block_4_project_BN/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
block_5_project_BN/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
block_4_project_BN/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
block_3_project_BN/ AssignMovingAvg/ mul ( 32 / 32 flops)
block_3_project_BN/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
block_3_project_BN/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
block_3_project_BN/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
block_5_project_BN/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
bn_Conv1/ AssignMovingAvg/ mul ( 32 / 32 flops)
bn_Conv1/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
bn_Conv1/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg/ mul ( 32 / 32 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
block_1_project_BN/ AssignMovingAvg/ mul ( 24 / 24 flops)
block_2_project_BN/ AssignMovingAvg/ mul ( 24 / 24 flops)
block_1_project_BN/ AssignMovingAvg/ sub_1 ( 24 / 24 flops)
block_2_project_BN/ AssignMovingAvg_1/ sub_1 ( 24 / 24 flops)
block_1_project_BN/ AssignMovingAvg_1/ mul ( 24 / 24 flops)
block_2_project_BN/ AssignMovingAvg_1/ mul ( 24 / 24 flops)
block_2_project_BN/ AssignMovingAvg/ sub_1 ( 24 / 24 flops)
block_1_project_BN/ AssignMovingAvg_1/ sub_1 ( 24 / 24 flops)
expanded_conv_project_BN/ AssignMovingAvg/ mul ( 16 / 16 flops)
expanded_conv_project_BN/ AssignMovingAvg/ sub_1 ( 16 / 16 flops)
expanded_conv_project_BN/ AssignMovingAvg_1/ mul ( 16 / 16 flops)
expanded_conv_project_BN/ AssignMovingAvg_1/ sub_1 ( 16 / 16 flops)
block_16_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_5_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_5_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_15_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_15_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_6_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_15_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_15_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_6_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_15_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_15_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_14_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_6_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_14_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_14_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_6_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_14_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_14_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_14_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_6_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
Conv_1_bn/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_13_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_13_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_13_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_13_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_13_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_13_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_7_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
Conv_1_bn/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_12_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_10_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_2_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_2_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_3_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_2_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_7_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_2_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_12_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_3_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_8_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_12_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_12_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_8_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_12_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_12_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_2_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_8_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_11_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_3_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_8_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_11_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_3_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_2_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_8_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_1_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_3_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_8_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_3_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_11_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_4_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_11_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_11_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_1_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_10_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_4_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_9_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_1_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_10_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_4_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_10_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_1_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_4_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_4_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_4_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_1_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
bn_Conv1/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_11_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_5_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
bn_Conv1/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_1_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_10_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_5_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_16_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_16_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_5_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_10_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_16_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
expanded_conv_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_16_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_5_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
expanded_conv_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_16_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
loss/ mul ( 1 / 1 flops)
loss/ predictions_loss/ softmax_cross_entropy_with_logits/ Sub ( 1 / 1 flops)
loss/ predictions_loss/ softmax_cross_entropy_with_logits/ Sub_1 ( 1 / 1 flops)
loss/ predictions_loss/ softmax_cross_entropy_with_logits/ Sub_2 ( 1 / 1 flops)
block_6_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
== == == == == == == == == == == End of Report== == == == == == == == == == == == ==
62 ops no flops stats due to incomplete shapes.
Incomplete shape.
Incomplete shape.
== == == == == == == == == == == == = Options== == == == == == == == == == == == == == =
- max_depth 10000
- min_bytes 0
- min_peak_bytes 0
- min_residual_bytes 0
- min_output_bytes 0
- min_micros 0
- min_accelerator_micros 0
- min_cpu_micros 0
- min_params 0
- min_float_ops 0
- min_occurrence 0
- step - 1
- order_by name
- account_type_regexes _trainable_variables
- start_name_regexes . *
- trim_name_regexes
- show_name_regexes . *
- hide_name_regexes
- account_displayed_op_only true
- select params
- output stdout:
== == == == == == == == == Model Analysis Report== == == == == == == == == == ==
Doc:
scope: The nodes in the model graph are organized by their names, which is hierarchical like filesystem.
param: Number of parameters ( in the Variable) .
Profile:
node name | # parameters
_TFProfRoot ( -- / 3.50 m params)
Conv1 ( -- / 864 params)
Conv1/ kernel ( 3 x3x3x32, 864 / 864 params)
Conv_1 ( -- / 409.60 k params)
Conv_1/ kernel ( 1 x1x320x1280, 409.60 k/ 409.60 k params)
Conv_1_bn ( -- / 2.56 k params)
Conv_1_bn/ beta ( 1280 , 1.28 k/ 1.28 k params)
Conv_1_bn/ gamma ( 1280 , 1.28 k/ 1.28 k params)
block_10_depthwise ( -- / 3.46 k params)
block_10_depthwise/ depthwise_kernel ( 3 x3x384x1, 3.46 k/ 3.46 k params)
block_10_depthwise_BN ( -- / 768 params)
block_10_depthwise_BN/ beta ( 384 , 384 / 384 params)
block_10_depthwise_BN/ gamma ( 384 , 384 / 384 params)
block_10_expand ( -- / 24.58 k params)
block_10_expand/ kernel ( 1 x1x64x384, 24.58 k/ 24.58 k params)
block_10_expand_BN ( -- / 768 params)
block_10_expand_BN/ beta ( 384 , 384 / 384 params)
block_10_expand_BN/ gamma ( 384 , 384 / 384 params)
block_10_project ( -- / 36.86 k params)
block_10_project/ kernel ( 1 x1x384x96, 36.86 k/ 36.86 k params)
block_10_project_BN ( -- / 192 params)
block_10_project_BN/ beta ( 96 , 96 / 96 params)
block_10_project_BN/ gamma ( 96 , 96 / 96 params)
block_11_depthwise ( -- / 5.18 k params)
block_11_depthwise/ depthwise_kernel ( 3 x3x576x1, 5.18 k/ 5.18 k params)
block_11_depthwise_BN ( -- / 1.15 k params)
block_11_depthwise_BN/ beta ( 576 , 576 / 576 params)
block_11_depthwise_BN/ gamma ( 576 , 576 / 576 params)
block_11_expand ( -- / 55.30 k params)
block_11_expand/ kernel ( 1 x1x96x576, 55.30 k/ 55.30 k params)
block_11_expand_BN ( -- / 1.15 k params)
block_11_expand_BN/ beta ( 576 , 576 / 576 params)
block_11_expand_BN/ gamma ( 576 , 576 / 576 params)
block_11_project ( -- / 55.30 k params)
block_11_project/ kernel ( 1 x1x576x96, 55.30 k/ 55.30 k params)
block_11_project_BN ( -- / 192 params)
block_11_project_BN/ beta ( 96 , 96 / 96 params)
block_11_project_BN/ gamma ( 96 , 96 / 96 params)
block_12_depthwise ( -- / 5.18 k params)
block_12_depthwise/ depthwise_kernel ( 3 x3x576x1, 5.18 k/ 5.18 k params)
block_12_depthwise_BN ( -- / 1.15 k params)
block_12_depthwise_BN/ beta ( 576 , 576 / 576 params)
block_12_depthwise_BN/ gamma ( 576 , 576 / 576 params)
block_12_expand ( -- / 55.30 k params)
block_12_expand/ kernel ( 1 x1x96x576, 55.30 k/ 55.30 k params)
block_12_expand_BN ( -- / 1.15 k params)
block_12_expand_BN/ beta ( 576 , 576 / 576 params)
block_12_expand_BN/ gamma ( 576 , 576 / 576 params)
block_12_project ( -- / 55.30 k params)
block_12_project/ kernel ( 1 x1x576x96, 55.30 k/ 55.30 k params)
block_12_project_BN ( -- / 192 params)
block_12_project_BN/ beta ( 96 , 96 / 96 params)
block_12_project_BN/ gamma ( 96 , 96 / 96 params)
block_13_depthwise ( -- / 5.18 k params)
block_13_depthwise/ depthwise_kernel ( 3 x3x576x1, 5.18 k/ 5.18 k params)
block_13_depthwise_BN ( -- / 1.15 k params)
block_13_depthwise_BN/ beta ( 576 , 576 / 576 params)
block_13_depthwise_BN/ gamma ( 576 , 576 / 576 params)
block_13_expand ( -- / 55.30 k params)
block_13_expand/ kernel ( 1 x1x96x576, 55.30 k/ 55.30 k params)
block_13_expand_BN ( -- / 1.15 k params)
block_13_expand_BN/ beta ( 576 , 576 / 576 params)
block_13_expand_BN/ gamma ( 576 , 576 / 576 params)
block_13_project ( -- / 92.16 k params)
block_13_project/ kernel ( 1 x1x576x160, 92.16 k/ 92.16 k params)
block_13_project_BN ( -- / 320 params)
block_13_project_BN/ beta ( 160 , 160 / 160 params)
block_13_project_BN/ gamma ( 160 , 160 / 160 params)
block_14_depthwise ( -- / 8.64 k params)
block_14_depthwise/ depthwise_kernel ( 3 x3x960x1, 8.64 k/ 8.64 k params)
block_14_depthwise_BN ( -- / 1.92 k params)
block_14_depthwise_BN/ beta ( 960 , 960 / 960 params)
block_14_depthwise_BN/ gamma ( 960 , 960 / 960 params)
block_14_expand ( -- / 153.60 k params)
block_14_expand/ kernel ( 1 x1x160x960, 153.60 k/ 153.60 k params)
block_14_expand_BN ( -- / 1.92 k params)
block_14_expand_BN/ beta ( 960 , 960 / 960 params)
block_14_expand_BN/ gamma ( 960 , 960 / 960 params)
block_14_project ( -- / 153.60 k params)
block_14_project/ kernel ( 1 x1x960x160, 153.60 k/ 153.60 k params)
block_14_project_BN ( -- / 320 params)
block_14_project_BN/ beta ( 160 , 160 / 160 params)
block_14_project_BN/ gamma ( 160 , 160 / 160 params)
block_15_depthwise ( -- / 8.64 k params)
block_15_depthwise/ depthwise_kernel ( 3 x3x960x1, 8.64 k/ 8.64 k params)
block_15_depthwise_BN ( -- / 1.92 k params)
block_15_depthwise_BN/ beta ( 960 , 960 / 960 params)
block_15_depthwise_BN/ gamma ( 960 , 960 / 960 params)
block_15_expand ( -- / 153.60 k params)
block_15_expand/ kernel ( 1 x1x160x960, 153.60 k/ 153.60 k params)
block_15_expand_BN ( -- / 1.92 k params)
block_15_expand_BN/ beta ( 960 , 960 / 960 params)
block_15_expand_BN/ gamma ( 960 , 960 / 960 params)
block_15_project ( -- / 153.60 k params)
block_15_project/ kernel ( 1 x1x960x160, 153.60 k/ 153.60 k params)
block_15_project_BN ( -- / 320 params)
block_15_project_BN/ beta ( 160 , 160 / 160 params)
block_15_project_BN/ gamma ( 160 , 160 / 160 params)
block_16_depthwise ( -- / 8.64 k params)
block_16_depthwise/ depthwise_kernel ( 3 x3x960x1, 8.64 k/ 8.64 k params)
block_16_depthwise_BN ( -- / 1.92 k params)
block_16_depthwise_BN/ beta ( 960 , 960 / 960 params)
block_16_depthwise_BN/ gamma ( 960 , 960 / 960 params)
block_16_expand ( -- / 153.60 k params)
block_16_expand/ kernel ( 1 x1x160x960, 153.60 k/ 153.60 k params)
block_16_expand_BN ( -- / 1.92 k params)
block_16_expand_BN/ beta ( 960 , 960 / 960 params)
block_16_expand_BN/ gamma ( 960 , 960 / 960 params)
block_16_project ( -- / 307.20 k params)
block_16_project/ kernel ( 1 x1x960x320, 307.20 k/ 307.20 k params)
block_16_project_BN ( -- / 640 params)
block_16_project_BN/ beta ( 320 , 320 / 320 params)
block_16_project_BN/ gamma ( 320 , 320 / 320 params)
block_1_depthwise ( -- / 864 params)
block_1_depthwise/ depthwise_kernel ( 3 x3x96x1, 864 / 864 params)
block_1_depthwise_BN ( -- / 192 params)
block_1_depthwise_BN/ beta ( 96 , 96 / 96 params)
block_1_depthwise_BN/ gamma ( 96 , 96 / 96 params)
block_1_expand ( -- / 1.54 k params)
block_1_expand/ kernel ( 1 x1x16x96, 1.54 k/ 1.54 k params)
block_1_expand_BN ( -- / 192 params)
block_1_expand_BN/ beta ( 96 , 96 / 96 params)
block_1_expand_BN/ gamma ( 96 , 96 / 96 params)
block_1_project ( -- / 2.30 k params)
block_1_project/ kernel ( 1 x1x96x24, 2.30 k/ 2.30 k params)
block_1_project_BN ( -- / 48 params)
block_1_project_BN/ beta ( 24 , 24 / 24 params)
block_1_project_BN/ gamma ( 24 , 24 / 24 params)
block_2_depthwise ( -- / 1.30 k params)
block_2_depthwise/ depthwise_kernel ( 3 x3x144x1, 1.30 k/ 1.30 k params)
block_2_depthwise_BN ( -- / 288 params)
block_2_depthwise_BN/ beta ( 144 , 144 / 144 params)
block_2_depthwise_BN/ gamma ( 144 , 144 / 144 params)
block_2_expand ( -- / 3.46 k params)
block_2_expand/ kernel ( 1 x1x24x144, 3.46 k/ 3.46 k params)
block_2_expand_BN ( -- / 288 params)
block_2_expand_BN/ beta ( 144 , 144 / 144 params)
block_2_expand_BN/ gamma ( 144 , 144 / 144 params)
block_2_project ( -- / 3.46 k params)
block_2_project/ kernel ( 1 x1x144x24, 3.46 k/ 3.46 k params)
block_2_project_BN ( -- / 48 params)
block_2_project_BN/ beta ( 24 , 24 / 24 params)
block_2_project_BN/ gamma ( 24 , 24 / 24 params)
block_3_depthwise ( -- / 1.30 k params)
block_3_depthwise/ depthwise_kernel ( 3 x3x144x1, 1.30 k/ 1.30 k params)
block_3_depthwise_BN ( -- / 288 params)
block_3_depthwise_BN/ beta ( 144 , 144 / 144 params)
block_3_depthwise_BN/ gamma ( 144 , 144 / 144 params)
block_3_expand ( -- / 3.46 k params)
block_3_expand/ kernel ( 1 x1x24x144, 3.46 k/ 3.46 k params)
block_3_expand_BN ( -- / 288 params)
block_3_expand_BN/ beta ( 144 , 144 / 144 params)
block_3_expand_BN/ gamma ( 144 , 144 / 144 params)
block_3_project ( -- / 4.61 k params)
block_3_project/ kernel ( 1 x1x144x32, 4.61 k/ 4.61 k params)
block_3_project_BN ( -- / 64 params)
block_3_project_BN/ beta ( 32 , 32 / 32 params)
block_3_project_BN/ gamma ( 32 , 32 / 32 params)
block_4_depthwise ( -- / 1.73 k params)
block_4_depthwise/ depthwise_kernel ( 3 x3x192x1, 1.73 k/ 1.73 k params)
block_4_depthwise_BN ( -- / 384 params)
block_4_depthwise_BN/ beta ( 192 , 192 / 192 params)
block_4_depthwise_BN/ gamma ( 192 , 192 / 192 params)
block_4_expand ( -- / 6.14 k params)
block_4_expand/ kernel ( 1 x1x32x192, 6.14 k/ 6.14 k params)
block_4_expand_BN ( -- / 384 params)
block_4_expand_BN/ beta ( 192 , 192 / 192 params)
block_4_expand_BN/ gamma ( 192 , 192 / 192 params)
block_4_project ( -- / 6.14 k params)
block_4_project/ kernel ( 1 x1x192x32, 6.14 k/ 6.14 k params)
block_4_project_BN ( -- / 64 params)
block_4_project_BN/ beta ( 32 , 32 / 32 params)
block_4_project_BN/ gamma ( 32 , 32 / 32 params)
block_5_depthwise ( -- / 1.73 k params)
block_5_depthwise/ depthwise_kernel ( 3 x3x192x1, 1.73 k/ 1.73 k params)
block_5_depthwise_BN ( -- / 384 params)
block_5_depthwise_BN/ beta ( 192 , 192 / 192 params)
block_5_depthwise_BN/ gamma ( 192 , 192 / 192 params)
block_5_expand ( -- / 6.14 k params)
block_5_expand/ kernel ( 1 x1x32x192, 6.14 k/ 6.14 k params)
block_5_expand_BN ( -- / 384 params)
block_5_expand_BN/ beta ( 192 , 192 / 192 params)
block_5_expand_BN/ gamma ( 192 , 192 / 192 params)
block_5_project ( -- / 6.14 k params)
block_5_project/ kernel ( 1 x1x192x32, 6.14 k/ 6.14 k params)
block_5_project_BN ( -- / 64 params)
block_5_project_BN/ beta ( 32 , 32 / 32 params)
block_5_project_BN/ gamma ( 32 , 32 / 32 params)
block_6_depthwise ( -- / 1.73 k params)
block_6_depthwise/ depthwise_kernel ( 3 x3x192x1, 1.73 k/ 1.73 k params)
block_6_depthwise_BN ( -- / 384 params)
block_6_depthwise_BN/ beta ( 192 , 192 / 192 params)
block_6_depthwise_BN/ gamma ( 192 , 192 / 192 params)
block_6_expand ( -- / 6.14 k params)
block_6_expand/ kernel ( 1 x1x32x192, 6.14 k/ 6.14 k params)
block_6_expand_BN ( -- / 384 params)
block_6_expand_BN/ beta ( 192 , 192 / 192 params)
block_6_expand_BN/ gamma ( 192 , 192 / 192 params)
block_6_project ( -- / 12.29 k params)
block_6_project/ kernel ( 1 x1x192x64, 12.29 k/ 12.29 k params)
block_6_project_BN ( -- / 128 params)
block_6_project_BN/ beta ( 64 , 64 / 64 params)
block_6_project_BN/ gamma ( 64 , 64 / 64 params)
block_7_depthwise ( -- / 3.46 k params)
block_7_depthwise/ depthwise_kernel ( 3 x3x384x1, 3.46 k/ 3.46 k params)
block_7_depthwise_BN ( -- / 768 params)
block_7_depthwise_BN/ beta ( 384 , 384 / 384 params)
block_7_depthwise_BN/ gamma ( 384 , 384 / 384 params)
block_7_expand ( -- / 24.58 k params)
block_7_expand/ kernel ( 1 x1x64x384, 24.58 k/ 24.58 k params)
block_7_expand_BN ( -- / 768 params)
block_7_expand_BN/ beta ( 384 , 384 / 384 params)
block_7_expand_BN/ gamma ( 384 , 384 / 384 params)
block_7_project ( -- / 24.58 k params)
block_7_project/ kernel ( 1 x1x384x64, 24.58 k/ 24.58 k params)
block_7_project_BN ( -- / 128 params)
block_7_project_BN/ beta ( 64 , 64 / 64 params)
block_7_project_BN/ gamma ( 64 , 64 / 64 params)
block_8_depthwise ( -- / 3.46 k params)
block_8_depthwise/ depthwise_kernel ( 3 x3x384x1, 3.46 k/ 3.46 k params)
block_8_depthwise_BN ( -- / 768 params)
block_8_depthwise_BN/ beta ( 384 , 384 / 384 params)
block_8_depthwise_BN/ gamma ( 384 , 384 / 384 params)
block_8_expand ( -- / 24.58 k params)
block_8_expand/ kernel ( 1 x1x64x384, 24.58 k/ 24.58 k params)
block_8_expand_BN ( -- / 768 params)
block_8_expand_BN/ beta ( 384 , 384 / 384 params)
block_8_expand_BN/ gamma ( 384 , 384 / 384 params)
block_8_project ( -- / 24.58 k params)
block_8_project/ kernel ( 1 x1x384x64, 24.58 k/ 24.58 k params)
block_8_project_BN ( -- / 128 params)
block_8_project_BN/ beta ( 64 , 64 / 64 params)
block_8_project_BN/ gamma ( 64 , 64 / 64 params)
block_9_depthwise ( -- / 3.46 k params)
block_9_depthwise/ depthwise_kernel ( 3 x3x384x1, 3.46 k/ 3.46 k params)
block_9_depthwise_BN ( -- / 768 params)
block_9_depthwise_BN/ beta ( 384 , 384 / 384 params)
block_9_depthwise_BN/ gamma ( 384 , 384 / 384 params)
block_9_expand ( -- / 24.58 k params)
block_9_expand/ kernel ( 1 x1x64x384, 24.58 k/ 24.58 k params)
block_9_expand_BN ( -- / 768 params)
block_9_expand_BN/ beta ( 384 , 384 / 384 params)
block_9_expand_BN/ gamma ( 384 , 384 / 384 params)
block_9_project ( -- / 24.58 k params)
block_9_project/ kernel ( 1 x1x384x64, 24.58 k/ 24.58 k params)
block_9_project_BN ( -- / 128 params)
block_9_project_BN/ beta ( 64 , 64 / 64 params)
block_9_project_BN/ gamma ( 64 , 64 / 64 params)
bn_Conv1 ( -- / 64 params)
bn_Conv1/ beta ( 32 , 32 / 32 params)
bn_Conv1/ gamma ( 32 , 32 / 32 params)
expanded_conv_depthwise ( -- / 288 params)
expanded_conv_depthwise/ depthwise_kernel ( 3 x3x32x1, 288 / 288 params)
expanded_conv_depthwise_BN ( -- / 64 params)
expanded_conv_depthwise_BN/ beta ( 32 , 32 / 32 params)
expanded_conv_depthwise_BN/ gamma ( 32 , 32 / 32 params)
expanded_conv_project ( -- / 512 params)
expanded_conv_project/ kernel ( 1 x1x32x16, 512 / 512 params)
expanded_conv_project_BN ( -- / 32 params)
expanded_conv_project_BN/ beta ( 16 , 16 / 16 params)
expanded_conv_project_BN/ gamma ( 16 , 16 / 16 params)
predictions ( -- / 1.28 m params)
predictions/ bias ( 1000 , 1.00 k/ 1.00 k params)
predictions/ kernel ( 1280 x1000, 1.28 m/ 1.28 m params)
== == == == == == == == == == == End of Report== == == == == == == == == == == == ==
Incomplete shape.
Incomplete shape.
FLOPs: 7 , 007 , 905 ; Trainable params: 3 , 504 , 872
以上是keras的application中给出的代码实现，以下是自实现MobileNet的结果测试：
Use `tf. compat. v1. graph_util. tensor_shape_from_node_def_name`
[ 0418 21 : 45 : 18 ] From D: \Anaconda3\envs\wen\lib\site- packages\tensorflow\python\profiler\internal\flops_registry. py: 142 : tensor_shape_from_node_def_name ( from tensorflow. python. framework. graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf. compat. v1. graph_util. tensor_shape_from_node_def_name`
62 ops no flops stats due to incomplete shapes.
Incomplete shape.
Incomplete shape.
Incomplete shape.
Incomplete shape.
== == == == == == == == == == == == = Options== == == == == == == == == == == == == == =
- max_depth 10000
- min_bytes 0
- min_peak_bytes 0
- min_residual_bytes 0
- min_output_bytes 0
- min_micros 0
- min_accelerator_micros 0
- min_cpu_micros 0
- min_params 0
- min_float_ops 1
- min_occurrence 0
- step - 1
- order_by float_ops
- account_type_regexes . *
- start_name_regexes . *
- trim_name_regexes
- show_name_regexes . *
- hide_name_regexes
- account_displayed_op_only true
- select float_ops
- output stdout:
== == == == == == == == == Model Analysis Report== == == == == == == == == == ==
Doc:
scope: The nodes in the model graph are organized by their names, which is hierarchical like filesystem.
flops: Number of float operations. Note: Please read the implementation for the math behind it.
Profile:
node name |
_TFProfRoot ( - - / 4. 57m flops)
Conv_1/ kernel/ Initializer/ random_uniform ( 409. 60k/ 819. 20k flops)
Conv_1/ kernel/ Initializer/ random_uniform/ mul ( 409. 60k/ 409. 60k flops)
Conv_1/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_16_project/ kernel/ Initializer/ random_uniform ( 307. 20k/ 614. 40k flops)
block_16_project/ kernel/ Initializer/ random_uniform/ mul ( 307. 20k/ 307. 20k flops)
block_16_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_15_project/ kernel/ Initializer/ random_uniform ( 153. 60k/ 307. 20k flops)
block_15_project/ kernel/ Initializer/ random_uniform/ mul ( 153. 60k/ 153. 60k flops)
block_15_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_16_expand/ kernel/ Initializer/ random_uniform ( 153. 60k/ 307. 20k flops)
block_16_expand/ kernel/ Initializer/ random_uniform/ mul ( 153. 60k/ 153. 60k flops)
block_16_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_14_project/ kernel/ Initializer/ random_uniform ( 153. 60k/ 307. 20k flops)
block_14_project/ kernel/ Initializer/ random_uniform/ mul ( 153. 60k/ 153. 60k flops)
block_14_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_15_expand/ kernel/ Initializer/ random_uniform ( 153. 60k/ 307. 20k flops)
block_15_expand/ kernel/ Initializer/ random_uniform/ mul ( 153. 60k/ 153. 60k flops)
block_15_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_14_expand/ kernel/ Initializer/ random_uniform ( 153. 60k/ 307. 20k flops)
block_14_expand/ kernel/ Initializer/ random_uniform/ mul ( 153. 60k/ 153. 60k flops)
block_14_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_13_project/ kernel/ Initializer/ random_uniform ( 92. 16k/ 184. 32k flops)
block_13_project/ kernel/ Initializer/ random_uniform/ mul ( 92. 16k/ 92. 16k flops)
block_13_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
Logits/ kernel/ Initializer/ random_uniform ( 62. 72k/ 125. 44k flops)
Logits/ kernel/ Initializer/ random_uniform/ mul ( 62. 72k/ 62. 72k flops)
Logits/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_12_project/ kernel/ Initializer/ random_uniform ( 55. 30k/ 110. 59k flops)
block_12_project/ kernel/ Initializer/ random_uniform/ mul ( 55. 30k/ 55. 30k flops)
block_12_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_11_expand/ kernel/ Initializer/ random_uniform ( 55. 30k/ 110. 59k flops)
block_11_expand/ kernel/ Initializer/ random_uniform/ mul ( 55. 30k/ 55. 30k flops)
block_11_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_12_expand/ kernel/ Initializer/ random_uniform ( 55. 30k/ 110. 59k flops)
block_12_expand/ kernel/ Initializer/ random_uniform/ mul ( 55. 30k/ 55. 30k flops)
block_12_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_11_project/ kernel/ Initializer/ random_uniform ( 55. 30k/ 110. 59k flops)
block_11_project/ kernel/ Initializer/ random_uniform/ mul ( 55. 30k/ 55. 30k flops)
block_11_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_13_expand/ kernel/ Initializer/ random_uniform ( 55. 30k/ 110. 59k flops)
block_13_expand/ kernel/ Initializer/ random_uniform/ mul ( 55. 30k/ 55. 30k flops)
block_13_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_10_project/ kernel/ Initializer/ random_uniform ( 36. 86k/ 73. 73k flops)
block_10_project/ kernel/ Initializer/ random_uniform/ mul ( 36. 86k/ 36. 86k flops)
block_10_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_9_expand/ kernel/ Initializer/ random_uniform ( 24. 58k/ 49. 15k flops)
block_9_expand/ kernel/ Initializer/ random_uniform/ mul ( 24. 58k/ 24. 58k flops)
block_9_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_8_expand/ kernel/ Initializer/ random_uniform ( 24. 58k/ 49. 15k flops)
block_8_expand/ kernel/ Initializer/ random_uniform/ mul ( 24. 58k/ 24. 58k flops)
block_8_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_10_expand/ kernel/ Initializer/ random_uniform ( 24. 58k/ 49. 15k flops)
block_10_expand/ kernel/ Initializer/ random_uniform/ mul ( 24. 58k/ 24. 58k flops)
block_10_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_7_project/ kernel/ Initializer/ random_uniform ( 24. 58k/ 49. 15k flops)
block_7_project/ kernel/ Initializer/ random_uniform/ mul ( 24. 58k/ 24. 58k flops)
block_7_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_7_expand/ kernel/ Initializer/ random_uniform ( 24. 58k/ 49. 15k flops)
block_7_expand/ kernel/ Initializer/ random_uniform/ mul ( 24. 58k/ 24. 58k flops)
block_7_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_8_project/ kernel/ Initializer/ random_uniform ( 24. 58k/ 49. 15k flops)
block_8_project/ kernel/ Initializer/ random_uniform/ mul ( 24. 58k/ 24. 58k flops)
block_8_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_9_project/ kernel/ Initializer/ random_uniform ( 24. 58k/ 49. 15k flops)
block_9_project/ kernel/ Initializer/ random_uniform/ mul ( 24. 58k/ 24. 58k flops)
block_9_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_6_project/ kernel/ Initializer/ random_uniform ( 12. 29k/ 24. 58k flops)
block_6_project/ kernel/ Initializer/ random_uniform/ mul ( 12. 29k/ 12. 29k flops)
block_6_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_16_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 8. 64k/ 17. 28k flops)
block_16_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 8. 64k/ 8. 64k flops)
block_16_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_15_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 8. 64k/ 17. 28k flops)
block_15_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 8. 64k/ 8. 64k flops)
block_15_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_14_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 8. 64k/ 17. 28k flops)
block_14_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 8. 64k/ 8. 64k flops)
block_14_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_5_expand/ kernel/ Initializer/ random_uniform ( 6. 14k/ 12. 29k flops)
block_5_expand/ kernel/ Initializer/ random_uniform/ mul ( 6. 14k/ 6. 14k flops)
block_5_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_5_project/ kernel/ Initializer/ random_uniform ( 6. 14k/ 12. 29k flops)
block_5_project/ kernel/ Initializer/ random_uniform/ mul ( 6. 14k/ 6. 14k flops)
block_5_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_4_project/ kernel/ Initializer/ random_uniform ( 6. 14k/ 12. 29k flops)
block_4_project/ kernel/ Initializer/ random_uniform/ mul ( 6. 14k/ 6. 14k flops)
block_4_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_6_expand/ kernel/ Initializer/ random_uniform ( 6. 14k/ 12. 29k flops)
block_6_expand/ kernel/ Initializer/ random_uniform/ mul ( 6. 14k/ 6. 14k flops)
block_6_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_4_expand/ kernel/ Initializer/ random_uniform ( 6. 14k/ 12. 29k flops)
block_4_expand/ kernel/ Initializer/ random_uniform/ mul ( 6. 14k/ 6. 14k flops)
block_4_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_11_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 5. 18k/ 10. 37k flops)
block_11_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 5. 18k/ 5. 18k flops)
block_11_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_13_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 5. 18k/ 10. 37k flops)
block_13_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 5. 18k/ 5. 18k flops)
block_13_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_12_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 5. 18k/ 10. 37k flops)
block_12_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 5. 18k/ 5. 18k flops)
block_12_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_3_project/ kernel/ Initializer/ random_uniform ( 4. 61k/ 9. 22k flops)
block_3_project/ kernel/ Initializer/ random_uniform/ mul ( 4. 61k/ 4. 61k flops)
block_3_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_3_expand/ kernel/ Initializer/ random_uniform ( 3. 46k/ 6. 91k flops)
block_3_expand/ kernel/ Initializer/ random_uniform/ mul ( 3. 46k/ 3. 46k flops)
block_3_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_2_project/ kernel/ Initializer/ random_uniform ( 3. 46k/ 6. 91k flops)
block_2_project/ kernel/ Initializer/ random_uniform/ mul ( 3. 46k/ 3. 46k flops)
block_2_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_2_expand/ kernel/ Initializer/ random_uniform ( 3. 46k/ 6. 91k flops)
block_2_expand/ kernel/ Initializer/ random_uniform/ mul ( 3. 46k/ 3. 46k flops)
block_2_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_10_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 3. 46k/ 6. 91k flops)
block_10_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 3. 46k/ 3. 46k flops)
block_10_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_7_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 3. 46k/ 6. 91k flops)
block_7_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 3. 46k/ 3. 46k flops)
block_7_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_8_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 3. 46k/ 6. 91k flops)
block_8_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 3. 46k/ 3. 46k flops)
block_8_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_9_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 3. 46k/ 6. 91k flops)
block_9_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 3. 46k/ 3. 46k flops)
block_9_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_1_project/ kernel/ Initializer/ random_uniform ( 2. 30k/ 4. 61k flops)
block_1_project/ kernel/ Initializer/ random_uniform/ mul ( 2. 30k/ 2. 30k flops)
block_1_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_4_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1. 73k/ 3. 46k flops)
block_4_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1. 73k/ 1. 73k flops)
block_4_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_6_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1. 73k/ 3. 46k flops)
block_6_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1. 73k/ 1. 73k flops)
block_6_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_5_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1. 73k/ 3. 46k flops)
block_5_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1. 73k/ 1. 73k flops)
block_5_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_1_expand/ kernel/ Initializer/ random_uniform ( 1. 54k/ 3. 07k flops)
block_1_expand/ kernel/ Initializer/ random_uniform/ mul ( 1. 54k/ 1. 54k flops)
block_1_expand/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_2_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1. 30k/ 2. 59k flops)
block_2_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1. 30k/ 1. 30k flops)
block_2_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_3_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 1. 30k/ 2. 59k flops)
block_3_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 1. 30k/ 1. 30k flops)
block_3_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_1_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 864 / 1. 73k flops)
block_1_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 864 / 864 flops)
block_1_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
Conv_1_bn/ AssignMovingAvg/ mul ( 1. 28k/ 1. 28k flops)
Conv_1_bn/ AssignMovingAvg/ sub_1 ( 1. 28k/ 1. 28k flops)
Conv_1_bn/ AssignMovingAvg_1/ mul ( 1. 28k/ 1. 28k flops)
Conv_1_bn/ AssignMovingAvg_1/ sub_1 ( 1. 28k/ 1. 28k flops)
expanded_conv_project/ kernel/ Initializer/ random_uniform ( 512 / 1. 02k flops)
expanded_conv_project/ kernel/ Initializer/ random_uniform/ mul ( 512 / 512 flops)
expanded_conv_project/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_14_depthwise_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_15_depthwise_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_15_depthwise_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_15_depthwise_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_15_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_15_expand_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_15_expand_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_14_depthwise_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_15_expand_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_16_depthwise_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_14_depthwise_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_16_depthwise_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_16_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_14_expand_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_16_expand_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_16_expand_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_16_expand_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_16_depthwise_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_16_expand_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_15_expand_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
block_14_expand_BN/ AssignMovingAvg_1/ mul ( 960 / 960 flops)
block_14_expand_BN/ AssignMovingAvg/ sub_1 ( 960 / 960 flops)
block_14_expand_BN/ AssignMovingAvg/ mul ( 960 / 960 flops)
block_14_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 960 / 960 flops)
expanded_conv_depthwise/ depthwise_kernel/ Initializer/ random_uniform ( 288 / 577 flops)
expanded_conv_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ mul ( 288 / 288 flops)
expanded_conv_depthwise/ depthwise_kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
Conv1/ kernel/ Initializer/ random_uniform ( 288 / 577 flops)
Conv1/ kernel/ Initializer/ random_uniform/ mul ( 288 / 288 flops)
Conv1/ kernel/ Initializer/ random_uniform/ sub ( 1 / 1 flops)
block_13_expand_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_13_expand_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_13_expand_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_13_expand_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_11_expand_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_11_depthwise_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_11_depthwise_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_11_depthwise_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_11_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_11_expand_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_11_expand_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_11_expand_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_12_depthwise_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_12_depthwise_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_12_depthwise_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_12_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_12_expand_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_12_expand_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_12_expand_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_12_expand_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_13_depthwise_BN/ AssignMovingAvg/ mul ( 576 / 576 flops)
block_13_depthwise_BN/ AssignMovingAvg/ sub_1 ( 576 / 576 flops)
block_13_depthwise_BN/ AssignMovingAvg_1/ mul ( 576 / 576 flops)
block_13_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 576 / 576 flops)
block_7_depthwise_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_9_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_10_expand_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_8_depthwise_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_9_expand_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_9_expand_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_8_depthwise_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_9_expand_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_9_expand_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_7_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_8_expand_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_8_expand_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_10_expand_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_10_expand_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_7_depthwise_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_8_expand_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_10_expand_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_10_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_8_expand_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_9_depthwise_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_10_depthwise_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_7_depthwise_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_10_depthwise_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_10_depthwise_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_9_depthwise_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_7_expand_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_7_expand_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_8_depthwise_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_9_depthwise_BN/ AssignMovingAvg_1/ mul ( 384 / 384 flops)
block_7_expand_BN/ AssignMovingAvg/ sub_1 ( 384 / 384 flops)
block_8_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 384 / 384 flops)
block_7_expand_BN/ AssignMovingAvg/ mul ( 384 / 384 flops)
block_16_project_BN/ AssignMovingAvg/ mul ( 320 / 320 flops)
block_16_project_BN/ AssignMovingAvg/ sub_1 ( 320 / 320 flops)
block_16_project_BN/ AssignMovingAvg_1/ mul ( 320 / 320 flops)
block_16_project_BN/ AssignMovingAvg_1/ sub_1 ( 320 / 320 flops)
block_4_depthwise_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_4_depthwise_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_4_expand_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_4_expand_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_6_expand_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_6_expand_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_4_expand_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_6_expand_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_4_expand_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_6_expand_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_5_depthwise_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_6_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_6_depthwise_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_6_depthwise_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_5_expand_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_4_depthwise_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_5_expand_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_5_expand_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_5_expand_BN/ AssignMovingAvg/ mul ( 192 / 192 flops)
block_4_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_5_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 192 / 192 flops)
block_5_depthwise_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_6_depthwise_BN/ AssignMovingAvg_1/ mul ( 192 / 192 flops)
block_5_depthwise_BN/ AssignMovingAvg/ sub_1 ( 192 / 192 flops)
block_14_project_BN/ AssignMovingAvg/ sub_1 ( 160 / 160 flops)
block_14_project_BN/ AssignMovingAvg_1/ mul ( 160 / 160 flops)
block_14_project_BN/ AssignMovingAvg_1/ sub_1 ( 160 / 160 flops)
block_15_project_BN/ AssignMovingAvg/ mul ( 160 / 160 flops)
block_15_project_BN/ AssignMovingAvg/ sub_1 ( 160 / 160 flops)
block_15_project_BN/ AssignMovingAvg_1/ mul ( 160 / 160 flops)
block_15_project_BN/ AssignMovingAvg_1/ sub_1 ( 160 / 160 flops)
block_13_project_BN/ AssignMovingAvg_1/ sub_1 ( 160 / 160 flops)
block_13_project_BN/ AssignMovingAvg/ mul ( 160 / 160 flops)
block_13_project_BN/ AssignMovingAvg/ sub_1 ( 160 / 160 flops)
block_13_project_BN/ AssignMovingAvg_1/ mul ( 160 / 160 flops)
block_14_project_BN/ AssignMovingAvg/ mul ( 160 / 160 flops)
block_3_depthwise_BN/ AssignMovingAvg/ sub_1 ( 144 / 144 flops)
block_2_depthwise_BN/ AssignMovingAvg_1/ mul ( 144 / 144 flops)
block_2_expand_BN/ AssignMovingAvg_1/ mul ( 144 / 144 flops)
block_3_expand_BN/ AssignMovingAvg_1/ sub_1 ( 144 / 144 flops)
block_2_expand_BN/ AssignMovingAvg_1/ sub_1 ( 144 / 144 flops)
block_2_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 144 / 144 flops)
block_3_expand_BN/ AssignMovingAvg/ sub_1 ( 144 / 144 flops)
block_3_expand_BN/ AssignMovingAvg/ mul ( 144 / 144 flops)
block_2_expand_BN/ AssignMovingAvg/ mul ( 144 / 144 flops)
block_2_depthwise_BN/ AssignMovingAvg/ mul ( 144 / 144 flops)
block_2_expand_BN/ AssignMovingAvg/ sub_1 ( 144 / 144 flops)
block_3_expand_BN/ AssignMovingAvg_1/ mul ( 144 / 144 flops)
block_3_depthwise_BN/ AssignMovingAvg/ mul ( 144 / 144 flops)
block_2_depthwise_BN/ AssignMovingAvg/ sub_1 ( 144 / 144 flops)
block_3_depthwise_BN/ AssignMovingAvg_1/ mul ( 144 / 144 flops)
block_3_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 144 / 144 flops)
block_1_depthwise_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_10_project_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_10_project_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_11_project_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_12_project_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_12_project_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_1_depthwise_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_12_project_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_11_project_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_11_project_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_12_project_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_10_project_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_1_expand_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_1_expand_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_1_expand_BN/ AssignMovingAvg/ sub_1 ( 96 / 96 flops)
block_1_expand_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_1_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_10_project_BN/ AssignMovingAvg_1/ sub_1 ( 96 / 96 flops)
block_11_project_BN/ AssignMovingAvg/ mul ( 96 / 96 flops)
block_1_depthwise_BN/ AssignMovingAvg_1/ mul ( 96 / 96 flops)
block_6_project_BN/ AssignMovingAvg_1/ mul ( 64 / 64 flops)
block_7_project_BN/ AssignMovingAvg/ sub_1 ( 64 / 64 flops)
block_6_project_BN/ AssignMovingAvg_1/ sub_1 ( 64 / 64 flops)
block_6_project_BN/ AssignMovingAvg/ sub_1 ( 64 / 64 flops)
block_6_project_BN/ AssignMovingAvg/ mul ( 64 / 64 flops)
block_7_project_BN/ AssignMovingAvg/ mul ( 64 / 64 flops)
block_8_project_BN/ AssignMovingAvg_1/ sub_1 ( 64 / 64 flops)
block_9_project_BN/ AssignMovingAvg_1/ mul ( 64 / 64 flops)
block_8_project_BN/ AssignMovingAvg_1/ mul ( 64 / 64 flops)
block_9_project_BN/ AssignMovingAvg/ sub_1 ( 64 / 64 flops)
block_9_project_BN/ AssignMovingAvg/ mul ( 64 / 64 flops)
block_8_project_BN/ AssignMovingAvg/ sub_1 ( 64 / 64 flops)
block_8_project_BN/ AssignMovingAvg/ mul ( 64 / 64 flops)
block_9_project_BN/ AssignMovingAvg_1/ sub_1 ( 64 / 64 flops)
block_7_project_BN/ AssignMovingAvg_1/ sub_1 ( 64 / 64 flops)
block_7_project_BN/ AssignMovingAvg_1/ mul ( 64 / 64 flops)
block_3_project_BN/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
block_3_project_BN/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
bn_Conv1/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
bn_Conv1/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
block_5_project_BN/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
block_4_project_BN/ AssignMovingAvg/ mul ( 32 / 32 flops)
bn_Conv1/ AssignMovingAvg/ mul ( 32 / 32 flops)
block_4_project_BN/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
block_4_project_BN/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
block_5_project_BN/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
block_5_project_BN/ AssignMovingAvg/ mul ( 32 / 32 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
block_3_project_BN/ AssignMovingAvg/ mul ( 32 / 32 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg/ mul ( 32 / 32 flops)
block_3_project_BN/ AssignMovingAvg_1/ mul ( 32 / 32 flops)
block_5_project_BN/ AssignMovingAvg/ sub_1 ( 32 / 32 flops)
bn_Conv1/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
block_4_project_BN/ AssignMovingAvg_1/ sub_1 ( 32 / 32 flops)
block_2_project_BN/ AssignMovingAvg/ mul ( 24 / 24 flops)
block_1_project_BN/ AssignMovingAvg_1/ mul ( 24 / 24 flops)
block_2_project_BN/ AssignMovingAvg/ sub_1 ( 24 / 24 flops)
block_2_project_BN/ AssignMovingAvg_1/ mul ( 24 / 24 flops)
block_1_project_BN/ AssignMovingAvg_1/ sub_1 ( 24 / 24 flops)
block_2_project_BN/ AssignMovingAvg_1/ sub_1 ( 24 / 24 flops)
block_1_project_BN/ AssignMovingAvg/ sub_1 ( 24 / 24 flops)
block_1_project_BN/ AssignMovingAvg/ mul ( 24 / 24 flops)
expanded_conv_project_BN/ AssignMovingAvg/ mul ( 16 / 16 flops)
expanded_conv_project_BN/ AssignMovingAvg/ sub_1 ( 16 / 16 flops)
expanded_conv_project_BN/ AssignMovingAvg_1/ mul ( 16 / 16 flops)
expanded_conv_project_BN/ AssignMovingAvg_1/ sub_1 ( 16 / 16 flops)
block_10_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_10_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_2_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_2_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_2_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_2_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_2_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_3_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_3_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_3_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_3_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_3_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_3_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_15_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_14_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_15_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_6_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_15_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_6_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_6_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_15_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_14_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_14_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_14_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_14_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_14_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_11_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_13_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_13_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_13_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_13_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_13_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_6_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_15_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_15_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_7_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_6_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_13_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_16_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_8_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_12_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_16_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_8_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_6_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_12_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_16_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_8_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_12_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_12_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_8_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_12_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_12_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_16_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_8_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_5_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_5_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_8_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_16_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_16_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_11_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_9_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_5_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_1_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_1_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_11_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_11_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_11_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_11_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_5_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_10_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_5_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_9_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_1_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_4_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_9_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_5_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_4_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
bn_Conv1/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_1_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_4_expand_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
bn_Conv1/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_4_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_1_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
Conv_1_bn/ AssignMovingAvg/ sub ( 1 / 1 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_4_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_1_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
expanded_conv_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_4_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_2_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
Conv_1_bn/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
expanded_conv_project_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_10_depthwise_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
block_10_depthwise_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
expanded_conv_project_BN/ AssignMovingAvg_1/ sub ( 1 / 1 flops)
block_10_expand_BN/ AssignMovingAvg/ sub ( 1 / 1 flops)
loss/ Logits_loss/ softmax_cross_entropy_with_logits/ Sub ( 1 / 1 flops)
loss/ Logits_loss/ softmax_cross_entropy_with_logits/ Sub_1 ( 1 / 1 flops)
loss/ Logits_loss/ softmax_cross_entropy_with_logits/ Sub_2 ( 1 / 1 flops)
loss/ mul ( 1 / 1 flops)
== == == == == == == == == == == End of Report== == == == == == == == == == == == ==
62 ops no flops stats due to incomplete shapes.
Incomplete shape.
Incomplete shape.
Incomplete shape.
== == == == == == == == == == == == = Options== == == == == == == == == == == == == == =
- max_depth 10000
- min_bytes 0
- min_peak_bytes 0
- min_residual_bytes 0
- min_output_bytes 0
- min_micros 0
- min_accelerator_micros 0
- min_cpu_micros 0
- min_params 0
- min_float_ops 0
- min_occurrence 0
- step - 1
- order_by name
- account_type_regexes _trainable_variables
- start_name_regexes . *
- trim_name_regexes
- show_name_regexes . *
- hide_name_regexes
- account_displayed_op_only true
- select params
- output stdout:
== == == == == == == == == Model Analysis Report== == == == == == == == == == ==
Incomplete shape.
Doc:
scope: The nodes in the model graph are organized by their names, which is hierarchical like filesystem.
param: Number of parameters ( in the Variable) .
Profile:
node name |
_TFProfRoot ( - - / 2. 29m params)
Conv1 ( - - / 288 params)
Conv1/ kernel ( 3x3x1x32, 288 / 288 params)
Conv_1 ( - - / 409. 60k params)
Conv_1/ kernel ( 1x1x320x1280, 409. 60k/ 409. 60k params)
Conv_1_bn ( - - / 2. 56k params)
Conv_1_bn/ beta ( 1280 , 1. 28k/ 1. 28k params)
Conv_1_bn/ gamma ( 1280 , 1. 28k/ 1. 28k params)
Logits ( - - / 62. 77k params)
Logits/ bias ( 49 , 49 / 49 params)
Logits/ kernel ( 1280x49, 62. 72k/ 62. 72k params)
block_10_depthwise ( - - / 3. 46k params)
block_10_depthwise/ depthwise_kernel ( 3x3x384x1, 3. 46k/ 3. 46k params)
block_10_depthwise_BN ( - - / 768 params)
block_10_depthwise_BN/ beta ( 384 , 384 / 384 params)
block_10_depthwise_BN/ gamma ( 384 , 384 / 384 params)
block_10_expand ( - - / 24. 58k params)
block_10_expand/ kernel ( 1x1x64x384, 24. 58k/ 24. 58k params)
block_10_expand_BN ( - - / 768 params)
block_10_expand_BN/ beta ( 384 , 384 / 384 params)
block_10_expand_BN/ gamma ( 384 , 384 / 384 params)
block_10_project ( - - / 36. 86k params)
block_10_project/ kernel ( 1x1x384x96, 36. 86k/ 36. 86k params)
block_10_project_BN ( - - / 192 params)
block_10_project_BN/ beta ( 96 , 96 / 96 params)
block_10_project_BN/ gamma ( 96 , 96 / 96 params)
block_11_depthwise ( - - / 5. 18k params)
block_11_depthwise/ depthwise_kernel ( 3x3x576x1, 5. 18k/ 5. 18k params)
block_11_depthwise_BN ( - - / 1. 15k params)
block_11_depthwise_BN/ beta ( 576 , 576 / 576 params)
block_11_depthwise_BN/ gamma ( 576 , 576 / 576 params)
block_11_expand ( - - / 55. 30k params)
block_11_expand/ kernel ( 1x1x96x576, 55. 30k/ 55. 30k params)
block_11_expand_BN ( - - / 1. 15k params)
block_11_expand_BN/ beta ( 576 , 576 / 576 params)
block_11_expand_BN/ gamma ( 576 , 576 / 576 params)
block_11_project ( - - / 55. 30k params)
block_11_project/ kernel ( 1x1x576x96, 55. 30k/ 55. 30k params)
block_11_project_BN ( - - / 192 params)
block_11_project_BN/ beta ( 96 , 96 / 96 params)
block_11_project_BN/ gamma ( 96 , 96 / 96 params)
block_12_depthwise ( - - / 5. 18k params)
block_12_depthwise/ depthwise_kernel ( 3x3x576x1, 5. 18k/ 5. 18k params)
block_12_depthwise_BN ( - - / 1. 15k params)
block_12_depthwise_BN/ beta ( 576 , 576 / 576 params)
block_12_depthwise_BN/ gamma ( 576 , 576 / 576 params)
block_12_expand ( - - / 55. 30k params)
block_12_expand/ kernel ( 1x1x96x576, 55. 30k/ 55. 30k params)
block_12_expand_BN ( - - / 1. 15k params)
block_12_expand_BN/ beta ( 576 , 576 / 576 params)
block_12_expand_BN/ gamma ( 576 , 576 / 576 params)
block_12_project ( - - / 55. 30k params)
block_12_project/ kernel ( 1x1x576x96, 55. 30k/ 55. 30k params)
block_12_project_BN ( - - / 192 params)
block_12_project_BN/ beta ( 96 , 96 / 96 params)
block_12_project_BN/ gamma ( 96 , 96 / 96 params)
block_13_depthwise ( - - / 5. 18k params)
block_13_depthwise/ depthwise_kernel ( 3x3x576x1, 5. 18k/ 5. 18k params)
block_13_depthwise_BN ( - - / 1. 15k params)
block_13_depthwise_BN/ beta ( 576 , 576 / 576 params)
block_13_depthwise_BN/ gamma ( 576 , 576 / 576 params)
block_13_expand ( - - / 55. 30k params)
block_13_expand/ kernel ( 1x1x96x576, 55. 30k/ 55. 30k params)
block_13_expand_BN ( - - / 1. 15k params)
block_13_expand_BN/ beta ( 576 , 576 / 576 params)
block_13_expand_BN/ gamma ( 576 , 576 / 576 params)
block_13_project ( - - / 92. 16k params)
block_13_project/ kernel ( 1x1x576x160, 92. 16k/ 92. 16k params)
block_13_project_BN ( - - / 320 params)
block_13_project_BN/ beta ( 160 , 160 / 160 params)
block_13_project_BN/ gamma ( 160 , 160 / 160 params)
block_14_depthwise ( - - / 8. 64k params)
block_14_depthwise/ depthwise_kernel ( 3x3x960x1, 8. 64k/ 8. 64k params)
block_14_depthwise_BN ( - - / 1. 92k params)
block_14_depthwise_BN/ beta ( 960 , 960 / 960 params)
block_14_depthwise_BN/ gamma ( 960 , 960 / 960 params)
block_14_expand ( - - / 153. 60k params)
block_14_expand/ kernel ( 1x1x160x960, 153. 60k/ 153. 60k params)
block_14_expand_BN ( - - / 1. 92k params)
block_14_expand_BN/ beta ( 960 , 960 / 960 params)
block_14_expand_BN/ gamma ( 960 , 960 / 960 params)
block_14_project ( - - / 153. 60k params)
block_14_project/ kernel ( 1x1x960x160, 153. 60k/ 153. 60k params)
block_14_project_BN ( - - / 320 params)
block_14_project_BN/ beta ( 160 , 160 / 160 params)
block_14_project_BN/ gamma ( 160 , 160 / 160 params)
block_15_depthwise ( - - / 8. 64k params)
block_15_depthwise/ depthwise_kernel ( 3x3x960x1, 8. 64k/ 8. 64k params)
block_15_depthwise_BN ( - - / 1. 92k params)
block_15_depthwise_BN/ beta ( 960 , 960 / 960 params)
block_15_depthwise_BN/ gamma ( 960 , 960 / 960 params)
block_15_expand ( - - / 153. 60k params)
block_15_expand/ kernel ( 1x1x160x960, 153. 60k/ 153. 60k params)
block_15_expand_BN ( - - / 1. 92k params)
block_15_expand_BN/ beta ( 960 , 960 / 960 params)
block_15_expand_BN/ gamma ( 960 , 960 / 960 params)
block_15_project ( - - / 153. 60k params)
block_15_project/ kernel ( 1x1x960x160, 153. 60k/ 153. 60k params)
block_15_project_BN ( - - / 320 params)
block_15_project_BN/ beta ( 160 , 160 / 160 params)
block_15_project_BN/ gamma ( 160 , 160 / 160 params)
block_16_depthwise ( - - / 8. 64k params)
block_16_depthwise/ depthwise_kernel ( 3x3x960x1, 8. 64k/ 8. 64k params)
block_16_depthwise_BN ( - - / 1. 92k params)
block_16_depthwise_BN/ beta ( 960 , 960 / 960 params)
block_16_depthwise_BN/ gamma ( 960 , 960 / 960 params)
block_16_expand ( - - / 153. 60k params)
block_16_expand/ kernel ( 1x1x160x960, 153. 60k/ 153. 60k params)
block_16_expand_BN ( - - / 1. 92k params)
block_16_expand_BN/ beta ( 960 , 960 / 960 params)
block_16_expand_BN/ gamma ( 960 , 960 / 960 params)
block_16_project ( - - / 307. 20k params)
block_16_project/ kernel ( 1x1x960x320, 307. 20k/ 307. 20k params)
block_16_project_BN ( - - / 640 params)
block_16_project_BN/ beta ( 320 , 320 / 320 params)
block_16_project_BN/ gamma ( 320 , 320 / 320 params)
block_1_depthwise ( - - / 864 params)
block_1_depthwise/ depthwise_kernel ( 3x3x96x1, 864 / 864 params)
block_1_depthwise_BN ( - - / 192 params)
block_1_depthwise_BN/ beta ( 96 , 96 / 96 params)
block_1_depthwise_BN/ gamma ( 96 , 96 / 96 params)
block_1_expand ( - - / 1. 54k params)
block_1_expand/ kernel ( 1x1x16x96, 1. 54k/ 1. 54k params)
block_1_expand_BN ( - - / 192 params)
block_1_expand_BN/ beta ( 96 , 96 / 96 params)
block_1_expand_BN/ gamma ( 96 , 96 / 96 params)
block_1_project ( - - / 2. 30k params)
block_1_project/ kernel ( 1x1x96x24, 2. 30k/ 2. 30k params)
block_1_project_BN ( - - / 48 params)
block_1_project_BN/ beta ( 24 , 24 / 24 params)
block_1_project_BN/ gamma ( 24 , 24 / 24 params)
block_2_depthwise ( - - / 1. 30k params)
block_2_depthwise/ depthwise_kernel ( 3x3x144x1, 1. 30k/ 1. 30k params)
block_2_depthwise_BN ( - - / 288 params)
block_2_depthwise_BN/ beta ( 144 , 144 / 144 params)
block_2_depthwise_BN/ gamma ( 144 , 144 / 144 params)
block_2_expand ( - - / 3. 46k params)
block_2_expand/ kernel ( 1x1x24x144, 3. 46k/ 3. 46k params)
block_2_expand_BN ( - - / 288 params)
block_2_expand_BN/ beta ( 144 , 144 / 144 params)
block_2_expand_BN/ gamma ( 144 , 144 / 144 params)
block_2_project ( - - / 3. 46k params)
block_2_project/ kernel ( 1x1x144x24, 3. 46k/ 3. 46k params)
block_2_project_BN ( - - / 48 params)
block_2_project_BN/ beta ( 24 , 24 / 24 params)
block_2_project_BN/ gamma ( 24 , 24 / 24 params)
block_3_depthwise ( - - / 1. 30k params)
block_3_depthwise/ depthwise_kernel ( 3x3x144x1, 1. 30k/ 1. 30k params)
block_3_depthwise_BN ( - - / 288 params)
block_3_depthwise_BN/ beta ( 144 , 144 / 144 params)
block_3_depthwise_BN/ gamma ( 144 , 144 / 144 params)
block_3_expand ( - - / 3. 46k params)
block_3_expand/ kernel ( 1x1x24x144, 3. 46k/ 3. 46k params)
block_3_expand_BN ( - - / 288 params)
block_3_expand_BN/ beta ( 144 , 144 / 144 params)
block_3_expand_BN/ gamma ( 144 , 144 / 144 params)
block_3_project ( - - / 4. 61k params)
block_3_project/ kernel ( 1x1x144x32, 4. 61k/ 4. 61k params)
block_3_project_BN ( - - / 64 params)
block_3_project_BN/ beta ( 32 , 32 / 32 params)
block_3_project_BN/ gamma ( 32 , 32 / 32 params)
block_4_depthwise ( - - / 1. 73k params)
block_4_depthwise/ depthwise_kernel ( 3x3x192x1, 1. 73k/ 1. 73k params)
block_4_depthwise_BN ( - - / 384 params)
block_4_depthwise_BN/ beta ( 192 , 192 / 192 params)
block_4_depthwise_BN/ gamma ( 192 , 192 / 192 params)
block_4_expand ( - - / 6. 14k params)
block_4_expand/ kernel ( 1x1x32x192, 6. 14k/ 6. 14k params)
block_4_expand_BN ( - - / 384 params)
block_4_expand_BN/ beta ( 192 , 192 / 192 params)
block_4_expand_BN/ gamma ( 192 , 192 / 192 params)
block_4_project ( - - / 6. 14k params)
block_4_project/ kernel ( 1x1x192x32, 6. 14k/ 6. 14k params)
block_4_project_BN ( - - / 64 params)
block_4_project_BN/ beta ( 32 , 32 / 32 params)
block_4_project_BN/ gamma ( 32 , 32 / 32 params)
block_5_depthwise ( - - / 1. 73k params)
block_5_depthwise/ depthwise_kernel ( 3x3x192x1, 1. 73k/ 1. 73k params)
block_5_depthwise_BN ( - - / 384 params)
block_5_depthwise_BN/ beta ( 192 , 192 / 192 params)
block_5_depthwise_BN/ gamma ( 192 , 192 / 192 params)
block_5_expand ( - - / 6. 14k params)
block_5_expand/ kernel ( 1x1x32x192, 6. 14k/ 6. 14k params)
block_5_expand_BN ( - - / 384 params)
block_5_expand_BN/ beta ( 192 , 192 / 192 params)
block_5_expand_BN/ gamma ( 192 , 192 / 192 params)
block_5_project ( - - / 6. 14k params)
block_5_project/ kernel ( 1x1x192x32, 6. 14k/ 6. 14k params)
block_5_project_BN ( - - / 64 params)
block_5_project_BN/ beta ( 32 , 32 / 32 params)
block_5_project_BN/ gamma ( 32 , 32 / 32 params)
block_6_depthwise ( - - / 1. 73k params)
block_6_depthwise/ depthwise_kernel ( 3x3x192x1, 1. 73k/ 1. 73k params)
block_6_depthwise_BN ( - - / 384 params)
block_6_depthwise_BN/ beta ( 192 , 192 / 192 params)
block_6_depthwise_BN/ gamma ( 192 , 192 / 192 params)
block_6_expand ( - - / 6. 14k params)
block_6_expand/ kernel ( 1x1x32x192, 6. 14k/ 6. 14k params)
block_6_expand_BN ( - - / 384 params)
block_6_expand_BN/ beta ( 192 , 192 / 192 params)
block_6_expand_BN/ gamma ( 192 , 192 / 192 params)
block_6_project ( - - / 12. 29k params)
block_6_project/ kernel ( 1x1x192x64, 12. 29k/ 12. 29k params)
block_6_project_BN ( - - / 128 params)
block_6_project_BN/ beta ( 64 , 64 / 64 params)
block_6_project_BN/ gamma ( 64 , 64 / 64 params)
block_7_depthwise ( - - / 3. 46k params)
block_7_depthwise/ depthwise_kernel ( 3x3x384x1, 3. 46k/ 3. 46k params)
block_7_depthwise_BN ( - - / 768 params)
block_7_depthwise_BN/ beta ( 384 , 384 / 384 params)
block_7_depthwise_BN/ gamma ( 384 , 384 / 384 params)
block_7_expand ( - - / 24. 58k params)
block_7_expand/ kernel ( 1x1x64x384, 24. 58k/ 24. 58k params)
block_7_expand_BN ( - - / 768 params)
block_7_expand_BN/ beta ( 384 , 384 / 384 params)
block_7_expand_BN/ gamma ( 384 , 384 / 384 params)
block_7_project ( - - / 24. 58k params)
block_7_project/ kernel ( 1x1x384x64, 24. 58k/ 24. 58k params)
block_7_project_BN ( - - / 128 params)
block_7_project_BN/ beta ( 64 , 64 / 64 params)
block_7_project_BN/ gamma ( 64 , 64 / 64 params)
block_8_depthwise ( - - / 3. 46k params)
block_8_depthwise/ depthwise_kernel ( 3x3x384x1, 3. 46k/ 3. 46k params)
block_8_depthwise_BN ( - - / 768 params)
block_8_depthwise_BN/ beta ( 384 , 384 / 384 params)
block_8_depthwise_BN/ gamma ( 384 , 384 / 384 params)
block_8_expand ( - - / 24. 58k params)
block_8_expand/ kernel ( 1x1x64x384, 24. 58k/ 24. 58k params)
block_8_expand_BN ( - - / 768 params)
block_8_expand_BN/ beta ( 384 , 384 / 384 params)
block_8_expand_BN/ gamma ( 384 , 384 / 384 params)
block_8_project ( - - / 24. 58k params)
block_8_project/ kernel ( 1x1x384x64, 24. 58k/ 24. 58k params)
block_8_project_BN ( - - / 128 params)
block_8_project_BN/ beta ( 64 , 64 / 64 params)
block_8_project_BN/ gamma ( 64 , 64 / 64 params)
block_9_depthwise ( - - / 3. 46k params)
block_9_depthwise/ depthwise_kernel ( 3x3x384x1, 3. 46k/ 3. 46k params)
block_9_depthwise_BN ( - - / 768 params)
block_9_depthwise_BN/ beta ( 384 , 384 / 384 params)
block_9_depthwise_BN/ gamma ( 384 , 384 / 384 params)
block_9_expand ( - - / 24. 58k params)
block_9_expand/ kernel ( 1x1x64x384, 24. 58k/ 24. 58k params)
block_9_expand_BN ( - - / 768 params)
block_9_expand_BN/ beta ( 384 , 384 / 384 params)
block_9_expand_BN/ gamma ( 384 , 384 / 384 params)
block_9_project ( - - / 24. 58k params)
block_9_project/ kernel ( 1x1x384x64, 24. 58k/ 24. 58k params)
block_9_project_BN ( - - / 128 params)
block_9_project_BN/ beta ( 64 , 64 / 64 params)
block_9_project_BN/ gamma ( 64 , 64 / 64 params)
bn_Conv1 ( - - / 64 params)
bn_Conv1/ beta ( 32 , 32 / 32 params)
bn_Conv1/ gamma ( 32 , 32 / 32 params)
expanded_conv_depthwise ( - - / 288 params)
expanded_conv_depthwise/ depthwise_kernel ( 3x3x32x1, 288 / 288 params)
expanded_conv_depthwise_BN ( - - / 64 params)
expanded_conv_depthwise_BN/ beta ( 32 , 32 / 32 params)
expanded_conv_depthwise_BN/ gamma ( 32 , 32 / 32 params)
expanded_conv_project ( - - / 512 params)
expanded_conv_project/ kernel ( 1x1x32x16, 512 / 512 params)
expanded_conv_project_BN ( - - / 32 params)
expanded_conv_project_BN/ beta ( 16 , 16 / 16 params)
expanded_conv_project_BN/ gamma ( 16 , 16 / 16 params)
== == == == == == == == == == == End of Report== == == == == == == == == == == == ==
FLOPs: 4 , 572 , 193 ; Trainable params: 2 , 286 , 065
WARNING: tensorflow: From E: / master_ImRecognition/ main. py: 99 : The name tf. keras. backend. get_session is deprecated. Please use tf. compat. v1. keras. backend. get_session instead.
[ 0418 21 : 45 : 19 ] From E: / master_ImRecognition/ main. py: 99 : The name tf. keras. backend. get_session is deprecated. Please use tf. compat. v1. keras. backend. get_session instead.
2021 - 04 - 18 21 : 45 : 19.082183 : I tensorflow/ core/ common_runtime/ gpu/ gpu_device. cc: 1261 ] Device interconnect StreamExecutor with strength 1 edge matrix:
2021 - 04 - 18 21 : 45 : 19.082353 : I tensorflow/ core/ common_runtime/ gpu/ gpu_device. cc: 1267 ]
2021 - 04 - 18 21 : 45 : 19.082452 : I tensorflow/ compiler/ jit/ xla_gpu_device. cc: 99 ] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021 - 04 - 18 21 : 45 : 19.257091 : I tensorflow/ compiler/ mlir/ mlir_graph_optimization_pass. cc: 196 ] None of the MLIR optimization passes are enabled ( registered 0 passes)
Incomplete shape.
Incomplete shape.
Incomplete shape.
Incomplete shape.
Incomplete shape.
Incomplete shape.
== == == == == == == == == == == == = Options== == == == == == == == == == == == == == =
- max_depth 10000
- min_bytes 0
- min_peak_bytes 0
- min_residual_bytes 0
- min_output_bytes 0
- min_micros 0
- min_accelerator_micros 0
- min_cpu_micros 0
- min_params 0
- min_float_ops 1
- min_occurrence 0
- step - 1
- order_by float_ops
- account_type_regexes . *
- start_name_regexes . *
- trim_name_regexes
- show_name_regexes . *
- hide_name_regexes
- account_displayed_op_only true
- select float_ops
- output stdout:
== == == == == == == == == Model Analysis Report== == == == == == == == == == ==
Incomplete shape.
Incomplete shape.
Incomplete shape.
Incomplete shape.
Incomplete shape.
Incomplete shape.
Doc:
op: The nodes are operation kernel type , such as MatMul, Conv2D. Graph nodes belonging to the same type are aggregated together.
flops: Number of float operations. Note: Please read the implementation for the math behind it.
Profile:
node name |
Mul 2. 29m float_ops ( 100.00 % , 50.00 % )
Add 2. 25m float_ops ( 50.00 % , 49.25 % )
Sub 34. 27k float_ops ( 0.75 % , 0.75 % )
== == == == == == == == == == == End of Report== == == == == == == == == == == == ==
Model: "mobilenetv2_1.00_200"
方法二：
def get_flops ( model) :
run_meta = tf. RunMetadata( )
opts = tf. profiler. ProfileOptionBuilder. float_operation( )
flops = tf. profiler. profile( graph= K. get_session( ) . graph,
run_meta= run_meta,
cmd= 'op' ,
options= opts)
return flops. total_float_ops
结果与上述方法一基本相同，不同TensorFlow版本的代码差异。
方法三： 使用net_flops()函数的结果，与MobieNetV2论文结果较接近，但仍存在一定的误差：
Layer Name | Input Shape | Output Shape | Kernel Size | Filters | Strides | FLOPS
-- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
input_1 | [ 224 , 224 , 3 ] | [ 224 , 224 , 3 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
Conv1 | [ 224 , 224 , 3 ] | [ 112 , 112 , 32 ] | ( 3 , 3 ) | 32 | ( 2 , 2 ) | 21676032.0000
bn_Conv1 | [ 112 , 112 , 32 ] | [ 112 , 112 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
Conv1_relu | [ 112 , 112 , 32 ] | [ 112 , 112 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
expanded_conv_depthwise | [ 112 , 112 , 32 ] | [ 112 , 112 , 32 ] | ( 3 , 3 ) | 32 | ( 1 , 1 ) | 7225344.0000
expanded_conv_depthwise_BN | [ 112 , 112 , 32 ] | [ 112 , 112 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
expanded_conv_depthwise_relu | [ 112 , 112 , 32 ] | [ 112 , 112 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
expanded_conv_project | [ 112 , 112 , 32 ] | [ 112 , 112 , 16 ] | ( 1 , 1 ) | 16 | ( 1 , 1 ) | 12845056.0000
expanded_conv_project_BN | [ 112 , 112 , 16 ] | [ 112 , 112 , 16 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_expand | [ 112 , 112 , 16 ] | [ 112 , 112 , 96 ] | ( 1 , 1 ) | 96 | ( 1 , 1 ) | 38535168.0000
block_1_expand_BN | [ 112 , 112 , 96 ] | [ 112 , 112 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_expand_relu | [ 112 , 112 , 96 ] | [ 112 , 112 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_depthwise | [ 113 , 113 , 96 ] | [ 56 , 56 , 96 ] | ( 3 , 3 ) | 96 | ( 2 , 2 ) | 5516208.0000
block_1_depthwise_BN | [ 56 , 56 , 96 ] | [ 56 , 56 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_depthwise_relu | [ 56 , 56 , 96 ] | [ 56 , 56 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_project | [ 56 , 56 , 96 ] | [ 56 , 56 , 24 ] | ( 1 , 1 ) | 24 | ( 1 , 1 ) | 14450688.0000
block_1_project_BN | [ 56 , 56 , 24 ] | [ 56 , 56 , 24 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_expand | [ 56 , 56 , 24 ] | [ 56 , 56 , 144 ] | ( 1 , 1 ) | 144 | ( 1 , 1 ) | 21676032.0000
block_2_expand_BN | [ 56 , 56 , 144 ] | [ 56 , 56 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_expand_relu | [ 56 , 56 , 144 ] | [ 56 , 56 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_depthwise | [ 56 , 56 , 144 ] | [ 56 , 56 , 144 ] | ( 3 , 3 ) | 144 | ( 1 , 1 ) | 8128512.0000
block_2_depthwise_BN | [ 56 , 56 , 144 ] | [ 56 , 56 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_depthwise_relu | [ 56 , 56 , 144 ] | [ 56 , 56 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_project | [ 56 , 56 , 144 ] | [ 56 , 56 , 24 ] | ( 1 , 1 ) | 24 | ( 1 , 1 ) | 21676032.0000
block_2_project_BN | [ 56 , 56 , 24 ] | [ 56 , 56 , 24 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_add | [ 56 , 56 , 24 , 2 ] | [ 56 , 56 , 24 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 75264.0000
block_3_expand | [ 56 , 56 , 24 ] | [ 56 , 56 , 144 ] | ( 1 , 1 ) | 144 | ( 1 , 1 ) | 21676032.0000
block_3_expand_BN | [ 56 , 56 , 144 ] | [ 56 , 56 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_expand_relu | [ 56 , 56 , 144 ] | [ 56 , 56 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_depthwise | [ 57 , 57 , 144 ] | [ 28 , 28 , 144 ] | ( 3 , 3 ) | 144 | ( 2 , 2 ) | 2105352.0000
block_3_depthwise_BN | [ 28 , 28 , 144 ] | [ 28 , 28 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_depthwise_relu | [ 28 , 28 , 144 ] | [ 28 , 28 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_project | [ 28 , 28 , 144 ] | [ 28 , 28 , 32 ] | ( 1 , 1 ) | 32 | ( 1 , 1 ) | 7225344.0000
block_3_project_BN | [ 28 , 28 , 32 ] | [ 28 , 28 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_expand | [ 28 , 28 , 32 ] | [ 28 , 28 , 192 ] | ( 1 , 1 ) | 192 | ( 1 , 1 ) | 9633792.0000
block_4_expand_BN | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_expand_relu | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_depthwise | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | ( 3 , 3 ) | 192 | ( 1 , 1 ) | 2709504.0000
block_4_depthwise_BN | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_depthwise_relu | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_project | [ 28 , 28 , 192 ] | [ 28 , 28 , 32 ] | ( 1 , 1 ) | 32 | ( 1 , 1 ) | 9633792.0000
block_4_project_BN | [ 28 , 28 , 32 ] | [ 28 , 28 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_add | [ 28 , 28 , 32 , 2 ] | [ 28 , 28 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 25088.0000
block_5_expand | [ 28 , 28 , 32 ] | [ 28 , 28 , 192 ] | ( 1 , 1 ) | 192 | ( 1 , 1 ) | 9633792.0000
block_5_expand_BN | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_expand_relu | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_depthwise | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | ( 3 , 3 ) | 192 | ( 1 , 1 ) | 2709504.0000
block_5_depthwise_BN | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_depthwise_relu | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_project | [ 28 , 28 , 192 ] | [ 28 , 28 , 32 ] | ( 1 , 1 ) | 32 | ( 1 , 1 ) | 9633792.0000
block_5_project_BN | [ 28 , 28 , 32 ] | [ 28 , 28 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_add | [ 28 , 28 , 32 , 2 ] | [ 28 , 28 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 25088.0000
block_6_expand | [ 28 , 28 , 32 ] | [ 28 , 28 , 192 ] | ( 1 , 1 ) | 192 | ( 1 , 1 ) | 9633792.0000
block_6_expand_BN | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_expand_relu | [ 28 , 28 , 192 ] | [ 28 , 28 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_depthwise | [ 29 , 29 , 192 ] | [ 14 , 14 , 192 ] | ( 3 , 3 ) | 192 | ( 2 , 2 ) | 726624.0000
block_6_depthwise_BN | [ 14 , 14 , 192 ] | [ 14 , 14 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_depthwise_relu | [ 14 , 14 , 192 ] | [ 14 , 14 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_project | [ 14 , 14 , 192 ] | [ 14 , 14 , 64 ] | ( 1 , 1 ) | 64 | ( 1 , 1 ) | 4816896.0000
block_6_project_BN | [ 14 , 14 , 64 ] | [ 14 , 14 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_expand | [ 14 , 14 , 64 ] | [ 14 , 14 , 384 ] | ( 1 , 1 ) | 384 | ( 1 , 1 ) | 9633792.0000
block_7_expand_BN | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_expand_relu | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_depthwise | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | ( 3 , 3 ) | 384 | ( 1 , 1 ) | 1354752.0000
block_7_depthwise_BN | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_depthwise_relu | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_project | [ 14 , 14 , 384 ] | [ 14 , 14 , 64 ] | ( 1 , 1 ) | 64 | ( 1 , 1 ) | 9633792.0000
block_7_project_BN | [ 14 , 14 , 64 ] | [ 14 , 14 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_add | [ 14 , 14 , 64 , 2 ] | [ 14 , 14 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 12544.0000
block_8_expand | [ 14 , 14 , 64 ] | [ 14 , 14 , 384 ] | ( 1 , 1 ) | 384 | ( 1 , 1 ) | 9633792.0000
block_8_expand_BN | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_expand_relu | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_depthwise | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | ( 3 , 3 ) | 384 | ( 1 , 1 ) | 1354752.0000
block_8_depthwise_BN | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_depthwise_relu | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_project | [ 14 , 14 , 384 ] | [ 14 , 14 , 64 ] | ( 1 , 1 ) | 64 | ( 1 , 1 ) | 9633792.0000
block_8_project_BN | [ 14 , 14 , 64 ] | [ 14 , 14 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_add | [ 14 , 14 , 64 , 2 ] | [ 14 , 14 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 12544.0000
block_9_expand | [ 14 , 14 , 64 ] | [ 14 , 14 , 384 ] | ( 1 , 1 ) | 384 | ( 1 , 1 ) | 9633792.0000
block_9_expand_BN | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_expand_relu | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_depthwise | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | ( 3 , 3 ) | 384 | ( 1 , 1 ) | 1354752.0000
block_9_depthwise_BN | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_depthwise_relu | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_project | [ 14 , 14 , 384 ] | [ 14 , 14 , 64 ] | ( 1 , 1 ) | 64 | ( 1 , 1 ) | 9633792.0000
block_9_project_BN | [ 14 , 14 , 64 ] | [ 14 , 14 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_add | [ 14 , 14 , 64 , 2 ] | [ 14 , 14 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 12544.0000
block_10_expand | [ 14 , 14 , 64 ] | [ 14 , 14 , 384 ] | ( 1 , 1 ) | 384 | ( 1 , 1 ) | 9633792.0000
block_10_expand_BN | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_10_expand_relu | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_10_depthwise | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | ( 3 , 3 ) | 384 | ( 1 , 1 ) | 1354752.0000
block_10_depthwise_BN | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_10_depthwise_relu | [ 14 , 14 , 384 ] | [ 14 , 14 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_10_project | [ 14 , 14 , 384 ] | [ 14 , 14 , 96 ] | ( 1 , 1 ) | 96 | ( 1 , 1 ) | 14450688.0000
block_10_project_BN | [ 14 , 14 , 96 ] | [ 14 , 14 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_expand | [ 14 , 14 , 96 ] | [ 14 , 14 , 576 ] | ( 1 , 1 ) | 576 | ( 1 , 1 ) | 21676032.0000
block_11_expand_BN | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_expand_relu | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_depthwise | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | ( 3 , 3 ) | 576 | ( 1 , 1 ) | 2032128.0000
block_11_depthwise_BN | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_depthwise_relu | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_project | [ 14 , 14 , 576 ] | [ 14 , 14 , 96 ] | ( 1 , 1 ) | 96 | ( 1 , 1 ) | 21676032.0000
block_11_project_BN | [ 14 , 14 , 96 ] | [ 14 , 14 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_add | [ 14 , 14 , 96 , 2 ] | [ 14 , 14 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 18816.0000
block_12_expand | [ 14 , 14 , 96 ] | [ 14 , 14 , 576 ] | ( 1 , 1 ) | 576 | ( 1 , 1 ) | 21676032.0000
block_12_expand_BN | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_expand_relu | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_depthwise | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | ( 3 , 3 ) | 576 | ( 1 , 1 ) | 2032128.0000
block_12_depthwise_BN | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_depthwise_relu | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_project | [ 14 , 14 , 576 ] | [ 14 , 14 , 96 ] | ( 1 , 1 ) | 96 | ( 1 , 1 ) | 21676032.0000
block_12_project_BN | [ 14 , 14 , 96 ] | [ 14 , 14 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_add | [ 14 , 14 , 96 , 2 ] | [ 14 , 14 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 18816.0000
block_13_expand | [ 14 , 14 , 96 ] | [ 14 , 14 , 576 ] | ( 1 , 1 ) | 576 | ( 1 , 1 ) | 21676032.0000
block_13_expand_BN | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_expand_relu | [ 14 , 14 , 576 ] | [ 14 , 14 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_depthwise | [ 15 , 15 , 576 ] | [ 7 , 7 , 576 ] | ( 3 , 3 ) | 576 | ( 2 , 2 ) | 583200.0000
block_13_depthwise_BN | [ 7 , 7 , 576 ] | [ 7 , 7 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_depthwise_relu | [ 7 , 7 , 576 ] | [ 7 , 7 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_project | [ 7 , 7 , 576 ] | [ 7 , 7 , 160 ] | ( 1 , 1 ) | 160 | ( 1 , 1 ) | 9031680.0000
block_13_project_BN | [ 7 , 7 , 160 ] | [ 7 , 7 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_expand | [ 7 , 7 , 160 ] | [ 7 , 7 , 960 ] | ( 1 , 1 ) | 960 | ( 1 , 1 ) | 15052800.0000
block_14_expand_BN | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_expand_relu | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_depthwise | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | ( 3 , 3 ) | 960 | ( 1 , 1 ) | 846720.0000
block_14_depthwise_BN | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_depthwise_relu | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_project | [ 7 , 7 , 960 ] | [ 7 , 7 , 160 ] | ( 1 , 1 ) | 160 | ( 1 , 1 ) | 15052800.0000
block_14_project_BN | [ 7 , 7 , 160 ] | [ 7 , 7 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_add | [ 7 , 7 , 160 , 2 ] | [ 7 , 7 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 7840.0000
block_15_expand | [ 7 , 7 , 160 ] | [ 7 , 7 , 960 ] | ( 1 , 1 ) | 960 | ( 1 , 1 ) | 15052800.0000
block_15_expand_BN | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_expand_relu | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_depthwise | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | ( 3 , 3 ) | 960 | ( 1 , 1 ) | 846720.0000
block_15_depthwise_BN | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_depthwise_relu | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_project | [ 7 , 7 , 960 ] | [ 7 , 7 , 160 ] | ( 1 , 1 ) | 160 | ( 1 , 1 ) | 15052800.0000
block_15_project_BN | [ 7 , 7 , 160 ] | [ 7 , 7 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_add | [ 7 , 7 , 160 , 2 ] | [ 7 , 7 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 7840.0000
block_16_expand | [ 7 , 7 , 160 ] | [ 7 , 7 , 960 ] | ( 1 , 1 ) | 960 | ( 1 , 1 ) | 15052800.0000
block_16_expand_BN | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_16_expand_relu | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_16_depthwise | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | ( 3 , 3 ) | 960 | ( 1 , 1 ) | 846720.0000
block_16_depthwise_BN | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_16_depthwise_relu | [ 7 , 7 , 960 ] | [ 7 , 7 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_16_project | [ 7 , 7 , 960 ] | [ 7 , 7 , 320 ] | ( 1 , 1 ) | 320 | ( 1 , 1 ) | 30105600.0000
block_16_project_BN | [ 7 , 7 , 320 ] | [ 7 , 7 , 320 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
Conv_1 | [ 7 , 7 , 320 ] | [ 7 , 7 , 1280 ] | ( 1 , 1 ) | 1280 | ( 1 , 1 ) | 40140800.0000
Conv_1_bn | [ 7 , 7 , 1280 ] | [ 7 , 7 , 1280 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
out_relu | [ 7 , 7 , 1280 ] | [ 7 , 7 , 1280 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
global_average_pooling2d | [ 7 , 7 , 1280 ] | [ [ 1280 ] , 1 , 1 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 62720.0000
Tensor ( "global_average_pooling2d/Mean:0" , shape= ( None, 1280 ) , dtype= float32)
predictions | 1280 | [ 1000 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 2560000.0000
Total FLOPs: 602 , 122 , 488.000000
Total MACCs: 300 , 921 , 692.000000
以上是keras的application中给出的代码实现，以下是自实现MobileNet的结果测试：
2021 - 04 - 18 21 : 45 : 15.332238 : W tensorflow/ core/ common_runtime/ gpu/ gpu_device. cc: 1757 ] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https: // www. tensorflow. org/ install/ gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices. . .
Layer Name | Input Shape | Output Shape | Kernel Size | Filters | Strides | FLOPS
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
input_1 | [ 200 , 12 , 1 ] | [ 200 , 12 , 1 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
Conv1_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
Conv1 | [ 201 , 13 , 1 ] | [ 100 , 6 , 32 ] | ( 3 , 3 ) | 32 | ( 2 , 2 ) | 376272.0000
bn_Conv1 | [ 100 , 6 , 32 ] | [ 100 , 6 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
Conv1_relu | [ 100 , 6 , 32 ] | [ 100 , 6 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
expanded_conv_depthwise | [ 100 , 6 , 32 ] | [ 100 , 6 , 32 ] | ( 3 , 3 ) | 32 | ( 1 , 1 ) | 345600.0000
expanded_conv_depthwise_BN | [ 100 , 6 , 32 ] | [ 100 , 6 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
expanded_conv_depthwise_relu | [ 100 , 6 , 32 ] | [ 100 , 6 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
expanded_conv_project | [ 100 , 6 , 32 ] | [ 100 , 6 , 16 ] | ( 1 , 1 ) | 16 | ( 1 , 1 ) | 614400.0000
expanded_conv_project_BN | [ 100 , 6 , 16 ] | [ 100 , 6 , 16 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_expand | [ 100 , 6 , 16 ] | [ 100 , 6 , 96 ] | ( 1 , 1 ) | 96 | ( 1 , 1 ) | 1843200.0000
block_1_expand_BN | [ 100 , 6 , 96 ] | [ 100 , 6 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_expand_relu | [ 100 , 6 , 96 ] | [ 100 , 6 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_depthwise | [ 101 , 7 , 96 ] | [ 50 , 3 , 96 ] | ( 3 , 3 ) | 96 | ( 2 , 2 ) | 305424.0000
block_1_depthwise_BN | [ 50 , 3 , 96 ] | [ 50 , 3 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_depthwise_relu | [ 50 , 3 , 96 ] | [ 50 , 3 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_1_project | [ 50 , 3 , 96 ] | [ 50 , 3 , 24 ] | ( 1 , 1 ) | 24 | ( 1 , 1 ) | 691200.0000
block_1_project_BN | [ 50 , 3 , 24 ] | [ 50 , 3 , 24 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_expand | [ 50 , 3 , 24 ] | [ 50 , 3 , 144 ] | ( 1 , 1 ) | 144 | ( 1 , 1 ) | 1036800.0000
block_2_expand_BN | [ 50 , 3 , 144 ] | [ 50 , 3 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_expand_relu | [ 50 , 3 , 144 ] | [ 50 , 3 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_depthwise | [ 50 , 3 , 144 ] | [ 50 , 3 , 144 ] | ( 3 , 3 ) | 144 | ( 1 , 1 ) | 388800.0000
block_2_depthwise_BN | [ 50 , 3 , 144 ] | [ 50 , 3 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_depthwise_relu | [ 50 , 3 , 144 ] | [ 50 , 3 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_project | [ 50 , 3 , 144 ] | [ 50 , 3 , 24 ] | ( 1 , 1 ) | 24 | ( 1 , 1 ) | 1036800.0000
block_2_project_BN | [ 50 , 3 , 24 ] | [ 50 , 3 , 24 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_2_add | [ 50 , 3 , 24 , 2 ] | [ 50 , 3 , 24 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 3600.0000
block_3_expand | [ 50 , 3 , 24 ] | [ 50 , 3 , 144 ] | ( 1 , 1 ) | 144 | ( 1 , 1 ) | 1036800.0000
block_3_expand_BN | [ 50 , 3 , 144 ] | [ 50 , 3 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_expand_relu | [ 50 , 3 , 144 ] | [ 50 , 3 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_depthwise | [ 51 , 5 , 144 ] | [ 25 , 2 , 144 ] | ( 3 , 3 ) | 144 | ( 2 , 2 ) | 165240.0000
block_3_depthwise_BN | [ 25 , 2 , 144 ] | [ 25 , 2 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_depthwise_relu | [ 25 , 2 , 144 ] | [ 25 , 2 , 144 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_3_project | [ 25 , 2 , 144 ] | [ 25 , 2 , 32 ] | ( 1 , 1 ) | 32 | ( 1 , 1 ) | 460800.0000
block_3_project_BN | [ 25 , 2 , 32 ] | [ 25 , 2 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_expand | [ 25 , 2 , 32 ] | [ 25 , 2 , 192 ] | ( 1 , 1 ) | 192 | ( 1 , 1 ) | 614400.0000
block_4_expand_BN | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_expand_relu | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_depthwise | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | ( 3 , 3 ) | 192 | ( 1 , 1 ) | 172800.0000
block_4_depthwise_BN | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_depthwise_relu | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_project | [ 25 , 2 , 192 ] | [ 25 , 2 , 32 ] | ( 1 , 1 ) | 32 | ( 1 , 1 ) | 614400.0000
block_4_project_BN | [ 25 , 2 , 32 ] | [ 25 , 2 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_4_add | [ 25 , 2 , 32 , 2 ] | [ 25 , 2 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 1600.0000
block_5_expand | [ 25 , 2 , 32 ] | [ 25 , 2 , 192 ] | ( 1 , 1 ) | 192 | ( 1 , 1 ) | 614400.0000
block_5_expand_BN | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_expand_relu | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_depthwise | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | ( 3 , 3 ) | 192 | ( 1 , 1 ) | 172800.0000
block_5_depthwise_BN | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_depthwise_relu | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_project | [ 25 , 2 , 192 ] | [ 25 , 2 , 32 ] | ( 1 , 1 ) | 32 | ( 1 , 1 ) | 614400.0000
block_5_project_BN | [ 25 , 2 , 32 ] | [ 25 , 2 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_5_add | [ 25 , 2 , 32 , 2 ] | [ 25 , 2 , 32 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 1600.0000
block_6_expand | [ 25 , 2 , 32 ] | [ 25 , 2 , 192 ] | ( 1 , 1 ) | 192 | ( 1 , 1 ) | 614400.0000
block_6_expand_BN | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_expand_relu | [ 25 , 2 , 192 ] | [ 25 , 2 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_depthwise | [ 27 , 3 , 192 ] | [ 13 , 1 , 192 ] | ( 3 , 3 ) | 192 | ( 2 , 2 ) | 69984.0000
block_6_depthwise_BN | [ 13 , 1 , 192 ] | [ 13 , 1 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_depthwise_relu | [ 13 , 1 , 192 ] | [ 13 , 1 , 192 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_6_project | [ 13 , 1 , 192 ] | [ 13 , 1 , 64 ] | ( 1 , 1 ) | 64 | ( 1 , 1 ) | 319488.0000
block_6_project_BN | [ 13 , 1 , 64 ] | [ 13 , 1 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_expand | [ 13 , 1 , 64 ] | [ 13 , 1 , 384 ] | ( 1 , 1 ) | 384 | ( 1 , 1 ) | 638976.0000
block_7_expand_BN | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_expand_relu | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_depthwise | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | ( 3 , 3 ) | 384 | ( 1 , 1 ) | 89856.0000
block_7_depthwise_BN | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_depthwise_relu | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_project | [ 13 , 1 , 384 ] | [ 13 , 1 , 64 ] | ( 1 , 1 ) | 64 | ( 1 , 1 ) | 638976.0000
block_7_project_BN | [ 13 , 1 , 64 ] | [ 13 , 1 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_7_add | [ 13 , 1 , 64 , 2 ] | [ 13 , 1 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 832.0000
block_8_expand | [ 13 , 1 , 64 ] | [ 13 , 1 , 384 ] | ( 1 , 1 ) | 384 | ( 1 , 1 ) | 638976.0000
block_8_expand_BN | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_expand_relu | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_depthwise | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | ( 3 , 3 ) | 384 | ( 1 , 1 ) | 89856.0000
block_8_depthwise_BN | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_depthwise_relu | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_project | [ 13 , 1 , 384 ] | [ 13 , 1 , 64 ] | ( 1 , 1 ) | 64 | ( 1 , 1 ) | 638976.0000
block_8_project_BN | [ 13 , 1 , 64 ] | [ 13 , 1 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_8_add | [ 13 , 1 , 64 , 2 ] | [ 13 , 1 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 832.0000
block_9_expand | [ 13 , 1 , 64 ] | [ 13 , 1 , 384 ] | ( 1 , 1 ) | 384 | ( 1 , 1 ) | 638976.0000
block_9_expand_BN | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_expand_relu | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_depthwise | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | ( 3 , 3 ) | 384 | ( 1 , 1 ) | 89856.0000
block_9_depthwise_BN | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_depthwise_relu | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_project | [ 13 , 1 , 384 ] | [ 13 , 1 , 64 ] | ( 1 , 1 ) | 64 | ( 1 , 1 ) | 638976.0000
block_9_project_BN | [ 13 , 1 , 64 ] | [ 13 , 1 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_9_add | [ 13 , 1 , 64 , 2 ] | [ 13 , 1 , 64 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 832.0000
block_10_expand | [ 13 , 1 , 64 ] | [ 13 , 1 , 384 ] | ( 1 , 1 ) | 384 | ( 1 , 1 ) | 638976.0000
block_10_expand_BN | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_10_expand_relu | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_10_depthwise | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | ( 3 , 3 ) | 384 | ( 1 , 1 ) | 89856.0000
block_10_depthwise_BN | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_10_depthwise_relu | [ 13 , 1 , 384 ] | [ 13 , 1 , 384 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_10_project | [ 13 , 1 , 384 ] | [ 13 , 1 , 96 ] | ( 1 , 1 ) | 96 | ( 1 , 1 ) | 958464.0000
block_10_project_BN | [ 13 , 1 , 96 ] | [ 13 , 1 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_expand | [ 13 , 1 , 96 ] | [ 13 , 1 , 576 ] | ( 1 , 1 ) | 576 | ( 1 , 1 ) | 1437696.0000
block_11_expand_BN | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_expand_relu | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_depthwise | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | ( 3 , 3 ) | 576 | ( 1 , 1 ) | 134784.0000
block_11_depthwise_BN | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_depthwise_relu | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_project | [ 13 , 1 , 576 ] | [ 13 , 1 , 96 ] | ( 1 , 1 ) | 96 | ( 1 , 1 ) | 1437696.0000
block_11_project_BN | [ 13 , 1 , 96 ] | [ 13 , 1 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_11_add | [ 13 , 1 , 96 , 2 ] | [ 13 , 1 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 1248.0000
block_12_expand | [ 13 , 1 , 96 ] | [ 13 , 1 , 576 ] | ( 1 , 1 ) | 576 | ( 1 , 1 ) | 1437696.0000
block_12_expand_BN | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_expand_relu | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_depthwise | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | ( 3 , 3 ) | 576 | ( 1 , 1 ) | 134784.0000
block_12_depthwise_BN | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_depthwise_relu | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_project | [ 13 , 1 , 576 ] | [ 13 , 1 , 96 ] | ( 1 , 1 ) | 96 | ( 1 , 1 ) | 1437696.0000
block_12_project_BN | [ 13 , 1 , 96 ] | [ 13 , 1 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_12_add | [ 13 , 1 , 96 , 2 ] | [ 13 , 1 , 96 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 1248.0000
block_13_expand | [ 13 , 1 , 96 ] | [ 13 , 1 , 576 ] | ( 1 , 1 ) | 576 | ( 1 , 1 ) | 1437696.0000
block_13_expand_BN | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_expand_relu | [ 13 , 1 , 576 ] | [ 13 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_pad | [ '' , '' , '' ] | [ '' , '' , '' ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_depthwise | [ 15 , 3 , 576 ] | [ 7 , 1 , 576 ] | ( 3 , 3 ) | 576 | ( 2 , 2 ) | 116640.0000
block_13_depthwise_BN | [ 7 , 1 , 576 ] | [ 7 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_depthwise_relu | [ 7 , 1 , 576 ] | [ 7 , 1 , 576 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_13_project | [ 7 , 1 , 576 ] | [ 7 , 1 , 160 ] | ( 1 , 1 ) | 160 | ( 1 , 1 ) | 1290240.0000
block_13_project_BN | [ 7 , 1 , 160 ] | [ 7 , 1 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_expand | [ 7 , 1 , 160 ] | [ 7 , 1 , 960 ] | ( 1 , 1 ) | 960 | ( 1 , 1 ) | 2150400.0000
block_14_expand_BN | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_expand_relu | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_depthwise | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | ( 3 , 3 ) | 960 | ( 1 , 1 ) | 120960.0000
block_14_depthwise_BN | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_depthwise_relu | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_project | [ 7 , 1 , 960 ] | [ 7 , 1 , 160 ] | ( 1 , 1 ) | 160 | ( 1 , 1 ) | 2150400.0000
block_14_project_BN | [ 7 , 1 , 160 ] | [ 7 , 1 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_14_add | [ 7 , 1 , 160 , 2 ] | [ 7 , 1 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 1120.0000
block_15_expand | [ 7 , 1 , 160 ] | [ 7 , 1 , 960 ] | ( 1 , 1 ) | 960 | ( 1 , 1 ) | 2150400.0000
block_15_expand_BN | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_expand_relu | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_depthwise | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | ( 3 , 3 ) | 960 | ( 1 , 1 ) | 120960.0000
block_15_depthwise_BN | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_depthwise_relu | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_project | [ 7 , 1 , 960 ] | [ 7 , 1 , 160 ] | ( 1 , 1 ) | 160 | ( 1 , 1 ) | 2150400.0000
block_15_project_BN | [ 7 , 1 , 160 ] | [ 7 , 1 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_15_add | [ 7 , 1 , 160 , 2 ] | [ 7 , 1 , 160 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 1120.0000
block_16_expand | [ 7 , 1 , 160 ] | [ 7 , 1 , 960 ] | ( 1 , 1 ) | 960 | ( 1 , 1 ) | 2150400.0000
block_16_expand_BN | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_16_expand_relu | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_16_depthwise | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | ( 3 , 3 ) | 960 | ( 1 , 1 ) | 120960.0000
block_16_depthwise_BN | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_16_depthwise_relu | [ 7 , 1 , 960 ] | [ 7 , 1 , 960 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
block_16_project | [ 7 , 1 , 960 ] | [ 7 , 1 , 320 ] | ( 1 , 1 ) | 320 | ( 1 , 1 ) | 4300800.0000
block_16_project_BN | [ 7 , 1 , 320 ] | [ 7 , 1 , 320 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
Conv_1 | [ 7 , 1 , 320 ] | [ 7 , 1 , 1280 ] | ( 1 , 1 ) | 1280 | ( 1 , 1 ) | 5734400.0000
Conv_1_bn | [ 7 , 1 , 1280 ] | [ 7 , 1 , 1280 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
out_relu | [ 7 , 1 , 1280 ] | [ 7 , 1 , 1280 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 0.0000
global_average_pooling2d | [ 7 , 1 , 1280 ] | [ [ 1280 ] , 1 , 1 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 8960.0000
Tensor( "global_average_pooling2d/Mean:0" , shape= ( None , 1280 ) , dtype= float32)
Logits | 1280 | [ 49 ] | [ 0 , 0 ] | [ 0 , 0 ] | [ 1 , 1 ] | 125440.0000
Total FLOPs: 48 , 062 , 568.000000
Total MACCs: 24 , 019 , 788.000000
以下是论文原文给出的数据：
