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from __future__ import absolute_import, division, print_function, unicode_literals
import torch
import torch.nn.functional as F
from tests import utils
class SimpleSoftPlusModel(torch.nn.Module):
def __init__(self):
super(SimpleSoftPlusModel, self).__init__()
def forward(self, tensor):
tenso... |
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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
# Copyright (c) Glow Contributors. See CONTRIBUTORS file.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
# Copyright (c) Glow Contributors. See CONTRIBUTORS file.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
from __future__ import absolute_import, division, print_function, unicode_literals
import unittest
import torch
import torch.jit
import torch_glow
from tests import utils
class Bar(torch.nn.Module):
def __init__(self):
super(Bar, self).__init__()
self.q = torch.nn.quantized.Quantize(
... |
from __future__ import absolute_import, division, print_function, unicode_literals
import unittest
import torch
from tests import utils
class TestQuantizedConv2dBigStrideSmallKernel(utils.TorchGlowTestCase):
# These tests should be run on NNPI card manually, or else
# buck test will only run them on emulato... |
# COPIED FROM: torchvision/transforms/functional.py
import numbers
import numpy as np
import torch
from PIL import Image
try:
import accimage
except ImportError:
accimage = None
def _is_pil_image(img):
return isinstance(img, Image.Image)
def _is_numpy(img):
return isinstance(img, np.ndarray)
d... |
# COPIED FROM: torchvision/models/resnet.py
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
__all__ = [
"ResNet",
"resnet18",
"resnet34",
"resnet50",
"resnet101",
"resnet152",
"resnext50_32x4d",
"resnext101_32x8d",
"wide_resnet50_2",
"wide_resnet101_2",
]
mod... |
# isort:skip_file
from __future__ import absolute_import, division, print_function, unicode_literals
import torch
import torch.nn as nn
import torch_glow
class Model(nn.Module):
def __init__(self):
super(Model, self).__init__()
self.linear = nn.Linear(10, 2)
def forward(self, x):
ret... |
# isort:skip_file
from __future__ import absolute_import, division, print_function, unicode_literals
import torch
import torch_glow
x = torch.randn(4)
y = torch.randn(4)
@torch.jit.script
def foo(a, b):
c = a.mul(b)
a = c.mul(c)
a = c.mul(a)
d = c.div(a)
return d
print("original jit ir")
print... |
# isort:skip_file
from __future__ import absolute_import, division, print_function, unicode_literals
import argparse
import torch
import torch_glow
import utils.torchvision_fake.resnet as resnet
import utils.torchvision_fake.transforms as torchvisionTransforms
from PIL import Image
def load_image(image_path):
i... |
import collections
import collections.abc
import copy
from contextlib import contextmanager
from enum import Enum
from typing import Any, Iterable, List, Mapping, Optional, Tuple, Union
import torch
import torch_glow
__all__ = [
"to_glow",
"to_glow_selective",
"get_submod_inputs",
"CompilationSpec",
... |
from ._torch_glow import *
from .to_glow import *
|
#!/usr/bin/env python
import os
import re
import sys
import shutil
import subprocess
from pathlib import Path
from setuptools import setup, find_packages
import distutils.command.clean
import torch
from tools import setup_helpers
ROOT_DIR = Path(__file__).parent.resolve()
def _run_cmd(cmd):
try:
return ... |
#!/usr/bin/env python3
"""Convert a Wav2Vec2/HuBERT model published by fairseq into torchaudio format
Examples
```
python convert_fairseq_models.py \
--input-file hubert_base_ls960.pt \
--output-file hubert_fairseq_base_ls960.pth
python convert_fairseq_models.py \
--input-file hubert_large_ll60k.pt \
--outpu... |
#!/usr/bin/env python3
"""Convert the fairseq models available in voxpopuli repo https://github.com/facebookresearch/voxpopuli
The available checkpoints should open with fairseq.
But the following error cannot be resolved with almost any version of fairseq.
https://github.com/facebookresearch/voxpopuli/issues/29
So t... |
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