WIP: Fixing clamp tests

functorch/csrc/BatchRulesBinaryOps.cpp

@@ -183,6 +183,9 @@ TORCH_LIBRARY_IMPL(aten, FT_BATCHED_KEY, m) {
   UNARY_POINTWISE(clamp_max);
   POINTWISE_BOXED(clamp_max_);
 
+  UNARY_POINTWISE(clip);
+  POINTWISE_BOXED(clip.Tensor);
+
   // Commented out so we have a test op
   // BINARY_SCALAR_2(copysign, Tensor, Scalar);
   BINARY_SCALAR_2(div, Tensor, Scalar);

functorch/csrc/BatchRulesViews.cpp

@@ -478,7 +478,6 @@ TORCH_LIBRARY_IMPL(aten, FT_BATCHED_KEY, m) {
   VMAP_SUPPORT("view", view_batching_rule);
   VMAP_SUPPORT("expand", expand_batch_rule);
   VMAP_SUPPORT("unfold", unfold_batch_rule);
-  VMAP_SUPPORT("movedim.intlist", movedim_batch_rule);
 }
 
 }}

functorch/csrc/BatchingRegistrations.cpp

@@ -888,7 +888,6 @@ TORCH_LIBRARY_IMPL(aten, FT_BATCHED_KEY, m) {
   m.impl("view_as", native::view_as); // composite wrt autograd
 
   m.impl("addmm", addmm_batching_rule);
-  // clamp operations
 
 // unary pointwise, out-of-place, no additional arguments.
 #define TO_BATCHING_RULE(name, ...) \

test/test_ops.py

@@ -306,7 +306,6 @@ def vjp_of_vjp(*args_and_cotangents):
                 self.assertEqual(loop_out, batched_out, atol=1e-4, rtol=1e-4)
     vmapvjp_fail = vjp_fail.union({
         # All of the following are bugs and need to be fixed
-        xfail('clamp', ''),
         xfail('diag_embed'),
         xfail('eig'),
         xfail('nn.functional.conv_transpose2d'),