whitespace

apex/parallel/distributed.py

@@ -584,8 +584,8 @@ class DistributedDataParallel(Module):
                 # self.buckets = [[None for _ in range(self.bucket_sizes[i])]
                 #                 for i in range(self.num_buckets)]
                 if not self.buckets:
-                    self.buckets = [[None for _ in range(self.bucket_sizes[i])] 
-                                    for i in range(self.num_buckets)] 
+                    self.buckets = [[None for _ in range(self.bucket_sizes[i])]
+                                    for i in range(self.num_buckets)]
                 else:
                     assert len(self.buckets) == self.num_buckets, "len(buckets) = {}, expected {}".format(
                         len(self.buckets), self.num_buckets)

csrc/fused_adam_cuda_kernel.cu

@@ -98,18 +98,18 @@ struct AdamFunctor
         T incoming_m[ILP];
         T incoming_v[ILP];
         T incoming_g[ILP];
-        
+
         for(int i_start = 0;
             i_start < n && i_start < chunk_size;
             i_start += blockDim.x*ILP) {
-            
+
             #pragma unroll
             for(int ii = 0; ii < ILP; ii++) {
                 incoming_p[ii] = 0;
                 incoming_m[ii] = 0;
                 incoming_v[ii] = 0;
                 incoming_g[ii] = 0;
-                
+
                 int i = i_start + threadIdx.x + ii*blockDim.x;
                 if (i < n && i < chunk_size) {
                     incoming_p[ii] = p[i];
@@ -296,7 +296,7 @@ void fused_adam_cuda_mt(
             }));
         }
     } else {
-        if (tl_sz == 5) { 
+        if (tl_sz == 5) {
             AT_DISPATCH_FLOATING_TYPES(tensor_lists[3][0].type(), "adam_cuda_mt_kernel", ([&] {
                 multi_tensor_apply<5>(
                     BLOCK_SIZE,