From 80b8124d60f8bd118aed6ce11f4e200f8e2236a9 Mon Sep 17 00:00:00 2001
From: bai-yangfan <baiyangfan@huawei.com>
Date: Wed, 16 Dec 2020 11:16:04 +0800
Subject: [PATCH] nn_notes

---
 mindspore/nn/metrics/error.py     | 2 ++
 mindspore/nn/metrics/fbeta.py     | 5 +++--
 mindspore/nn/metrics/precision.py | 3 +++
 mindspore/nn/metrics/recall.py    | 2 ++
 mindspore/nn/wrap/cell_wrapper.py | 5 +++--
 5 files changed, 13 insertions(+), 4 deletions(-)

diff --git a/mindspore/nn/metrics/error.py b/mindspore/nn/metrics/error.py
index 4b517d9d82..5abae9430d 100644
--- a/mindspore/nn/metrics/error.py
+++ b/mindspore/nn/metrics/error.py
@@ -39,6 +39,8 @@ class MAE(Metric):
         >>> error.clear()
         >>> error.update(x, y)
         >>> result = error.eval()
+        >>> print(result)
+        0.037499990314245224
     """
     def __init__(self):
         super(MAE, self).__init__()
diff --git a/mindspore/nn/metrics/fbeta.py b/mindspore/nn/metrics/fbeta.py
index d5a7087288..f2f3b435dc 100755
--- a/mindspore/nn/metrics/fbeta.py
+++ b/mindspore/nn/metrics/fbeta.py
@@ -36,10 +36,11 @@ class Fbeta(Metric):
         >>> x = Tensor(np.array([[0.2, 0.5], [0.3, 0.1], [0.9, 0.6]]))
         >>> y = Tensor(np.array([1, 0, 1]))
         >>> metric = nn.Fbeta(1)
+        >>> metric.clear()
         >>> metric.update(x, y)
         >>> fbeta = metric.eval()
         >>> print(fbeta)
-        [0.66666667  0.66666667]
+        [0.66666667 0.66666667]
     """
     def __init__(self, beta):
         super(Fbeta, self).__init__()
@@ -133,7 +134,7 @@ class F1(Fbeta):
         >>> metric.update(x, y)
         >>> result = metric.eval()
         >>> print(result)
-        [0.66666667  0.66666667]
+        [0.66666667 0.66666667]
     """
     def __init__(self):
         super(F1, self).__init__(1.0)
diff --git a/mindspore/nn/metrics/precision.py b/mindspore/nn/metrics/precision.py
index 096d936a87..a0a4c727d7 100644
--- a/mindspore/nn/metrics/precision.py
+++ b/mindspore/nn/metrics/precision.py
@@ -47,6 +47,9 @@ class Precision(EvaluationBase):
         >>> metric.clear()
         >>> metric.update(x, y)
         >>> precision = metric.eval()
+        >>> print(precision)
+        [0.5 1. ]
+
     """
     def __init__(self, eval_type='classification'):
         super(Precision, self).__init__(eval_type)
diff --git a/mindspore/nn/metrics/recall.py b/mindspore/nn/metrics/recall.py
index 32657995b3..f3f8d89b3c 100644
--- a/mindspore/nn/metrics/recall.py
+++ b/mindspore/nn/metrics/recall.py
@@ -47,6 +47,8 @@ class Recall(EvaluationBase):
         >>> metric.clear()
         >>> metric.update(x, y)
         >>> recall = metric.eval()
+        >>> print(recall)
+        [1. 0.5]
     """
     def __init__(self, eval_type='classification'):
         super(Recall, self).__init__(eval_type)
diff --git a/mindspore/nn/wrap/cell_wrapper.py b/mindspore/nn/wrap/cell_wrapper.py
index 57d5cc7c6b..0b5c874ca2 100644
--- a/mindspore/nn/wrap/cell_wrapper.py
+++ b/mindspore/nn/wrap/cell_wrapper.py
@@ -276,7 +276,7 @@ class GetNextSingleOp(Cell):
         >>> relu = P.ReLU()
         >>> result = relu(data).asnumpy()
         >>> print(result.shape)
-        >>> (32, 1, 32, 32)
+        (32, 1, 32, 32)
     """
 
     def __init__(self, dataset_types, dataset_shapes, queue_name):
@@ -356,6 +356,7 @@ class WithEvalCell(Cell):
     Args:
         network (Cell): The network Cell.
         loss_fn (Cell): The loss Cell.
+        add_cast_fp32 (bool): Adjust the data type to float32.
 
     Inputs:
         - **data** (Tensor) - Tensor of shape :math:`(N, \ldots)`.
@@ -410,7 +411,7 @@ class ParameterUpdate(Cell):
         >>> param = network.parameters_dict()['weight']
         >>> update = nn.ParameterUpdate(param)
         >>> update.phase = "update_param"
-        >>> weight = Tensor(np.arrange(12).reshape((4, 3)), mindspore.float32)
+        >>> weight = Tensor(np.arange(12).reshape((4, 3)), mindspore.float32)
         >>> network_updata = update(weight)
     """