Comments (5)
please see tensorpack/tensorpack#1259
from rl-medical.
why placement Conv3D in CPU ? and i how to placement to GPU device?
from rl-medical.
@layer_register(log_shape=True)
@convert_to_tflayer_args(
args_names=['filters', 'kernel_size'],
name_mapping={
'out_channel': 'filters',
'kernel_shape': 'kernel_size',
'stride': 'strides',
})
def Conv3D()
And
@layer_register(log_shape=True)
def Conv3D()
have what differences?
i has errrors when using first Conv3D()
File "C:\Anaconda3\envs\tf1.6\lib\site-packages\tensorpack\tfutils\argscope.py", line 45, in argscope
_check_args_exist(l.symbolic_function)
File "C:\Anaconda3\envs\tf1.6\lib\site-packages\tensorpack\tfutils\argscope.py", line 41, in _check_args_exist
assert k in args, "No argument {} in {}".format(k, l.name)
AssertionError: No argument nl in Conv3D
@amiralansary @crypdick @thanosvlo @thanosvlo
please help me!
from rl-medical.
why target/conv0/Conv3D can placement at GPU ,but conv0/Conv3D cannot placement at GPU?
{
"cat": "Tensor",
"id": 22,
"ph": "O",
"tid": 0,
"name": "conv0/Conv3D",
"args": {
"snapshot": {
"tensor_description": "dtype: DT_FLOAT\nshape {\n dim {\n size: 24\n }\n dim {\n size: 45\n }\n dim {\n size: 45\n }\n dim {\n size: 45\n }\n dim {\n size: 32\n }\n}\nallocation_description {\n requested_bytes: 279936000\n allocated_bytes: 279936000\n allocator_name: cpu\n allocation_id: 1\n has_single_reference: true\n ptr: 3082879072\n}\n"
}
},
"pid": 2,
"ts": 1562635795004270
},
{
"cat": "Tensor",
"id": 382,
"ph": "O",
"tid": 13,
"name": "target/conv0/Conv3D",
"args": {
"snapshot": {
"tensor_description": "dtype: DT_FLOAT\nshape {\n dim {\n size: 24\n }\n dim {\n size: 45\n }\n dim {\n size: 45\n }\n dim {\n size: 45\n }\n dim {\n size: 32\n }\n}\nallocation_description {\n requested_bytes: 279936000\n allocated_bytes: 279936000\n allocator_name: GPU_0_bfc\n allocation_id: 430\n has_single_reference: true\n ptr: 116364673024\n}\n"
}
},
"pid": 4,
"ts": 1562635790607019
},
from rl-medical.
@courins The slow down is obviously a result of running the code on the cpu and not the gpu. The reason of that is not clear to me, either your envs or tensorpack.
It seems that you have solved this issue using a newer version of tensorpack here tensorpack/tensorpack#1259 , by upgrading to the current tensorpack master and TF 1.13, and modify the code accodring to this
I close this issue and refer to the upgrade open issue #9
from rl-medical.
Related Issues (20)
- dataset HOT 3
- 'function' object has no attribute 'symbolic_function' HOT 2
- Input data format HOT 1
- DQN.py training demo code error HOT 2
- How to resume old training
- A Question about medical.py HOT 1
- About the success ratio for Automatic View Planning HOT 1
- How to get corresponding landmarks of ADNI dataset HOT 1
- multi-agent landmark detection HOT 11
- about ADNI dataset HOT 2
- Hi, where can I download the cardiac MRI dataset and the fetal brain ultrasound MRI HOT 1
- how can I get the cardiac dataset in this project? HOT 7
- About 2D model HOT 1
- Help
- Improve accuracy
- References to AtariPlayer in expreplay.py HOT 1
- Modifying DQN model to accept 3D images HOT 13
- Models HOT 1
- Upgrade to latest tensorpack dependency: DQN.py returning a 'NotImplementedError' HOT 5
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from rl-medical.