Commit b2ee7d5c authored by Amir MOHAMMADI's avatar Amir MOHAMMADI
Browse files

[pre-commit] fix pre-commit complaints

parent 06c797fe
Pipeline #49168 passed with stages
in 4 minutes and 45 seconds
import math
import numbers import numbers
import tensorflow as tf import tensorflow as tf
import math from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Dropout
from tensorflow.keras.layers import GlobalAvgPool2D
def _check_input( def _check_input(
...@@ -164,7 +168,7 @@ def Normalize(mean, std=1.0, **kwargs): ...@@ -164,7 +168,7 @@ def Normalize(mean, std=1.0, **kwargs):
class SphereFaceLayer(tf.keras.layers.Layer): class SphereFaceLayer(tf.keras.layers.Layer):
""" r"""
Implements the SphereFace loss from equation (7) of `SphereFace: Deep Hypersphere Embedding for Face Recognition <https://arxiv.org/abs/1704.08063>`_ Implements the SphereFace loss from equation (7) of `SphereFace: Deep Hypersphere Embedding for Face Recognition <https://arxiv.org/abs/1704.08063>`_
If the parameter `original` is set to `True` it will computes exactly what's written in eq (7): :math:`\\text{soft}(x_i) = \\frac{exp(||x_i||\\text{cos}(\\psi(\\theta_{yi})))}{exp(||x_i||\\text{cos}(\\psi(\\theta_{yi}))) + \sum_{j;j\\neq yi} exp(||x_i||\\text{cos}(\psi(\\theta_{j}))) }`. If the parameter `original` is set to `True` it will computes exactly what's written in eq (7): :math:`\\text{soft}(x_i) = \\frac{exp(||x_i||\\text{cos}(\\psi(\\theta_{yi})))}{exp(||x_i||\\text{cos}(\\psi(\\theta_{yi}))) + \sum_{j;j\\neq yi} exp(||x_i||\\text{cos}(\psi(\\theta_{j}))) }`.
...@@ -256,15 +260,6 @@ class ModifiedSoftMaxLayer(tf.keras.layers.Layer): ...@@ -256,15 +260,6 @@ class ModifiedSoftMaxLayer(tf.keras.layers.Layer):
return logits return logits
from tensorflow.keras.layers import (
BatchNormalization,
Dropout,
Dense,
Concatenate,
GlobalAvgPool2D,
)
def add_bottleneck(model, bottleneck_size=128, dropout_rate=0.2): def add_bottleneck(model, bottleneck_size=128, dropout_rate=0.2):
""" """
Amend a bottleneck layer to a Keras Model Amend a bottleneck layer to a Keras Model
......
from .alexnet import AlexNet_simplified from .alexnet import AlexNet_simplified
from .arcface import ArcFaceLayer
from .arcface import ArcFaceLayer3Penalties
from .arcface import ArcFaceModel
from .densenet import DeepPixBiS from .densenet import DeepPixBiS
from .densenet import DenseNet from .densenet import DenseNet
from .densenet import densenet161 # noqa: F401 from .densenet import densenet161 # noqa: F401
from .mine import MineModel
from .embedding_validation import EmbeddingValidation from .embedding_validation import EmbeddingValidation
from .arcface import ArcFaceLayer, ArcFaceLayer3Penalties, ArcFaceModel from .mine import MineModel
# gets sphinx autodoc done right - don't remove it # gets sphinx autodoc done right - don't remove it
def __appropriate__(*args): def __appropriate__(*args):
......
import math
import tensorflow as tf import tensorflow as tf
from .embedding_validation import EmbeddingValidation
from bob.learn.tensorflow.metrics.embedding_accuracy import accuracy_from_embeddings from bob.learn.tensorflow.metrics.embedding_accuracy import accuracy_from_embeddings
import math
from .embedding_validation import EmbeddingValidation
class ArcFaceModel(EmbeddingValidation): class ArcFaceModel(EmbeddingValidation):
...@@ -148,4 +151,3 @@ class ArcFaceLayer3Penalties(tf.keras.layers.Layer): ...@@ -148,4 +151,3 @@ class ArcFaceLayer3Penalties(tf.keras.layers.Layer):
logits = self.s * logits logits = self.s * logits
return logits return logits
import tensorflow as tf import tensorflow as tf
from bob.learn.tensorflow.metrics.embedding_accuracy import accuracy_from_embeddings from bob.learn.tensorflow.metrics.embedding_accuracy import accuracy_from_embeddings
...@@ -10,7 +11,8 @@ class EmbeddingValidation(tf.keras.Model): ...@@ -10,7 +11,8 @@ class EmbeddingValidation(tf.keras.Model):
""" """
def compile( def compile(
self, **kwargs, self,
**kwargs,
): ):
""" """
Compile Compile
...@@ -29,7 +31,6 @@ class EmbeddingValidation(tf.keras.Model): ...@@ -29,7 +31,6 @@ class EmbeddingValidation(tf.keras.Model):
logits, _ = self(X, training=True) logits, _ = self(X, training=True)
loss = self.loss(y, logits) loss = self.loss(y, logits)
trainable_vars = self.trainable_variables
self.optimizer.minimize(loss, self.trainable_variables, tape=tape) self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
self.compiled_metrics.update_state(y, logits, sample_weight=None) self.compiled_metrics.update_state(y, logits, sample_weight=None)
......
from bob.learn.tensorflow.models import (
EmbeddingValidation,
ArcFaceLayer,
ArcFaceModel,
ArcFaceLayer3Penalties,
)
from bob.learn.tensorflow.layers import (
SphereFaceLayer,
ModifiedSoftMaxLayer,
)
import numpy as np import numpy as np
from bob.learn.tensorflow.layers import ModifiedSoftMaxLayer
from bob.learn.tensorflow.layers import SphereFaceLayer
from bob.learn.tensorflow.models import ArcFaceLayer
from bob.learn.tensorflow.models import ArcFaceLayer3Penalties
def test_arcface_layer(): def test_arcface_layer():
......
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