Remove duplicate assert_shape from helper functions.

theano/tensor/nnet/abstract_conv.py

@@ -523,14 +523,6 @@ def conv2d(input,
 
     input = as_tensor_variable(input)
     filters = as_tensor_variable(filters)
-
-    input = assert_shape(input, input_shape,
-                         'conv2d shape mismatch: shape of '
-                         'input does not match given input_shape.')
-    filters = assert_shape(filters, filter_shape,
-                           'conv2d shape mismatch: shape of '
-                           'filters does not match given filter_shape.')
-
     conv_op = AbstractConv2d(imshp=input_shape,
                              kshp=filter_shape,
                              border_mode=border_mode,
@@ -630,14 +622,6 @@ def conv3d(input,
 
     input = as_tensor_variable(input)
     filters = as_tensor_variable(filters)
-
-    input = assert_shape(input, input_shape,
-                         'conv3d shape mismatch: shape of '
-                         'input does not match given input_shape.')
-    filters = assert_shape(filters, filter_shape,
-                           'conv3d shape mismatch: shape of '
-                           'filters does not match given filter_shape.')
-
     conv_op = AbstractConv3d(imshp=input_shape,
                              kshp=filter_shape,
                              border_mode=border_mode,
@@ -764,9 +748,6 @@ def conv2d_grad_wrt_inputs(output_grad,
         for dim in [0, 1, 2, 3]:
             assert isinstance(filter_shape[dim], (theano.tensor.TensorConstant,
                                                   integer_types, type(None)))
-        filters = assert_shape(filters, filter_shape,
-                               'conv2d_grad_wrt_inputs shape mismatch: shape of '
-                               'filters does not match given filter_shape.')
 
     # setting the last two dimensions of input_shape to None, if
     # the type of these dimensions is TensorVariable.
@@ -902,9 +883,6 @@ def conv3d_grad_wrt_inputs(output_grad,
         for dim in [0, 1, 2, 3, 4]:
             assert isinstance(filter_shape[dim], (theano.tensor.TensorConstant,
                                                   integer_types, type(None)))
-        filters = assert_shape(filters, filter_shape,
-                               'conv3d_grad_wrt_inputs shape mismatch: shape of '
-                               'filters does not match given filter_shape.')
 
     # setting the last three dimensions of input_shape to None, if
     # the type of these dimensions is TensorVariable.