Remove softplus from blocklist

- unblock nn.functional.softplus test
- unblock test_softplus test

test/test_mps.py

@@ -4679,29 +4679,31 @@ def helper(shape, dim=0):
  for dim in range(len(shape)):
  helper(shape, dim)
 
- # # Test softplus
- # def test_softplus(self):
- #  def helper(shape, beta=1, threshold=20):
- #  cpu_x = torch.randn(shape, device='cpu', dtype=torch.float, requires_grad=True)
- #  x = cpu_x.detach().clone().to('mps').requires_grad_()
+ # Test softplus
+ def test_softplus(self):
+ def helper(shape, beta=1, threshold=20):
+ cpu_x = torch.randn(shape, device='cpu', dtype=torch.float, requires_grad=True)
+ x = cpu_x.detach().clone().to('mps').requires_grad_()
 
- #  softplus_result = torch.nn.Softplus(beta=beta, threshold=threshold)(x)
- #  softplus_result_cpu = torch.nn.Softplus(beta=beta, threshold=threshold)(cpu_x)
+ softplus_result = torch.nn.Softplus(beta=beta, threshold=threshold)(x)
+ softplus_result_cpu = torch.nn.Softplus(beta=beta, threshold=threshold)(cpu_x)
 
- #  cpu_grad = torch.randn(softplus_result.shape)
- #  grad = cpu_grad.to('mps')
+ cpu_grad = torch.randn(softplus_result.shape)
+ grad = cpu_grad.to('mps')
 
- #  softplus_result.backward(gradient=grad)
- #  softplus_result_cpu.backward(gradient=cpu_grad)
+ softplus_result.backward(gradient=grad)
+ softplus_result_cpu.backward(gradient=cpu_grad)
 
- #  self.assertEqual(softplus_result, softplus_result_cpu)
- #  self.assertEqual(x.grad, cpu_x.grad)
+ self.assertEqual(softplus_result, softplus_result_cpu)
+ self.assertEqual(x.grad, cpu_x.grad)
 
- # # Test empty shape too
- # for shape in [(), (2, 3), (10, 10), (2, 3, 4, 5)]:
- # for beta in [0.5, 1, 2, 3, 4]:
- # for threshold in [0.5, 20, 30, 40, 50]:
- # helper(shape, beta, threshold)
+ # Test empty shape too
+ for shape in [(), (2, 3), (10, 10), (2, 3, 4, 5)]:
+ for beta in [0.5, 1, 2, 3, 4]:
+ for threshold in [0.5, 20, 30, 40, 50]:
+ helper(shape, beta, threshold)
+
+ # Test silu
 
  def test_silu(self):
  def helper(shape):
@@ -9198,6 +9200,7 @@ class TestConsistency(TestCase):
  'zeros': ['b8', 'f16', 'f32', 'i16', 'i32', 'i64', 'u8'],
  'zeros_like': ['b8', 'f16', 'f32', 'i16', 'i32', 'i64', 'u8'],
  'index_add': ['b8', 'f16', 'f32', 'i16', 'i32', 'i64', 'u8'],
+ 'nn.functional.softplus': ['f32'],
  }
 
  ALLOWLIST_OP_GRAD = {
@@ -9379,7 +9382,6 @@ class TestConsistency(TestCase):
  # All the entries in this list should be removed
  BLOCKLIST = {
  # Functions that hard crash
- 'nn.functional.softplus': [torch.float32],
  'sgn': [torch.bool],
  'linalg.inv': [torch.float32],
  'linalg.inv_ex': [torch.float32],