Anuj040

"""Custom losses"""

import tensorflow as tf

# pylint: disable = attribute-defined-outside-init, no-name-in-module, unexpected-keyword-arg
# pylint: disable = no-value-for-parameter
from tensorflow.python.ops import state_ops as tf_state_ops


class SeeSawWeightCalculator(tf.keras.layers.Layer):

Anuj040

"""module for implementing time to vector encoding"""

import tensorflow as tf
import tensorflow.keras.layers as KL


class Time2Vec(KL.Layer):
    """time2vector encoding layer"""

    def __init__(self, kernel: int = 64, activation: str = "sin") -> None:

Anuj040

import os
from typing import Tuple

import tensorflow as tf
import tensorflow.keras.backend as K
import tensorflow.keras.layers as KL
import tensorflow.keras.models as KM
import tensorflow_datasets as tfds
from tensorflow.python.keras.callbacks import ModelCheckpoint

Anuj040

"""Module implementing custom model.fit for model training"""

import tensorflow as tf
import tensorflow.keras.models as KM
import tensorflow_probability as tfp


class Trainer(KM.Model):  # pylint: disable=too-many-ancestors
    """Custom function for model training using model.fit()
        With functionality for selective back propagation for accelerated training.

Anuj040

import tensorflow as tf
import tensorflow.keras.layers as KL
import tensorflow.keras.models as KM

def channel_attention(features: int, reduction: int = 16, name: str = "") -> KM.Model:
    """channel attention model

    Args:
        features (int): number of features for incoming tensor
        reduction (int, optional): Reduction ratio for the MLP to squeeze information across channels. Defaults to 16.