add back lr_scheduler

config/torch/optim/lr_scheduler.py

@@ -0,0 +1,123 @@
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
+#
+# Generated by configen, do not edit.
+# See https://github.com/facebookresearch/hydra/tree/master/tools/configen
+# fmt: off
+# isort:skip_file
+# flake8: noqa
+
+from dataclasses import dataclass, field
+from omegaconf import MISSING
+from typing import Any
+
+
+@dataclass
+class LambdaLRConf:
+    _target_: str = "torch.optim.lr_scheduler.LambdaLR"
+    optimizer: Any = MISSING
+    lr_lambda: Any = MISSING
+    last_epoch: Any = -1
+
+
+@dataclass
+class MultiplicativeLRConf:
+    _target_: str = "torch.optim.lr_scheduler.MultiplicativeLR"
+    optimizer: Any = MISSING
+    lr_lambda: Any = MISSING
+    last_epoch: Any = -1
+
+
+@dataclass
+class StepLRConf:
+    _target_: str = "torch.optim.lr_scheduler.StepLR"
+    optimizer: Any = MISSING
+    step_size: Any = MISSING
+    gamma: Any = 0.1
+    last_epoch: Any = -1
+
+
+@dataclass
+class MultiStepLRConf:
+    _target_: str = "torch.optim.lr_scheduler.MultiStepLR"
+    optimizer: Any = MISSING
+    milestones: Any = MISSING
+    gamma: Any = 0.1
+    last_epoch: Any = -1
+
+
+@dataclass
+class ExponentialLRConf:
+    _target_: str = "torch.optim.lr_scheduler.ExponentialLR"
+    optimizer: Any = MISSING
+    gamma: Any = MISSING
+    last_epoch: Any = -1
+
+
+@dataclass
+class CosineAnnealingLRConf:
+    _target_: str = "torch.optim.lr_scheduler.CosineAnnealingLR"
+    optimizer: Any = MISSING
+    T_max: Any = MISSING
+    eta_min: Any = 0
+    last_epoch: Any = -1
+
+
+@dataclass
+class ReduceLROnPlateauConf:
+    _target_: str = "torch.optim.lr_scheduler.ReduceLROnPlateau"
+    optimizer: Any = MISSING
+    mode: str = 'min'
+    factor: Any = 0.1
+    patience: Any = 10
+    verbose: Any = False
+    threshold: Any = 0.0001
+    threshold_mode: str = 'rel'
+    cooldown: Any = 0
+    min_lr: Any = 0
+    eps: Any = 1e-08
+
+
+@dataclass
+class CyclicLRConf:
+    _target_: str = "torch.optim.lr_scheduler.CyclicLR"
+    optimizer: Any = MISSING
+    base_lr: Any = MISSING
+    max_lr: Any = MISSING
+    step_size_up: Any = 2000
+    step_size_down: Any = None
+    mode: str = 'triangular'
+    gamma: Any = 1.0
+    scale_fn: Any = None
+    scale_mode: str = 'cycle'
+    cycle_momentum: Any = True
+    base_momentum: Any = 0.8
+    max_momentum: Any = 0.9
+    last_epoch: Any = -1
+
+
+@dataclass
+class CosineAnnealingWarmRestartsConf:
+    _target_: str = "torch.optim.lr_scheduler.CosineAnnealingWarmRestarts"
+    optimizer: Any = MISSING
+    T_0: Any = MISSING
+    T_mult: Any = 1
+    eta_min: Any = 0
+    last_epoch: Any = -1
+
+
+@dataclass
+class OneCycleLRConf:
+    _target_: str = "torch.optim.lr_scheduler.OneCycleLR"
+    optimizer: Any = MISSING
+    max_lr: Any = MISSING
+    total_steps: Any = None
+    epochs: Any = None
+    steps_per_epoch: Any = None
+    pct_start: Any = 0.3
+    anneal_strategy: str = 'cos'
+    cycle_momentum: Any = True
+    base_momentum: Any = 0.85
+    max_momentum: Any = 0.95
+    div_factor: Any = 25.0
+    final_div_factor: Any = 10000.0
+    last_epoch: Any = -1