diff --git a/official/cv/maskrcnn/src/maskrcnn/fpn_neck.py b/official/cv/maskrcnn/src/maskrcnn/fpn_neck.py
index d4e9b8b62d6994248ac2e4c0b009d44bba9a3bc5..6a98de5d2c0b8b80587f7c9330979795e7d77ca8 100644
--- a/official/cv/maskrcnn/src/maskrcnn/fpn_neck.py
+++ b/official/cv/maskrcnn/src/maskrcnn/fpn_neck.py
@@ -55,7 +55,7 @@ class FeatPyramidNeck(nn.Cell):
Tuple, with tensors of same channel size.
Examples:
- neck = FeatPyramidNeck([100,200,300], 50, 4)
+ neck = FeatPyramidNeck([100,200,300], 50, 4, config.feature_shapes)
input_data = (normal(0,0.1,(1,c,1280//(4*2**i), 768//(4*2**i)),
dtype=np.float32) \
for i, c in enumerate(config.fpn_in_channels))
@@ -65,7 +65,8 @@ class FeatPyramidNeck(nn.Cell):
def __init__(self,
in_channels,
out_channels,
- num_outs):
+ num_outs,
+ feature_shapes):
super(FeatPyramidNeck, self).__init__()
if context.get_context("device_target") == "Ascend":
@@ -91,9 +92,9 @@ class FeatPyramidNeck(nn.Cell):
self.fpn_convs_.append(fpn_conv)
self.lateral_convs_list = nn.layer.CellList(self.lateral_convs_list_)
self.fpn_convs_list = nn.layer.CellList(self.fpn_convs_)
- self.interpolate1 = P.ResizeBilinear((48, 80))
- self.interpolate2 = P.ResizeBilinear((96, 160))
- self.interpolate3 = P.ResizeBilinear((192, 320))
+ self.interpolate1 = P.ResizeBilinear(feature_shapes[2])
+ self.interpolate2 = P.ResizeBilinear(feature_shapes[1])
+ self.interpolate3 = P.ResizeBilinear(feature_shapes[0])
self.cast = P.Cast()
self.maxpool = P.MaxPool(kernel_size=1, strides=2, pad_mode="same")
diff --git a/official/cv/maskrcnn/src/maskrcnn/mask_rcnn_r50.py b/official/cv/maskrcnn/src/maskrcnn/mask_rcnn_r50.py
index eec5350df3e95785021755255a75618c12fa69ee..c5be17cb1641d00344b86f8e5b64fb6fd33086fc 100644
--- a/official/cv/maskrcnn/src/maskrcnn/mask_rcnn_r50.py
+++ b/official/cv/maskrcnn/src/maskrcnn/mask_rcnn_r50.py
@@ -96,7 +96,8 @@ class Mask_Rcnn_Resnet50(nn.Cell):
# Fpn
self.fpn_ncek = FeatPyramidNeck(config.fpn_in_channels,
config.fpn_out_channels,
- config.fpn_num_outs)
+ config.fpn_num_outs,
+ config.feature_shapes)
# Rpn and rpn loss
self.gt_labels_stage1 = Tensor(np.ones((self.train_batch_size, config.num_gts)).astype(np.uint8))
diff --git a/official/cv/maskrcnn/src/maskrcnn/proposal_generator.py b/official/cv/maskrcnn/src/maskrcnn/proposal_generator.py
index d3c0f781e36679b24fd81848e61533baffaac032..f556d0e176b50a63ed8f803dfda66d95b338af20 100644
--- a/official/cv/maskrcnn/src/maskrcnn/proposal_generator.py
+++ b/official/cv/maskrcnn/src/maskrcnn/proposal_generator.py
@@ -1,4 +1,4 @@
-# Copyright 2020-2021 Huawei Technologies Co., Ltd
+# Copyright 2020-2022 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.
@@ -64,15 +64,14 @@ class Proposal(nn.Cell):
self.target_means = target_means
self.target_stds = target_stds
self.use_sigmoid_cls = use_sigmoid_cls
+ self.reshape_shape = (-1, 1)
if self.use_sigmoid_cls:
self.cls_out_channels = num_classes - 1
self.activation = P.Sigmoid()
- self.reshape_shape = (-1, 1)
else:
self.cls_out_channels = num_classes
self.activation = P.Softmax(axis=1)
- self.reshape_shape = (-1, 2)
if self.cls_out_channels <= 0:
raise ValueError('num_classes={} is too small'.format(num_classes))
diff --git a/research/cv/FaceRecognition/base_config.yaml b/research/cv/FaceRecognition/base_config.yaml
index f975ad90f319c579fd7896cb34155c57e085c363..211b03221cf046e67187040944ae51206bc959c2 100644
--- a/research/cv/FaceRecognition/base_config.yaml
+++ b/research/cv/FaceRecognition/base_config.yaml
@@ -27,7 +27,6 @@ backbone: "r100"
use_se: 1
emb_size: 512
act_type: "relu"
-fp16: 1
pre_bn: 1
inference: 0
use_drop: 1
diff --git a/research/cv/FaceRecognition/base_config_cpu.yaml b/research/cv/FaceRecognition/base_config_cpu.yaml
index 3ea99b1a09bec9231f7d1320a47598fdd33f8243..51891748188465ce1741bfc64ecfe82efc2deec2 100644
--- a/research/cv/FaceRecognition/base_config_cpu.yaml
+++ b/research/cv/FaceRecognition/base_config_cpu.yaml
@@ -27,7 +27,6 @@ backbone: "r100"
use_se: 1
emb_size: 512
act_type: "relu"
-fp16: 1
pre_bn: 1
inference: 0
use_drop: 1
diff --git a/research/cv/FaceRecognition/beta_config.yaml b/research/cv/FaceRecognition/beta_config.yaml
index 1a4a2a4ac477033fc1811c39ac8f89fa32f824fa..a8b31381107618670e078499d0f088f1fdb5bbb8 100644
--- a/research/cv/FaceRecognition/beta_config.yaml
+++ b/research/cv/FaceRecognition/beta_config.yaml
@@ -27,7 +27,6 @@ backbone: "r100"
use_se: 0
emb_size: 256
act_type: "relu"
-fp16: 1
pre_bn: 0
inference: 0
use_drop: 1
diff --git a/research/cv/FaceRecognition/beta_config_cpu.yaml b/research/cv/FaceRecognition/beta_config_cpu.yaml
index a0f329a17a4f07fcd20cd86e28222231d46add68..f57680ec6d25b422a298d20b4d4ce783341560e3 100644
--- a/research/cv/FaceRecognition/beta_config_cpu.yaml
+++ b/research/cv/FaceRecognition/beta_config_cpu.yaml
@@ -27,7 +27,6 @@ backbone: "r100"
use_se: 0
emb_size: 256
act_type: "relu"
-fp16: 1
pre_bn: 0
inference: 0
use_drop: 1
diff --git a/research/cv/FaceRecognition/default_config.yaml b/research/cv/FaceRecognition/default_config.yaml
index 5cf5601226c520b6336d20f021955c152e79c469..22bc9b75f86190485954cbf4febd14e2b7442f8b 100644
--- a/research/cv/FaceRecognition/default_config.yaml
+++ b/research/cv/FaceRecognition/default_config.yaml
@@ -27,7 +27,6 @@ backbone: "r100"
use_se: 1
emb_size: 512
act_type: "relu"
-fp16: 1
pre_bn: 1
inference: 0
use_drop: 1
diff --git a/research/cv/FaceRecognition/inference_config.yaml b/research/cv/FaceRecognition/inference_config.yaml
index a427b1910453141e87708df58ea10c19de4088f3..2d000b3e3ad3a18c44a534a995c3a63234ad6aee 100644
--- a/research/cv/FaceRecognition/inference_config.yaml
+++ b/research/cv/FaceRecognition/inference_config.yaml
@@ -29,7 +29,6 @@ backbone: "r100"
use_se: 0
emb_size: 256
act_type: "relu"
-fp16: 1
pre_bn: 0
inference: 1
use_drop: 0
diff --git a/research/cv/FaceRecognition/inference_config_cpu.yaml b/research/cv/FaceRecognition/inference_config_cpu.yaml
index ad52c98049ffa42b36150b7ffdf15ee812ffcad9..f0b015600a7f7641d5076c5f47e7aaa8cf780b0a 100644
--- a/research/cv/FaceRecognition/inference_config_cpu.yaml
+++ b/research/cv/FaceRecognition/inference_config_cpu.yaml
@@ -29,7 +29,6 @@ backbone: "r100"
use_se: 0
emb_size: 256
act_type: "relu"
-fp16: 1
pre_bn: 0
inference: 1
use_drop: 0
diff --git a/research/cv/FaceRecognition/train.py b/research/cv/FaceRecognition/train.py
index c5bf4acd5ec6f906170cfb4c023b198bd54c8750..6bea022c3bf244e1a8143605d83c33b6cfd09510 100644
--- a/research/cv/FaceRecognition/train.py
+++ b/research/cv/FaceRecognition/train.py
@@ -260,12 +260,11 @@ def run_train():
network_1 = DistributedHelper(_backbone, margin_fc_1)
config.logger.info('DistributedHelper----out----')
config.logger.info('network fp16----in----')
- if config.fp16 == 1:
- network_1.add_flags_recursive(fp16=True)
+ network_1.add_flags_recursive(fp16=True)
config.logger.info('network fp16----out----')
criterion_1 = get_loss(config)
- if config.fp16 == 1 and config.model_parallel == 0:
+ if config.model_parallel == 0:
criterion_1.add_flags_recursive(fp32=True)
network_1 = load_pretrain(config, network_1)
diff --git a/research/cv/centernet/src/decode.py b/research/cv/centernet/src/decode.py
index d7291a73d8329857e6a69c9103c646bea4d9f44d..54c44f59e5829087f8296a8e523b2f5702035739 100644
--- a/research/cv/centernet/src/decode.py
+++ b/research/cv/centernet/src/decode.py
@@ -148,7 +148,6 @@ class GatherFeatureByInd(nn.Cell):
self.reshape = ops.Reshape()
self.enable_cpu_gatherd = enable_cpu_gatherd
if self.enable_cpu_gatherd:
- self.value = Tensor(2, mstype.int32)
self.gather_nd = ops.GatherD()
self.expand_dims = ops.ExpandDims()
else:
@@ -165,7 +164,7 @@ class GatherFeatureByInd(nn.Cell):
# (b, J, K, N)
index = self.expand_dims(ind, -1)
index = self.tile(index, (1, 1, 1, N))
- feat = self.gather_nd(feat, self.value, index)
+ feat = self.gather_nd(feat, 2, index)
else:
ind = self.reshape(ind, (-1, 1))
ind_b = nn.Range(0, b * J, 1)()
diff --git a/research/cv/centernet/src/utils.py b/research/cv/centernet/src/utils.py
index b065dd97672ed514f456f08ab70856597bd74b2a..89b73d803c6ff2ee3a993ce997978f18e20b68ae 100644
--- a/research/cv/centernet/src/utils.py
+++ b/research/cv/centernet/src/utils.py
@@ -134,7 +134,6 @@ class GatherFeature(nn.Cell):
self.reshape = ops.Reshape()
self.enable_cpu_gather = enable_cpu_gather
if self.enable_cpu_gather:
- self.value = Tensor(1, mstype.int32)
self.gather_nd = ops.GatherD()
self.expand_dims = ops.ExpandDims()
else:
@@ -147,7 +146,7 @@ class GatherFeature(nn.Cell):
# (b, N, c)
index = self.expand_dims(ind, -1)
index = self.tile(index, (1, 1, c))
- feat = self.gather_nd(feat, self.value, index)
+ feat = self.gather_nd(feat, 1, index)
else:
# (b, N)->(b*N, 1)
b, N = self.shape(ind)