Lightweight dynamic conditional GAN with pyramid attention for text-to-image synthesis

•We propose a Conditional Manipulating Modular (CM-M) in Conditional Manipulating Block (CM-B) to compensate semantic information.•We develop a Pyramid Attention Refine Block (PAR-B) to capture multi-scale context.•The perceptual loss L1 and image-consistency loss L2 are used to optimize the generator to improve the sharpness and consistency of generated images.