Project: s41467-024-44930-y | Function: call (python)

system: You are an expert Python programmer implementing algorithms from scientific papers.
Complete the masked function based on the algorithm description.
Follow Python best practices and maintain consistent code style.
Return **only** the complete Python function code.

user: Complete this Python function:

**DESCRIPTION:** Temporal attention mechanism that computes attention weights to highlight important temporal segments in ECG signals

**KEY TERMS:** {
  "x": "input ECG features",
  "att": "attention weights",
  "y": "attended features",
  "sigmoid": "attention activation"
}

**CONTEXT CODE:** #TemporalAttention block
import tensorflow as tf
from tensorflow.keras import layers,Sequential,Model
class TemporalAttention(layers.Layer):
    def __init__(self, feature_dim,kernel_size,stride,name='',**kwargs):
        super(TemporalAttention,self).__init__(name=name,**kwargs)
        self.conv = tf.keras.layers.Conv1D(filters=feature_dim,kernel_size=kernel_size,strides=stride, padding='same')
        self.bn = tf.keras.layers.BatchNormalization(axis=-1)
        self.sigmoid = tf.keras.layers.Activation('sigmoid')
        
    def call(self,x):
        # MASKED: Temporal attention mechanism that computes attention weights to highlight important temporal segments in ECG signals implementation
        raise NotImplementedError("This function is masked for testing purposes.")

Complete the function implementation replacing "raise NotImplementedError".