Black to Block for various files (#42913)

Summary:
Fixes  #41735 #41736 #41737 #41738 all areas where black is mentioned is replaced to block

Pull Request resolved: #42913

Reviewed By: houseroad

Differential Revision: D23112873

Pulled By: malfet

fbshipit-source-id: a515b56dc2ed20aa75741c577988d95f750b364c

torch/onnx/symbolic_helper.py

@@ -190,7 +190,7 @@ def _onnx_opset_unsupported_detailed(op_name, current_opset, supported_opset, re
                        'opset {}. {}. Please try opset version {}.'.format(op_name, current_opset, reason, supported_opset))
 
 
-def _black_list_in_opset(name):
+def _block_list_in_opset(name):
     def symbolic_fn(*args, **kwargs):
         raise RuntimeError("ONNX export failed on {}, which is not implemented for opset {}. "
                            "Try exporting with other opset versions."

torch/onnx/symbolic_opset7.py

@@ -1,4 +1,4 @@
-from torch.onnx.symbolic_helper import _black_list_in_opset
+from torch.onnx.symbolic_helper import _block_list_in_opset
 
 import torch.onnx.symbolic_opset9 as sym_opset9
 
@@ -15,7 +15,7 @@
 #   MaxPool: added optional indices output.
 #   Scan
 
-black_listed_operators = [
+block_listed_operators = [
     "scan", "expand", "expand_as", "meshgrid",
     "adaptive_max_pool1d", "adaptive_max_pool2d", "adaptive_max_pool3d",
     "max_pool1d_with_indices", "max_pool2d_with_indices", "max_pool3d_with_indices"
@@ -43,5 +43,5 @@ def min(g, self, dim_or_y=None, keepdim=None):
     return sym_opset9.min(g, self, dim_or_y, keepdim)
 
 
-for black_listed_op in black_listed_operators:
-    vars()[black_listed_op] = _black_list_in_opset(black_listed_op)
+for block_listed_op in block_listed_operators:
+    vars()[block_listed_op] = _block_list_in_opset(block_listed_op)

torch/onnx/symbolic_opset8.py

@@ -4,7 +4,7 @@
 import torch.onnx.symbolic_helper as sym_help
 import torch.onnx.symbolic_opset9 as sym_opset9
 
-from torch.onnx.symbolic_helper import parse_args, _unimplemented, _black_list_in_opset, _try_get_scalar_type
+from torch.onnx.symbolic_helper import parse_args, _unimplemented, _block_list_in_opset, _try_get_scalar_type
 from torch.onnx.symbolic_opset9 import _cast_Float
 
 import warnings
@@ -39,14 +39,14 @@
 #   Upsample: moved scales from attribute to input.
 #   Scan
 
-black_listed_operators = [
+block_listed_operators = [
     "nonzero", "where", "scatter", "scatter_add", "erf", "sign", "isnan", "gather",
     "arange", "masked_fill",
     "index_fill", "index_copy"
 ]
 
-for black_listed_op in black_listed_operators:
-    vars()[black_listed_op] = _black_list_in_opset(black_listed_op)
+for block_listed_op in block_listed_operators:
+    vars()[block_listed_op] = _block_list_in_opset(block_listed_op)
 
 
 def _interpolate(name, dim, interpolate_mode):