Formation of neural network architectures of models and downloading their weights to obtain the personality traits scores (audio and video fusion)
_b5.av_models_b5_
- Neural network models 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: 1.0.0a16 License: BSD License
Formation of neural network architectures of models
[4]:
res_load_av_models_b5 = _b5.load_av_models_b5(
show_summary = False, # Displaying the formed neural network architecture of the model
out = True, # Display
runtime = True, # Runtime count
run = True # Run blocking
)
[2023-12-14 22:44:38] Formation of neural network architectures of models for obtaining the personality traits scores (multimodal fusion) …
— Runtime: 0.095 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_openness = _b5.weights_for_big5_['av']['fi']['b5']['openness']['sberdisk']
url_conscientiousness = _b5.weights_for_big5_['av']['fi']['b5']['conscientiousness']['sberdisk']
url_extraversion = _b5.weights_for_big5_['av']['fi']['b5']['extraversion']['sberdisk']
url_agreeableness = _b5.weights_for_big5_['av']['fi']['b5']['agreeableness']['sberdisk']
url_non_neuroticism = _b5.weights_for_big5_['av']['fi']['b5']['non_neuroticism']['sberdisk']
res_load_av_models_weights_b5 = _b5.load_av_models_weights_b5(
url_openness = url_openness, # Openness
url_conscientiousness = url_conscientiousness, # Conscientiousness
url_extraversion = url_extraversion, # Extraversion
url_agreeableness = url_agreeableness, # Agreeableness
url_non_neuroticism = url_non_neuroticism, # Non-Neuroticism
force_reload = True, # 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
)
[2023-12-14 22:44:53] Downloading the weights of neural network models to obtain the personality traits scores (multimodal fusion) …
[2023-12-14 22:44:53] File download “weights_2022-08-28_11-14-35.h5” (100.0%) … Openness
[2023-12-14 22:44:54] File download “weights_2022-08-28_11-08-10.h5” (100.0%) … Conscientiousness
[2023-12-14 22:44:54] File download “weights_2022-08-28_11-17-57.h5” (100.0%) … Extraversion
[2023-12-14 22:44:54] File download “weights_2022-08-28_11-25-11.h5” (100.0%) … Agreeableness
[2023-12-14 22:44:54] File download “weights_2022-06-14_21-44-09.h5” (100.0%) … Non-Neuroticism
— Runtime: 0.914 sec. —
Displaying the formed neural network architecture of the model
Openness
Conscientiousness
Extraversion
Agreeableness
Non-Neuroticism
[6]:
_b5.av_models_b5_['openness'].summary()
Model: "model"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 64)] 0
dense_1 (Dense) (None, 1) 65
activ_1 (Activation) (None, 1) 0
=================================================================
Total params: 65 (260.00 Byte)
Trainable params: 65 (260.00 Byte)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________