From cf7c9a65f9bee7a42576b495890f3eb958bac7e4 Mon Sep 17 00:00:00 2001
From: liuxiao93 <liuxiao93@huawei.com>
Date: Fri, 13 Nov 2020 10:56:43 +0800
Subject: [PATCH] fix bug of nn.CentralCrop.

---
 mindspore/nn/layer/image.py   | 15 ++++++---------
 mindspore/nn/layer/pooling.py |  2 +-
 2 files changed, 7 insertions(+), 10 deletions(-)

diff --git a/mindspore/nn/layer/image.py b/mindspore/nn/layer/image.py
index ba7d7d6f4a..a8cacfd960 100644
--- a/mindspore/nn/layer/image.py
+++ b/mindspore/nn/layer/image.py
@@ -409,15 +409,15 @@ def _raise_dims_rank_error(input_shape, param_name, func_name):
     raise ValueError(f"{func_name} {param_name} should be 3d or 4d, but got shape {input_shape}")
 
 @constexpr
-def _get_bbox(rank, shape, size_h, size_w):
+def _get_bbox(rank, shape, central_fraction):
     """get bbox start and size for slice"""
     if rank == 3:
         c, h, w = shape
     else:
         n, c, h, w = shape
 
-    bbox_h_start = int((float(h) - size_h) / 2)
-    bbox_w_start = int((float(w) - size_w) / 2)
+    bbox_h_start = int((float(h) - np.float32(h * central_fraction)) / 2)
+    bbox_w_start = int((float(w) - np.float32(w * central_fraction)) / 2)
     bbox_h_size = h - bbox_h_start * 2
     bbox_w_size = w - bbox_w_start * 2
 
@@ -454,22 +454,19 @@ class CentralCrop(Cell):
     def __init__(self, central_fraction):
         super(CentralCrop, self).__init__()
         validator.check_value_type("central_fraction", central_fraction, [float], self.cls_name)
-        self.central_fraction = validator.check_float_range(central_fraction, 0.0, 1.0, Rel.INC_RIGHT,
-                                                            'central_fraction', self.cls_name)
+        validator.check_float_range(central_fraction, 0.0, 1.0, Rel.INC_RIGHT, 'central_fraction', self.cls_name)
+        self.central_fraction = central_fraction
         self.slice = P.Slice()
 
     def construct(self, image):
         image_shape = F.shape(image)
         rank = len(image_shape)
-        h, w = image_shape[-2], image_shape[-1]
         if not rank in (3, 4):
             return _raise_dims_rank_error(image_shape, "image", self.cls_name)
         if self.central_fraction == 1.0:
             return image
 
-        size_h = self.central_fraction * h
-        size_w = self.central_fraction * w
-        bbox_begin, bbox_size = _get_bbox(rank, image_shape, size_h, size_w)
+        bbox_begin, bbox_size = _get_bbox(rank, image_shape, self.central_fraction)
         image = self.slice(image, bbox_begin, bbox_size)
 
         return image
diff --git a/mindspore/nn/layer/pooling.py b/mindspore/nn/layer/pooling.py
index 7cab152545..9beb5fc80b 100644
--- a/mindspore/nn/layer/pooling.py
+++ b/mindspore/nn/layer/pooling.py
@@ -182,7 +182,7 @@ class MaxPool1d(_PoolNd):
         Tensor of shape :math:`(N, C, L_{out}))`.
 
     Examples:
-        >>> max_pool = nn.MaxPool1d(kernel_size=3, strides=1)
+        >>> max_pool = nn.MaxPool1d(kernel_size=3, stride=1)
         >>> x = Tensor(np.random.randint(0, 10, [1, 2, 4]), mindspore.float32)
         >>> output = max_pool(x)
         >>> output.shape