randn_like in minrf (#10298)

tested that it trains to similar loss

examples/minrf.py

@@ -1,5 +1,4 @@
 # much taken from https://github.com/cloneofsimo/minRF
-import math
 from tinygrad import Tensor, nn, GlobalCounters, TinyJit
 from tinygrad.helpers import getenv, trange
 from extra.models.llama import Attention, FeedForward, precompute_freqs_cis
@@ -95,7 +94,7 @@ class DiT_Llama:
     cond = (Tensor.rand(cond.shape[0]) < dropout_prob).where(cond.full_like(self.num_classes), cond)
 
     # this is rectified flow
-    z1 = Tensor.randn(x.shape)  # TODO: add Tensor.randn_like (and friends) to tinygrad
+    z1 = x.randn_like()
     zt = (1 - texp) * x + texp * z1
     vtheta = self(zt, t, cond)