How to convert Keras h5 to PyTorch pth format?
You must be careful with the versions from TF and PyTorch (as some commands may be different).
Basically you must:
1 - Know your layer and activation structure on Keras:
You can get the layer information with:
model_keras.summary()

If you can't get info about activation functions, try:
for layer in model_keras.layers:
    print(layer.output)

2 - Build a model on PyTorch that has the same layer structure (and activation) as on Keras
3 - The recently created PyTorch model (let's say model_pyt) has different weights and biases from your model on Keras, so you must copy those weights and biases from the Keras model to PyTorch model:
BE CAREFUL HERE, PYTORCH WEIGHTS ARE TRANSPOSED IN RELATION TO KERAS WEIGHTS
Then, for example, copying a weight would be like:
model_pyt.layer1.weight.data = torch.tensor(model_keras.layers[0].get_weights()[0].T)

And for the bias:
model_pyt.layer1.bias.data = torch.tensor(model_keras.layers[0].get_weights()[1])

repeat that for all layers.
Then, your PyTorch model has the same architecture and weights as the Keras model and might behave in the same way.