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ndronen / PyTorch issue 35643
Created April 25, 2020 09:06
Straw man proposal for PyTorch issue
"""
This is a straw man proposal to begin discussion of how to change the
PyTorch hooks API to support capture/inspection/modification of
keyword arguments.
https://github.com/pytorch/pytorch/issues/35643
"""
import unittest
/home/ubuntu/conda/miniconda3/envs/distiller-python-3.5/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/home/ubuntu/conda/miniconda3/envs/distiller-python-3.5/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/home/ubuntu/conda/miniconda3/envs/distiller-python-3.5/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/home/ubuntu/conda/miniconda3/envs/distiller-python-3.5/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
Log file for this run: /home/ubuntu/proj/distiller-python-3.5/examples/pruning_filters_for_efficient_convnets/logs/2018.08.20-10
@ndronen
ndronen / model.py
Last active April 28, 2018 19:50
Semantic segmentation with ENet in PyTorch
#!/usr/bin/env python
"""
A quick, partial implementation of ENet (https://arxiv.org/abs/1606.02147) using PyTorch.
The original Torch ENet implementation can process a 480x360 image in ~12 ms (on a P2 AWS
instance). TensorFlow takes ~35 ms. The PyTorch implementation takes ~25 ms, an improvement
over TensorFlow, but worse than the original Torch.
"""
from __future__ import absolute_import
@ndronen
ndronen / gist:f6ce80b7343a73c18072
Created July 9, 2015 21:20
Minimal working example of something that doesn't work with nn.Concat.
#!/usr/bin/env th
require 'nn';
local cmd = torch.CmdLine()
cmd:text()
cmd:text("What's wrong with this use of nn.Concat?")
cmd:text('Options:')
cmd:option('-noConcat', false, 'do not include concat layer')
#!/usr/bin/env th
local cmd = torch.CmdLine()
cmd:text('Demonstration of incompatibility between nn and fbcunn temporal convolutions.')
cmd:text()
cmd:text('Running with -fbconv causes a tensor dimension mismatch error in TemporalConvolutionFB_updateOutput.')
cmd:text()
cmd:text('I think the bug is somewhere in ConvolutionBias.cu.')
cmd:text()
cmd:text('Options:')