[incubator-mxnet-site] branch asf-site updated: Publish triggered by CI

aaronmarkham Tue, 17 Nov 2020 16:51:54 -0800

This is an automated email from the ASF dual-hosted git repository.

aaronmarkham pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git



The following commit(s) were added to refs/heads/asf-site by this push:
     new 75ca4f5  Publish triggered by CI
75ca4f5 is described below

commit 75ca4f5c741ce635a658b6ceb70ac03125301fa9
Author: mxnet-ci <[email protected]>
AuthorDate: Wed Nov 18 00:44:34 2020 +0000

    Publish triggered by CI
---
 api/python/docs/api/contrib/ndarray/index.html     | 14 +++++++-------
 api/python/docs/api/contrib/symbol/index.html      | 14 +++++++-------
 .../docs/api/legacy/ndarray/contrib/index.html     | 14 +++++++-------
 api/python/docs/api/legacy/ndarray/ndarray.html    | 22 +++++++++++-----------
 api/python/docs/api/legacy/ndarray/op/index.html   | 22 +++++++++++-----------
 .../docs/api/legacy/ndarray/sparse/index.html      | 10 +++++-----
 .../docs/api/legacy/symbol/contrib/index.html      | 14 +++++++-------
 api/python/docs/api/legacy/symbol/op/index.html    | 22 +++++++++++-----------
 .../docs/api/legacy/symbol/sparse/index.html       | 10 +++++-----
 api/python/docs/api/legacy/symbol/symbol.html      | 22 +++++++++++-----------
 .../api/npx/generated/mxnet.npx.embedding.html     |  4 ++--
 .../docs/api/npx/generated/mxnet.npx.one_hot.html  |  2 +-
 api/python/docs/searchindex.js                     |  2 +-
 date.txt                                           |  1 -
 feed.xml                                           |  2 +-
 .../api/python/docs/api/contrib/ndarray/index.html | 14 +++++++-------
 .../api/python/docs/api/contrib/symbol/index.html  | 14 +++++++-------
 .../docs/api/legacy/ndarray/contrib/index.html     | 14 +++++++-------
 .../python/docs/api/legacy/ndarray/ndarray.html    | 22 +++++++++++-----------
 .../python/docs/api/legacy/ndarray/op/index.html   | 22 +++++++++++-----------
 .../docs/api/legacy/ndarray/sparse/index.html      | 10 +++++-----
 .../docs/api/legacy/symbol/contrib/index.html      | 14 +++++++-------
 .../python/docs/api/legacy/symbol/op/index.html    | 22 +++++++++++-----------
 .../docs/api/legacy/symbol/sparse/index.html       | 10 +++++-----
 .../api/python/docs/api/legacy/symbol/symbol.html  | 22 +++++++++++-----------
 .../api/npx/generated/mxnet.npx.embedding.html     |  4 ++--
 .../docs/api/npx/generated/mxnet.npx.one_hot.html  |  2 +-
 versions/master/api/python/docs/searchindex.js     |  2 +-
 versions/master/feed.xml                           |  2 +-
 29 files changed, 174 insertions(+), 175 deletions(-)

diff --git a/api/python/docs/api/contrib/ndarray/index.html 
b/api/python/docs/api/contrib/ndarray/index.html
index d80f093..d49bbac 100644
--- a/api/python/docs/api/contrib/ndarray/index.html
+++ b/api/python/docs/api/contrib/ndarray/index.html
@@ -1796,11 +1796,11 @@ The DeformablePSROIPooling operation is described in <a 
class="reference externa
 <li><p><strong>rois</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Bounding box coordinates, a 
2D array of [[batch_index, x1, y1, x2, y2]]. (x1, y1) and (x2, y2) are top left 
and down right corners of designated region of interest. batch_index indicates 
the index of corresponding image in the input data</p></li>
 <li><p><strong>trans</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – transition parameter</p></li>
 <li><p><strong>spatial_scale</strong> (<em>float</em><em>, 
</em><em>required</em>) – Ratio of input feature map height (or w) to raw image 
height (or w). Equals the reciprocal of total stride in convolutional 
layers</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
-<li><p><strong>group_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix group size</p></li>
-<li><p><strong>pooled_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix pooled size</p></li>
-<li><p><strong>part_size</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='0'</em>) – fix part size</p></li>
-<li><p><strong>sample_per_part</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='1'</em>) – fix samples per 
part</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
+<li><p><strong>group_size</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix group size</p></li>
+<li><p><strong>pooled_size</strong> (<em>long</em><em>, 
</em><em>required</em>) – fix pooled size</p></li>
+<li><p><strong>part_size</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix part size</p></li>
+<li><p><strong>sample_per_part</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – fix samples per 
part</p></li>
 <li><p><strong>trans_std</strong> (<em>float</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix transition 
std</p></li>
 <li><p><strong>no_trans</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Whether to disable trans 
parameter.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -4120,8 +4120,8 @@ and max thresholds representing the threholds for 
quantizing the float32 output
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
 <li><p><strong>min_weight</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Minimum value of 
data.</p></li>
 <li><p><strong>max_weight</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Maximum value of 
data.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
diff --git a/api/python/docs/api/contrib/symbol/index.html 
b/api/python/docs/api/contrib/symbol/index.html
index 626c148..74833cd 100644
--- a/api/python/docs/api/contrib/symbol/index.html
+++ b/api/python/docs/api/contrib/symbol/index.html
@@ -1796,11 +1796,11 @@ The DeformablePSROIPooling operation is described in <a 
class="reference externa
 <li><p><strong>rois</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Bounding box coordinates, a 
2D array of [[batch_index, x1, y1, x2, y2]]. (x1, y1) and (x2, y2) are top left 
and down right corners of designated region of interest. batch_index indicates 
the index of corresponding image in the input data</p></li>
 <li><p><strong>trans</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – transition parameter</p></li>
 <li><p><strong>spatial_scale</strong> (<em>float</em><em>, 
</em><em>required</em>) – Ratio of input feature map height (or w) to raw image 
height (or w). Equals the reciprocal of total stride in convolutional 
layers</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
-<li><p><strong>group_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix group size</p></li>
-<li><p><strong>pooled_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix pooled size</p></li>
-<li><p><strong>part_size</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='0'</em>) – fix part size</p></li>
-<li><p><strong>sample_per_part</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='1'</em>) – fix samples per 
part</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
+<li><p><strong>group_size</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix group size</p></li>
+<li><p><strong>pooled_size</strong> (<em>long</em><em>, 
</em><em>required</em>) – fix pooled size</p></li>
+<li><p><strong>part_size</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix part size</p></li>
+<li><p><strong>sample_per_part</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – fix samples per 
part</p></li>
 <li><p><strong>trans_std</strong> (<em>float</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix transition 
std</p></li>
 <li><p><strong>no_trans</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Whether to disable trans 
parameter.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -4125,8 +4125,8 @@ and max thresholds representing the threholds for 
quantizing the float32 output
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The embedding weight 
matrix.</p></li>
 <li><p><strong>min_weight</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Minimum value of 
data.</p></li>
 <li><p><strong>max_weight</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Maximum value of 
data.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
diff --git a/api/python/docs/api/legacy/ndarray/contrib/index.html 
b/api/python/docs/api/legacy/ndarray/contrib/index.html
index 320fce6..d78d39b 100644
--- a/api/python/docs/api/legacy/ndarray/contrib/index.html
+++ b/api/python/docs/api/legacy/ndarray/contrib/index.html
@@ -2130,11 +2130,11 @@ The DeformablePSROIPooling operation is described in <a 
class="reference externa
 <li><p><strong>rois</strong> (<a class="reference internal" 
href="../../symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Bounding box coordinates, a 
2D array of [[batch_index, x1, y1, x2, y2]]. (x1, y1) and (x2, y2) are top left 
and down right corners of designated region of interest. batch_index indicates 
the index of corresponding image in the input data</p></li>
 <li><p><strong>trans</strong> (<a class="reference internal" 
href="../../symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – transition parameter</p></li>
 <li><p><strong>spatial_scale</strong> (<em>float</em><em>, 
</em><em>required</em>) – Ratio of input feature map height (or w) to raw image 
height (or w). Equals the reciprocal of total stride in convolutional 
layers</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
-<li><p><strong>group_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix group size</p></li>
-<li><p><strong>pooled_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix pooled size</p></li>
-<li><p><strong>part_size</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='0'</em>) – fix part size</p></li>
-<li><p><strong>sample_per_part</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='1'</em>) – fix samples per 
part</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
+<li><p><strong>group_size</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix group size</p></li>
+<li><p><strong>pooled_size</strong> (<em>long</em><em>, 
</em><em>required</em>) – fix pooled size</p></li>
+<li><p><strong>part_size</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix part size</p></li>
+<li><p><strong>sample_per_part</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – fix samples per 
part</p></li>
 <li><p><strong>trans_std</strong> (<em>float</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix transition 
std</p></li>
 <li><p><strong>no_trans</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Whether to disable trans 
parameter.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -4454,8 +4454,8 @@ and max thresholds representing the threholds for 
quantizing the float32 output
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
 <li><p><strong>min_weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Minimum value of 
data.</p></li>
 <li><p><strong>max_weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Maximum value of 
data.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
diff --git a/api/python/docs/api/legacy/ndarray/ndarray.html 
b/api/python/docs/api/legacy/ndarray/ndarray.html
index 33dda72..d203b4e 100644
--- a/api/python/docs/api/legacy/ndarray/ndarray.html
+++ b/api/python/docs/api/legacy/ndarray/ndarray.html
@@ -3074,8 +3074,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -6342,9 +6342,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
@@ -9460,7 +9460,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – array of locations where 
to set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
@@ -11853,9 +11853,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
@@ -11894,8 +11894,8 @@ Examples:</p>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
 <li><p><strong>axis</strong> (<em>int</em><em>, </em><em>required</em>) – Axis 
along which to be sliced, supports negative indexes.</p></li>
-<li><p><strong>begin</strong> (<em>int</em><em>, </em><em>required</em>) – The 
beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
-<li><p><strong>end</strong> (<em>int</em><em> or </em><em>None</em><em>, 
</em><em>required</em>) – The ending index along the axis to be sliced,  
supports negative indexes.</p></li>
+<li><p><strong>begin</strong> (<em>long</em><em>, </em><em>required</em>) – 
The beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
+<li><p><strong>end</strong> (<em>, </em><em>required</em>) – The ending index 
along the axis to be sliced,  supports negative indexes.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
diff --git a/api/python/docs/api/legacy/ndarray/op/index.html 
b/api/python/docs/api/legacy/ndarray/op/index.html
index 8ac5582..13b511c 100644
--- a/api/python/docs/api/legacy/ndarray/op/index.html
+++ b/api/python/docs/api/legacy/ndarray/op/index.html
@@ -2939,8 +2939,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -6207,9 +6207,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
@@ -9325,7 +9325,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – array of locations where 
to set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
@@ -11718,9 +11718,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
@@ -11759,8 +11759,8 @@ Examples:</p>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
 <li><p><strong>axis</strong> (<em>int</em><em>, </em><em>required</em>) – Axis 
along which to be sliced, supports negative indexes.</p></li>
-<li><p><strong>begin</strong> (<em>int</em><em>, </em><em>required</em>) – The 
beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
-<li><p><strong>end</strong> (<em>int</em><em> or </em><em>None</em><em>, 
</em><em>required</em>) – The ending index along the axis to be sliced,  
supports negative indexes.</p></li>
+<li><p><strong>begin</strong> (<em>long</em><em>, </em><em>required</em>) – 
The beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
+<li><p><strong>end</strong> (<em>, </em><em>required</em>) – The ending index 
along the axis to be sliced,  supports negative indexes.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
diff --git a/api/python/docs/api/legacy/ndarray/sparse/index.html 
b/api/python/docs/api/legacy/ndarray/sparse/index.html
index 1bd8e39..9143534 100644
--- a/api/python/docs/api/legacy/ndarray/sparse/index.html
+++ b/api/python/docs/api/legacy/ndarray/sparse/index.html
@@ -2661,8 +2661,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -4741,9 +4741,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
diff --git a/api/python/docs/api/legacy/symbol/contrib/index.html 
b/api/python/docs/api/legacy/symbol/contrib/index.html
index e6a6d95..c203ee1 100644
--- a/api/python/docs/api/legacy/symbol/contrib/index.html
+++ b/api/python/docs/api/legacy/symbol/contrib/index.html
@@ -2017,11 +2017,11 @@ The DeformablePSROIPooling operation is described in <a 
class="reference externa
 <li><p><strong>rois</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Bounding box coordinates, a 
2D array of [[batch_index, x1, y1, x2, y2]]. (x1, y1) and (x2, y2) are top left 
and down right corners of designated region of interest. batch_index indicates 
the index of corresponding image in the input data</p></li>
 <li><p><strong>trans</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – transition parameter</p></li>
 <li><p><strong>spatial_scale</strong> (<em>float</em><em>, 
</em><em>required</em>) – Ratio of input feature map height (or w) to raw image 
height (or w). Equals the reciprocal of total stride in convolutional 
layers</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
-<li><p><strong>group_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix group size</p></li>
-<li><p><strong>pooled_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix pooled size</p></li>
-<li><p><strong>part_size</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='0'</em>) – fix part size</p></li>
-<li><p><strong>sample_per_part</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='1'</em>) – fix samples per 
part</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
+<li><p><strong>group_size</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix group size</p></li>
+<li><p><strong>pooled_size</strong> (<em>long</em><em>, 
</em><em>required</em>) – fix pooled size</p></li>
+<li><p><strong>part_size</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix part size</p></li>
+<li><p><strong>sample_per_part</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – fix samples per 
part</p></li>
 <li><p><strong>trans_std</strong> (<em>float</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix transition 
std</p></li>
 <li><p><strong>no_trans</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Whether to disable trans 
parameter.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -4346,8 +4346,8 @@ and max thresholds representing the threholds for 
quantizing the float32 output
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The embedding weight 
matrix.</p></li>
 <li><p><strong>min_weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Minimum value of 
data.</p></li>
 <li><p><strong>max_weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Maximum value of 
data.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
diff --git a/api/python/docs/api/legacy/symbol/op/index.html 
b/api/python/docs/api/legacy/symbol/op/index.html
index 0455de9..8607223 100644
--- a/api/python/docs/api/legacy/symbol/op/index.html
+++ b/api/python/docs/api/legacy/symbol/op/index.html
@@ -2897,8 +2897,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -6168,9 +6168,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
@@ -9287,7 +9287,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – array of locations where to 
set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
@@ -11680,9 +11680,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
@@ -11721,8 +11721,8 @@ Examples:</p>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Source input</p></li>
 <li><p><strong>axis</strong> (<em>int</em><em>, </em><em>required</em>) – Axis 
along which to be sliced, supports negative indexes.</p></li>
-<li><p><strong>begin</strong> (<em>int</em><em>, </em><em>required</em>) – The 
beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
-<li><p><strong>end</strong> (<em>int</em><em> or </em><em>None</em><em>, 
</em><em>required</em>) – The ending index along the axis to be sliced,  
supports negative indexes.</p></li>
+<li><p><strong>begin</strong> (<em>long</em><em>, </em><em>required</em>) – 
The beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
+<li><p><strong>end</strong> (<em>, </em><em>required</em>) – The ending index 
along the axis to be sliced,  supports negative indexes.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
diff --git a/api/python/docs/api/legacy/symbol/sparse/index.html 
b/api/python/docs/api/legacy/symbol/sparse/index.html
index cebd41c..2fa74f3 100644
--- a/api/python/docs/api/legacy/symbol/sparse/index.html
+++ b/api/python/docs/api/legacy/symbol/sparse/index.html
@@ -1646,8 +1646,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -3728,9 +3728,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
diff --git a/api/python/docs/api/legacy/symbol/symbol.html 
b/api/python/docs/api/legacy/symbol/symbol.html
index 7b7ea26..8b4ee54 100644
--- a/api/python/docs/api/legacy/symbol/symbol.html
+++ b/api/python/docs/api/legacy/symbol/symbol.html
@@ -2963,8 +2963,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
The input array to the embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
The embedding weight matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -6234,9 +6234,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
@@ -9353,7 +9353,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
array of locations where to set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
@@ -11746,9 +11746,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
@@ -11787,8 +11787,8 @@ Examples:</p>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
Source input</p></li>
 <li><p><strong>axis</strong> (<em>int</em><em>, </em><em>required</em>) – Axis 
along which to be sliced, supports negative indexes.</p></li>
-<li><p><strong>begin</strong> (<em>int</em><em>, </em><em>required</em>) – The 
beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
-<li><p><strong>end</strong> (<em>int</em><em> or </em><em>None</em><em>, 
</em><em>required</em>) – The ending index along the axis to be sliced,  
supports negative indexes.</p></li>
+<li><p><strong>begin</strong> (<em>long</em><em>, </em><em>required</em>) – 
The beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
+<li><p><strong>end</strong> (<em>, </em><em>required</em>) – The ending index 
along the axis to be sliced,  supports negative indexes.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
diff --git a/api/python/docs/api/npx/generated/mxnet.npx.embedding.html 
b/api/python/docs/api/npx/generated/mxnet.npx.embedding.html
index 635a3c0..e74bd2d 100644
--- a/api/python/docs/api/npx/generated/mxnet.npx.embedding.html
+++ b/api/python/docs/api/npx/generated/mxnet.npx.embedding.html
@@ -1393,8 +1393,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<em>ndarray</em>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<em>ndarray</em>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<em>ndarray</em><em>, </em><em>optional</em>) – 
The output ndarray to hold the result.</p></li>
diff --git a/api/python/docs/api/npx/generated/mxnet.npx.one_hot.html 
b/api/python/docs/api/npx/generated/mxnet.npx.one_hot.html
index 11b226b..83c4240 100644
--- a/api/python/docs/api/npx/generated/mxnet.npx.one_hot.html
+++ b/api/python/docs/api/npx/generated/mxnet.npx.one_hot.html
@@ -1379,7 +1379,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<em>ndarray</em>) – array of locations where 
to set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
diff --git a/api/python/docs/searchindex.js b/api/python/docs/searchindex.js
index 7f7dc34..c4cc397 100644
--- a/api/python/docs/searchindex.js
+++ b/api/python/docs/searchindex.js
@@ -1 +1 @@
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 [...]
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diff --git a/date.txt b/date.txt
deleted file mode 100644
index c76c63b..0000000
--- a/date.txt
+++ /dev/null
@@ -1 +0,0 @@
-Tue Nov 17 18:44:33 UTC 2020
diff --git a/feed.xml b/feed.xml
index 46b36c1..596062a 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1 +1 @@
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xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/"; 
version="4.0.0">Jekyll</generator><link 
href="https://mxnet.apache.org/versions/master/feed.xml"; rel="self" 
type="application/atom+xml" /><link 
href="https://mxnet.apache.org/versions/master/"; rel="alternate" 
type="text/html" 
/><updated>2020-11-17T18:33:31+00:00</updated><id>https://mxnet.apache.org/versions/master/feed.xml</id><title
 type="html">Apache MXNet</title><su [...]
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+<?xml version="1.0" encoding="utf-8"?><feed 
xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/"; 
version="4.0.0">Jekyll</generator><link 
href="https://mxnet.apache.org/versions/master/feed.xml"; rel="self" 
type="application/atom+xml" /><link 
href="https://mxnet.apache.org/versions/master/"; rel="alternate" 
type="text/html" 
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diff --git a/versions/master/api/python/docs/api/contrib/ndarray/index.html 
b/versions/master/api/python/docs/api/contrib/ndarray/index.html
index d80f093..d49bbac 100644
--- a/versions/master/api/python/docs/api/contrib/ndarray/index.html
+++ b/versions/master/api/python/docs/api/contrib/ndarray/index.html
@@ -1796,11 +1796,11 @@ The DeformablePSROIPooling operation is described in <a 
class="reference externa
 <li><p><strong>rois</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Bounding box coordinates, a 
2D array of [[batch_index, x1, y1, x2, y2]]. (x1, y1) and (x2, y2) are top left 
and down right corners of designated region of interest. batch_index indicates 
the index of corresponding image in the input data</p></li>
 <li><p><strong>trans</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – transition parameter</p></li>
 <li><p><strong>spatial_scale</strong> (<em>float</em><em>, 
</em><em>required</em>) – Ratio of input feature map height (or w) to raw image 
height (or w). Equals the reciprocal of total stride in convolutional 
layers</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
-<li><p><strong>group_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix group size</p></li>
-<li><p><strong>pooled_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix pooled size</p></li>
-<li><p><strong>part_size</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='0'</em>) – fix part size</p></li>
-<li><p><strong>sample_per_part</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='1'</em>) – fix samples per 
part</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
+<li><p><strong>group_size</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix group size</p></li>
+<li><p><strong>pooled_size</strong> (<em>long</em><em>, 
</em><em>required</em>) – fix pooled size</p></li>
+<li><p><strong>part_size</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix part size</p></li>
+<li><p><strong>sample_per_part</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – fix samples per 
part</p></li>
 <li><p><strong>trans_std</strong> (<em>float</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix transition 
std</p></li>
 <li><p><strong>no_trans</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Whether to disable trans 
parameter.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -4120,8 +4120,8 @@ and max thresholds representing the threholds for 
quantizing the float32 output
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
 <li><p><strong>min_weight</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Minimum value of 
data.</p></li>
 <li><p><strong>max_weight</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Maximum value of 
data.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
diff --git a/versions/master/api/python/docs/api/contrib/symbol/index.html 
b/versions/master/api/python/docs/api/contrib/symbol/index.html
index 626c148..74833cd 100644
--- a/versions/master/api/python/docs/api/contrib/symbol/index.html
+++ b/versions/master/api/python/docs/api/contrib/symbol/index.html
@@ -1796,11 +1796,11 @@ The DeformablePSROIPooling operation is described in <a 
class="reference externa
 <li><p><strong>rois</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Bounding box coordinates, a 
2D array of [[batch_index, x1, y1, x2, y2]]. (x1, y1) and (x2, y2) are top left 
and down right corners of designated region of interest. batch_index indicates 
the index of corresponding image in the input data</p></li>
 <li><p><strong>trans</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – transition parameter</p></li>
 <li><p><strong>spatial_scale</strong> (<em>float</em><em>, 
</em><em>required</em>) – Ratio of input feature map height (or w) to raw image 
height (or w). Equals the reciprocal of total stride in convolutional 
layers</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
-<li><p><strong>group_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix group size</p></li>
-<li><p><strong>pooled_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix pooled size</p></li>
-<li><p><strong>part_size</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='0'</em>) – fix part size</p></li>
-<li><p><strong>sample_per_part</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='1'</em>) – fix samples per 
part</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
+<li><p><strong>group_size</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix group size</p></li>
+<li><p><strong>pooled_size</strong> (<em>long</em><em>, 
</em><em>required</em>) – fix pooled size</p></li>
+<li><p><strong>part_size</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix part size</p></li>
+<li><p><strong>sample_per_part</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – fix samples per 
part</p></li>
 <li><p><strong>trans_std</strong> (<em>float</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix transition 
std</p></li>
 <li><p><strong>no_trans</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Whether to disable trans 
parameter.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -4125,8 +4125,8 @@ and max thresholds representing the threholds for 
quantizing the float32 output
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The embedding weight 
matrix.</p></li>
 <li><p><strong>min_weight</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Minimum value of 
data.</p></li>
 <li><p><strong>max_weight</strong> (<a class="reference internal" 
href="../../legacy/symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Maximum value of 
data.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
diff --git 
a/versions/master/api/python/docs/api/legacy/ndarray/contrib/index.html 
b/versions/master/api/python/docs/api/legacy/ndarray/contrib/index.html
index 320fce6..d78d39b 100644
--- a/versions/master/api/python/docs/api/legacy/ndarray/contrib/index.html
+++ b/versions/master/api/python/docs/api/legacy/ndarray/contrib/index.html
@@ -2130,11 +2130,11 @@ The DeformablePSROIPooling operation is described in <a 
class="reference externa
 <li><p><strong>rois</strong> (<a class="reference internal" 
href="../../symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Bounding box coordinates, a 
2D array of [[batch_index, x1, y1, x2, y2]]. (x1, y1) and (x2, y2) are top left 
and down right corners of designated region of interest. batch_index indicates 
the index of corresponding image in the input data</p></li>
 <li><p><strong>trans</strong> (<a class="reference internal" 
href="../../symbol/symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – transition parameter</p></li>
 <li><p><strong>spatial_scale</strong> (<em>float</em><em>, 
</em><em>required</em>) – Ratio of input feature map height (or w) to raw image 
height (or w). Equals the reciprocal of total stride in convolutional 
layers</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
-<li><p><strong>group_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix group size</p></li>
-<li><p><strong>pooled_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix pooled size</p></li>
-<li><p><strong>part_size</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='0'</em>) – fix part size</p></li>
-<li><p><strong>sample_per_part</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='1'</em>) – fix samples per 
part</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
+<li><p><strong>group_size</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix group size</p></li>
+<li><p><strong>pooled_size</strong> (<em>long</em><em>, 
</em><em>required</em>) – fix pooled size</p></li>
+<li><p><strong>part_size</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix part size</p></li>
+<li><p><strong>sample_per_part</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – fix samples per 
part</p></li>
 <li><p><strong>trans_std</strong> (<em>float</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix transition 
std</p></li>
 <li><p><strong>no_trans</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Whether to disable trans 
parameter.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -4454,8 +4454,8 @@ and max thresholds representing the threholds for 
quantizing the float32 output
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
 <li><p><strong>min_weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Minimum value of 
data.</p></li>
 <li><p><strong>max_weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Maximum value of 
data.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
diff --git a/versions/master/api/python/docs/api/legacy/ndarray/ndarray.html 
b/versions/master/api/python/docs/api/legacy/ndarray/ndarray.html
index 33dda72..d203b4e 100644
--- a/versions/master/api/python/docs/api/legacy/ndarray/ndarray.html
+++ b/versions/master/api/python/docs/api/legacy/ndarray/ndarray.html
@@ -3074,8 +3074,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -6342,9 +6342,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
@@ -9460,7 +9460,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – array of locations where 
to set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
@@ -11853,9 +11853,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
@@ -11894,8 +11894,8 @@ Examples:</p>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
 <li><p><strong>axis</strong> (<em>int</em><em>, </em><em>required</em>) – Axis 
along which to be sliced, supports negative indexes.</p></li>
-<li><p><strong>begin</strong> (<em>int</em><em>, </em><em>required</em>) – The 
beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
-<li><p><strong>end</strong> (<em>int</em><em> or </em><em>None</em><em>, 
</em><em>required</em>) – The ending index along the axis to be sliced,  
supports negative indexes.</p></li>
+<li><p><strong>begin</strong> (<em>long</em><em>, </em><em>required</em>) – 
The beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
+<li><p><strong>end</strong> (<em>, </em><em>required</em>) – The ending index 
along the axis to be sliced,  supports negative indexes.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
diff --git a/versions/master/api/python/docs/api/legacy/ndarray/op/index.html 
b/versions/master/api/python/docs/api/legacy/ndarray/op/index.html
index 8ac5582..13b511c 100644
--- a/versions/master/api/python/docs/api/legacy/ndarray/op/index.html
+++ b/versions/master/api/python/docs/api/legacy/ndarray/op/index.html
@@ -2939,8 +2939,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -6207,9 +6207,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
@@ -9325,7 +9325,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – array of locations where 
to set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
@@ -11718,9 +11718,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
@@ -11759,8 +11759,8 @@ Examples:</p>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
 <li><p><strong>axis</strong> (<em>int</em><em>, </em><em>required</em>) – Axis 
along which to be sliced, supports negative indexes.</p></li>
-<li><p><strong>begin</strong> (<em>int</em><em>, </em><em>required</em>) – The 
beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
-<li><p><strong>end</strong> (<em>int</em><em> or </em><em>None</em><em>, 
</em><em>required</em>) – The ending index along the axis to be sliced,  
supports negative indexes.</p></li>
+<li><p><strong>begin</strong> (<em>long</em><em>, </em><em>required</em>) – 
The beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
+<li><p><strong>end</strong> (<em>, </em><em>required</em>) – The ending index 
along the axis to be sliced,  supports negative indexes.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
diff --git 
a/versions/master/api/python/docs/api/legacy/ndarray/sparse/index.html 
b/versions/master/api/python/docs/api/legacy/ndarray/sparse/index.html
index 1bd8e39..9143534 100644
--- a/versions/master/api/python/docs/api/legacy/ndarray/sparse/index.html
+++ b/versions/master/api/python/docs/api/legacy/ndarray/sparse/index.html
@@ -2661,8 +2661,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
@@ -4741,9 +4741,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>out</strong> (<a class="reference internal" 
href="../ndarray.html#mxnet.ndarray.NDArray" 
title="mxnet.ndarray.NDArray"><em>NDArray</em></a><em>, </em><em>optional</em>) 
– The output NDArray to hold the result.</p></li>
 </ul>
 </dd>
diff --git 
a/versions/master/api/python/docs/api/legacy/symbol/contrib/index.html 
b/versions/master/api/python/docs/api/legacy/symbol/contrib/index.html
index e6a6d95..c203ee1 100644
--- a/versions/master/api/python/docs/api/legacy/symbol/contrib/index.html
+++ b/versions/master/api/python/docs/api/legacy/symbol/contrib/index.html
@@ -2017,11 +2017,11 @@ The DeformablePSROIPooling operation is described in <a 
class="reference externa
 <li><p><strong>rois</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Bounding box coordinates, a 
2D array of [[batch_index, x1, y1, x2, y2]]. (x1, y1) and (x2, y2) are top left 
and down right corners of designated region of interest. batch_index indicates 
the index of corresponding image in the input data</p></li>
 <li><p><strong>trans</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – transition parameter</p></li>
 <li><p><strong>spatial_scale</strong> (<em>float</em><em>, 
</em><em>required</em>) – Ratio of input feature map height (or w) to raw image 
height (or w). Equals the reciprocal of total stride in convolutional 
layers</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
-<li><p><strong>group_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix group size</p></li>
-<li><p><strong>pooled_size</strong> (<em>int</em><em>, </em><em>required</em>) 
– fix pooled size</p></li>
-<li><p><strong>part_size</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='0'</em>) – fix part size</p></li>
-<li><p><strong>sample_per_part</strong> (<em>int</em><em>, 
</em><em>optional</em><em>, </em><em>default='1'</em>) – fix samples per 
part</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix output dim</p></li>
+<li><p><strong>group_size</strong> (<em>long</em><em>, </em><em>required</em>) 
– fix group size</p></li>
+<li><p><strong>pooled_size</strong> (<em>long</em><em>, 
</em><em>required</em>) – fix pooled size</p></li>
+<li><p><strong>part_size</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix part size</p></li>
+<li><p><strong>sample_per_part</strong> (<em>long</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – fix samples per 
part</p></li>
 <li><p><strong>trans_std</strong> (<em>float</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – fix transition 
std</p></li>
 <li><p><strong>no_trans</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Whether to disable trans 
parameter.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -4346,8 +4346,8 @@ and max thresholds representing the threholds for 
quantizing the float32 output
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The embedding weight 
matrix.</p></li>
 <li><p><strong>min_weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Minimum value of 
data.</p></li>
 <li><p><strong>max_weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Maximum value of 
data.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
diff --git a/versions/master/api/python/docs/api/legacy/symbol/op/index.html 
b/versions/master/api/python/docs/api/legacy/symbol/op/index.html
index 0455de9..8607223 100644
--- a/versions/master/api/python/docs/api/legacy/symbol/op/index.html
+++ b/versions/master/api/python/docs/api/legacy/symbol/op/index.html
@@ -2897,8 +2897,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -6168,9 +6168,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
@@ -9287,7 +9287,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – array of locations where to 
set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
@@ -11680,9 +11680,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
@@ -11721,8 +11721,8 @@ Examples:</p>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Source input</p></li>
 <li><p><strong>axis</strong> (<em>int</em><em>, </em><em>required</em>) – Axis 
along which to be sliced, supports negative indexes.</p></li>
-<li><p><strong>begin</strong> (<em>int</em><em>, </em><em>required</em>) – The 
beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
-<li><p><strong>end</strong> (<em>int</em><em> or </em><em>None</em><em>, 
</em><em>required</em>) – The ending index along the axis to be sliced,  
supports negative indexes.</p></li>
+<li><p><strong>begin</strong> (<em>long</em><em>, </em><em>required</em>) – 
The beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
+<li><p><strong>end</strong> (<em>, </em><em>required</em>) – The ending index 
along the axis to be sliced,  supports negative indexes.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
diff --git 
a/versions/master/api/python/docs/api/legacy/symbol/sparse/index.html 
b/versions/master/api/python/docs/api/legacy/symbol/sparse/index.html
index cebd41c..2fa74f3 100644
--- a/versions/master/api/python/docs/api/legacy/symbol/sparse/index.html
+++ b/versions/master/api/python/docs/api/legacy/symbol/sparse/index.html
@@ -1646,8 +1646,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -3728,9 +3728,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="../symbol.html#mxnet.symbol.Symbol" 
title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
diff --git a/versions/master/api/python/docs/api/legacy/symbol/symbol.html 
b/versions/master/api/python/docs/api/legacy/symbol/symbol.html
index 7b7ea26..8b4ee54 100644
--- a/versions/master/api/python/docs/api/legacy/symbol/symbol.html
+++ b/versions/master/api/python/docs/api/legacy/symbol/symbol.html
@@ -2963,8 +2963,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
The input array to the embedding operator.</p></li>
 <li><p><strong>weight</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
The embedding weight matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
@@ -6234,9 +6234,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
@@ -9353,7 +9353,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
array of locations where to set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
@@ -11746,9 +11746,9 @@ a dense tensor.</p>
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
Source input</p></li>
-<li><p><strong>begin</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– starting indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>end</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) 
– ending indices for the slice operation, supports negative indices.</p></li>
-<li><p><strong>step</strong> 
(<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
+<li><p><strong>begin</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – starting indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>end</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>required</em>) – ending indices for the slice operation, supports 
negative indices.</p></li>
+<li><p><strong>step</strong> (<em>tuple of &lt;&gt;</em><em>, 
</em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>]</em>) – step 
for the slice operation, supports negative values.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
@@ -11787,8 +11787,8 @@ Examples:</p>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<a class="reference internal" 
href="#mxnet.symbol.Symbol" title="mxnet.symbol.Symbol"><em>Symbol</em></a>) – 
Source input</p></li>
 <li><p><strong>axis</strong> (<em>int</em><em>, </em><em>required</em>) – Axis 
along which to be sliced, supports negative indexes.</p></li>
-<li><p><strong>begin</strong> (<em>int</em><em>, </em><em>required</em>) – The 
beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
-<li><p><strong>end</strong> (<em>int</em><em> or </em><em>None</em><em>, 
</em><em>required</em>) – The ending index along the axis to be sliced,  
supports negative indexes.</p></li>
+<li><p><strong>begin</strong> (<em>long</em><em>, </em><em>required</em>) – 
The beginning index along the axis to be sliced,  supports negative 
indexes.</p></li>
+<li><p><strong>end</strong> (<em>, </em><em>required</em>) – The ending index 
along the axis to be sliced,  supports negative indexes.</p></li>
 <li><p><strong>name</strong> (<em>string</em><em>, </em><em>optional.</em>) – 
Name of the resulting symbol.</p></li>
 </ul>
 </dd>
diff --git 
a/versions/master/api/python/docs/api/npx/generated/mxnet.npx.embedding.html 
b/versions/master/api/python/docs/api/npx/generated/mxnet.npx.embedding.html
index 635a3c0..e74bd2d 100644
--- a/versions/master/api/python/docs/api/npx/generated/mxnet.npx.embedding.html
+++ b/versions/master/api/python/docs/api/npx/generated/mxnet.npx.embedding.html
@@ -1393,8 +1393,8 @@ from standard updates. For more details, please check the 
Optimization API at:
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>data</strong> (<em>ndarray</em>) – The input array to the 
embedding operator.</p></li>
 <li><p><strong>weight</strong> (<em>ndarray</em>) – The embedding weight 
matrix.</p></li>
-<li><p><strong>input_dim</strong> (<em>int</em><em>, </em><em>required</em>) – 
Vocabulary size of the input indices.</p></li>
-<li><p><strong>output_dim</strong> (<em>int</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
+<li><p><strong>input_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Vocabulary size of the input indices.</p></li>
+<li><p><strong>output_dim</strong> (<em>long</em><em>, </em><em>required</em>) 
– Dimension of the embedding vectors.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – Data type of weight.</p></li>
 <li><p><strong>sparse_grad</strong> (<em>boolean</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – Compute row sparse 
gradient in the backward calculation. If set to True, the grad’s storage type 
is row_sparse.</p></li>
 <li><p><strong>out</strong> (<em>ndarray</em><em>, </em><em>optional</em>) – 
The output ndarray to hold the result.</p></li>
diff --git 
a/versions/master/api/python/docs/api/npx/generated/mxnet.npx.one_hot.html 
b/versions/master/api/python/docs/api/npx/generated/mxnet.npx.one_hot.html
index 11b226b..83c4240 100644
--- a/versions/master/api/python/docs/api/npx/generated/mxnet.npx.one_hot.html
+++ b/versions/master/api/python/docs/api/npx/generated/mxnet.npx.one_hot.html
@@ -1379,7 +1379,7 @@ in an output array of shape <code class="docutils literal 
notranslate"><span cla
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>indices</strong> (<em>ndarray</em>) – array of locations where 
to set on_value</p></li>
-<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
+<li><p><strong>depth</strong> (<em>long</em><em>, </em><em>required</em>) – 
Depth of the one hot dimension.</p></li>
 <li><p><strong>on_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=1</em>) – The value assigned to 
the locations represented by indices.</p></li>
 <li><p><strong>off_value</strong> (<em>double</em><em>, 
</em><em>optional</em><em>, </em><em>default=0</em>) – The value assigned to 
the locations not represented by indices.</p></li>
 <li><p><strong>dtype</strong> (<em>{'bfloat16'</em><em>, 
</em><em>'float16'</em><em>, </em><em>'float32'</em><em>, 
</em><em>'float64'</em><em>, </em><em>'int32'</em><em>, 
</em><em>'int64'</em><em>, </em><em>'int8'</em><em>, 
</em><em>'uint8'}</em><em>,</em><em>optional</em><em>, 
</em><em>default='float32'</em>) – DType of the output</p></li>
diff --git a/versions/master/api/python/docs/searchindex.js 
b/versions/master/api/python/docs/searchindex.js
index 7f7dc34..c4cc397 100644
--- a/versions/master/api/python/docs/searchindex.js
+++ b/versions/master/api/python/docs/searchindex.js
@@ -1 +1 @@
-Search.setIndex({docnames:["api/autograd/index","api/context/index","api/contrib/index","api/contrib/io/index","api/contrib/ndarray/index","api/contrib/onnx/index","api/contrib/symbol/index","api/contrib/tensorboard/index","api/contrib/tensorrt/index","api/contrib/text/index","api/engine/index","api/executor/index","api/gluon/block","api/gluon/constant","api/gluon/contrib/index","api/gluon/data/index","api/gluon/data/vision/datasets/index","api/gluon/data/vision/index","api/gluon/data/vi
 [...]
\ No newline at end of file
+Search.setIndex({docnames:["api/autograd/index","api/context/index","api/contrib/index","api/contrib/io/index","api/contrib/ndarray/index","api/contrib/onnx/index","api/contrib/symbol/index","api/contrib/tensorboard/index","api/contrib/tensorrt/index","api/contrib/text/index","api/engine/index","api/executor/index","api/gluon/block","api/gluon/constant","api/gluon/contrib/index","api/gluon/data/index","api/gluon/data/vision/datasets/index","api/gluon/data/vision/index","api/gluon/data/vi
 [...]
\ No newline at end of file
diff --git a/versions/master/feed.xml b/versions/master/feed.xml
index 46b36c1..596062a 100644
--- a/versions/master/feed.xml
+++ b/versions/master/feed.xml
@@ -1 +1 @@
-<?xml version="1.0" encoding="utf-8"?><feed 
xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/"; 
version="4.0.0">Jekyll</generator><link 
href="https://mxnet.apache.org/versions/master/feed.xml"; rel="self" 
type="application/atom+xml" /><link 
href="https://mxnet.apache.org/versions/master/"; rel="alternate" 
type="text/html" 
/><updated>2020-11-17T18:33:31+00:00</updated><id>https://mxnet.apache.org/versions/master/feed.xml</id><title
 type="html">Apache MXNet</title><su [...]
\ No newline at end of file
+<?xml version="1.0" encoding="utf-8"?><feed 
xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/"; 
version="4.0.0">Jekyll</generator><link 
href="https://mxnet.apache.org/versions/master/feed.xml"; rel="self" 
type="application/atom+xml" /><link 
href="https://mxnet.apache.org/versions/master/"; rel="alternate" 
type="text/html" 
/><updated>2020-11-18T00:33:38+00:00</updated><id>https://mxnet.apache.org/versions/master/feed.xml</id><title
 type="html">Apache MXNet</title><su [...]
\ No newline at end of file

[incubator-mxnet-site] branch asf-site updated: Publish triggered by CI

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