update DeepCF model

test=develop

paddle/fluid/operators/gather.cu.h

@@ -64,6 +64,7 @@ void GPUGather(const platform::DeviceContext& ctx, const Tensor& src,
   for (int i = 1; i < src_dims.size(); ++i) slice_size *= src_dims[i];
 
   const T* p_src = src.data<T>();
+  // why must be int?
   const int* p_index = index.data<int>();
   T* p_output = output->data<T>();
 

python/paddle/fluid/framework.py

@@ -744,7 +744,7 @@ class Operator(object):
         if _in_imperative_mode():
             if type is None:
                 raise ValueError(
-                    "`type` to initilized an Operator can not be None.")
+                    "`type` to initialized an Operator can not be None.")
             self.iop = core.OpBase(type)
 
             # TODO(minqiyang): remove these lines after we take apart all

python/paddle/fluid/imperative/base.py

@@ -55,7 +55,8 @@ def to_variable(value, block=None):
             type=core.VarDesc.VarType.LOD_TENSOR,
             name=None,
             shape=value.shape,
-            dtype=value.dtype)
+            dtype=value.dtype,
+            stop_gradient=True)
         var = py_var._ivar.value()
         tensor = var.get_tensor()
         tensor.set(value, framework._current_expected_place())

python/paddle/fluid/imperative/tracer.py

@@ -14,7 +14,9 @@
 
 from __future__ import print_function
 
+import sys
 import six
+from six.moves import reduce
 
 from collections import defaultdict
 from paddle.fluid import core
@@ -49,7 +51,16 @@ class Tracer(core.Tracer):
     def trace_op(self, op, stop_gradient=False):
         # record op's trace id
         op.iop._trace_id = self._trace_id
-
+        """
+        all_input_stop_grads = True
+        for vars in op.inputs.values():
+            for v in vars:
+                sys.stderr.write('%s %s\n' % (v.name, v.stop_gradient))
+                all_input_stop_grads &= v.stop_gradient
+
+        stop_gradient = False if not stop_gradient else True
+        stop_gradient = all_input_stop_grads | stop_gradient
+        """
         backward_refs = self.trace(op.iop, op.inputs, op.outputs, op.attrs,
                                    framework._current_expected_place(),
                                    stop_gradient)

python/paddle/fluid/initializer.py

@@ -756,7 +756,7 @@ class NumpyArrayInitializer(Initializer):
             values = [int(v) for v in self._value.flat]
         else:
             raise ValueError("Unsupported dtype %s", self._value.dtype)
-        if self._value.size > 1024 * 1024 * 5:
+        if self._value.size > 1024 * 1024 * 1024:
             raise ValueError("The size of input is too big. Please consider "
                              "saving it to file and 'load_op' to load it")
         op = block._prepend_op(