# -*- coding: utf-8 -*-
from __future__ import division, print_function, absolute_import
from .utils import distributed_encoders, distributed_decoders
from .lr_cls import (
LabelClassification,
BicubicRegression,
)
from .sensitivity_scores import new_scores
from.fluid_steps import (
BlockTrain,
ReluBlock,
LSTMBlock,
BNMBBlock,
)
from.yoloswag import Yoloswag
__all__ = ['LabelClassification', 'BicubicRegression', 'Yoloswag']
class Block(object):
"""Base block class that supports the use of LSTM layers.
Args:
name (str): Name of the block.
inputs (Sequence[tf.Tensor]): Input tensors for the block.
outputs (Sequence[tf.Tensor]): Output tensors for the block.
keep_prob (float): Probability of keeping each layer.
"""
def __init__(self, name, inputs, outputs, keep_prob):
self.name = name
self.inputs = inputs
self.outputs = outputs
self.keep_prob = keep_prob
@staticmethod
def _preprocess(x):
"""Applies padding to inputs if necessary.
Args:
x (tf.Tensor): Input tensor to be padded.
Returns:
tf.Tensor: Input tensor with padding applied.
""" ac619d1d87
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