update NAS-Bench-201 API to support str2matrix and str2lists

lib/nas_201_api/api.py

@@ -251,15 +251,15 @@ class NASBench201API(object):
       else:
         print('This index ({:}) is out of range (0~{:}).'.format(index, len(self.meta_archs)))
 
-  # This func shows how to read the string0based architecture encoding
+  # This func shows how to read the string-based architecture encoding
   #   the same as the `str2structure` func in `AutoDL-Projects/lib/models/cell_searchs/genotypes.py`
   # Usage:
-  #   arch = api.str2structure( '|nor_conv_1x1~0|+|none~0|none~1|+|none~0|none~1|skip_connect~2|' )
+  #   arch = api.str2lists( '|nor_conv_1x1~0|+|none~0|none~1|+|none~0|none~1|skip_connect~2|' )
   #   print ('there are {:} nodes in this arch'.format(len(arch)+1)) # arch is a list
   #   for i, node in enumerate(arch):
   #     print('the {:}-th node is the sum of these {:} nodes with op: {:}'.format(i+1, len(node), node))
   @staticmethod
-  def str2structure(xstr):
+  def str2lists(xstr):
     assert isinstance(xstr, str), 'must take string (not {:}) as input'.format(type(xstr))
     nodestrs = xstr.split('+')
     genotypes = []
@@ -271,6 +271,37 @@ class NASBench201API(object):
       genotypes.append( input_infos )
     return genotypes
 
+  # This func shows how to convert the string-based architecture encoding to the encoding strategy in NAS-Bench-101
+  # Usage:
+  #   # this will return a numpy matrix (2-D np.array)
+  #   matrix = api.str2matrix( '|nor_conv_1x1~0|+|none~0|none~1|+|none~0|none~1|skip_connect~2|' )
+  #   # This matrix is 4-by-4 matrix representing a cell with 4 nodes (only the lower left triangle is useful).
+  #      [ [0, 0, 0, 0],  # the first line represents the input (0-th) node
+  #        [2, 0, 0, 0],  # the second line represents the 1-st node, is calculated by 2-th-op( 0-th-node )
+  #        [0, 0, 0, 0],  # the third line represents the 2-nd node, is calculated by 0-th-op( 0-th-node ) + 0-th-op( 1-th-node )
+  #        [0, 0, 1, 0] ] # the fourth line represents the 3-rd node, is calculated by 0-th-op( 0-th-node ) + 0-th-op( 1-th-node ) + 1-th-op( 2-th-node )
+  #   In NAS-Bench-201 search space, 0-th-op is 'none', 1-th-op is 'skip_connect'
+  #      2-th-op is 'nor_conv_1x1', 3-th-op is 'nor_conv_3x3', 4-th-op is 'avg_pool_3x3'.
+  @staticmethod
+  def str2matrix(xstr):
+    assert isinstance(xstr, str), 'must take string (not {:}) as input'.format(type(xstr))
+    # this only support NAS-Bench-201 search space
+    # this defination will be consistant with this line https://github.com/D-X-Y/AutoDL-Projects/blob/master/lib/models/cell_operations.py#L24
+    # If a node has two input-edges from the same node, this function does not work. One edge will be overleaped.
+    NAS_BENCH_201         = ['none', 'skip_connect', 'nor_conv_1x1', 'nor_conv_3x3', 'avg_pool_3x3']
+    nodestrs = xstr.split('+')
+    num_nodes = len(nodestrs) + 1
+    matrix = np.zeros((num_nodes,num_nodes))
+    for i, node_str in enumerate(nodestrs):
+      inputs = list(filter(lambda x: x != '', node_str.split('|')))
+      for xinput in inputs: assert len(xinput.split('~')) == 2, 'invalid input length : {:}'.format(xinput)
+      for xi in inputs:
+        op, idx = xi.split('~')
+        if op not in NAS_BENCH_201: raise ValueError('this op ({:}) is not in {:}'.format(op, NAS_BENCH_201))
+        op_idx, node_idx = NAS_BENCH_201.index(op), int(idx)
+        matrix[i+1, node_idx] = op_idx
+    return matrix
+
 
 
 class ArchResults(object):