move image for python api.

docs/api/api_python/mindspore.train.rst

@@ -6,23 +6,23 @@ mindspore.train.summary
 
 使用SummaryRecord将需要的数据存储为summary文件和lineage文件，使用方法包括自定义回调函数和自定义训练循环。保存的summary文件使用MindInsight进行可视化分析。
 
-.. include:: mindspore.train/mindspore.train.summary.SummaryRecord.rst
+.. include:: train/mindspore.train.summary.SummaryRecord.rst
 
 mindspore.train.callback
 ------------------------
 
-.. include:: mindspore.train/mindspore.train.callback.Callback.rst
+.. include:: train/mindspore.train.callback.Callback.rst
 
-.. include:: mindspore.train/mindspore.train.callback.LossMonitor.rst
+.. include:: train/mindspore.train.callback.LossMonitor.rst
 
-.. include:: mindspore.train/mindspore.train.callback.TimeMonitor.rst
+.. include:: train/mindspore.train.callback.TimeMonitor.rst
 
-.. include:: mindspore.train/mindspore.train.callback.ModelCheckpoint.rst
+.. include:: train/mindspore.train.callback.ModelCheckpoint.rst
 
-.. include:: mindspore.train/mindspore.train.SummaryCollector.rst
+.. include:: train/mindspore.train.SummaryCollector.rst
 
-.. include:: mindspore.train/mindspore.train.callback.CheckpointConfig.rst
+.. include:: train/mindspore.train.callback.CheckpointConfig.rst
 
-.. include:: mindspore.train/mindspore.train.callback.RunContext.rst
+.. include:: train/mindspore.train.callback.RunContext.rst
 
-.. include:: mindspore.train/mindspore.train.callback.LearningRateScheduler.rst
+.. include:: train/mindspore.train.callback.LearningRateScheduler.rst

mindspore/python/mindspore/dataset/audio/transforms.py

@@ -780,9 +780,9 @@ class FrequencyMasking(AudioTensorOperation):
         >>> transforms = [audio.FrequencyMasking(frequency_mask_param=1)]
         >>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])
 
-    .. image:: api_img/frequency_masking_original.png
+    .. image:: frequency_masking_original.png
 
-    .. image:: api_img/frequency_masking.png
+    .. image:: frequency_masking.png
     """
 
     @check_masking
@@ -1242,9 +1242,9 @@ class TimeMasking(AudioTensorOperation):
         >>> transforms = [audio.TimeMasking(time_mask_param=1)]
         >>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])
 
-    .. image:: api_img/time_masking_original.png
+    .. image:: time_masking_original.png
 
-    .. image:: api_img/time_masking.png
+    .. image:: time_masking.png
     """
 
     @check_masking
@@ -1281,11 +1281,11 @@ class TimeStretch(AudioTensorOperation):
         >>> transforms = [audio.TimeStretch()]
         >>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])
 
-    .. image:: api_img/time_stretch_rate1.5.png
+    .. image:: time_stretch_rate1.5.png
 
-    .. image:: api_img/time_stretch_original.png
+    .. image:: time_stretch_original.png
 
-    .. image:: api_img/time_stretch_rate0.8.png
+    .. image:: time_stretch_rate0.8.png
     """
 
     @check_time_stretch

mindspore/python/mindspore/dataset/utils/browse_dataset.py

@@ -91,7 +91,7 @@ def imshow_det_bbox(image, bboxes, labels, segm=None, class_names=None, score_th
 
     Examples using `imshow_det_bbox` on VOC2012:
 
-    .. image:: api_img/browse_dataset.png
+    .. image:: browse_dataset.png
 
     """
 

mindspore/python/mindspore/ops/operations/array_ops.py

@@ -849,7 +849,7 @@ class Gather(Primitive):
 
     The following figure shows the calculation process of Gather commonly:
 
-    .. image:: api_img/Gather.png
+    .. image:: Gather.png
 
     where params represents the input `input_params`, and indices represents the index to be sliced `input_indices`.
 
@@ -2087,7 +2087,7 @@ class UnsortedSegmentSum(PrimitiveWithInfer):
 
     The following figure shows the calculation process of UnsortedSegmentSum:
 
-    .. image:: api_img/UnsortedSegmentSum.png
+    .. image:: UnsortedSegmentSum.png
 
     Note:
         - If the segment_id i is absent in the segment_ids, then output[i] will be filled with 0.
@@ -2195,7 +2195,7 @@ class UnsortedSegmentMin(PrimitiveWithCheck):
 
     The following figure shows the calculation process of UnsortedSegmentMin:
 
-    .. image:: api_img/UnsortedSegmentMin.png
+    .. image:: UnsortedSegmentMin.png
 
     .. math::
 
@@ -2265,7 +2265,7 @@ class UnsortedSegmentMax(PrimitiveWithCheck):
 
     The following figure shows the calculation process of UnsortedSegmentMax:
 
-    .. image:: api_img/UnsortedSegmentMax.png
+    .. image:: UnsortedSegmentMax.png
 
     .. math::
 
@@ -2395,7 +2395,7 @@ class UnsortedSegmentProd(PrimitiveWithInfer):
 
     The following figure shows the calculation process of UnsortedSegmentProd:
 
-    .. image:: api_img/UnsortedSegmentProd.png
+    .. image:: UnsortedSegmentProd.png
 
     Inputs:
         - **input_x** (Tensor) - The shape is :math:`(x_1, x_2, ..., x_R)`.
@@ -3723,7 +3723,7 @@ class ScatterNd(PrimitiveWithInfer):
     The following figure shows the calculation process of inserting two slices in the first dimension of a rank-3
     with two matrices of new values:
 
-    .. image:: api_img/ScatterNd.png
+    .. image:: ScatterNd.png
 
     Inputs:
         - **indices** (Tensor) - The index of scattering in the new tensor with int32 or int64 data type.