[NewIR]pulish name in backward.py (#56650)

xiaoguoguo626807 · web-flow · commit b32314b67fa9 · 2023-08-25T14:09:30.000+08:00
* modify sum with divide net bug mutablesttribute

* delete prin

* pulish backward

* pulish backward
diff --git a/python/paddle/autograd/backward.py b/python/paddle/autograd/backward.py
@@ -52,8 +52,7 @@ def check_all_puts(block, inputs, outputs):
 
 def update_no_grad_set_by_stopgradient(block, no_grad_set):
     for op in block.ops:
-        for opresult_idx in range(op.num_results()):
-            value = op.result(opresult_idx)
+        for value in op.results():
             if value.stop_gradient and value not in no_grad_set:
                 no_grad_set.add(value)
 
@@ -63,9 +62,7 @@ def update_bwdop_structure(backward_ops, op_to_opgrad_list, grad_op):
     op_to_opgrad_list.append(grad_op)
 
 
-def prepare_grad_outputs(
-    block, grad_outputs, outputs, value_to_valuegrad, op_to_opgrad
-):
+def prepare_grad_outputs(grad_outputs, outputs, state):
     """
     if grad_outputs is none, add fill_1 op to create grad_outputs,
     else check whether outputs shape and dtype is same to grad_outputs, otherwise raise error.
@@ -100,10 +97,10 @@ def prepare_grad_outputs(
 
             update_bwdop_structure(
                 backward_ops,
-                op_to_opgrad[output.get_defining_op()],
+                state.op_to_opgrad[output.get_defining_op()],
                 fillop,
             )
-            value_to_valuegrad[output] = [[output_grad]]
+            state.value_to_valuegrad[output] = [[output_grad]]
         else:
             if output.shape != grad.shape:
                 raise ValueError(
@@ -117,9 +114,11 @@ def prepare_grad_outputs(
                 )
             feedop = grad.get_defining_op()
             update_bwdop_structure(
-                backward_ops, op_to_opgrad[output.get_defining_op()], feedop
+                backward_ops,
+                state.op_to_opgrad[output.get_defining_op()],
+                feedop,
             )
-            value_to_valuegrad[output] = [[grad]]
+            state.value_to_valuegrad[output] = [[grad]]
 
     # add input for bwd first op
     complete_outputs = outputs
@@ -130,7 +129,7 @@ def prepare_grad_outputs(
         if output in visited_output:
             continue
         for opresult in output.get_defining_op().results():
-            if opresult in value_to_valuegrad:
+            if opresult in state.value_to_valuegrad:
                 visited_output.add(opresult)
                 continue
             else:
@@ -143,10 +142,10 @@ def prepare_grad_outputs(
 
                 update_bwdop_structure(
                     backward_ops,
-                    op_to_opgrad[opresult.get_defining_op()],
+                    state.op_to_opgrad[opresult.get_defining_op()],
                     fillop,
                 )
-                value_to_valuegrad[opresult] = [grad_value]
+                state.value_to_valuegrad[opresult] = [grad_value]
 
                 visited_output.add(opresult)
 
@@ -196,7 +195,6 @@ def prune_ops(total_ops, inputs_set, outputs_set, no_grad_set):
 
     # from output to input
     for i, op in reversed(list(enumerate(total_ops))):
-        # while op support
         if some_in_set(op.results(), outputs_set):
             for operand in op.operands_source():
                 if operand not in no_grad_set:
@@ -233,7 +231,7 @@ def prune_ops(total_ops, inputs_set, outputs_set, no_grad_set):
 
 
 def update_no_grad_set_after_prune(
-    block, effective_forward_op, no_grad_set, inputs, outputs
+    block, effective_forward_ops, no_grad_set, inputs, outputs
 ):
     '''
     update no_grad_set after forward prune
@@ -249,14 +247,14 @@ def update_no_grad_set_after_prune(
                     if value not in no_grad_set:
                         inputs_set.add(value)
 
-        for op in effective_forward_op:
+        for op in effective_forward_ops:
             for value in op.operands_source():
-                if value not in inputs_set:  # and value.get_stopgradient():
+                if value not in inputs_set:
                     no_grad_set.add(value)
 
     outputs_set = set(outputs)
     no_grad_set_tmp = set()
-    for op in reversed(effective_forward_op):
+    for op in reversed(effective_forward_ops):
         for output in op.results():
             if output not in outputs_set and not some_in_set(
                 [output], set(op.operands_source())
@@ -313,7 +311,7 @@ def inverse_sort_op(ops):
 
 
 def append_backward_ops(
-    block, effective_forward_op, no_grad_set, backward_ops, state
+    block, effective_forward_ops, no_grad_set, backward_ops, state
 ):
     '''
     add grad_op in order of topological inverse sort
@@ -417,28 +415,26 @@ def make_output_grad(op):
         return zero_flag, output_grad
 
     def make_input_stopgradient(op):
-        input_grad_stopgradient_list = []
+        input_grad_stopgradients = []
         for input in op.operands_source():
             if input.get_defining_op().name() == "builtin.combine":
                 stop_gradient = make_input_stopgradient(input.get_defining_op())
-                input_grad_stopgradient_list.append(
+                input_grad_stopgradients.append(
                     [info[0] for info in stop_gradient]
                 )
             else:
                 if input in no_grad_set:
-                    input_grad_stopgradient_list.append([True])
+                    input_grad_stopgradients.append([True])
                 else:
-                    input_grad_stopgradient_list.append([False])
-        return input_grad_stopgradient_list
+                    input_grad_stopgradients.append([False])
+        return input_grad_stopgradients
 
-    def update_input_grad_map(op, input_grad_list):
+    def update_input_grad_map(op, input_grads):
         for i, input in enumerate(op.operands_source()):
             if input.get_defining_op().name() == "builtin.combine":
-                update_input_grad_map(
-                    input.get_defining_op(), input_grad_list[i]
-                )
+                update_input_grad_map(input.get_defining_op(), input_grads[i])
             else:
-                input_grad = input_grad_list[i]
+                input_grad = input_grads[i]
                 if isinstance(input_grad, list):
                     state.value_to_valuegrad[input].append(input_grad)
                 else:
@@ -451,31 +447,31 @@ def update_input_grad_map(op, input_grad_list):
     # [op4] (op4's inputs and outputs are not vectorType)
     # einsum has twp vectorType outputs, special pattern
 
-    clear_effective_forward_op = []
+    clear_effective_forward_ops = []
 
-    for op in effective_forward_op:
+    for op in effective_forward_ops:
         if op.name() != "builtin.combine" and op.name() != "builtin.split":
-            clear_effective_forward_op.append(op)
+            clear_effective_forward_ops.append(op)
 
-    for op in clear_effective_forward_op:
+    for op in clear_effective_forward_ops:
         if paddle.framework.core.has_vjp(op):
             # prepare output_grad
-            output_grad_list = []  # (opresult)
+            output_grads = []  # (opresult)
             zero_flag, output_grad = make_output_grad(op)
-            output_grad_list.append(output_grad)
+            output_grads.append(output_grad)
 
             # all(zero_flag) support this op has no contribution for grad
             # should be delete (prune sub_graph)
-            if len(output_grad_list) == 0 or all(zero_flag):
+            if len(output_grads) == 0 or all(zero_flag):
                 continue
 
             # prepare input_grad stop_gradient info.
-            input_grad_stopgradient_list = make_input_stopgradient(op)
+            input_grad_stopgradients = make_input_stopgradient(op)
 
             # create grad_op
             before_ops_num = len(block.ops)
-            input_grad_list = paddle.framework.core.call_vjp(
-                op, output_grad_list, input_grad_stopgradient_list
+            input_grads = paddle.framework.core.call_vjp(
+                op, output_grads, input_grad_stopgradients
             )
             after_ops_num = len(block.ops)
 
@@ -486,7 +482,7 @@ def update_input_grad_map(op, input_grad_list):
                 )
 
             # update input_grad map
-            update_input_grad_map(op, input_grad_list)
+            update_input_grad_map(op, input_grads)
 
         else:
             if op.num_operands() == 0 and op.num_results() != 0:
@@ -519,15 +515,18 @@ def update_input_grad_map(op, input_grad_list):
 
 def create_backward_prune_set(inputs, outputs, no_grad_set, state):
     outputs_set = set()
-    for input in inputs:
-        for item in input.first_use().owner().operands_source():
-            if state.value_to_valuegrad[item] != []:
-                outputs_set.add(state.value_to_valuegrad[item][0][0])
+    for input_ in inputs:
+        if not input_.use_empty():
+            for item in input_.first_use().owner().operands_source():
+                if state.value_to_valuegrad[item] != []:
+                    outputs_set.add(state.value_to_valuegrad[item][0][0])
+        else:
+            raise ValueError("input privided by inputs has no use")
+
     inputs_set = set()
     for output in outputs:
         if state.value_to_valuegrad[output] != []:
             inputs_set.add(state.value_to_valuegrad[output][0][0])
-
     inputs_set_tmp = set()
     for out_grad in inputs_set:
         for item in out_grad.first_use().owner().operands_source():
@@ -538,7 +537,6 @@ def create_backward_prune_set(inputs, outputs, no_grad_set, state):
     for key in state.value_to_valuegrad:
         if key in no_grad_set:
             no_gradvar_set.add(state.value_to_valuegrad[key][0][0])
-
     for key in state.value_to_sumvaluegrad:
         if key in no_grad_set:
             for item in state.value_to_sumvaluegrad[key][0]:
@@ -575,26 +573,22 @@ def calc_gradient_helper(outputs, inputs, grad_outputs, no_grad_set):
     # update no_grad_set if some value stop_gradient=True
     update_no_grad_set_by_stopgradient(block, no_grad_set)
     complete_outputs, _, backward_ops = prepare_grad_outputs(
-        block,
-        grad_outputs,
-        outputs,
-        state.value_to_valuegrad,
-        state.op_to_opgrad,
+        grad_outputs, outputs, state
     )
 
     inputs_set = set(inputs)
     outputs_set = set(complete_outputs)
-    effective_forward_op, _ = prune_ops(
+    effective_forward_ops, _ = prune_ops(
         block.ops, inputs_set, outputs_set, no_grad_set
     )
     update_no_grad_set_after_prune(
-        block, effective_forward_op, no_grad_set, inputs, complete_outputs
+        block, effective_forward_ops, no_grad_set, inputs, complete_outputs
     )
 
-    inverse_effective_forward_op = inverse_sort_op(effective_forward_op)
+    inverse_effective_forward_ops = inverse_sort_op(effective_forward_ops)
 
     append_backward_ops(
-        block, inverse_effective_forward_op, no_grad_set, backward_ops, state
+        block, inverse_effective_forward_ops, no_grad_set, backward_ops, state
     )
     # now value_to_valuegrad should be value <-> value (add sum op for the same values's gradvalue)
 
@@ -719,26 +713,26 @@ def grad(
         outputs,
         'outputs',
         ((paddle.ir.Value, paddle.ir.OpResult), list, tuple),
-        'paddle.ir.grad',
+        'paddle.autograd.backward.grad',
     )
     check_type(
         inputs,
         'inputs',
         ((paddle.ir.Value, paddle.ir.OpResult), list, tuple),
-        'paddle.ir.grad',
+        'paddle.autograd.backward.grad',
     )
     check_type(
         grad_outputs,
         'grad_outputs',
         ((paddle.ir.Value, paddle.ir.OpResult), list, tuple, type(None)),
-        'paddle.ir.grad',
+        'paddle.autograd.backward.grad',
     )
 
     check_type(
         no_grad_vars,
         'no_grad_vars',
         ((paddle.ir.Value, paddle.ir.OpResult), list, tuple, set, type(None)),
-        'paddle.ir.grad',
+        'paddle.autograd.backward.grad',
     )
     outputs = _as_list(outputs)
     inputs = _as_list(inputs)
