code clean

python/paddle/v2/fluid/backward.py

 from paddle.v2.fluid import framework as framework
 from . import core
 import collections
-import pdb
 
 __all__ = ['append_backward']
 
@@ -45,7 +44,7 @@ def _infer_var_data_type_(var_name, block):
         grad_var.set_dtype(core.DataType.FP32)
 
 
-def _is_all_in_set_(cands, s):
+def _all_in_set_(cands, s):
     for c in cands:
         if not c in s:
             return False
@@ -61,112 +60,114 @@ def _append_grad_suffix_(name):
     return name + core.grad_var_suffix()
 
 
-def _append_backward_ops_(target,
-                          block,
-                          target_block,
-                          no_grad_set,
-                          callback=None):
-    grad_op_descs = []
-    grad_to_var = dict()
-    program = block.program
-    for each_op in reversed(block.ops):
-        grad_sub_block_list = []
-        if each_op.has_attr("sub_block"):
-            sub_block_idx = each_op.block_attr("sub_block")
-            sub_block = program.block(sub_block_idx)
-            grad_sub_block = program.create_block(parent_idx=sub_block_idx)
-            sub_grad_to_var = _append_backward_ops_(
-                target, sub_block, grad_sub_block, no_grad_set, callback)
-            grad_to_var = dict(grad_to_var, **sub_grad_to_var)
-            grad_sub_block_list.append(grad_sub_block.desc)
-        grad_op_desc, op_grad_to_var = core.get_grad_op_desc(
-            each_op.desc, no_grad_set[block.idx], grad_sub_block_list)
-        grad_op_descs.append(grad_op_desc)
-        grad_to_var = dict(grad_to_var, **op_grad_to_var)
-    # grad_op_descs = [[op1_g1, op1_g2], [op2_g], ...]
-    # flatten grad_op_descs
-    grad_op_descs = [op for sublist in grad_op_descs for op in sublist]  # ?????
-
+def _addup_repetitive_outputs_(op_descs):
+    # In backward part, an variable my be the output of more than one ops.
+    # In this case, the variable should be the accumulation of all the outputs.
+    # We adopt adding `sum_op`s to implement the accumulate.
     pending_sum_ops = []
     var_rename_count = collections.defaultdict(int)
-    var_inputs = collections.defaultdict(list)
-    for idx, op_desc in enumerate(grad_op_descs):
+    renamed_vars = collections.defaultdict(list)
+    for idx, op_desc in enumerate(op_descs):
         for var_name in op_desc.input_arg_names():
-            if len(var_inputs[var_name]) > 1:
-                pending_sum_ops.append((_create_op_desc_(
-                    op_type="sum",
-                    inputs={"X": var_inputs[var_name]},
-                    outputs={"Out": [var_name]},
-                    attrs={}), idx))
-                var_inputs[var_name] = [var_name]
+            if len(renamed_vars[var_name]) > 1:
+                pending_sum_ops.append(
+                    (_create_op_desc_("sum", {"X": renamed_vars[var_name]},
+                                      {"Out": [var_name]}, {}), idx))
+                renamed_vars[var_name] = [var_name]
         for var_name in op_desc.output_arg_names():
-            if var_name in op_desc.input_arg_names():
-                # in place operator
+            if var_name == core.empty_var_name(
+            ) or var_name in op_desc.input_arg_names():
+                # empty variable or inplace op
                 continue
-            if var_name == core.empty_var_name() or len(var_inputs[
-                    var_name]) == 0:
+            if len(renamed_vars[var_name]) == 0:
                 # it's the first time we get the variable
-                var_inputs[var_name] = [var_name]
+                renamed_vars[var_name] = [var_name]
             else:
-                if len(var_inputs[var_name]) == 1:
+                if len(renamed_vars[var_name]) == 1:
                     new_name = var_name + "@RENAME@" + \
                         str(var_rename_count[var_name])
-                    var_rename_count[var_name] = var_rename_count[var_name] + 1
+                    var_rename_count[var_name] += 1
                     # rename original var_name
-                    var_inputs[var_name][0] = new_name
-                    _rename_arg_(grad_op_descs, var_name, new_name, 0, idx)
+                    renamed_vars[var_name][0] = new_name
+                    _rename_arg_(op_descs, var_name, new_name, 0, idx)
                     _rename_arg_(pending_sum_ops, var_name, new_name)
 
                 new_name = var_name + "@RENAME@" + \
                     str(var_rename_count[var_name])
-                var_rename_count[var_name] = var_rename_count[var_name] + 1
+                var_rename_count[var_name] += 1
                 op_desc.rename_output(var_name, new_name)
-                var_inputs[var_name].append(new_name)
-    for var_name, inputs in var_inputs.iteritems():
+                renamed_vars[var_name].append(new_name)
+    for var_name, inputs in renamed_vars.iteritems():
         if len(inputs) > 1:
             pending_sum_ops.append((_create_op_desc_(
-                op_type="sum",
-                inputs={"X": inputs},
-                outputs={"Out": [var_name]},
-                attrs={}), len(grad_op_descs)))
+                "sum", {"X": inputs}, {"Out": [var_name]}, {}), len(op_descs)))
     # sum_op descs are sorted according to their insert position
     for p in reversed(pending_sum_ops):
-        grad_op_descs.insert(p[1], p[0])
-    # Remove ops whose outputs are all in no_grad_set
-    grad_op_descs = filter(
-        lambda op_desc: not _is_all_in_set_(op_desc.output_arg_names(), no_grad_set[block.idx]),
-        grad_op_descs)
+        op_descs.insert(p[1], p[0])
+
+    return op_descs
+
+
+def _remove_no_grad_branch_(op_descs, no_grad_set):
+    # Remove ops whose outputs are all in no_grad_dict
+    op_descs = filter(
+        lambda op_desc: not _all_in_set_(op_desc.output_arg_names(), no_grad_set),
+        op_descs)
     # Insert fill_zeros_like_op
     to_insert = []
-    for idx, op_desc in enumerate(grad_op_descs):
+    for idx, op_desc in enumerate(op_descs):
         for arg in op_desc.input_arg_names():
-            if core.grad_var_suffix() in arg and arg in no_grad_set[block.idx]:
-                to_insert.append((arg, idx))
-    for ele in reversed(to_insert):
-        arg = ele[0]
-        fill_zeros_like_op = _create_op_desc_(
-            "fill_zeros_like", {"X": [_strip_grad_suffix_(arg)]}, {"Y": [arg]},
-            {})
-        grad_op_descs.insert(ele[1], fill_zeros_like_op)
+            if core.grad_var_suffix() in arg and arg in no_grad_set:
+                to_insert.append((_create_op_desc_("fill_zeros_like", {
+                    "X": [_strip_grad_suffix_(arg)]
+                }, {"Y": [arg]}, {}), idx))
+
+    map(lambda p: op_descs.insert(p[1], p[0]), reversed(to_insert))
+
+    return op_descs
+
+
+def _append_backward_ops_(target,
+                          block,
+                          target_block,
+                          no_grad_dict,
+                          grad_to_var,
+                          callback=None):
+    grad_op_descs = []
+    program = block.program
+    for op in reversed(block.ops):
+        grad_sub_block_list = []
+        # If the op has its own sub-block, deal with the sub-block first
+        if op.has_attr("sub_block"):
+            sub_block = program.block(op.block_attr("sub_block"))
+            grad_sub_block = program.create_block(parent_idx=sub_block.idx)
+            _append_backward_ops_(target, sub_block, grad_sub_block,
+                                  no_grad_dict, grad_to_var, callback)
+            grad_sub_block_list.append(grad_sub_block.desc)
+
+        grad_op_desc, op_grad_to_var = core.get_grad_op_desc(
+            op.desc, no_grad_dict[block.idx], grad_sub_block_list)
+        grad_op_descs.extend(grad_op_desc)
+        grad_to_var.update(op_grad_to_var)
+
+    grad_op_descs = _addup_repetitive_outputs_(grad_op_descs)
+
+    grad_op_descs = _remove_no_grad_branch_(grad_op_descs,
+                                            no_grad_dict[block.idx])
 
     if target_block.idx == 0:
-        grad_target_name = _append_grad_suffix_(target.name)
-        # target_block.desc.var(grad_target_name.encode("ascii"))
         grad_op_descs.insert(
             0,
-            _create_op_desc_(
-                op_type="fill_constant",
-                inputs={},
-                outputs={"Out": [grad_target_name]},
-                attrs={"shape": [1],
+            _create_op_desc_("fill_constant", {}, {
+                "Out": [_append_grad_suffix_(target.name)]
+            }, {"shape": [1],
                 "value": 1.0,
                 "dtype": target.dtype}))
+    # append op_desc in grad_op_descs to target_block
     for op_desc in grad_op_descs:
         new_op_desc = target_block.desc.append_op()
         new_op_desc.copy_from(op_desc)
 
-    return grad_to_var
-
 
 def _append_backward_vars_(block, start_op_idx, grad_to_var, grad_info_map):
     for op_idx in range(start_op_idx, block.desc.op_size()):
@@ -194,15 +195,15 @@ def _append_backward_vars_(block, start_op_idx, grad_to_var, grad_info_map):
                 _infer_var_data_type_(arg, block)
 
 
-def append_backward(loss, parameter_list=None, no_grad_set=None):
+def append_backward(loss, parameter_list=None, no_grad_dict=None):
     """
     Create and add gradient Operators in BlockDesc to compute
     gradients of `loss` for parameters in parameter_list
 
     :param loss: an variable generated by cost function.
     :type loss: Variable
-    :param no_grad_set: variable that should not create gradient
-    :type no_grad_set: set
+    :param no_grad_dict: variable that should not create gradient
+    :type no_grad_dict: set
     :param parameter_list: parameters that need to compute gradient and 
     update to optimize the lost.
     :type: list
@@ -212,8 +213,8 @@ def append_backward(loss, parameter_list=None, no_grad_set=None):
     assert isinstance(loss, framework.Variable)
 
     program = loss.block.program
-    if no_grad_set is None:
-        no_grad_set = dict()
+    if no_grad_dict is None:
+        no_grad_dict = dict()
         assert isinstance(program, framework.Program)
         for block in program.blocks:
             assert isinstance(block, framework.Block)
@@ -222,19 +223,21 @@ def append_backward(loss, parameter_list=None, no_grad_set=None):
                 assert isinstance(var, framework.Variable)
                 if var.stop_gradient:
                     block_no_grad_set.add(_append_grad_suffix_(var.name))
-            no_grad_set[block.idx] = block_no_grad_set
-    else:
-        # FIX ME
-        no_grad_set = {0: no_grad_set}
+            no_grad_dict[block.idx] = block_no_grad_set
+    elif isinstance(no_grad_dict, set):
+        no_grad_dict = {0: no_grad_dict}
 
     grad_info_map = dict()
     root_block = program.block(0)
 
     fwd_op_num = root_block.desc.op_size()
     current_block_idx = program.current_block_idx
-    grad_to_var = _append_backward_ops_(loss, root_block, root_block,
-                                        no_grad_set)
+    grad_to_var = dict()
+
+    _append_backward_ops_(loss, root_block, root_block, no_grad_dict,
+                          grad_to_var)
     _append_backward_vars_(root_block, fwd_op_num, grad_to_var, grad_info_map)
+
     program.current_block_idx = current_block_idx
     program.sync_with_cpp()