Formation of the neural network architecture of the model and downloading its weights to obtain features / scores based on deep features (audio modality)
_b5.audio_model_nn_
- Neural network model tf.keras.Model for obtaining features / scores based on deep features
Import required packages
[2]:
from oceanai.modules.lab.build import Run
Build
[3]:
_b5 = Run(
lang = 'en', # Interface 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
)
[2023-12-10 16:45:19] OCEANAI - personality 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 the neural network architecture of the model
[4]:
res_load_audio_model_nn = _b5.load_audio_model_nn(
show_summary = False, # Display of the generated neural network архитектуры модели
out = True, # Display
runtime = True, # Runtime count
run = True # Run blocking
)
[2023-12-10 16:45:19] Formation of a neural network architecture for obtaining scores by deep features (audio modality) …
— Runtime: 1.221 sec. —
Downloading the weights of the neural network model
[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_['audio']['fi']['nn']['sberdisk']
res_load_audio_model_weights_nn = _b5.load_audio_model_weights_nn(
url = url, # Full path to the file with weights of the neural network model
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
)
[2023-12-10 16:45:23] Downloading the weights of the neural network model to obtain scores by deep features (audio modality) …
[2023-12-10 16:45:27] File download “weights_2022-05-03_07-46-14.h5” (100.0%) …
— Runtime: 4.175 sec. —
Displaying the formed neural network architecture of the model
[6]:
_b5.audio_model_nn_.summary()
Model: "model_1"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 224, 224, 3)] 0
block1_conv1 (Conv2D) (None, 224, 224, 64) 1792
block1_conv2 (Conv2D) (None, 224, 224, 64) 36928
block1_pool (MaxPooling2D) (None, 112, 112, 64) 0
block2_conv1 (Conv2D) (None, 112, 112, 128) 73856
block2_conv2 (Conv2D) (None, 112, 112, 128) 147584
block2_pool (MaxPooling2D) (None, 56, 56, 128) 0
block3_conv1 (Conv2D) (None, 56, 56, 256) 295168
block3_conv2 (Conv2D) (None, 56, 56, 256) 590080
block3_conv3 (Conv2D) (None, 56, 56, 256) 590080
block3_pool (MaxPooling2D) (None, 28, 28, 256) 0
block4_conv1 (Conv2D) (None, 28, 28, 512) 1180160
block4_conv2 (Conv2D) (None, 28, 28, 512) 2359808
block4_conv3 (Conv2D) (None, 28, 28, 512) 2359808
block4_pool (MaxPooling2D) (None, 14, 14, 512) 0
block5_conv1 (Conv2D) (None, 14, 14, 512) 2359808
block5_conv2 (Conv2D) (None, 14, 14, 512) 2359808
block5_conv3 (Conv2D) (None, 14, 14, 512) 2359808
block5_pool (MaxPooling2D) (None, 7, 7, 512) 0
flatten (Flatten) (None, 25088) 0
dense (Dense) (None, 512) 12845568
dropout (Dropout) (None, 512) 0
dense_256 (Dense) (None, 256) 131328
dense_1 (Dense) (None, 5) 1285
=================================================================
Total params: 27,692,869
Trainable params: 27,692,869
Non-trainable params: 0
_________________________________________________________________