add example of self-supervised SimCLR training - V2 (#50)

* add example of self-supervised SimCLR training

* simclr v2, replace nvidia dali dataloader

* updated

* sync to latest code writing style

* sync to latest code writing style and modify README

* detail README & standardize dataset path

examples/simclr_cifar10_data_parallel/models/simclr.py

@@ -0,0 +1,36 @@
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from .Backbone import backbone
+
+class projection_MLP(nn.Module):
+    def __init__(self, in_dim, out_dim=256):
+        super().__init__()
+        hidden_dim = in_dim
+        self.layer1 = nn.Sequential(
+            nn.Linear(in_dim, hidden_dim),
+            nn.ReLU(inplace=True)
+        )
+        self.layer2 = nn.Linear(hidden_dim, out_dim)
+    def forward(self, x):
+        x = self.layer1(x)
+        x = self.layer2(x)
+        return x 
+
+class SimCLR(nn.Module):
+
+    def __init__(self, model='resnet18', **kwargs):
+        super().__init__()
+        
+        self.backbone = backbone(model, **kwargs)
+        self.projector = projection_MLP(self.backbone.output_dim)
+        self.encoder = nn.Sequential(
+            self.backbone,
+            self.projector
+        )
+        
+    def forward(self, x1, x2):
+
+        z1 = self.encoder(x1)
+        z2 = self.encoder(x2)
+        return z1, z2