What is the dimension of the output of each layer?e If the output has 3 dimensions, you should use height x width x depth to indicate the dimension.e If the output has 2 dimensions, you should use height x width to indicate the dimension.e If the output is a vector, you should use height x 1 to indicate the dimension.e

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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For the following source code section:e
# build model
model =
Sequential()
model.add(Conv2D(filters=16, input_shape=(32, 32, 3), kernel_size=(3, 3),
strides=(1, 1), padding='same', activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2), padding='valid'))
model.add(Conv2D(filters=32, kernel_size=(3, 3), strides=(1, 1),
padding='same', activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2), padding='valid'))
model.add(Flatten())
model.add(Dense(units=1024, activation='relu'))
model.add(Dense(units=512, activation='relu'))
model.add(Dense(units=10, activation='softmax'))
What is the dimension of the output of each layer?e
If the output has 3 dimensions, you should use height x width x depth to indicate the
dimension.e
If the output has 2 dimensions, you should use height x width to indicate the dimension.e
If the output is a vector, you should use height x 1 to indicate the dimension.e
Transcribed Image Text:For the following source code section:e # build model model = Sequential() model.add(Conv2D(filters=16, input_shape=(32, 32, 3), kernel_size=(3, 3), strides=(1, 1), padding='same', activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2), padding='valid')) model.add(Conv2D(filters=32, kernel_size=(3, 3), strides=(1, 1), padding='same', activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2), padding='valid')) model.add(Flatten()) model.add(Dense(units=1024, activation='relu')) model.add(Dense(units=512, activation='relu')) model.add(Dense(units=10, activation='softmax')) What is the dimension of the output of each layer?e If the output has 3 dimensions, you should use height x width x depth to indicate the dimension.e If the output has 2 dimensions, you should use height x width to indicate the dimension.e If the output is a vector, you should use height x 1 to indicate the dimension.e
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