Change iter_parameters back and port unittests code to Python3

Author: velconia

python/paddle/fluid/framework.py

@@ -963,9 +963,9 @@ def _var_recursive(self, name):
         raise ValueError("Var {0} is not found recursively".format(name))
 
     def all_parameters(self):
-        return list(self._iter_parameters())
+        return list(self.iter_parameters())
 
-    def _iter_parameters(self):
+    def iter_parameters(self):
         return (item[1] for item in list(self.vars.items())
                 if isinstance(item[1], Parameter))
 
@@ -1199,7 +1199,7 @@ def _copy_param_info_from(self, other):
         if not isinstance(other, Block):
             raise TypeError(
                 "_copy_param_info_from should be invoked with Block")
-        for p in other._iter_parameters():
+        for p in other.iter_parameters():
             assert isinstance(p, Parameter)
             v = self.vars.get(p.name, None)
             if v is None:

python/paddle/fluid/tests/test_beam_search_decoder.py

@@ -155,7 +155,7 @@ def train_loop(main_program):
         ]
         feeder = fluid.DataFeeder(feed_list, place)
 
-        for pass_id in xrange(1):
+        for pass_id in range(1):
             for batch_id, data in enumerate(train_reader()):
                 outs = exe.run(main_program,
                                feed=feeder.feed(data),
@@ -204,8 +204,8 @@ def decode_main(use_cuda):
     ]
     feeder = fluid.DataFeeder(feed_list, place)
 
-    data = train_reader().next()
-    feed_dict = feeder.feed(map(lambda x: [x[0]], data))
+    data = next(train_reader())
+    feed_dict = feeder.feed([[x[0]] for x in data])
     feed_dict['init_ids'] = init_ids
     feed_dict['init_scores'] = init_scores
 
@@ -214,7 +214,7 @@ def decode_main(use_cuda):
         feed=feed_dict,
         fetch_list=[translation_ids, translation_scores],
         return_numpy=False)
-    print result_ids.lod()
+    print(result_ids.lod())
 
 
 class TestBeamSearchDecoder(unittest.TestCase):

python/paddle/fluid/tests/unittests/dist_se_resnext.py

@@ -301,15 +301,15 @@ def run_trainer(self, place, endpoints, trainer_id, trainers, is_dist=True):
             trainer_id=trainer_id)
 
         feed_var_list = [
-            var for var in trainer_prog.global_block().vars.itervalues()
+            var for var in trainer_prog.global_block().vars.values()
             if var.is_data
         ]
 
         feeder = fluid.DataFeeder(feed_var_list, place)
         reader_generator = train_reader()
         first_loss, = exe.run(fetch_list=[avg_cost.name])
         print(first_loss)
-        for i in xrange(5):
+        for i in range(5):
             loss, = exe.run(fetch_list=[avg_cost.name])
         last_loss, = exe.run(fetch_list=[avg_cost.name])
         print(last_loss)

python/paddle/fluid/tests/unittests/op_test.py

@@ -25,14 +25,16 @@
 from paddle.fluid.op import Operator
 from paddle.fluid.executor import Executor
 from paddle.fluid.framework import Program, OpProtoHolder, Variable
-from testsuite import create_op, set_input, append_input_output, append_loss_ops
+from .testsuite import create_op, set_input, append_input_output, append_loss_ops
+from functools import reduce
+from six.moves import zip
 
 
 def randomize_probability(batch_size, class_num, dtype='float32'):
     prob = np.random.uniform(
         0.1, 1.0, size=(batch_size, class_num)).astype(dtype)
     prob_sum = prob.sum(axis=1)
-    for i in xrange(len(prob)):
+    for i in range(len(prob)):
         prob[i] /= prob_sum[i]
     return prob
 
@@ -86,7 +88,7 @@ def __set_elem__(tensor, i, e):
 
     # we only compute gradient of one element each time.
     # we use a for loop to compute the gradient of every element.
-    for i in xrange(tensor_size):
+    for i in range(tensor_size):
         if in_place:
             set_input(scope, op, inputs, place)
 
@@ -139,7 +141,7 @@ def infer_dtype(numpy_dict):
             assert isinstance(
                 numpy_dict,
                 dict), "self.inputs, self.outputs must be numpy_dict"
-            for var_name, var_value in numpy_dict.iteritems():
+            for var_name, var_value in numpy_dict.items():
                 if isinstance(var_value, (np.ndarray, np.generic)):
                     self.try_call_once(var_value.dtype)
                 elif isinstance(var_value, (list, tuple)):
@@ -197,7 +199,7 @@ def _append_ops(self, block):
 
     def _get_io_vars(self, block, numpy_inputs):
         inputs = {}
-        for name, value in numpy_inputs.iteritems():
+        for name, value in numpy_inputs.items():
             if isinstance(value, list):
                 var_list = [
                     block.var(sub_name) for sub_name, sub_value in value
@@ -240,7 +242,7 @@ def _calc_output(self, place, parallel=False):
         # if the fetch_list is customized by user, we use it directly.
         # if not, fill the fetch_list by the user configured outputs in test.
         if len(fetch_list) == 0:
-            for var_name, var in outputs.iteritems():
+            for var_name, var in outputs.items():
                 if isinstance(var, list):
                     for v in var:
                         fetch_list.append(v)
@@ -252,7 +254,7 @@ def _calc_output(self, place, parallel=False):
                 fetch_list.append(str(out_name))
         # fetch_list = map(block.var, fetch_list)
         if not isinstance(fetch_list[0], fluid.framework.Variable):
-            fetch_list = map(block.var, fetch_list)
+            fetch_list = list(map(block.var, fetch_list))
         outs = executor.run(program,
                             feed=feed_map,
                             fetch_list=fetch_list,
@@ -334,7 +336,7 @@ def check_output_customized(self, checker):
     def __assert_is_close(self, numeric_grads, analytic_grads, names,
                           max_relative_error, msg_prefix):
 
-        for a, b, name in itertools.izip(numeric_grads, analytic_grads, names):
+        for a, b, name in zip(numeric_grads, analytic_grads, names):
             abs_a = np.abs(a)
             abs_a[abs_a < 1e-3] = 1
 
@@ -460,6 +462,6 @@ def _get_gradient(self,
                 use_cuda=use_cuda, loss_name=loss.name, main_program=program)
         else:
             executor = Executor(place)
-        return map(np.array,
-                   executor.run(prog, feed_dict, fetch_list,
-                                return_numpy=False))
+        return list(
+            map(np.array,
+                executor.run(prog, feed_dict, fetch_list, return_numpy=False)))

python/paddle/fluid/tests/unittests/test_accuracy_op.py

@@ -14,7 +14,7 @@
 
 import unittest
 import numpy as np
-from op_test import OpTest
+from .op_test import OpTest
 
 
 class TestAccuracyOp(OpTest):
@@ -26,7 +26,7 @@ def setUp(self):
         label = np.random.randint(0, 2, (n, 1))
         self.inputs = {'Out': infer, 'Indices': indices, "Label": label}
         num_correct = 0
-        for rowid in xrange(n):
+        for rowid in range(n):
             for ele in indices[rowid]:
                 if ele == label[rowid]:
                     num_correct += 1

python/paddle/fluid/tests/unittests/test_activation_mkldnn_op.py

@@ -15,9 +15,9 @@
 import unittest
 import numpy as np
 import paddle.fluid.core as core
-from op_test import OpTest
+from .op_test import OpTest
 from scipy.special import expit
-from test_activation_op import TestRelu, TestTanh, TestSqrt, TestAbs
+from .test_activation_op import TestRelu, TestTanh, TestSqrt, TestAbs
 
 
 class TestMKLDNNReluDim2(TestRelu):

python/paddle/fluid/tests/unittests/test_activation_op.py

@@ -15,7 +15,7 @@
 import unittest
 import numpy as np
 import paddle.fluid.core as core
-from op_test import OpTest
+from .op_test import OpTest
 from scipy.special import expit
 
 

python/paddle/fluid/tests/unittests/test_adadelta_op.py

@@ -14,7 +14,7 @@
 
 import unittest
 import numpy as np
-from op_test import OpTest
+from .op_test import OpTest
 
 
 class TestAdadeltaOp1(OpTest):

python/paddle/fluid/tests/unittests/test_adagrad_op.py

@@ -16,7 +16,7 @@
 import numpy as np
 import paddle.fluid.core as core
 from paddle.fluid.op import Operator
-from op_test import OpTest
+from .op_test import OpTest
 import math
 
 

python/paddle/fluid/tests/unittests/test_adam_op.py

@@ -14,7 +14,7 @@
 
 import unittest
 import numpy as np
-from op_test import OpTest
+from .op_test import OpTest
 from paddle.fluid import core
 from paddle.fluid.op import Operator
 
@@ -273,7 +273,7 @@ def check_with_place(self, place):
         self.setup(scope, place)
 
         op_args = dict()
-        for key, np_array in self.dense_inputs.iteritems():
+        for key, np_array in self.dense_inputs.items():
             var = scope.var(key).get_tensor()
             var.set(np_array, place)
             op_args[key] = key
@@ -290,7 +290,7 @@ def check_with_place(self, place):
         adam_op = Operator("adam", **op_args)
         adam_op.run(scope, place)
 
-        for key, np_array in self.outputs.iteritems():
+        for key, np_array in self.outputs.items():
             out_var = scope.var(key).get_tensor()
             actual = np.array(out_var)
             actual = actual.reshape([actual.size])