DTaoo / VGGish

An implementation of vggish in keras with tf backend
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error raised when loading model_weights "include_top=True" #11

Open TwistFateBOY opened 4 years ago

TwistFateBOY commented 4 years ago

here is the code model = VGGish(include_top=True) model.load_weights(WEIGHTS_PATH_TOP)

here is the bug ValueError: Dimension 0 in both shapes must be equal, but are 63488 and 12288. Shapes are [63488,4096] and [12288,4096]. for 'Assign_12' (op: 'Assign') with input shapes: [63488,4096], [12288,4096].

what's wrong?

sourav22899 commented 4 years ago

@TwistFateBOY This is the same issue raised in issue#2. The following solution is mentioned to solve it.

This is because the length of single example in our version is different from the slim one, i.e., 496 vs 96, or 4.96 vs 0.96. The different lengths could result in different feature dimensions after the flatten operation. To remove the problem, you can change the parameter into "NUM_FRAMES =96", "EXAMPLE_WINDOW_SECONDS = 0.96", and "EXAMPLE_HOP_SECONDS = 0.96".