mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
0dae2ba5bd
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`. Pull Request resolved: https://github.com/pytorch/pytorch/pull/127123 Approved by: https://github.com/Skylion007 ghstack dependencies: #127122
55 lines
1.5 KiB
Python
55 lines
1.5 KiB
Python
import sys
|
|
|
|
import onnx
|
|
import pytorch_test_common
|
|
import torch
|
|
import torch.jit
|
|
from torch.autograd import Variable
|
|
|
|
import caffe2.python.onnx.backend as c2
|
|
|
|
torch.set_default_tensor_type("torch.FloatTensor")
|
|
try:
|
|
import torch
|
|
except ImportError:
|
|
print("Cannot import torch, hence caffe2-torch test will not run.")
|
|
sys.exit(0)
|
|
|
|
|
|
def run_embed_params(proto, model, input, state_dict=None, use_gpu=True):
|
|
"""
|
|
This is only a helper debug function so we can test embed_params=False
|
|
case as well on pytorch front
|
|
This should likely be removed from the release version of the code
|
|
"""
|
|
device = "CPU"
|
|
if use_gpu:
|
|
device = "CUDA"
|
|
model_def = onnx.ModelProto.FromString(proto)
|
|
onnx.checker.check_model(model_def)
|
|
prepared = c2.prepare(model_def, device=device)
|
|
|
|
if state_dict:
|
|
parameters = []
|
|
# Passed in state_dict may have a different order. Make
|
|
# sure our order is consistent with the model's order.
|
|
# TODO: Even better: keyword arguments!
|
|
for k in model.state_dict():
|
|
if k in state_dict:
|
|
parameters.append(state_dict[k])
|
|
else:
|
|
parameters = list(model.state_dict().values())
|
|
|
|
W = {}
|
|
for k, v in zip(
|
|
model_def.graph.input, pytorch_test_common.flatten((input, parameters))
|
|
):
|
|
if isinstance(v, Variable):
|
|
W[k.name] = v.data.cpu().numpy()
|
|
else:
|
|
W[k.name] = v.cpu().numpy()
|
|
|
|
caffe2_out = prepared.run(inputs=W)
|
|
|
|
return caffe2_out
|