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Fix urllib error on colab hub example #150

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Merged
nv-kkudrynski merged 1 commit into from
Aug 14, 2019
Merged

Fix urllib error on colab hub example #150

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29 changes: 13 additions & 16 deletions hubconf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,15 @@ def unwrap_distributed(state_dict):
new_state_dict[new_key] = value
return new_state_dict

def _download_checkpoint(checkpoint, force_reload):
model_dir = os.path.join(torch.hub._get_torch_home(), 'checkpoints')
if not os.path.exists(model_dir):
os.makedirs(model_dir)
ckpt_file = os.path.join(model_dir, os.path.basename(checkpoint))
if not os.path.exists(ckpt_file) or force_reload:
sys.stderr.write('Downloading checkpoint from {}\n'.format(checkpoint))
urllib.request.urlretrieve(checkpoint, ckpt_file)
return ckpt_file

dependencies = ['torch']

Expand Down Expand Up @@ -66,10 +75,7 @@ def nvidia_ncf(pretrained=True, **kwargs):
checkpoint = 'https://developer.nvidia.com/joc-ncf-fp16-pyt-20190225'
else:
checkpoint = 'https://developer.nvidia.com/joc-ncf-fp32-pyt-20190225'
ckpt_file = os.path.join(torch.hub._get_torch_home(), "checkpoints", os.path.basename(checkpoint))
if not os.path.exists(ckpt_file) or force_reload:
sys.stderr.write('Downloading checkpoint from {}\n'.format(checkpoint))
urllib.request.urlretrieve(checkpoint, ckpt_file)
ckpt_file = _download_checkpoint(checkpoint, force_reload)
ckpt = torch.load(ckpt_file)

if checkpoint_from_distributed(ckpt):
Expand Down Expand Up @@ -130,10 +136,7 @@ def nvidia_tacotron2(pretrained=True, **kwargs):
checkpoint = 'https://developer.nvidia.com/joc-tacotron2-fp16-pyt-20190306'
else:
checkpoint = 'https://developer.nvidia.com/joc-tacotron2-fp32-pyt-20190306'
ckpt_file = os.path.join(torch.hub._get_torch_home(), "checkpoints", os.path.basename(checkpoint))
if not os.path.exists(ckpt_file) or force_reload:
sys.stderr.write('Downloading checkpoint from {}\n'.format(checkpoint))
urllib.request.urlretrieve(checkpoint, ckpt_file)
ckpt_file = _download_checkpoint(checkpoint, force_reload)
ckpt = torch.load(ckpt_file)
state_dict = ckpt['state_dict']
if checkpoint_from_distributed(state_dict):
Expand Down Expand Up @@ -190,10 +193,7 @@ def nvidia_waveglow(pretrained=True, **kwargs):
checkpoint = 'https://developer.nvidia.com/joc-waveglow-fp16-pyt-20190306'
else:
checkpoint = 'https://developer.nvidia.com/joc-waveglow-fp32-pyt-20190306'
ckpt_file = os.path.join(torch.hub._get_torch_home(), "checkpoints", os.path.basename(checkpoint))
if not os.path.exists(ckpt_file) or force_reload:
sys.stderr.write('Downloading checkpoint from {}\n'.format(checkpoint))
urllib.request.urlretrieve(checkpoint, ckpt_file)
ckpt_file = _download_checkpoint(checkpoint, force_reload)
ckpt = torch.load(ckpt_file)
state_dict = ckpt['state_dict']
if checkpoint_from_distributed(state_dict):
Expand Down Expand Up @@ -360,10 +360,7 @@ def batchnorm_to_float(module):
checkpoint = 'https://developer.nvidia.com/joc-ssd-fp16-pyt-20190225'
else:
checkpoint = 'https://developer.nvidia.com/joc-ssd-fp32-pyt-20190225'
ckpt_file = os.path.join(torch.hub._get_torch_home(), "checkpoints", os.path.basename(checkpoint))
if not os.path.exists(ckpt_file) or force_reload:
sys.stderr.write('Downloading checkpoint from {}\n'.format(checkpoint))
urllib.request.urlretrieve(checkpoint, ckpt_file)
ckpt_file = _download_checkpoint(checkpoint, force_reload)
ckpt = torch.load(ckpt_file)
ckpt = ckpt['model']
if checkpoint_from_distributed(ckpt):
Expand Down