Fix round(0.0) special issue

python/paddle/fluid/compat.py

@@ -183,9 +183,11 @@ def round(x, d=0):
         if x > 0.0:
             p = 10 ** d
             return float(math.floor((x * p) + math.copysign(0.5, x))) / p
-        else:
+        elif x < 0.0:
             p = 10 ** d
             return float(math.ceil((x * p) + math.copysign(0.5, x))) / p
+        else:
+            return math.copysign(0.0, x)
     else:
         import __builtin__
         return __builtin__.round(x, d)

python/paddle/fluid/debugger.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 import sys
+import six
 import re
 from .graphviz import GraphPreviewGenerator
 from .proto import framework_pb2

python/paddle/fluid/graphviz.py

@@ -15,6 +15,7 @@
 import os
 import random
 import six
+import functools
 import subprocess
 import logging
 

python/paddle/fluid/profiler.py

@@ -15,6 +15,7 @@
 from . import core
 from contextlib import contextmanager
 import os
+import six
 
 __all__ = [
     'cuda_profiler', 'reset_profiler', 'profiler', 'start_profiler',
@@ -88,7 +89,7 @@ def cuda_profiler(output_file, output_mode=None, config=None):
     config = NVPROF_CONFIG if config is None else config
     config_file = 'nvprof_config_file'
     with open(config_file, 'wb') as fp:
-        fp.writelines(["%s\n" % item for item in config])
+        fp.writelines([six.b("%s\n" % item) for item in config])
     core.nvprof_init(output_file, output_mode, config_file)
     # Enables profiler collection by the active CUDA profiling tool.
     core.nvprof_start()

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

@@ -440,6 +440,8 @@ class TestCompatible(unittest.TestCase):
         self.assertEqual(3.0, cpt.round(3.4))
         self.assertEqual(4.0, cpt.round(3.5))
         self.assertEqual(0.0, cpt.round(0.1))
+        self.assertEqual(0.0, cpt.round(0.0))
+        self.assertEqual(-0.0, cpt.round(-0.0))
         self.assertEqual(-0.0, cpt.round(-0.1))
         self.assertEqual(-3.0, cpt.round(-3.4))
         self.assertEqual(-4.0, cpt.round(-3.5))

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

@@ -21,7 +21,7 @@ def conv_shift_forward(x, y):
     out = np.zeros_like(x)
     M = x.shape[1]
     N = y.shape[1]
-    y_half_width = (N - 1) / 2
+    y_half_width = (N - 1) // 2
     for i in range(M):
         for j in range(N):
             out[:, i] += x[:, (i + j + M - y_half_width) % M] * y[:, j]

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

@@ -15,6 +15,7 @@
 import unittest
 import numpy as np
 import math
+import functools
 from op_test import OpTest
 from test_lstm_op import identity, sigmoid, tanh, relu
 
@@ -38,7 +39,7 @@ class TestGRUOp(OpTest):
         for i in range(len(seq_lens)):
             seq_starts.append(seq_starts[-1] + seq_lens[i])
         sorted_seqs = sorted(
-            list(range(len(seq_lens))), lambda x, y: seq_lens[y] - seq_lens[x])
+            list(range(len(seq_lens))), key=functools.cmp_to_key(lambda x, y: seq_lens[y] - seq_lens[x]))
         num_batch = seq_lens[sorted_seqs[0]]
         for batch_idx in range(num_batch):
             idx_in_seq = []

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

@@ -14,6 +14,7 @@
 
 import unittest
 
+import six
 import numpy as np
 import paddle.fluid.core as core
 
@@ -48,7 +49,7 @@ class TestBook(unittest.TestCase):
 
         exe.run(init_program, feed={}, fetch_list=[])
 
-        for i in range(100):
+        for i in six.moves.xrange(100):
             tensor_x = np.array(
                 [[1, 1], [1, 2], [3, 4], [5, 2]]).astype("float32")
             tensor_y = np.array([[-2], [-3], [-7], [-7]]).astype("float32")
@@ -64,7 +65,7 @@ class TestBook(unittest.TestCase):
                                  'y': tensor_y},
                            fetch_list=[avg_cost])[0]
 
-        reload(executor)  # reload to build a new scope
+        six.moves.reload_module(executor)  # reload to build a new scope
         exe = executor.Executor(place)
 
         [infer_prog, feed_var_names, fetch_vars] = load_inference_model(

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

@@ -24,9 +24,9 @@ def max_pool3D_forward_naive(x, ksize, strides, paddings, global_pool=False):
         ksize = [D, H, W]
         paddings = [0, 0, 0]
 
-    D_out = (D - ksize[0] + 2 * paddings[0]) / strides[0] + 1
-    H_out = (H - ksize[1] + 2 * paddings[1]) / strides[1] + 1
-    W_out = (W - ksize[2] + 2 * paddings[2]) / strides[2] + 1
+    D_out = (D - ksize[0] + 2 * paddings[0]) // strides[0] + 1
+    H_out = (H - ksize[1] + 2 * paddings[1]) // strides[1] + 1
+    W_out = (W - ksize[2] + 2 * paddings[2]) // strides[2] + 1
     out = np.zeros((N, C, D_out, H_out, W_out))
     mask = np.zeros((N, C, D_out, H_out, W_out))
     for k in range(D_out):
@@ -63,8 +63,8 @@ def max_pool2D_forward_naive(x, ksize, strides, paddings, global_pool=False):
         ksize = [H, W]
         paddings = [0, 0]
 
-    H_out = (H - ksize[0] + 2 * paddings[0]) / strides[0] + 1
-    W_out = (W - ksize[1] + 2 * paddings[1]) / strides[1] + 1
+    H_out = (H - ksize[0] + 2 * paddings[0]) // strides[0] + 1
+    W_out = (W - ksize[1] + 2 * paddings[1]) // strides[1] + 1
     out = np.zeros((N, C, H_out, W_out))
     mask = np.zeros((N, C, H_out, W_out))
     for i in range(H_out):