def plot_resnet110_sparse_iterative_lth_force(): common.lth_plot(network=common.RESNET110, is_iterative=True, prune_method=common.UNSTRUCTURED, min_max_y=(-0.03, 0.01), to_ignore=['lr_lottery', 'finetune', 'lottery'], force_single=True)
def plot_resnet20_sparse_iterative_lth(): common.lth_plot( network=common.RESNET20, is_iterative=True, prune_method=common.UNSTRUCTURED, min_max_y=(-0.03, 0.01), to_ignore=['reinit', 'lr_lottery'], )
def plot_resnet34_structured_B_lth(): common.lth_plot( network=common.RESNET34, is_iterative=False, prune_method=common.STRUCTURED_B, min_max_y=(-0.03, 0.01), comparison_points=[(0.8937159746276857, .7291 - .7331)], comparison_label=common.RETHINKING, )
def plot_resnet56_sparse_oneshot_lth(): common.lth_plot( network=common.RESNET56, is_iterative=False, prune_method=common.UNSTRUCTURED, min_max_y=(-0.03, 0.01), nbins=3, nybins=4, )
def plot_resnet34_structured_A_lth(): common.lth_plot( network=common.RESNET34, is_iterative=False, prune_method=common.STRUCTURED_A, min_max_y=(-0.03, 0.01), comparison_points=[(0.9246381154681216, .7303 - .7331)], comparison_label=common.RETHINKING, )
def plot_gnmt_sparse_oneshot_lth_core(): common.lth_plot( network=common.GNMT, is_iterative=False, prune_method=common.UNSTRUCTURED, min_max_y=(-6, 1.5), min_max_x=(None, 0.05), to_ignore=['reinit', 'lr_lottery'], nbins=8, )
def plot_resnet34_structured_A_lth_core(): common.lth_plot( network=common.RESNET34, is_iterative=False, prune_method=common.STRUCTURED_A, min_max_y=(-0.03, 0.01), to_ignore=['reinit', 'lr_lottery'], nbins=5, nybins=4, )
def plot_resnet56_sparse_oneshot_lth_core(): common.lth_plot( network=common.RESNET56, is_iterative=False, prune_method=common.UNSTRUCTURED, min_max_y=(-0.03, 0.01), to_ignore=['reinit', 'lr_lottery'], nbins=4, nybins=4, )
def plot_resnet110_structured_A_lth(): common.lth_plot(network=common.RESNET110, is_iterative=False, prune_method=common.STRUCTURED_A, min_max_y=(-0.03, 0.01), min_max_x=(0.9783, 0.955), comparison_points=[(0.9772632282872189, 0.9325 - 0.9314)], comparison_err=[0.0022], comparison_label=common.RETHINKING, dont_plot_x=[2, 3])
def plot_resnet110_structured_B_lth(): common.lth_plot( network=common.RESNET110, is_iterative=False, prune_method=common.STRUCTURED_B, min_max_y=(-0.03, 0.01), comparison_points=[(0.6875922984758561, 0.9360 - 0.9314)], comparison_err=[0.0025], comparison_label=common.RETHINKING, nbins=4, )
def plot_resnet56_structured_A_lth(): common.lth_plot( network=common.RESNET56, is_iterative=False, prune_method=common.STRUCTURED_A, min_max_y=(-0.03, 0.01), comparison_points=[(0.9209166901474594, 0.9309 - 0.9314)], comparison_err=[0.0014], comparison_label=common.RETHINKING, nbins=5, )
def plot_resnet56_structured_B_lth(): common.lth_plot( network=common.RESNET56, is_iterative=False, prune_method=common.STRUCTURED_B, min_max_y=(-0.03, 0.01), comparison_points=[(0.8711749788672866, 0.9305 - 0.9314)], comparison_err=[0.0018], comparison_label=common.RETHINKING, nbins=5, )
def plot_resnet56_sparse_iterative_lth(): common.lth_plot( network=common.RESNET56, is_iterative=True, prune_method=common.UNSTRUCTURED, min_max_y=(-0.03, 0.01), to_ignore=['reinit', 'lr_lottery'], comparison_points=[(0.1497, -0.0006), (0.1, 0.0016), (.05, -.0065), (.03, -.0135)], comparison_label=common.CARREIRA, nybins=4, )
def plot_resnet50_sparse_iterative_lth_force(): common.lth_plot( network=common.RESNET50, is_iterative=True, prune_method=common.UNSTRUCTURED, min_max_y=(-0.03, 0.01), comparison_points=[(0.195, -0.0002)], comparison_label=common.AMC, to_ignore=['reinit', 'lr_lottery', 'finetune', 'lottery'], nbins=5, nybins=4, force_single=True, )
def plot_gnmt_sparse_iterative_lth(): common.lth_plot( network=common.GNMT, is_iterative=True, prune_method=common.UNSTRUCTURED, min_max_y=(-6, 1.5), min_max_x=(None, 0.02815), comparison_points=[ (0.2, 26.86 - 26.77), (0.15, 26.52 - 26.77), (0.1, 26.19 - 26.77), ], nbins=8, comparison_label=common.ZHU_GUPTA, to_ignore=['reinit', 'lr_lottery'], )
def plot_resnet20_sparse_oneshot_lth(): common.lth_plot(network=common.RESNET20, is_iterative=False, prune_method=common.UNSTRUCTURED, min_max_y=(-0.03, 0.01))
def plot_gnmt_sparse_oneshot_lth(): common.lth_plot(network=common.GNMT, is_iterative=False, prune_method=common.UNSTRUCTURED, min_max_y=(-6, 1.5), min_max_x=(None, 0.05))