Python utility.make_scheduler() Examples

The following are 21 code examples of utility.make_scheduler(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module utility , or try the search function .
Example #1
Source File: trainer_finetune.py    From 3D_Appearance_SR with MIT License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        super(TrainerFT, self).__init__(args, loader, my_model, my_loss, ckp)
        # self.args = args
        # self.scale = args.scale
        #
        # self.ckp = ckp
        # self.loader_train = loader.loader_train
        # self.loader_test = loader.loader_test
        # self.model = my_model
        # self.loss = my_loss
        if self.args.model.lower() == 'finetune':
            self.optimizer = self.make_optimizer(args, self.model)
        # self.scheduler = utility.make_scheduler(args, self.optimizer)
        #
        # if self.args.load != '.':
        #     self.optimizer.load_state_dict(
        #         torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
        #     )
        #     for _ in range(len(ckp.log)): self.scheduler.step()
        #
        # self.error_last = 1e8
Example #2
Source File: trainer.py    From MSRN-PyTorch with MIT License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '.':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #3
Source File: trainer.py    From MSRN-PyTorch with MIT License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '.':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #4
Source File: trainer.py    From 2018_subeesh_epsr_eccvw with MIT License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '.':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #5
Source File: trainer.py    From NTIRE2019_EDRN with MIT License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '.':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
        del args,ckp,my_model,my_loss
Example #6
Source File: trainer.py    From AWSRN with MIT License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '.':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #7
Source File: trainer.py    From 3D_Appearance_SR with MIT License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '.':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #8
Source File: trainer.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #9
Source File: trainer.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #10
Source File: trainer.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #11
Source File: trainer.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 6 votes vote down vote up 
def __init__(self, args, loader, my_model, my_loss, ckp):
        self.args = args
        self.scale = args.scale

        self.ckp = ckp
        self.loader_train = loader.loader_train
        self.loader_test = loader.loader_test
        self.model = my_model
        self.loss = my_loss
        self.optimizer = utility.make_optimizer(args, self.model)
        self.scheduler = utility.make_scheduler(args, self.optimizer)

        if self.args.load != '':
            self.optimizer.load_state_dict(
                torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
            )
            for _ in range(len(ckp.log)): self.scheduler.step()

        self.error_last = 1e8
Example #12
Source File: adversarial.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #13
Source File: adversarial.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #14
Source File: adversarial.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #15
Source File: adversarial.py    From 3D_Appearance_SR with MIT License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #16
Source File: adversarial.py    From AWSRN with MIT License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #17
Source File: adversarial.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #18
Source File: adversarial.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #19
Source File: adversarial.py    From MSRN-PyTorch with MIT License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #20
Source File: adversarial.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)
Example #21
Source File: adversarial.py    From MSRN-PyTorch with MIT License 5 votes vote down vote up 
def __init__(self, args, gan_type):
        super(Adversarial, self).__init__()
        self.gan_type = gan_type
        self.gan_k = args.gan_k
        self.discriminator = discriminator.Discriminator(args, gan_type)
        if gan_type != 'WGAN_GP':
            self.optimizer = utility.make_optimizer(args, self.discriminator)
        else:
            self.optimizer = optim.Adam(
                self.discriminator.parameters(),
                betas=(0, 0.9), eps=1e-8, lr=1e-5
            )
        self.scheduler = utility.make_scheduler(args, self.optimizer)