confused about parameter updates and forward/backward pass according to batches and epochs in CNN?
$begingroup$
I am working on a CNN model, the code written in tensorflow, I did some googling about parameter updates such as weights ana biases when method is optimized and the loss is computed, two things made me confuse:
1- after output layer, the data goes to loss, the loss compute and then the model is begin optimization or in reverse of that?
2- Is parameters updated after each mini-batch fed to network (i.e. the forward and backward pass is done for every batch) or only updates when one epoch is completed? why some tutorials said that each epoch is ba forward/backward pass?
anyone can clarify it please? if with a reference its better for me.
tensorflow cnn
asked 3 mins ago
honar.cshonar.cs
1139
$endgroup$
add a comment |
$begingroup$
I am working on a CNN model, the code written in tensorflow, I did some googling about parameter updates such as weights ana biases when method is optimized and the loss is computed, two things made me confuse:
1- after output layer, the data goes to loss, the loss compute and then the model is begin optimization or in reverse of that?
2- Is parameters updated after each mini-batch fed to network (i.e. the forward and backward pass is done for every batch) or only updates when one epoch is completed? why some tutorials said that each epoch is ba forward/backward pass?
anyone can clarify it please? if with a reference its better for me.
tensorflow cnn
asked 3 mins ago
honar.cshonar.cs
1139
$endgroup$
add a comment |
$begingroup$
I am working on a CNN model, the code written in tensorflow, I did some googling about parameter updates such as weights ana biases when method is optimized and the loss is computed, two things made me confuse:
1- after output layer, the data goes to loss, the loss compute and then the model is begin optimization or in reverse of that?
2- Is parameters updated after each mini-batch fed to network (i.e. the forward and backward pass is done for every batch) or only updates when one epoch is completed? why some tutorials said that each epoch is ba forward/backward pass?
anyone can clarify it please? if with a reference its better for me.
tensorflow cnn
asked 3 mins ago
honar.cshonar.cs
1139
$endgroup$
I am working on a CNN model, the code written in tensorflow, I did some googling about parameter updates such as weights ana biases when method is optimized and the loss is computed, two things made me confuse:
1- after output layer, the data goes to loss, the loss compute and then the model is begin optimization or in reverse of that?
2- Is parameters updated after each mini-batch fed to network (i.e. the forward and backward pass is done for every batch) or only updates when one epoch is completed? why some tutorials said that each epoch is ba forward/backward pass?
anyone can clarify it please? if with a reference its better for me.
tensorflow cnn
tensorflow cnn
asked 3 mins ago
honar.cshonar.cs
1139
asked 3 mins ago
honar.cshonar.cs
1139
asked 3 mins ago
honar.cshonar.cs
1139
asked 3 mins ago
honar.cshonar.cs
1139
asked 3 mins ago
honar.cshonar.cs
1139
1139
add a comment |
add a comment |
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