From d6bfd938f17d9b95ebcb42c5e8e7df6788ca2bde Mon Sep 17 00:00:00 2001
From: Leyuan Wang <laurawly@gmail.com>
Date: Tue, 19 Mar 2019 22:05:01 +0000
Subject: [PATCH] fix lint

---
 topi/python/topi/cuda/sort.py |  7 +++--
 topi/python/topi/sort.py      | 49 +++++++++++++++++++++++++++++++++++
 2 files changed, 52 insertions(+), 4 deletions(-)

diff --git a/topi/python/topi/cuda/sort.py b/topi/python/topi/cuda/sort.py
index 6d13c319f352..8918d3ed78fc 100644
--- a/topi/python/topi/cuda/sort.py
+++ b/topi/python/topi/cuda/sort.py
@@ -42,7 +42,7 @@ def sort_ir(data, valid_count, output, axis, is_ascend, flag):
     axis_mul_after = 1
     shape = data.shape
     if axis < 0:
-        axis = len(shape) + axis;
+        axis = len(shape) + axis
     for i in range(0, len(shape)):
         size *= shape[i]
         if i < axis:
@@ -112,12 +112,12 @@ def argsort_gpu(data, valid_count, axis=-1, is_ascend=1, flag=0):
     out : tvm.Tensor
         The output of this function.
     """
-    data_buf = api.decl_buffer(data.shape, data.dtype,"data_buf", data_alignment=8)
+    data_buf = api.decl_buffer(data.shape, data.dtype, "data_buf", data_alignment=8)
     valid_count_buf = api.decl_buffer(valid_count.shape, valid_count.dtype,
                                       "valid_count_buf", data_alignment=4)
     out_buf = api.decl_buffer(data.shape, "int32", "out_buf", data_alignment=4)
 
-    out =  tvm.extern([data.shape],
+    out = tvm.extern([data.shape],
                       [data, valid_count],
                       lambda ins, outs: sort_ir(
                           ins[0], ins[1], outs[0], axis, bool(is_ascend), bool(flag)),
@@ -127,4 +127,3 @@ def argsort_gpu(data, valid_count, axis=-1, is_ascend=1, flag=0):
                       name="argsort_gpu",
                       tag="argsort_gpu")
     return out
-
diff --git a/topi/python/topi/sort.py b/topi/python/topi/sort.py
index 8f7d70db62fc..653ed6f6a0a6 100644
--- a/topi/python/topi/sort.py
+++ b/topi/python/topi/sort.py
@@ -3,6 +3,55 @@
 
 @tvm.target.generic_func
 def argsort(data, valid_count, axis=-1, is_ascend=1, flag=0):
+    """Performs sorting along the given axis and returns an array
+    of indices having the same shape as an input array that index
+    data in sorted order.
+
+    Parameters
+    ----------
+    data : tvm.Tensor
+        The input tensor.
+
+    valid_count : tvm.Tensor
+        1-D tensor for valid number of boxes only for ssd.
+
+    axis : optional, int
+	Axis along which to sort the input tensor.
+        By default the flattened array is used.
+
+    is_ascend : optional, boolean
+        Whether to sort in ascending or descending order.
+
+    flag : optional, boolean
+        Whether valid_count is valid.
+
+    Returns
+    -------
+    out : tvm.Tensor
+        Sorted index tensor.
+
+    Example
+    --------
+    .. code-block:: python
+
+        # An example to use argsort
+        dshape = (1, 5, 6)
+        data = tvm.placeholder(dshape, name="data")
+        valid_count = tvm.placeholder((dshape[0],), dtype="int32", name="valid_count")
+        axis = 0
+        is_ascend = False
+        flag = False
+        out = argsort(data, valid_count, axis, is_ascend, flag)
+        np_data = np.random.uniform(dshape)
+        np_valid_count = np.array([4])
+        s = topi.generic.schedule_argsort(out)
+        f = tvm.build(s, [data, valid_count, out], "llvm")
+        ctx = tvm.cpu()
+        tvm_data = tvm.nd.array(np_data, ctx)
+        tvm_valid_count = tvm.nd.array(np_valid_count, ctx)
+        tvm_out = tvm.nd.array(np.zeros(dshape, dtype=data.dtype), ctx)
+        f(tvm_data, tvm_valid_count, tvm_out)
+    """
     data_buf = api.decl_buffer(data.shape, data.dtype,
                                "sort_data_buf", data_alignment=8)
     valid_count_buf = api.decl_buffer(valid_count.shape, valid_count.dtype,