def print_net()

in lib/utils/net_rel.py [0:0]

• 31 lines of code
• 12 McCabe index (conditional complexity)

def print_net(model, namescope='gpu_0'):
    """Print the model network."""
    logger.info('Printing model: {}'.format(model.net.Name()))
    op_list = model.net.Proto().op
    for op in op_list:
        input_name = op.input
        # For simplicity: only print the first output
        # Not recommended if there are split layers
        output_name = str(op.output[0])
        op_type = op.type
        op_name = op.name

        if namescope is None or output_name.startswith(namescope):
            # Only print the forward pass network
            if output_name.find('grad') >= 0 or output_name.find('__m') >= 0:
                continue

            output_shape = workspace.FetchBlob(output_name).shape
            first_blob = True
            op_label = op_type + (op_name if op_name == '' else ':' + op_name)
            suffix = ' ------- (op: {})'.format(op_label)
            for j in range(len(input_name)):
                if input_name[j] in model.params:
                    continue
                input_blob = workspace.FetchBlob(input_name[j])
                if isinstance(input_blob, np.ndarray):
                    input_shape = input_blob.shape
                    logger.info('{:28s}: {:20s} => {:28s}: {:20s}{}'.format(
                        c2_utils.UnscopeName(str(input_name[j])),
                        '{}'.format(input_shape),
                        c2_utils.UnscopeName(str(output_name)),
                        '{}'.format(output_shape),
                        suffix))
                    if first_blob:
                        first_blob = False
                        suffix = ' ------|'
    logger.info('End of model: {}'.format(model.net.Name()))