TrainingExtensions/tensorflow/src/python/aimet_tensorflow/common/connectedgraph.py
def create_conv2d_dense_type_params(my_op: Op):
            """ Create products for conv2d, dense, depthwise conv2d, and similar """
            tf_op = my_op.get_module()

            weight_op = WeightTensorUtils.get_read_op(tf_op)
            create_and_connect_product('kernel', weight_op.outputs[0].shape, my_op, weight_op.outputs[0])

            if not BiasUtils.is_bias_none(tf_op):
                bias_op = BiasUtils.get_bias_read_op(tf_op)
                create_and_connect_product('bias', bias_op.outputs[0].shape, my_op, bias_op.outputs[0])
 Create products for conv2d, dense, depthwise conv2d, and similar 
Create products for conv2d, dense, depthwise conv2d, and similar
Create products for conv2d dense depthwise conv2d and similar
def create_conv2d_dense_type_params(my_op: Op):
            tf_op = my_op.get_module()
            weight_op = WeightTensorUtils.get_read_op(tf_op)
            create_and_connect_product('kernel', weight_op.outputs[0].shape, my_op, weight_op.outputs[0])
            if not BiasUtils.is_bias_none(tf_op):
                bias_op = BiasUtils.get_bias_read_op(tf_op)
                create_and_connect_product('bias', bias_op.outputs[0].shape, my_op, bias_op.outputs[0])
def create_conv2d_dense_type_params ( my_op : Op ) : tf_op = my_op . get_module ( ) weight_op = WeightTensorUtils . get_read_op ( tf_op ) create_and_connect_product ( 'kernel' , weight_op . outputs [ 0 ] . shape , my_op , weight_op . outputs [ 0 ] ) if not BiasUtils . is_bias_none ( tf_op ) : bias_op = BiasUtils . get_bias_read_op ( tf_op ) create_and_connect_product ( 'bias' , bias_op . outputs [ 0 ] . shape , my_op , bias_op . outputs [ 0 ] )
Create products for conv2d, dense, depthwise conv2d, and similar
Create products for conv2d dense depthwise conv2d and similar
""" Create products for conv2d, dense, depthwise conv2d, and similar """
my_op
Op