[functorch] update compile example imports (pytorch/functorch#834)

functorch/examples/compilation/fuse_module.py

@@ -1,5 +1,5 @@
 import timeit
-from functorch import compiled_module, tvm_compile
+from functorch.compile import compiled_module, tvm_compile
 import torch.nn as nn
 import torch
 from functools import partial
@@ -9,8 +9,8 @@ def nop(f, _):
     return f
 
 
-fw_compiler = partial(tvm_compile, name='fw_keops')
-bw_compiler = partial(tvm_compile, name='bw_keops')
+fw_compiler = tvm_compile(target='llvm', tuning_logfile='fw_keops')
+bw_compiler = tvm_compile(target='llvm', tuning_logfile='bw_keops')
 fw_compiler = nop
 bw_compiler = nop
 

functorch/examples/compilation/linear_train.py

@@ -4,7 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
-from functorch import nnc_jit, make_functional
+from functorch import make_functional
+from functorch.compile import nnc_jit
 import torch
 import torch.nn as nn
 import time

functorch/examples/compilation/simple_function.py

@@ -4,7 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
-from functorch import grad, nnc_jit, make_fx, make_nnc
+from functorch import grad, make_fx
+from functorch.compile import nnc_jit
 import torch
 import time
 
@@ -16,9 +17,7 @@ def f(x):
 inp = torch.randn(100)
 grad_pt = grad(f)
 grad_fx = make_fx(grad_pt)(inp)
-grad_nnc = nnc_jit(grad_pt, skip_specialization=True)
-loopnest = make_nnc(grad_pt)(inp)
-print(loopnest)
+grad_nnc = nnc_jit(grad_pt)
 
 
 def bench(name, f, iters=10000, warmup=3):