resize_nearest and bbox

mindspore/ops/_op_impl/tbe/__init__.py

@@ -177,8 +177,8 @@ from .lamb_update_with_lr import _lamb_update_with_lr_tbe
 from .rsqrt import _rsqrt_tbe
 from .sigmoid import _sigmoid_tbe
 from .sigmoid_grad import _sigmoid_grad_tbe
-from .resize_nearest_neighbor_d import _resize_nearest_neighbor_d_tbe
-from .resize_nearest_neighbor_grad_d import _resize_nearest_neighbor_grad_d_tbe
+from .resize_nearest_neighbor import _resize_nearest_neighbor_tbe
+from .resize_nearest_neighbor_grad import _resize_nearest_neighbor_grad_tbe
 from .pad_d import _pad_d_tbe
 from .arg_max_with_value import _arg_max_with_value_tbe
 from .arg_min_with_value import _arg_min_with_value_tbe

mindspore/ops/_op_impl/tbe/resize_nearest_neighbor.py

@@ -27,20 +27,12 @@ resize_nearest_neighbor_op_info = TBERegOp("ResizeNearestNeighbor") \
     .attr("align_corners", "optional", "bool", "all") \
     .input(0, "images", False, "required", "all") \
     .output(0, "y", True, "required", "all") \
-    .dtype_format(DataType.I8_Default, DataType.I8_Default) \
-    .dtype_format(DataType.I8_5HD, DataType.I8_5HD) \
-    .dtype_format(DataType.U8_Default, DataType.U8_Default) \
-    .dtype_format(DataType.U8_5HD, DataType.U8_5HD) \
-    .dtype_format(DataType.I32_Default, DataType.I32_Default) \
-    .dtype_format(DataType.I32_5HD, DataType.I32_5HD) \
-    .dtype_format(DataType.F16_Default, DataType.F16_Default) \
     .dtype_format(DataType.F16_5HD, DataType.F16_5HD) \
-    .dtype_format(DataType.F32_Default, DataType.F32_Default) \
     .dtype_format(DataType.F32_5HD, DataType.F32_5HD) \
     .get_op_info()
 
 
 @op_info_register(resize_nearest_neighbor_op_info)
-def _resize_nearest_neighbor_d_tbe():
+def _resize_nearest_neighbor_tbe():
     """ResizeNearestNeighbor TBE register"""
     return

mindspore/ops/_op_impl/tbe/resize_nearest_neighbor_d.py

-# Copyright 2020 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ============================================================================
-
-"""ResizeNearestNeighbor op"""
-from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
-
-resize_nearest_neighbor_d_op_info = TBERegOp("ResizeNearestNeighbor") \
-    .fusion_type("OPAQUE") \
-    .async_flag(False) \
-    .binfile_name("resize_nearest_neighbor_d.so") \
-    .compute_cost(10) \
-    .kernel_name("resize_nearest_neighbor_d") \
-    .partial_flag(True) \
-    .attr("size", "required", "listInt", "all") \
-    .attr("align_corners", "optional", "bool", "all") \
-    .input(0, "images", False, "required", "all") \
-    .output(0, "y", True, "required", "all") \
-    .dtype_format(DataType.I8_5HD, DataType.I8_5HD) \
-    .dtype_format(DataType.U8_5HD, DataType.U8_5HD) \
-    .dtype_format(DataType.I32_5HD, DataType.I32_5HD) \
-    .dtype_format(DataType.F16_5HD, DataType.F16_5HD) \
-    .dtype_format(DataType.F32_5HD, DataType.F32_5HD) \
-    .get_op_info()
-
-
-@op_info_register(resize_nearest_neighbor_d_op_info)
-def _resize_nearest_neighbor_d_tbe():
-    """ResizeNearestNeighbor TBE register"""
-    return

mindspore/ops/_op_impl/tbe/resize_nearest_neighbor_grad_d.py → mindspore/ops/_op_impl/tbe/resize_nearest_neighbor_grad.py

@@ -16,7 +16,7 @@
 """ResizeNearestNeighborgrad op"""
 from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
 
-resize_nearest_neighbor_grad_d_op_info = TBERegOp("ResizeNearestNeighborGrad") \
+resize_nearest_neighbor_grad_op_info = TBERegOp("ResizeNearestNeighborGrad") \
     .fusion_type("OPAQUE") \
     .async_flag(False) \
     .binfile_name("resize_nearest_neighbor_grad_d.so") \
@@ -31,7 +31,7 @@ resize_nearest_neighbor_grad_d_op_info = TBERegOp("ResizeNearestNeighborGrad") \
     .get_op_info()
 
 
-@op_info_register(resize_nearest_neighbor_grad_d_op_info)
-def _resize_nearest_neighbor_grad_d_tbe():
+@op_info_register(resize_nearest_neighbor_grad_op_info)
+def _resize_nearest_neighbor_grad_tbe():
     """ResizeNearestNeighborGrad TBE register"""
     return

mindspore/ops/operations/other_ops.py

@@ -75,8 +75,8 @@ class BoundingBoxEncode(PrimitiveWithInfer):
         stds (tuple): Stds for encoding bounding boxes calculation. Default: (1.0, 1.0, 1.0, 1.0).
 
     Inputs:
-        - **anchor_box** (Tensor) - Anchor boxes.
-        - **groundtruth_box** (Tensor) - Ground truth boxes.
+        - **anchor_box** (Tensor) - Anchor boxes. The shape of anchor_box must be (n, 4).
+        - **groundtruth_box** (Tensor) - Ground truth boxes. Which has the same shape with anchor_box.
 
     Outputs:
         Tensor, encoded bounding boxes.
@@ -128,8 +128,8 @@ class BoundingBoxDecode(PrimitiveWithInfer):
         wh_ratio_clip (float): The limit of width and height ratio for decoding box calculation. Default: 0.016.
 
     Inputs:
-        - **anchor_box** (Tensor) - Anchor boxes.
-        - **deltas** (Tensor) - Delta of boxes.
+        - **anchor_box** (Tensor) - Anchor boxes. The shape of anchor_box must be (n, 4).
+        - **deltas** (Tensor) - Delta of boxes. Which has the same shape with anchor_box.
 
     Outputs:
         Tensor, decoded boxes.