Hi @ptrblck, thanks that helped. I was able extract the sequence of layer information and corresponding weights using tf.all_variables().
The following are the components I am trying to transfer weights from tensorflow to pytorch now,
TF layers and weights:

Batchnorm layer: BatchNorm/beta:0, BatchNorm/moving_mean:0 and moving_variance:0
Conv layer: Conv/weights:0 and Conv/biases:0
Conv2d_transpose layer: Conv2d_transpose_1/weights:0 and Conv2d_transpose_1/biases:0

Can I just create the same sequence of layers in pytorch and assign these? Will there be computational flow differences between pytorch and tensorflow?
Wondering if you have idea on conversion for those particular layers.