From 5eb932d5d1b653d16ad3a7511606481989f6fbaf Mon Sep 17 00:00:00 2001 From: Owen Vallis Date: Tue, 8 Aug 2023 19:28:04 +0000 Subject: [PATCH] Fix formatting and modue import sort order. --- tensorflow_similarity/__init__.py | 2 +- tensorflow_similarity/augmenters/barlow.py | 2 -- tensorflow_similarity/augmenters/simclr.py | 2 -- tensorflow_similarity/evaluators/memory_evaluator.py | 1 - tensorflow_similarity/indexer.py | 1 - tensorflow_similarity/losses/__init__.py | 2 +- tensorflow_similarity/losses/lifted_structure_loss.py | 5 ++++- tensorflow_similarity/losses/simclr.py | 1 - tensorflow_similarity/matchers/match_majority_vote.py | 1 - tensorflow_similarity/matchers/match_nearest.py | 1 - tensorflow_similarity/training_metrics/distance_metrics.py | 2 -- tensorflow_similarity/visualization/vizualize_views.py | 1 - tests/losses/test_lifted_structure_loss.py | 4 +++- 13 files changed, 9 insertions(+), 16 deletions(-) diff --git a/tensorflow_similarity/__init__.py b/tensorflow_similarity/__init__.py index f1caf4be..b18f76e2 100644 --- a/tensorflow_similarity/__init__.py +++ b/tensorflow_similarity/__init__.py @@ -11,7 +11,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. -__version__ = "0.17.1" +__version__ = "0.17.2" from . import algebra # noqa diff --git a/tensorflow_similarity/augmenters/barlow.py b/tensorflow_similarity/augmenters/barlow.py index 22a40f1a..d7fbf7df 100644 --- a/tensorflow_similarity/augmenters/barlow.py +++ b/tensorflow_similarity/augmenters/barlow.py @@ -132,7 +132,6 @@ def augment( num_augmentations_per_example: int = 2, is_warmup: bool = True, ) -> list[Any]: - with tf.device("/cpu:0"): if y is None: y = tf.constant([0]) @@ -162,7 +161,6 @@ def augment( solarize_thresh=self.solarize_thresh, ) for _ in range(num_augmentations_per_example): - view = tf.map_fn( lambda img: augment_fn(image=img), inputs, diff --git a/tensorflow_similarity/augmenters/simclr.py b/tensorflow_similarity/augmenters/simclr.py index 4a503269..b067db67 100644 --- a/tensorflow_similarity/augmenters/simclr.py +++ b/tensorflow_similarity/augmenters/simclr.py @@ -108,7 +108,6 @@ def __init__( version: str = "v2", num_cpu: int | None = os.cpu_count(), ): - self.width = width self.height = height self.is_training = is_training @@ -132,7 +131,6 @@ def __init__( @tf.function def augment(self, x: Tensor, y: Tensor, num_views: int, is_warmup: bool) -> list[Tensor]: - with tf.device("/cpu:0"): inputs = tf.stack(x) inputs = tf.cast(inputs, dtype="float32") / 255.0 diff --git a/tensorflow_similarity/evaluators/memory_evaluator.py b/tensorflow_similarity/evaluators/memory_evaluator.py index dc51cb6d..1623d77f 100644 --- a/tensorflow_similarity/evaluators/memory_evaluator.py +++ b/tensorflow_similarity/evaluators/memory_evaluator.py @@ -317,7 +317,6 @@ def _optimal_cutpoint( "value": metrics[calibration_metric.name][idx].item(), } for metric_name in metrics.keys(): - optimal_cp[metric_name] = metrics[metric_name][idx].item() return optimal_cp diff --git a/tensorflow_similarity/indexer.py b/tensorflow_similarity/indexer.py index 295e5140..a0408260 100644 --- a/tensorflow_similarity/indexer.py +++ b/tensorflow_similarity/indexer.py @@ -325,7 +325,6 @@ def single_lookup(self, prediction: FloatTensor, k: int = 5) -> list[Lookup]: return lookups def batch_lookup(self, predictions: FloatTensor, k: int = 5, verbose: int = 1) -> list[list[Lookup]]: - """Find the k closest matches for a set of embeddings Args: diff --git a/tensorflow_similarity/losses/__init__.py b/tensorflow_similarity/losses/__init__.py index 89471a5d..3e11740e 100644 --- a/tensorflow_similarity/losses/__init__.py +++ b/tensorflow_similarity/losses/__init__.py @@ -17,6 +17,7 @@ """ from .barlow import Barlow # noqa from .circle_loss import CircleLoss # noqa +from .lifted_structure_loss import LiftedStructLoss # noqa from .metric_loss import MetricLoss # noqa from .multinegrank_loss import MultiNegativesRankLoss # noqa from .multisim_loss import MultiSimilarityLoss # noqa @@ -25,6 +26,5 @@ from .simsiam import SimSiamLoss # noqa from .softnn_loss import SoftNearestNeighborLoss # noqa from .triplet_loss import TripletLoss # noqa -from .lifted_structure_loss import LiftedStructLoss # noqa from .vicreg import VicReg # noqa from .xbm_loss import XBM # noqa diff --git a/tensorflow_similarity/losses/lifted_structure_loss.py b/tensorflow_similarity/losses/lifted_structure_loss.py index e5652f4c..dc542d7f 100644 --- a/tensorflow_similarity/losses/lifted_structure_loss.py +++ b/tensorflow_similarity/losses/lifted_structure_loss.py @@ -17,11 +17,14 @@ https://arxiv.org/abs/1511.06452 """ from __future__ import annotations + import tensorflow as tf + +from tensorflow_similarity import losses as tfsim_losses from tensorflow_similarity.algebra import build_masks from tensorflow_similarity.distances import Distance, distance_canonicalizer from tensorflow_similarity.types import FloatTensor, IntTensor -from tensorflow_similarity import losses as tfsim_losses + from .metric_loss import MetricLoss from .utils import positive_distances diff --git a/tensorflow_similarity/losses/simclr.py b/tensorflow_similarity/losses/simclr.py index 38dd6567..c93763db 100644 --- a/tensorflow_similarity/losses/simclr.py +++ b/tensorflow_similarity/losses/simclr.py @@ -39,7 +39,6 @@ def __init__(self, temperature: float = 0.05, **kwargs): self.temperature = temperature def contrast(self, hidden1: FloatTensor, hidden2: FloatTensor) -> FloatTensor: - # local replica batch size batch_size = tf.shape(hidden1)[0] diff --git a/tensorflow_similarity/matchers/match_majority_vote.py b/tensorflow_similarity/matchers/match_majority_vote.py index 8a57f926..62a0b3c4 100644 --- a/tensorflow_similarity/matchers/match_majority_vote.py +++ b/tensorflow_similarity/matchers/match_majority_vote.py @@ -24,7 +24,6 @@ class MatchMajorityVote(ClassificationMatch): """Match metrics for the most common label in a result set.""" def __init__(self, name: str = "majority_vote", **kwargs) -> None: - if "canonical_name" not in kwargs: kwargs["canonical_name"] = "match_majority_vote" diff --git a/tensorflow_similarity/matchers/match_nearest.py b/tensorflow_similarity/matchers/match_nearest.py index 966c60e7..40b20ae8 100644 --- a/tensorflow_similarity/matchers/match_nearest.py +++ b/tensorflow_similarity/matchers/match_nearest.py @@ -22,7 +22,6 @@ class MatchNearest(ClassificationMatch): """Match metrics for labels at k=1.""" def __init__(self, name: str = "nearest", **kwargs) -> None: - if "canonical_name" not in kwargs: kwargs["canonical_name"] = "match_nearest" diff --git a/tensorflow_similarity/training_metrics/distance_metrics.py b/tensorflow_similarity/training_metrics/distance_metrics.py index e3889c44..9bfdb4da 100644 --- a/tensorflow_similarity/training_metrics/distance_metrics.py +++ b/tensorflow_similarity/training_metrics/distance_metrics.py @@ -36,7 +36,6 @@ def __init__( negative_mining_strategy: str = "hard", **kwargs, ): - if not name: name = "%s_%s" % (aggregate, anchor[:3]) super().__init__(name=name, **kwargs) @@ -63,7 +62,6 @@ def __init__( self.aggregated_distances = tf.Variable(0, dtype=tf.keras.backend.floatx()) def update_state(self, labels: IntTensor, embeddings: FloatTensor, sample_weight: FloatTensor) -> None: - # [distances] pairwise_distances = self.distance(embeddings, embeddings) diff --git a/tensorflow_similarity/visualization/vizualize_views.py b/tensorflow_similarity/visualization/vizualize_views.py index bc4a07c7..a85646f1 100644 --- a/tensorflow_similarity/visualization/vizualize_views.py +++ b/tensorflow_similarity/visualization/vizualize_views.py @@ -40,7 +40,6 @@ def visualize_views( # Plot the images fig, axes = plt.subplots(num_row, num_col, figsize=fig_size) for i in range(num_imgs): - # If the number of rows is 1, the axes array is one-dimensional if num_row == 1: ax = axes[i % num_col] diff --git a/tests/losses/test_lifted_structure_loss.py b/tests/losses/test_lifted_structure_loss.py index 1bc18b96..c244bfb8 100644 --- a/tests/losses/test_lifted_structure_loss.py +++ b/tests/losses/test_lifted_structure_loss.py @@ -1,8 +1,10 @@ import tensorflow as tf from absl.testing import parameterized -from tensorflow.python.framework import combinations from tensorflow.keras.losses import Reduction +from tensorflow.python.framework import combinations + from tensorflow_similarity import losses + from . import utils