1.0.0 official release (#18)

* fix bug in fix_BN * gaitgl OUMVLP support. * update ./doc/3.advance_usage.md Cross-Dataset Evalution & Data Agumentation * update config * update docs.3 * update docs.3 * add loss doc and gather input decorator * refine the create model doc * support rearrange directory of unzipped OUMVLP * fix some bugs in loss_aggregator.py * refine docs and little fix * add oumvlp pretreatment description * pretreatment dataset fix oumvlp description * add gaitgl oumvlp result * assert gaitgl input size * add pipeline * update the readme. * update pipeline and readme * Corrigendum. * add logo and remove path * update new logo * Update README.md * modify logo size Co-authored-by: 12131100 <12131100@mail.sustech.edu.cn> Co-authored-by: noahshen98 <77523610+noahshen98@users.noreply.github.com> Co-authored-by: Noah <595311942@qq.com>
2021-12-08 20:05:28 +08:00
parent 6e71c7ac34
commit bb6cd5149a
39 changed files with 11401 additions and 230 deletions
@@ -1,13 +1,54 @@
+from ctypes import ArgumentError
 import torch.nn as nn
+import torch
 from utils import Odict
+import functools
+from utils import ddp_all_gather

-class BasicLoss(nn.Module):
-    def __init__(self, loss_term_weights=1.0):
-        super(BasicLoss, self).__init__()

-        self.loss_term_weights = loss_term_weights
-        self.pair_based_loss   = True
-        self.info              = Odict()
-    
+def gather_and_scale_wrapper(func):
+    """Internal wrapper: gather the input from multple cards to one card, and scale the loss by the number of cards.
+    """
+
+    @functools.wraps(func)
+    def inner(*args, **kwds):
+        try:
+
+            for k, v in kwds.items():
+                kwds[k] = ddp_all_gather(v)
+
+            loss, loss_info = func(*args, **kwds)
+            loss *= torch.distributed.get_world_size()
+            return loss, loss_info
+        except:
+            raise ArgumentError
+    return inner
+
+
+class BaseLoss(nn.Module):
+    """
+    Base class for all losses.
+
+    Your loss should also subclass this class. 
+
+    Attribute:
+        loss_term_weights: the weight of the loss.
+        info: the loss info.
+    """
+    loss_term_weights = 1.0
+    info = Odict()
+
    def forward(self, logits, labels):
-        raise NotImplementedError
+        """
+        The default forward function.
+
+        This function should be overridden by the subclass. 
+
+        Args:
+            logits: the logits of the model.
+            labels: the labels of the data.
+
+        Returns:
+            tuple of loss and info.
+        """
+        return .0, self.info