GAN/Architectures/models/gan.py
def generate_latent_points(self, n_samples):
        """generate points in latent space as input for the generator"""
        # generate points in the latent space
        latent_points = np.random.randn(self.latent_dim * n_samples)
        # reshape into a batch of inputs for the network
        latent_points = latent_points.reshape(n_samples, self.latent_dim)
        return latent_points
generate points in latent space as input for the generator
generate points in latent space as input for the generator
generate points in latent space as input for the generator
def generate_latent_points(self, n_samples):
        latent_points = np.random.randn(self.latent_dim * n_samples)
        latent_points = latent_points.reshape(n_samples, self.latent_dim)
        return latent_points
def generate_latent_points ( self , n_samples ) : latent_points = np . random . randn ( self . latent_dim * n_samples ) latent_points = latent_points . reshape ( n_samples , self . latent_dim ) return latent_points
generate points in latent space as input for the generator
generate points in latent space as input for the generator
"""generate points in latent space as input for the generator""" # generate points in the latent space # reshape into a batch of inputs for the network
self
n_samples