Formation of neural network architectures of models and downloading their weights to obtain the personality traits scores (audio, video and tex fusion)
_b5.avt_model_b5_- Neural network model tf.keras.Model for obtaining the personality traits scores
Import required packages
[2]:
from oceanai.modules.lab.build import Run
Build
[3]:
_b5 = Run(
lang = 'en', # Inference language
color_simple = '#333', # Plain text color (hexadecimal code)
color_info = '#1776D2', # The color of the text containing the information (hexadecimal code)
color_err = '#FF0000', # Error text color (hexadecimal code)
color_true = '#008001', # Text color containing positive information (hexadecimal code)
bold_text = True, # Bold text
num_to_df_display = 30, # Number of rows to display in tables
text_runtime = 'Runtime', # Runtime text
metadata = True # Displaying information about library
)
[2023-12-14 22:44:38] OCEANAI - personal traits: Authors: Elena Ryumina [ryumina_ev@mail.ru] Dmitry Ryumin [dl_03.03.1991@mail.ru] Alexey Karpov [karpov@iias.spb.su] Maintainers: Elena Ryumina [ryumina_ev@mail.ru] Dmitry Ryumin [dl_03.03.1991@mail.ru] Version: 1.0.0a5 License: BSD License
Formation of neural network architectures of models
[4]:
res_load_avt_model_b5 = _b5.load_avt_model_b5(
show_summary = False, # Displaying the formed neural network architecture of the model
out = True, # Display
runtime = True, # Runtime count
run = True # Run blocking
)
[2023-12-11 09:46:45] Formation of neural network architectures of models for obtaining the personality traits scores (multimodal fusion) …
— Runtime: 0.814 sec. —
Downloading weights of neural network models
[5]:
# Core settings
_b5.path_to_save_ = './models' # Directory to save the file
_b5.chunk_size_ = 2000000 # File download size from network in 1 step
url = _b5.weights_for_big5_['avt']['fi']['b5']['sberdisk']
res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(
url = url,
force_reload = False, # Forced download of a file with weights of a neural network model from the network
out = True, # Display
runtime = True, # Runtime count
run = True # Run blocking
)
[2023-12-11 09:46:46] Downloading the weights of neural network models to obtain the personality traits scores (multimodal fusion) …
[2023-12-11 09:46:46] File download “avt_fi_2023-12-03_11-36-51.h5”
— Runtime: 0.218 sec. —
Displaying the formed neural network architecture of the model
[6]:
_b5.avt_model_b5_.summary()
Model: "model"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
hc_t (InputLayer) [(None, 128)] 0 []
hc_a (InputLayer) [(None, 256)] 0 []
nn_t (InputLayer) [(None, 128)] 0 []
nn_a (InputLayer) [(None, 512)] 0 []
hc_v (InputLayer) [(None, 256)] 0 []
nn_v (InputLayer) [(None, 2048)] 0 []
ln_hc_t (LayerNormalization) (None, 128) 256 ['hc_t[0][0]']
ln_hc_a (LayerNormalization) (None, 256) 512 ['hc_a[0][0]']
ln_nn_t (LayerNormalization) (None, 128) 256 ['nn_t[0][0]']
ln_nn_a (LayerNormalization) (None, 512) 1024 ['nn_a[0][0]']
ln_hc_v (LayerNormalization) (None, 256) 512 ['hc_v[0][0]']
ln_nn_v (LayerNormalization) (None, 2048) 4096 ['nn_v[0][0]']
gata (GFL) (None, 64) 131072 ['ln_hc_t[0][0]',
'ln_hc_a[0][0]',
'ln_nn_t[0][0]',
'ln_nn_a[0][0]']
gatv (GFL) (None, 64) 327680 ['ln_hc_t[0][0]',
'ln_hc_v[0][0]',
'ln_nn_t[0][0]',
'ln_nn_v[0][0]']
gaav (GFL) (None, 64) 393216 ['ln_hc_a[0][0]',
'ln_hc_v[0][0]',
'ln_nn_a[0][0]',
'ln_nn_v[0][0]']
tf.concat (TFOpLambda) (None, 192) 0 ['gata[0][0]',
'gatv[0][0]',
'gaav[0][0]']
dense (Dense) (None, 50) 9650 ['tf.concat[0][0]']
dence_cl (Dense) (None, 5) 255 ['dense[0][0]']
==================================================================================================
Total params: 868,529
Trainable params: 868,529
Non-trainable params: 0
__________________________________________________________________________________________________