Comments (12)
You mean how to train a compressed model with multiple nodes/machines?
from pocketflow.
When using the horovod, i think it`s feasible.
from pocketflow.
Yes, but I mean compress the model by Prunning/Quantization, then train the compress model with multiple nodes/machines.
I have other questions:
- Can PocketFlow compress object detection network, such as Yolo, fasterCNN?
- I how to verify the inference speed of compressed model is faster than the full-precision uncompressed network?
thanks
from pocketflow.
When using the horovod, i think it`s feasible.
What's it?
from pocketflow.
Horovod is Distributed training framework for TensorFlow, Keras, and PyTorch.
- AFAIK,it not yet support the state-of-art models lke the Yolo or fasterCNN
- you can test in TensorRT
@as754770178
from pocketflow.
I exec command ./scripts/run_local.sh nets/resnet_at_cifar10_run.py --learner dis-chn-pruned
.
I read the checkpoint file of compressed model (saved in models_dcp_eval file) and pre-trained model, but I find the structure of net is same. Compressed model only delete the variable w.r.t Momentum and BatchNorm.
So I want to test the inference speed of compressed model and full-precision uncompressed network
from pocketflow.
- PocketFlow does not support object detection models (YOLO / Faster R-CNN) for the moment. We are working on this right now.
- For multi-node training, please use horovod, as suggested by @xieydd .
- To verify the inference speed, use TF-Lite models generated by
tools/conversion/export_pb_tflite_models.py
.
from pocketflow.
I mean use tf-serving to test the speed? Can horovod support compress model? I want compress model and train it together, like PocketFlow.
from pocketflow.
- Horovod is a distributed training framework. It does not care what code is running within.
- The speed improvement on GPU will be less significant than on ARM-based mobile devices, according to our experience.
from pocketflow.
Can PocketFlow compress multi-label Classification network?
from pocketflow.
Yes, you can define a new ModelHelper
class, including the network architecture and the computation of loss function's value, similar to other ModelHelper
classes defined under the nets
directory.
from pocketflow.
OK, thanks.
from pocketflow.
Related Issues (20)
- cifar10_channel pruned 的示例,通道剪枝(channel_pruning) 导出修改了计算图之后,速度比之前的更慢了! HOT 1
- Can the compression method provided by pocketflow be applied to MASK R-CNN? HOT 1
- QQ group HOT 1
- 我可以只用模型压缩部分么?
- TypeError: forward_train() missing 1 required positional argument: 'objects'
- Missing 1 required positional argument in constructor : data_format
- Download Pretrain Model But Get 502 Bad Gateway Error HOT 1
- You must feed a value for placeholder tensor 'model/input_1' with dtype float and shape [?,160,240,1]
- Question about export_chn_pruned_tflite_model.py HOT 1
- TF Version compatibility HOT 2
- Failed to create session
- Is it possible to compress the keras model with Pocket Flow
- Question about UniformLearner HOT 2
- Default tensorboard log output is huge
- FRCNN with VOC: Cannot batch tensors with different shapes in component 1.
- IndexError: list index out of range HOT 3
- Other issues:
- auto 通道裁剪问题
- test
- TF-Plus for Multi-GPU Training
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