4893c42a85f8919eb2e0251e545f85eaae05b948,posewarp_test.py,,train,#Any#Any#,17

Before Change

			//rnn = networks.warp_rnn(params,generator)
		"""

		X,Y = next(feed)

		sio.savemat("0.mat",{"X": X[0], "Y": Y, "pose": X[1]}), 
		

After Change

		with tf.device(gpu):
			vgg_model = VGG19(weights="imagenet",include_top=False,input_shape=(256,256,3))
			networks.make_trainable(vgg_model,False)
			generator = networks.network_warp(params,vgg_model)
		
			//generator.summary()
			//discriminator = networks.discriminator(params)
			//gan = networks.gan(generator,discriminator,params)
			//gan.load_weights("../results/networks/gan/5000.h5")
			//discriminator.compile(loss="binary_crossentropy",optimizer=Adam(lr=1e-4))
			//generator.load_weights("../results/networks/L2+VGG_0.001/100000.h5")
			//generator.load_weights("../results/networks/lifting/50000.h5")
			generator.load_weights("../results/networks/golf+lifting/17500.h5")
			//mask = Model(inputs=generator.inputs,outputs=generator.get_layer("mask").output)
		
		//generator.summary()
		//X,Y = next(feed)

Instances