# Path: paleo/layers/conv.py
# class Deconv2D(base.BaseLayer):
# class Conv2d(base.BaseLayer):
#     def __init__(self,
#                  name,
#                  inputs,
#                  filters,
#                  strides,
#                  padding,
#                  output_shape,
#                  use_cudnn=False,
#                  backprop=True,
#                  activation_fn='relu',
#                  percent_holes=0.0):
#     def gradients(self, wrt='inputs'):
#     def additional_summary(self):
#     def filters(self):
#     def strides(self):
#     def padding(self):
#     def backprop(self):
#     def weights_in_bytes(self):
#     def num_params(self):
#     def __init__(self,
#                  name,
#                  inputs,
#                  filters,
#                  strides,
#                  padding,
#                  use_cudnn=False,
#                  backprop=True,
#                  activation_fn='relu',
#                  percent_holes=0.0,
#                  hole_position='filters',
#                  splits=None):
#     def percent_holes(self):
#     def percent_holes_in_inputs(self):
#     def percent_holes_in_filters(self):
#     def activation_fn(self):
#     def bias(self):
#     def filters(self):
#     def backprop(self):
#     def strides(self):
#     def padding(self):
#     def split_model(self, num_splits):
#     def additional_summary(self):
#     def _calculate_output_shape(self):
#     def weights_in_bytes(self):
#     def num_params(self):
#     def gradients(self, wrt='inputs'):
#         def _compute_padding(layer):
#         _BYTES_FLOAT = 4
#         _BYTES_FLOAT = 4


import unittest
from paleo.layers import conv
"""Tests for Conv2D."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function




class Conv2DTest(unittest.TestCase):
    def setUp(self):

# Path: paleo/layers/conv.py
# class Deconv2D(base.BaseLayer):
# class Conv2d(base.BaseLayer):
#     def __init__(self,
#                  name,
#                  inputs,
#                  filters,
#                  strides,
#                  padding,
#                  output_shape,
#                  use_cudnn=False,
#                  backprop=True,
#                  activation_fn='relu',
#                  percent_holes=0.0):
#     def gradients(self, wrt='inputs'):
#     def additional_summary(self):
#     def filters(self):
#     def strides(self):
#     def padding(self):
#     def backprop(self):
#     def weights_in_bytes(self):
#     def num_params(self):
#     def __init__(self,
#                  name,
#                  inputs,
#                  filters,
#                  strides,
#                  padding,
#                  use_cudnn=False,
#                  backprop=True,
#                  activation_fn='relu',
#                  percent_holes=0.0,
#                  hole_position='filters',
#                  splits=None):
#     def percent_holes(self):
#     def percent_holes_in_inputs(self):
#     def percent_holes_in_filters(self):
#     def activation_fn(self):
#     def bias(self):
#     def filters(self):
#     def backprop(self):
#     def strides(self):
#     def padding(self):
#     def split_model(self, num_splits):
#     def additional_summary(self):
#     def _calculate_output_shape(self):
#     def weights_in_bytes(self):
#     def num_params(self):
#     def gradients(self, wrt='inputs'):
#         def _compute_padding(layer):
#         _BYTES_FLOAT = 4
#         _BYTES_FLOAT = 4


# Path: tests/conv_test.py
import unittest
from paleo.layers import conv

"""Tests for Conv2D."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function




class Conv2DTest(unittest.TestCase):
    def setUp(self):

        self.layer = conv.Conv2d(