feat(compatibility): Python3.6 compatibility

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Alexander Engelsberger 2021-08-30 17:15:40 +02:00
parent d7834e2cc0
commit 7b93cd4ad5
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9 changed files with 33 additions and 17 deletions

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@ -1,7 +1,11 @@
dist: bionic dist: bionic
sudo: false sudo: false
language: python language: python
python: 3.9 python:
- 3.9
- 3.8
- 3.7
- 3.6
cache: cache:
directories: directories:
- "$HOME/.cache/pip" - "$HOME/.cache/pip"

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@ -1,7 +1,5 @@
"""`models` plugin for the `prototorch` package.""" """`models` plugin for the `prototorch` package."""
from importlib.metadata import PackageNotFoundError, version
from .callbacks import PrototypeConvergence, PruneLoserPrototypes from .callbacks import PrototypeConvergence, PruneLoserPrototypes
from .cbc import CBC, ImageCBC from .cbc import CBC, ImageCBC
from .glvq import ( from .glvq import (

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@ -1,7 +1,5 @@
"""Abstract classes to be inherited by prototorch models.""" """Abstract classes to be inherited by prototorch models."""
from typing import Final, final
import pytorch_lightning as pl import pytorch_lightning as pl
import torch import torch
import torchmetrics import torchmetrics
@ -43,7 +41,6 @@ class ProtoTorchBolt(pl.LightningModule):
else: else:
return optimizer return optimizer
@final
def reconfigure_optimizers(self): def reconfigure_optimizers(self):
self.trainer.accelerator.setup_optimizers(self.trainer) self.trainer.accelerator.setup_optimizers(self.trainer)
@ -175,7 +172,7 @@ class NonGradientMixin(ProtoTorchMixin):
"""Mixin for custom non-gradient optimization.""" """Mixin for custom non-gradient optimization."""
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs) super().__init__(*args, **kwargs)
self.automatic_optimization: Final = False self.automatic_optimization = False
def training_step(self, train_batch, batch_idx, optimizer_idx=None): def training_step(self, train_batch, batch_idx, optimizer_idx=None):
raise NotImplementedError raise NotImplementedError
@ -183,7 +180,6 @@ class NonGradientMixin(ProtoTorchMixin):
class ImagePrototypesMixin(ProtoTorchMixin): class ImagePrototypesMixin(ProtoTorchMixin):
"""Mixin for models with image prototypes.""" """Mixin for models with image prototypes."""
@final
def on_train_batch_end(self, outputs, batch, batch_idx, dataloader_idx): def on_train_batch_end(self, outputs, batch, batch_idx, dataloader_idx):
"""Constrain the components to the range [0, 1] by clamping after updates.""" """Constrain the components to the range [0, 1] by clamping after updates."""
self.proto_layer.components.data.clamp_(0.0, 1.0) self.proto_layer.components.data.clamp_(0.0, 1.0)

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@ -55,7 +55,7 @@ class PruneLoserPrototypes(pl.Callback):
distribution = dict(zip(labels.tolist(), counts.tolist())) distribution = dict(zip(labels.tolist(), counts.tolist()))
if self.verbose: if self.verbose:
print(f"Re-adding pruned prototypes...") print(f"Re-adding pruned prototypes...")
print(f"{distribution=}") print(f"distribution={distribution}")
pl_module.add_prototypes( pl_module.add_prototypes(
distribution=distribution, distribution=distribution,
components_initializer=self.prototypes_initializer) components_initializer=self.prototypes_initializer)

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@ -112,7 +112,8 @@ class SiameseGLVQ(GLVQ):
proto_opt = self.optimizer(self.proto_layer.parameters(), proto_opt = self.optimizer(self.proto_layer.parameters(),
lr=self.hparams.proto_lr) lr=self.hparams.proto_lr)
# Only add a backbone optimizer if backbone has trainable parameters # Only add a backbone optimizer if backbone has trainable parameters
if (bb_params := list(self.backbone.parameters())): bb_params = list(self.backbone.parameters())
if (bb_params):
bb_opt = self.optimizer(bb_params, lr=self.hparams.bb_lr) bb_opt = self.optimizer(bb_params, lr=self.hparams.bb_lr)
optimizers = [proto_opt, bb_opt] optimizers = [proto_opt, bb_opt]
else: else:

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@ -28,8 +28,8 @@ class LVQ1(NonGradientMixin, GLVQ):
self.proto_layer.load_state_dict({"_components": updated_protos}, self.proto_layer.load_state_dict({"_components": updated_protos},
strict=False) strict=False)
print(f"{dis=}") print(f"dis={dis}")
print(f"{y=}") print(f"y={y}")
# Logging # Logging
self.log_acc(dis, y, tag="train_acc") self.log_acc(dis, y, tag="train_acc")

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@ -251,8 +251,6 @@ class VisImgComp(Vis2DAbstract):
size=self.embedding_data, size=self.embedding_data,
replace=False) replace=False)
data = self.x_train[ind] data = self.x_train[ind]
# print(f"{data.shape=}")
# print(f"{self.y_train[ind].shape=}")
tb.add_embedding(data.view(len(ind), -1), tb.add_embedding(data.view(len(ind), -1),
label_img=data, label_img=data,
global_step=None, global_step=None,

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@ -63,7 +63,7 @@ setup(
url=PROJECT_URL, url=PROJECT_URL,
download_url=DOWNLOAD_URL, download_url=DOWNLOAD_URL,
license="MIT", license="MIT",
python_requires=">=3.9", python_requires=">=3.6",
install_requires=INSTALL_REQUIRES, install_requires=INSTALL_REQUIRES,
extras_require={ extras_require={
"dev": DEV, "dev": DEV,
@ -80,6 +80,9 @@ setup(
"License :: OSI Approved :: MIT License", "License :: OSI Approved :: MIT License",
"Natural Language :: English", "Natural Language :: English",
"Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.6",
"Operating System :: OS Independent", "Operating System :: OS Independent",
"Topic :: Scientific/Engineering :: Artificial Intelligence", "Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Software Development :: Libraries", "Topic :: Software Development :: Libraries",

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@ -1,11 +1,27 @@
#! /bin/bash #! /bin/bash
# Read Flags
gpu=0
while [ -n "$1" ]; do
case "$1" in
--gpu) gpu=1;;
-g) gpu=1;;
*) path=$1;;
esac
shift
done
python --version
echo "Using GPU: " $gpu
# Loop
failed=0 failed=0
for example in $(find $1 -maxdepth 1 -name "*.py") for example in $(find $path -maxdepth 1 -name "*.py")
do do
echo -n "$x" $example '... ' echo -n "$x" $example '... '
export DISPLAY= && python $example --fast_dev_run 1 --gpus 0 &> run_log.txt export DISPLAY= && python $example --fast_dev_run 1 --gpus $gpu &> run_log.txt
if [[ $? -ne 0 ]]; then if [[ $? -ne 0 ]]; then
echo "FAILED!!" echo "FAILED!!"
cat run_log.txt cat run_log.txt