mirror of
https://github.com/pytorch/pytorch.git
synced 2025-11-03 23:45:05 +08:00
6e4f501f1a
Summary: In issue https://github.com/pytorch/pytorch/issues/36997 the user encountered a non-meaningful error message when trying to export the model to ONNX. The Pad operator in opset 9 requires the list of paddings to be constant. This PR tries to improve the error message given to the user when this is not the case. Pull Request resolved: https://github.com/pytorch/pytorch/pull/39651 Reviewed By: hl475 Differential Revision: D21992262 Pulled By: houseroad fbshipit-source-id: b817111c2a40deba85e4c6cdb874c1713312dba1
91 lines
2.9 KiB
Python
91 lines
2.9 KiB
Python
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
from __future__ import unicode_literals
|
|
|
|
import functools
|
|
import os
|
|
import unittest
|
|
import sys
|
|
import torch
|
|
import torch.autograd.function as function
|
|
|
|
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
|
|
sys.path.insert(-1, pytorch_test_dir)
|
|
|
|
from torch.testing._internal.common_utils import * # noqa: F401
|
|
|
|
torch.set_default_tensor_type('torch.FloatTensor')
|
|
|
|
BATCH_SIZE = 2
|
|
|
|
RNN_BATCH_SIZE = 7
|
|
RNN_SEQUENCE_LENGTH = 11
|
|
RNN_INPUT_SIZE = 5
|
|
RNN_HIDDEN_SIZE = 3
|
|
|
|
|
|
def _skipper(condition, reason):
|
|
def decorator(f):
|
|
@functools.wraps(f)
|
|
def wrapper(*args, **kwargs):
|
|
if condition():
|
|
raise unittest.SkipTest(reason)
|
|
return f(*args, **kwargs)
|
|
return wrapper
|
|
return decorator
|
|
|
|
|
|
skipIfNoCuda = _skipper(lambda: not torch.cuda.is_available(),
|
|
'CUDA is not available')
|
|
|
|
skipIfTravis = _skipper(lambda: os.getenv('TRAVIS'),
|
|
'Skip In Travis')
|
|
|
|
# skips tests for all versions below min_opset_version.
|
|
# if exporting the op is only supported after a specific version,
|
|
# add this wrapper to prevent running the test for opset_versions
|
|
# smaller than the currently tested opset_version
|
|
def skipIfUnsupportedMinOpsetVersion(min_opset_version):
|
|
def skip_dec(func):
|
|
def wrapper(self):
|
|
if self.opset_version < min_opset_version:
|
|
raise unittest.SkipTest("Skip verify test for unsupported opset_version")
|
|
return func(self)
|
|
return wrapper
|
|
return skip_dec
|
|
|
|
# skips tests for all versions above min_opset_version.
|
|
def skipIfUnsupportedMaxOpsetVersion(min_opset_version):
|
|
def skip_dec(func):
|
|
def wrapper(self):
|
|
if self.opset_version > min_opset_version:
|
|
raise unittest.SkipTest("Skip verify test for unsupported opset_version")
|
|
return func(self)
|
|
return wrapper
|
|
return skip_dec
|
|
|
|
# Enables tests for scripting, instead of only tracing the model.
|
|
def enableScriptTest():
|
|
def script_dec(func):
|
|
def wrapper(self):
|
|
self.is_script_test_enabled = True
|
|
return func(self)
|
|
return wrapper
|
|
return script_dec
|
|
|
|
# skips tests for opset_versions listed in unsupported_opset_versions.
|
|
# if the caffe2 test cannot be run for a specific version, add this wrapper
|
|
# (for example, an op was modified but the change is not supported in caffe2)
|
|
def skipIfUnsupportedOpsetVersion(unsupported_opset_versions):
|
|
def skip_dec(func):
|
|
def wrapper(self):
|
|
if self.opset_version in unsupported_opset_versions:
|
|
raise unittest.SkipTest("Skip verify test for unsupported opset_version")
|
|
return func(self)
|
|
return wrapper
|
|
return skip_dec
|
|
|
|
def flatten(x):
|
|
return tuple(function._iter_filter(lambda o: isinstance(o, torch.Tensor))(x))
|