Polish code

test=develop

paddle/fluid/framework/block_desc.cc

@@ -156,6 +156,7 @@ void BlockDesc::RemoveOp(size_t s, size_t e) {
 }
 
 void BlockDesc::RemoveOpInternal(const OpDesc *op_desc) {
+  // TODO(minqiyang): make this faster
   for (auto it = ops_.begin(); it != ops_.end(); ++it) {
     if (it->get() == op_desc) {
       ops_.erase(it);

paddle/fluid/imperative/layer.h

@@ -235,6 +235,8 @@ class PYBIND11_HIDDEN OpBase {
         backward_hooks_() {}
 
   virtual ~OpBase() {
+    // TODO(minqiyang): remove op_desc from block_desc in tracer
+    //
     // reset all output vars' pre op
     for (auto iter : output_vars_) {
       for (VarBase* var : iter.second) {
@@ -242,13 +244,6 @@ class PYBIND11_HIDDEN OpBase {
       }
     }
 
-    // remove op desc from block desc
-    if (op_desc_) {
-      if (block_) {
-        block_->RemoveOpInternal(op_desc_);
-      }
-    }
-
     // release resource
     for (framework::OpDesc* desc : grad_op_descs_) {
       delete desc;

python/paddle/fluid/initializer.py

@@ -19,7 +19,7 @@ import numpy as np
 from .wrapped_decorator import signature_safe_contextmanager
 from .core import VarDesc
 from . import unique_name
-from .imperative import base
+from .imperative import base as imperative_base
 
 __all__ = [
     'Constant', 'Uniform', 'Normal', 'TruncatedNormal', 'Xavier', 'Bilinear',
@@ -166,7 +166,7 @@ class ConstantInitializer(Initializer):
                 'force_cpu': self._force_cpu or force_init_on_cpu()
             },
             stop_gradient=True)
-        if not base.enabled():
+        if not imperative_base.enabled():
             var.op = op
         return op
 
@@ -246,7 +246,7 @@ class UniformInitializer(Initializer):
                 attrs={"in_dtype": out_var.dtype,
                        "out_dtype": var.dtype})
 
-        if not base.enabled():
+        if not imperative_base.enabled():
             var.op = op
         return op
 
@@ -325,7 +325,7 @@ class NormalInitializer(Initializer):
                 outputs={"Out": var},
                 attrs={"in_dtype": out_var.dtype,
                        "out_dtype": var.dtype})
-        if not base.enabled():
+        if not imperative_base.enabled():
             var.op = op
         return op
 
@@ -404,7 +404,7 @@ class TruncatedNormalInitializer(Initializer):
                 outputs={"Out": var},
                 attrs={"in_dtype": out_var.dtype,
                        "out_dtype": var.dtype})
-        if not base.enabled():
+        if not imperative_base.enabled():
             var.op = op
         return op
 
@@ -510,7 +510,7 @@ class XavierInitializer(Initializer):
                     "seed": self._seed
                 },
                 stop_gradient=True)
-        if not base.enabled():
+        if not imperative_base.enabled():
             var.op = op
         return op
 
@@ -611,7 +611,7 @@ class MSRAInitializer(Initializer):
                     "seed": self._seed
                 },
                 stop_gradient=True)
-        if not base.enabled():
+        if not imperative_base.enabled():
             var.op = op
         return op
 
@@ -710,7 +710,7 @@ class BilinearInitializer(Initializer):
                 'shape': list(shape),
                 value_name: values
             })
-        if not base.enabled():
+        if not imperative_base.enabled():
             var.op = op
         return op
 
@@ -769,7 +769,7 @@ class NumpyArrayInitializer(Initializer):
                 value_name: values
             },
             stop_gradient=True)
-        if not base.enabled():
+        if not imperative_base.enabled():
             var.op = op
         return op