提交 bb1376db 编写于 作者: Z zhiqiu

add flags setting

上级 a9f35981
......@@ -10,19 +10,26 @@ Global:
epochs: 120
print_batch_step: 10
use_visualdl: False
image_channel: &image_channel 4
# used for static mode and model export
image_shape: [3, 224, 224]
image_shape: [*image_channel, 224, 224]
save_inference_dir: ./inference
# training model under @to_static
to_static: False
use_dali: True
# mixed precision training
AMP:
scale_loss: 128.0
use_dynamic_loss_scaling: True
use_pure_fp16: &use_pure_fp16 False
# model architecture
Arch:
name: ResNet50
class_num: 1000
input_image_channel: *image_channel
data_format: "NHWC"
# loss function config for traing/eval process
Loss:
......@@ -67,10 +74,12 @@ DataLoader:
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
output_fp16: *use_pure_fp16
channel_num: *image_channel
sampler:
name: DistributedBatchSampler
batch_size: 64
batch_size: 256
drop_last: False
shuffle: True
loader:
......@@ -95,6 +104,8 @@ DataLoader:
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
output_fp16: *use_pure_fp16
channel_num: *image_channel
sampler:
name: DistributedBatchSampler
batch_size: 64
......@@ -120,6 +131,8 @@ Infer:
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
output_fp16: *use_pure_fp16
channel_num: *image_channel
- ToCHWImage:
PostProcess:
name: Topk
......
......@@ -112,6 +112,12 @@ class Trainer(object):
else:
self.scale_loss = 1.0
self.use_dynamic_loss_scaling = False
if self.amp:
AMP_RELATED_FLAGS_SETTING = {
'FLAGS_cudnn_batchnorm_spatial_persistent': 1,
'FLAGS_max_inplace_grad_add': 8,
}
paddle.fluid.set_flags(AMP_RELATED_FLAGS_SETTING)
self.train_loss_func = None
self.eval_loss_func = None
self.train_metric_func = None
......
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