Pytorch 1.0 branch ImportError: torch.utils.ffi is deprecated #412

andrewjong · 2019-01-04T01:05:35Z

I followed the instructions for Pytorch 1.0: switched to pytorch-1.0 branch, went to lib and ran python setup.py build develop. Install succeeded with no errors.

However, when I try to import roi_pool in the Python prompt, I get "torch.utils.ffi is deprecated" error. Isn't this supposed to be fixed in the pytorch-1.0 branch?

Python 3.7.2 (default, Dec 29 2018, 06:19:36) 
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from model.roi_pooling.modules import roi_pool
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/remoteuser/faster-rcnn.pytorch/lib/model/roi_pooling/modules/roi_pool.py", line 2, in <module>
    from ..functions.roi_pool import RoIPoolFunction
  File "/home/remoteuser/faster-rcnn.pytorch/lib/model/roi_pooling/functions/roi_pool.py", line 3, in <module>
    from .._ext import roi_pooling
  File "/home/remoteuser/faster-rcnn.pytorch/lib/model/roi_pooling/_ext/roi_pooling/__init__.py", line 2, in <module>
    from torch.utils.ffi import _wrap_function
  File "/home/remoteuser/.miniconda3/envs/outfit/lib/python3.7/site-packages/torch/utils/ffi/__init__.py", line 1, in <module>
    raise ImportError("torch.utils.ffi is deprecated. Please use cpp extensions instead.")
ImportError: torch.utils.ffi is deprecated. Please use cpp extensions instead.

Thank you!

The text was updated successfully, but these errors were encountered:

ericsqxd · 2019-01-04T03:10:24Z

I encountered the same problem. It is because the version of pytorch isn't compatible with the repo. You could change the pytorch to 0.4.0. I solve the problem in this way.

andrewjong · 2019-01-04T03:11:16Z

Thanks @ericsqxd , but the README says

Good news! This repo supports pytorch-1.0 now!!! We borrowed some code and techniques from maskrcnn-benchmark. Just go to pytorch-1.0 branch!

1.0 should be supported right?

adityaarun1 · 2019-01-05T16:06:57Z

@andrewjong @ericsqxd You need to checkout the pytorch-1.0 branch. The master branch supports Pytorch 0.4.

andrewjong · 2019-01-05T18:29:21Z

@adityaarun1 hello, yes. As mentioned in my post, I first switched to the pytorch-1.0 branch, but still encountered the error. Maybe it's just me; did it work for you?

adityaarun1 · 2019-01-06T02:50:18Z

Yes, it does work for me. Infact, I have successfully trained my model with the new branch. Ensure that you are on the correct branch with git branch.

lzxzy · 2019-01-16T02:24:27Z

@adityaarun1 hello, yes. As mentioned in my post, I first switched to the pytorch-1.0 branch, but still encountered the error. Maybe it's just me; did it work for you?

hi, I got the same error as you . So have you had solved the problem? thx.

ljtruong · 2019-01-22T03:00:18Z

@lzxzy confirmed it works. using git checkout pytorch-1.0 will fix your problem.

odellus · 2019-01-23T17:51:23Z

If you look here you can see the ffi tools are still used on the pytorch-1.0 branch.

adityaarun1 · 2019-01-23T18:08:10Z

@odellus If you look at the setup script lib/setup.py, it does not call the said file you mentioned. The ROI and NMS files that are used now reside here, source for the same are here. The files you pointed are required for PyTorch < 0.4.1 and have not been deleted from PyTorch 1.0 branch.

odellus · 2019-01-23T23:52:13Z

Okey dokey. Makes sense

…

On Wed, Jan 23, 2019, 10:08 AM Aditya Arun ***@***.*** wrote: @odellus <https://github.com/odellus> If you look at the setup script lib/setup.py, it does not call the said file you mentioned. The ROI and NMS files that are used now reside here <https://github.com/jwyang/faster-rcnn.pytorch/tree/pytorch-1.0/lib/model/roi_layers>, source for the same are here <https://github.com/jwyang/faster-rcnn.pytorch/tree/pytorch-1.0/lib/model/csrc>. The files you pointed are required for PyTorch < 0.4.1 and have not been deleted from PyTorch 1.0 branch. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#412 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AEeEbDd1-eKRLo29JoxrdPBYHwo99T91ks5vGKUNgaJpZM4ZpAtd> .

andrewjong · 2019-01-24T04:58:26Z

Closing this issue since it seems it works for others.

zcunyi · 2019-02-22T17:06:17Z

@odellus If you look at the setup script lib/setup.py, it does not call the said file you mentioned. The ROI and NMS files that are used now reside here, source for the same are here. The files you pointed are required for PyTorch < 0.4.1 and have not been deleted from PyTorch 1.0 branch.

But, how to solve the error?

adityaarun1 · 2019-02-22T19:08:59Z

@zcunyi After cloning the repo, you need to switch to the Pytorch-1.0 branch via git checkout pytorch-1.0. Then you can proceed with the installation instructions given in the README of pytorch-1.0 branch.

ma-xu · 2019-03-07T19:39:40Z

@lzxzy Hi, I got the same problem as you mentioned, did you solve the problem ?

andrewjong · 2019-03-11T17:10:23Z

I figured it out! My goal was to import the roi layers for my project. The problem was I had the wrong import statement for PyTorch 1.0.

Before I had:
from model.roi_pooling.modules import roi_pool
It should be:
from model.roi_layers import ROIPool

Then it works with no problems.

Edit: if anyone else is looking to use ROI layers from this repo in the future, I wrote a mini tutorial.

kangkang59812 · 2019-04-22T12:39:05Z

I clone the code from branch pytorch-1.0. But I still have this problem.

Qlulu · 2019-07-13T03:37:05Z

copy the following code to torch.utils.ffi.init.py,these codes are copied from torch.utils.ffi.init.py of pytorch 0.4.1,and then the raise ImportError can be solved.But I don't know whether the change will influence the next process.
#raise ImportError("torch.utils.ffi is deprecated. Please use cpp extensions instead.")
from functools import wraps
def _wrap_function(function, ffi):
@wraps(function)
def safe_call(args, **kwargs):
args = tuple(ffi.cast(_torch_to_cffi.get(arg.type(), 'void') + '', arg._cdata)
if isinstance(arg, torch.Tensor) or torch.is_storage(arg)
else arg
for arg in args)
args = (function,) + args
result = torch._C._safe_call(*args, **kwargs)
if isinstance(result, ffi.CData):
typeof = ffi.typeof(result)
if typeof.kind == 'pointer':
cdata = int(ffi.cast('uintptr_t', result))
cname = typeof.item.cname
if cname in _cffi_to_torch:
# TODO: Maybe there is a less janky way to eval
# off of this
return eval(_cffi_to_torch[cname])(cdata=cdata)
return result
return safe_call

E-Dreamer-LQ · 2019-07-26T13:19:32Z

Does this program work in pytorch1.0, how to fix the error or replace the error reporting module????

marcunzueta · 2019-08-02T22:09:09Z

@zcunyi After cloning the repo, you need to switch to the Pytorch-1.0 branch via git checkout pytorch-1.0. Then you can proceed with the installation instructions given in the README of pytorch-1.0 branch.

Awesome! Shall we add it specifically in the readme.md?

rpfly3 · 2019-11-06T18:33:21Z

If you look here you can see the ffi tools are still used on the pytorch-1.0 branch.

For my case, ffi is already deprecated in PyTorch 1.0.0

ERROR MSG:
Traceback (most recent call last):
File "waymo.py", line 30, in
from model.nms.nms_wrapper import nms
File "Workspace/Code/faster-rcnn.pytorch-pytorch-1.0/lib/model/nms/nms_wrapper.py", line 10, in
from model.nms.nms_gpu import nms_gpu
File "Workspace/Code/faster-rcnn.pytorch-pytorch-1.0/lib/model/nms/nms_gpu.py", line 4, in
from ._ext import nms
File "Workspace/Code/faster-rcnn.pytorch-pytorch-1.0/lib/model/nms/_ext/nms/init.py", line 2, in
from torch.utils.ffi import _wrap_function
File "python-environments/pytorch_1_0/lib/python3.6/site-packages/torch/utils/ffi/init.py", line 1, in
raise ImportError("torch.utils.ffi is deprecated. Please use cpp extensions instead.")
ImportError: torch.utils.ffi is deprecated. Please use cpp extensions instead.

lhaippp · 2020-04-13T02:59:58Z

check git branch to pytorch-1.0 worked for me

jity16 · 2020-09-07T16:36:46Z

I solved by adding the source code of torch.utils.ffi to my project without changing my pytorch version.(I use torch 1.4.0).
For example, save the following code to ffiext.py, then you can replace from torch.utils.ffi import _wrap_function with from ffiext import _wrap_function.
You can also find the following source code from 'https://s0pytorch0org.icopy.site/docs/0.4.1/_modules/torch/utils/ffi.html'.

import os
import glob
import tempfile
import shutil
from functools import wraps, reduce
from string import Template
import torch
import torch.cuda
from torch._utils import _accumulate

try:
	import cffi
except ImportError:
	raise ImportError("torch.utils.ffi requires the cffi package")


if cffi.__version_info__ < (1, 4, 0):
	raise ImportError("torch.utils.ffi requires cffi version >= 1.4, but "
					  "got " + '.'.join(map(str, cffi.__version_info__)))


def _generate_typedefs():
	typedefs = []
	for t in ['Double', 'Float', 'Long', 'Int', 'Short', 'Char', 'Byte']:
		for lib in ['TH', 'THCuda']:
			for kind in ['Tensor', 'Storage']:
				python_name = t + kind
				if t == 'Float' and lib == 'THCuda':
					th_name = 'THCuda' + kind
				else:
					th_name = lib + t + kind
				th_struct = 'struct ' + th_name

				typedefs += ['typedef {} {};'.format(th_struct, th_name)]
				# We have to assemble a string here, because we're going to
				# do this lookup based on tensor.type(), which returns a
				# string (not a type object, as this code was before)
				python_module = 'torch.cuda' if lib == 'THCuda' else 'torch'
				python_class = python_module + '.' + python_name
				_cffi_to_torch[th_struct] = python_class
				_torch_to_cffi[python_class] = th_struct
	return '\n'.join(typedefs) + '\n'
_cffi_to_torch = {}
_torch_to_cffi = {}
_typedefs = _generate_typedefs()


PY_MODULE_TEMPLATE = Template("""
from torch.utils.ffi import _wrap_function
from .$cffi_wrapper_name import lib as _lib, ffi as _ffi

__all__ = []
def _import_symbols(locals):
	for symbol in dir(_lib):
		fn = getattr(_lib, symbol)
		if callable(fn):
			locals[symbol] = _wrap_function(fn, _ffi)
		else:
			locals[symbol] = fn
		__all__.append(symbol)

_import_symbols(locals())
""")


def _setup_wrapper(with_cuda):
	here = os.path.abspath(os.path.dirname(__file__))
	lib_dir = os.path.join(here, '..', '..', 'lib')
	include_dirs = [
		os.path.join(lib_dir, 'include'),
		os.path.join(lib_dir, 'include', 'TH'),
	]

	wrapper_source = '#include <TH/TH.h>\n'
	if with_cuda:
		import torch.cuda
		wrapper_source += '#include <THC/THC.h>\n'
		if os.sys.platform == 'win32':
			cuda_include_dirs = glob.glob(os.getenv('CUDA_PATH', '') + '/include')
			cuda_include_dirs += glob.glob(os.getenv('NVTOOLSEXT_PATH', '') + '/include')
		else:
			cuda_include_dirs = glob.glob('/usr/local/cuda/include')
			cuda_include_dirs += glob.glob('/Developer/NVIDIA/CUDA-*/include')
		include_dirs.append(os.path.join(lib_dir, 'include', 'THC'))
		include_dirs.extend(cuda_include_dirs)
	return wrapper_source, include_dirs


def _create_module_dir(base_path, fullname):
	module, _, name = fullname.rpartition('.')
	if not module:
		target_dir = name
	else:
		target_dir = reduce(os.path.join, fullname.split('.'))
	target_dir = os.path.join(base_path, target_dir)
	try:
		os.makedirs(target_dir)
	except os.error:
		pass
	for dirname in _accumulate(fullname.split('.'), os.path.join):
		init_file = os.path.join(base_path, dirname, '__init__.py')
		open(init_file, 'a').close()  # Create file if it doesn't exist yet
	return name, target_dir


def _build_extension(ffi, cffi_wrapper_name, target_dir, verbose):
	try:
		tmpdir = tempfile.mkdtemp()
		ext_suf = '.pyd' if os.sys.platform == 'win32' else '.so'
		libname = cffi_wrapper_name + ext_suf
		outfile = ffi.compile(tmpdir=tmpdir, verbose=verbose, target=libname)
		shutil.copy(outfile, os.path.join(target_dir, libname))
	finally:
		shutil.rmtree(tmpdir)


def _make_python_wrapper(name, cffi_wrapper_name, target_dir):
	py_source = PY_MODULE_TEMPLATE.substitute(name=name,
											  cffi_wrapper_name=cffi_wrapper_name)
	with open(os.path.join(target_dir, '__init__.py'), 'w') as f:
		f.write(py_source)


def create_extension(name, headers, sources, verbose=True, with_cuda=False,
					 package=False, relative_to='.', **kwargs):
	base_path = os.path.abspath(os.path.dirname(relative_to))
	name_suffix, target_dir = _create_module_dir(base_path, name)
	if not package:
		cffi_wrapper_name = '_' + name_suffix
	else:
		cffi_wrapper_name = (name.rpartition('.')[0] +
							 '.{0}._{0}'.format(name_suffix))

	wrapper_source, include_dirs = _setup_wrapper(with_cuda)
	include_dirs.extend(kwargs.pop('include_dirs', []))

	if os.sys.platform == 'win32':
		library_dirs = glob.glob(os.getenv('CUDA_PATH', '') + '/lib/x64')
		library_dirs += glob.glob(os.getenv('NVTOOLSEXT_PATH', '') + '/lib/x64')

		here = os.path.abspath(os.path.dirname(__file__))
		lib_dir = os.path.join(here, '..', '..', 'lib')

		library_dirs.append(os.path.join(lib_dir))
	else:
		library_dirs = []
	library_dirs.extend(kwargs.pop('library_dirs', []))

	if isinstance(headers, str):
		headers = [headers]
	all_headers_source = ''
	for header in headers:
		with open(os.path.join(base_path, header), 'r') as f:
			all_headers_source += f.read() + '\n\n'

	ffi = cffi.FFI()
	sources = [os.path.join(base_path, src) for src in sources]
	# NB: TH headers are C99 now
	kwargs['extra_compile_args'] = ['-std=c99'] + kwargs.get('extra_compile_args', [])
	ffi.set_source(cffi_wrapper_name, wrapper_source + all_headers_source,
				   sources=sources,
				   include_dirs=include_dirs,
				   library_dirs=library_dirs, **kwargs)
	ffi.cdef(_typedefs + all_headers_source)

	_make_python_wrapper(name_suffix, '_' + name_suffix, target_dir)

	def build():
		_build_extension(ffi, cffi_wrapper_name, target_dir, verbose)
	ffi.build = build
	return ffi

def _wrap_function(function, ffi):
	@wraps(function)
	def safe_call(*args, **kwargs):
		args = tuple(ffi.cast(_torch_to_cffi.get(arg.type(), 'void') + '*', arg._cdata)
					 if isinstance(arg, torch.Tensor) or torch.is_storage(arg)
					 else arg
					 for arg in args)
		args = (function,) + args
		result = torch._C._safe_call(*args, **kwargs)
		if isinstance(result, ffi.CData):
			typeof = ffi.typeof(result)
			if typeof.kind == 'pointer':
				cdata = int(ffi.cast('uintptr_t', result))
				cname = typeof.item.cname
				if cname in _cffi_to_torch:
					# TODO: Maybe there is a less janky way to eval
					# off of this
					return eval(_cffi_to_torch[cname])(cdata=cdata)
		return result
	return safe_call

andrewjong closed this as completed Jan 24, 2019

pfjaeger mentioned this issue May 10, 2019

Pytorch 1.0 MIC-DKFZ/medicaldetectiontoolkit#41

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robertocarlosjuan mentioned this issue Jan 18, 2021

ImportError: torch.utils.ffi is deprecated. Please use cpp extensions instead. jiasenlu/NeuralBabyTalk#56

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Riei-Joaquim mentioned this issue Aug 18, 2022

cublas runtime error j96w/DenseFusion#177

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Pytorch 1.0 branch ImportError: torch.utils.ffi is deprecated #412

Pytorch 1.0 branch ImportError: torch.utils.ffi is deprecated #412

andrewjong commented Jan 4, 2019 •

edited

ericsqxd commented Jan 4, 2019

andrewjong commented Jan 4, 2019 •

edited

adityaarun1 commented Jan 5, 2019

andrewjong commented Jan 5, 2019

adityaarun1 commented Jan 6, 2019

lzxzy commented Jan 16, 2019

ljtruong commented Jan 22, 2019

odellus commented Jan 23, 2019

adityaarun1 commented Jan 23, 2019

odellus commented Jan 23, 2019 via email

andrewjong commented Jan 24, 2019

zcunyi commented Feb 22, 2019

adityaarun1 commented Feb 22, 2019

ma-xu commented Mar 7, 2019

andrewjong commented Mar 11, 2019 •

edited

kangkang59812 commented Apr 22, 2019

Qlulu commented Jul 13, 2019 •

edited

E-Dreamer-LQ commented Jul 26, 2019

marcunzueta commented Aug 2, 2019

rpfly3 commented Nov 6, 2019 •

edited

lhaippp commented Apr 13, 2020

jity16 commented Sep 7, 2020 •

edited

Pytorch 1.0 branch ImportError: torch.utils.ffi is deprecated #412

Pytorch 1.0 branch ImportError: torch.utils.ffi is deprecated #412

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andrewjong commented Jan 4, 2019 • edited

ericsqxd commented Jan 4, 2019

andrewjong commented Jan 4, 2019 • edited

adityaarun1 commented Jan 5, 2019

andrewjong commented Jan 5, 2019

adityaarun1 commented Jan 6, 2019

lzxzy commented Jan 16, 2019

ljtruong commented Jan 22, 2019

odellus commented Jan 23, 2019

adityaarun1 commented Jan 23, 2019

odellus commented Jan 23, 2019 via email

andrewjong commented Jan 24, 2019

zcunyi commented Feb 22, 2019

adityaarun1 commented Feb 22, 2019

ma-xu commented Mar 7, 2019

andrewjong commented Mar 11, 2019 • edited

kangkang59812 commented Apr 22, 2019

Qlulu commented Jul 13, 2019 • edited

E-Dreamer-LQ commented Jul 26, 2019

marcunzueta commented Aug 2, 2019

rpfly3 commented Nov 6, 2019 • edited

lhaippp commented Apr 13, 2020

jity16 commented Sep 7, 2020 • edited

andrewjong commented Jan 4, 2019 •

edited

andrewjong commented Jan 4, 2019 •

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andrewjong commented Mar 11, 2019 •

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Qlulu commented Jul 13, 2019 •

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