message: Reduce time of reduction_ops_test
diff: @@ -198,28 +198,9 @@ class SumReductionTest(BaseReductionTest):
  np_arr = self._makeIncremental((2,) * rank, dtypes.float32)
  self._compareAllAxes(np_arr)
  - # make sure we test all possible kernel invocations
  - # logic is the same for all ops, test just float32 for brevity
  - for size_x in [
  - 1, 3, 16, 17, 32, 33, 256, 257, 512, 513, 1024, 1025, 4096, 4097
  - ]:
  - for size_y in [
  - 1, 3, 16, 17, 32, 33, 256, 257, 512, 513, 1024, 1025, 4096, 4097
  - ]:
  - arr = np.ones([size_x, size_y], dtype=np.float32)
  - col_sum = np.sum(arr, axis=0)
  - row_sum = np.sum(arr, axis=1)
  -
  - with self.test_session(graph=ops.Graph(), use_gpu=True) as sess:
  - tf_row_sum = self._tf_reduce(arr, 1, False)
  - tf_col_sum = self._tf_reduce(arr, 0, False)
  - tf_out_row, tf_out_col = sess.run([tf_row_sum, tf_col_sum])
  - self.assertAllClose(col_sum, tf_out_col)
  - self.assertAllClose(row_sum, tf_out_row)
  -
  - for _ in range(1000):
  - size_x = int(2**np.random.uniform(0, 18))
  - size_y = int(2**np.random.uniform(0, 18))
  + for _ in range(10):
  + size_x = int(2**np.random.uniform(0, 15))
  + size_y = int(2**np.random.uniform(0, 15))
  if size_x * size_y > 1e7:
  size_y = int(1e7 / size_x)
  @@ -235,9 +216,9 @@ class SumReductionTest(BaseReductionTest):
  self.assertAllClose(col_sum, tf_out_col)
  self.assertAllClose(row_sum, tf_out_row)
  - for size_x in [1, 3, 16, 33, 65, 129]:
  - for size_y in [1, 3, 16, 33, 65, 129]:
  - for size_z in [1, 3, 16, 33, 65, 129]:
  + for size_x in [1, 3, 16, 33]:
  + for size_y in [1, 3, 16, 33]:
  + for size_z in [1, 3, 16, 33]:
  arr = np.ones([size_x, size_y, size_z], dtype=np.float32)
  sum_y = np.sum(arr, axis=1)
  sum_xz = np.sum(arr, axis=(0, 2))
  