Module Expr Str Import alias Import alias ImportFrom alias alias ImportFrom alias alias ImportFrom alias Import alias TryExcept body ImportFrom alias alias ImportFrom alias Assign NameStore NameLoad handlers ExceptHandler type NameLoad body Assign NameStore NameLoad Assign NameStore Str Assign NameStore Call AttributeLoad NameLoad attr Str FunctionDef arguments args NameParam NameParam NameParam NameParam defaults body Expr Str Assign TupleStore NameStore NameStore TupleLoad SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Slice Num Assign TupleStore NameStore NameStore TupleLoad SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Slice Num If Call NameLoad NameLoad NameLoad body Assign NameStore Call NameLoad GeneratorExp Call NameLoad SubscriptLoad NameLoad Index NameLoad SubscriptLoad NameLoad Index NameLoad SubscriptLoad NameLoad Index NameLoad SubscriptLoad NameLoad Index NameLoad comprehension NameStore Call NameLoad Call NameLoad NameLoad orelse Assign NameStore Call NameLoad GeneratorExp Call NameLoad SubscriptLoad NameLoad Index NameLoad SubscriptLoad NameLoad Index NameLoad NameLoad SubscriptLoad NameLoad Index NameLoad comprehension NameStore Call NameLoad Call NameLoad NameLoad Return BinOpAdd TupleLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults body Expr Str If CompareIn NameLoad ListLoad NameLoad NameLoad NameLoad NameLoad body Return NameLoad If CompareEq NameLoad Str body Assign NameStore BinOpFloorDiv NameLoad Num orelse If CompareEq NameLoad Str body Assign NameStore BinOpSub NameLoad Num orelse If CompareEq NameLoad Str body Assign NameStore Num orelse Assign NameStore NameLoad If CompareLt NameLoad Num body Raise Call NameLoad Str Assign NameStore BinOpAdd BinOpFloorDiv BinOpSub BinOpAdd NameLoad BinOpMult Num NameLoad NameLoad NameLoad Num Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad Str TupleLoad Num Num NameLoad body Expr Str Assign NameStore Call NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad Return Call NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad NameLoad Str TupleLoad Num Num NameLoad body Expr Str Assign NameStore Call NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad Return Call NameLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad NameLoad Str TupleLoad Num Num NameLoad body Expr Str Assign NameStore Call NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad Return Call NameLoad NameLoad NameLoad NameLoad decorator_list ClassDef bases NameLoad body Expr Str Assign NameStore NameLoad Assign NameStore TupleLoad Str Str Str Str Str FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad Str TupleLoad Num Num NameLoad body If Call NameLoad NameLoad NameLoad body Assign NameStore TupleLoad NameLoad NameLoad If Call NameLoad NameLoad NameLoad body Assign TupleStore NameStore NameStore Call NameLoad NameLoad NameLoad Assign NameStore TupleLoad NameLoad NameLoad If CompareEq NameLoad TupleLoad Num Num body Assign NameStore Str If UnaryOpNot BoolOpOr BoolOpAnd Call NameLoad NameLoad NameLoad CompareGtE Call NameLoad NameLoad Num CompareIn NameLoad TupleLoad Str Str Str body Raise Call NameLoad Call AttributeLoad Str attr NameLoad Assign AttributeStore NameLoad attr IfExp NameLoad Call NameLoad NameLoad NameLoad Assign AttributeStore NameLoad attr IfExp NameLoad Call NameLoad NameLoad NameLoad Assign AttributeStore NameLoad attr NameLoad Assign AttributeStore NameLoad attr NameLoad If CompareNotEq Call NameLoad NameLoad Num body Raise Call NameLoad Str Assign AttributeStore NameLoad attr Call NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Expr Str Assign TupleStore NameStore NameStore NameLoad Assign TupleStore NameStore NameLoad Assert CompareEq SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num Assign NameStore BinOpMult BinOpMult SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num Num AugAssignMult NameStore BinOpMult SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num AugAssignMult NameStore BinOpMult BinOpMult SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults Str body Expr Str If UnaryOpNot NameLoad body Raise Call NameLoad Str If UnaryOpNot CompareIn NameLoad TupleLoad Str Str body Raise Call NameLoad Call AttributeLoad Str attr NameLoad Assign NameStore Call NameLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad ListLoad Num Num Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword AttributeLoad NameLoad attr Assign NameStore Call NameLoad NameLoad Assign NameStore Call NameLoad Str For NameStore Call NameLoad SubscriptLoad AttributeLoad NameLoad attr Index Num body For NameStore Call NameLoad SubscriptLoad AttributeLoad NameLoad attr Index Num body For NameStore Call NameLoad SubscriptLoad AttributeLoad NameLoad attr Index Num body AugAssignAdd SubscriptStore NameLoad ExtSlice Index NameLoad Index NameLoad Ellipsis Call NameLoad SubscriptLoad NameLoad ExtSlice Index NameLoad Index NameLoad Ellipsis SubscriptLoad NameLoad ExtSlice Index NameLoad Index NameLoad Ellipsis Num NameLoad NameLoad Num Return NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad Str TupleLoad Num Num NameLoad body Expr Call AttributeLoad Call NameLoad NameLoad NameLoad attr NameLoad NameLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr NameLoad If CompareNotEq AttributeLoad AttributeLoad NameLoad attr attr Num body Raise Call NameLoad Str If CompareNotEq AttributeLoad AttributeLoad NameLoad attr attr Num body Raise Call NameLoad Str Assign NameStore ListLoad SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad NameLoad Assign NameStore Call Call AttributeLoad AttributeLoad NameLoad attr attr keyword NameLoad Return Call NameLoad NameLoad ListLoad NameLoad NameLoad ListLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults body Assign TupleStore NameStore NameStore NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign TupleStore NameStore NameLoad Assign NameStore AttributeLoad NameLoad attr If UnaryOpNot BoolOpOr BoolOpAnd Call NameLoad NameLoad NameLoad CompareGtE Call NameLoad NameLoad Num CompareIn NameLoad TupleLoad Str Str Str body Raise Call NameLoad Call AttributeLoad Str attr NameLoad If CompareEq NameLoad Str body Assign NameStore TupleLoad BinOpSub SubscriptLoad AttributeLoad NameLoad attr Index Num Num BinOpSub SubscriptLoad AttributeLoad NameLoad attr Index Num Num orelse If CompareEq NameLoad Str body Assign NameStore TupleLoad BinOpFloorDiv SubscriptLoad AttributeLoad NameLoad attr Index Num Num BinOpFloorDiv SubscriptLoad AttributeLoad NameLoad attr Index Num Num If Call NameLoad NameLoad NameLoad body Assign TupleStore NameStore NameStore Call NameLoad NameLoad NameLoad Assign NameStore Str Assign NameStore Call AttributeLoad NameLoad attr TupleLoad SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad AttributeLoad NameLoad attr Index Num BinOpAdd SubscriptLoad AttributeLoad NameLoad attr Index Num BinOpMult Num NameLoad BinOpAdd SubscriptLoad AttributeLoad NameLoad attr Index Num BinOpMult Num NameLoad keyword AttributeLoad NameLoad attr Assign SubscriptStore NameLoad ExtSlice Slice Slice Slice NameLoad BinOpAdd SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad Slice NameLoad BinOpAdd SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad NameLoad Assign NameStore NameLoad If UnaryOpNot AttributeLoad NameLoad attr body Assign NameStore SubscriptLoad NameLoad ExtSlice Slice Slice Slice Num Slice Num Assign NameStore Call AttributeLoad NameLoad attr NameLoad NameLoad keyword Str Assign NameStore SubscriptLoad NameLoad ExtSlice Slice Slice Slice SubscriptLoad AttributeLoad NameLoad attr Index Num Slice SubscriptLoad AttributeLoad NameLoad attr Index Num Assign SubscriptStore NameLoad Index Num Call AttributeLoad AttributeLoad SubscriptLoad AttributeLoad NameLoad attr Index Num attr attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign NameStore NameLoad If CompareIsNot SubscriptLoad NameLoad Index Num NameLoad body Assign NameStore SubscriptLoad AttributeLoad Call AttributeLoad NameLoad attr SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num attr Index Num If CompareIsNot SubscriptLoad NameLoad Index Num NameLoad body If CompareIs NameLoad NameLoad body Assign NameStore SubscriptLoad AttributeLoad Call AttributeLoad NameLoad attr SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num attr Index Num orelse AugAssignAdd NameStore SubscriptLoad AttributeLoad Call AttributeLoad NameLoad attr SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num attr Index Num Return ListLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign TupleStore NameStore NameStore NameLoad Assign TupleStore NameStore NameLoad Assign NameStore Call Call NameLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Slice Num Assign NameStore Call Call NameLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Slice Num Assign NameStore Call NameLoad NameLoad AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Assign NameStore Call NameLoad NameLoad AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Return TupleLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign NameStore SubscriptLoad NameLoad Index Num Assign NameStore SubscriptLoad NameLoad Index Num If CompareIsNot AttributeLoad NameLoad attr NameLoad body Assign NameStore ListComp IfExp CompareIs SubscriptLoad AttributeLoad NameLoad attr Index NameLoad NameLoad SubscriptLoad NameLoad Index NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad comprehension NameStore Call NameLoad Num If CompareIsNot AttributeLoad NameLoad attr NameLoad body Assign NameStore ListComp IfExp CompareIs SubscriptLoad AttributeLoad NameLoad attr Index NameLoad NameLoad SubscriptLoad NameLoad Index NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad comprehension NameStore Call NameLoad Num Assign NameStore Call NameLoad NameLoad NameLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr Return ListLoad NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad Str TupleLoad Num Num NameLoad body Expr Call AttributeLoad Call NameLoad NameLoad NameLoad attr NameLoad NameLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults body Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr NameLoad If CompareNotEq AttributeLoad AttributeLoad NameLoad attr attr Num body Raise Call NameLoad Str If CompareNotEq AttributeLoad AttributeLoad NameLoad attr attr Num body Raise Call NameLoad Str Assign NameStore Call NameLoad NameLoad Assign NameStore ListLoad SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad NameLoad Assign NameStore Call Call AttributeLoad AttributeLoad NameLoad attr attr keyword NameLoad Return Call NameLoad NameLoad ListLoad NameLoad NameLoad NameLoad ListLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults body Assign TupleStore NameStore NameStore NameStore NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign TupleStore NameStore NameLoad Assign NameStore AttributeLoad NameLoad attr If UnaryOpNot BoolOpOr BoolOpAnd Call NameLoad NameLoad NameLoad CompareGtE Call NameLoad NameLoad Num CompareIn NameLoad TupleLoad Str Str Str body Raise Call NameLoad Call AttributeLoad Str attr NameLoad If CompareEq NameLoad Str body Assign NameStore TupleLoad BinOpSub SubscriptLoad NameLoad Index Num Num BinOpSub SubscriptLoad NameLoad Index Num Num orelse If CompareEq NameLoad Str body Assign NameStore TupleLoad BinOpFloorDiv SubscriptLoad NameLoad Index Num Num BinOpFloorDiv SubscriptLoad NameLoad Index Num Num If Call NameLoad NameLoad NameLoad body Assign TupleStore NameStore NameStore Call NameLoad NameLoad NameLoad Assign NameStore Str Assign NameStore Call AttributeLoad NameLoad attr TupleLoad SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad AttributeLoad NameLoad attr Index Num BinOpAdd SubscriptLoad AttributeLoad NameLoad attr Index Num BinOpMult Num NameLoad BinOpAdd SubscriptLoad AttributeLoad NameLoad attr Index Num BinOpMult Num NameLoad keyword AttributeLoad NameLoad attr Assign SubscriptStore NameLoad ExtSlice Slice Slice Slice NameLoad BinOpAdd SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad Slice NameLoad BinOpAdd SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad NameLoad Assign NameStore NameLoad If BoolOpOr CompareGt SubscriptLoad AttributeLoad NameLoad attr Index Num Num CompareGt SubscriptLoad AttributeLoad NameLoad attr Index Num Num body Assign NameStore TupleLoad SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad AttributeLoad NameLoad attr Index Num BinOpAdd BinOpSub SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad NameLoad Index Num Num BinOpAdd BinOpSub SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad NameLoad Index Num Num Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword AttributeLoad NameLoad attr Assign SubscriptStore NameLoad ExtSlice Slice Slice Slice SubscriptLoad AttributeLoad NameLoad attr Index Num Slice SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad Assign NameStore NameLoad Assign NameStore SubscriptLoad Call AttributeLoad NameLoad attr Num Num Num Num ExtSlice Slice Slice Slice Num Slice Num Assign NameStore Call AttributeLoad NameLoad attr Num Num Num Num Assign NameStore Call AttributeLoad NameLoad attr NameLoad NameLoad keyword Str If AttributeLoad NameLoad attr body Assign NameStore SubscriptLoad Call AttributeLoad NameLoad attr Num Num Num Num ExtSlice Slice Slice Slice Num Slice Num orelse Assign NameStore Call AttributeLoad NameLoad attr Num Num Num Num Assign SubscriptStore NameLoad Index Num Call AttributeLoad AttributeLoad SubscriptLoad AttributeLoad NameLoad attr Index Num attr attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign TupleStore NameStore NameStore SubscriptLoad NameLoad Slice Num Assign TupleStore NameStore NameLoad Assign NameStore Call Call NameLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Slice Num Assign NameStore Call Call NameLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad NameLoad Assign NameStore Call NameLoad NameLoad AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Assign NameStore Call NameLoad NameLoad AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Assign NameStore TupleLoad Call Call AttributeLoad AttributeLoad NameLoad attr attr Return BinOpAdd TupleLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Return ListLoad ListLoad Num ListLoad Num ListLoad Num decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign NameStore SubscriptLoad NameLoad Index Num Assign NameStore SubscriptLoad NameLoad Index Num Assign NameStore IfExp CompareIsNot AttributeLoad NameLoad attr NameLoad SubscriptLoad AttributeLoad NameLoad attr Slice BinOpMult ListLoad NameLoad Num Assign NameStore ListLoad SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num SubscriptLoad SubscriptLoad AttributeLoad NameLoad attr Index Num Index Num SubscriptLoad SubscriptLoad AttributeLoad NameLoad attr Index Num Index Num Assign NameStore ListComp IfExp CompareIs SubscriptLoad NameLoad Index NameLoad NameLoad SubscriptLoad NameLoad Index NameLoad SubscriptLoad NameLoad Index NameLoad comprehension NameStore Call NameLoad Num Return ListLoad NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad Str TupleLoad Num Num NameLoad body Expr Call AttributeLoad Call NameLoad NameLoad NameLoad attr NameLoad NameLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults body Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr NameLoad If CompareNotEq AttributeLoad AttributeLoad NameLoad attr attr Num body Raise Call NameLoad Str If CompareNotEq AttributeLoad AttributeLoad NameLoad attr attr Num body Raise Call NameLoad Str Assign NameStore Call NameLoad NameLoad Assign NameStore ListLoad SubscriptLoad AttributeLoad AttributeLoad NameLoad attr attr Index Num SubscriptLoad AttributeLoad AttributeLoad NameLoad attr attr Index Num NameLoad NameLoad Assign NameStore Call Call AttributeLoad AttributeLoad NameLoad attr attr keyword NameLoad Return Call NameLoad NameLoad ListLoad NameLoad NameLoad NameLoad ListLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults body Assign TupleStore NameStore NameStore NameStore NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign TupleStore NameStore NameLoad Assign NameStore AttributeLoad NameLoad attr If UnaryOpNot BoolOpOr BoolOpAnd Call NameLoad NameLoad NameLoad CompareGtE Call NameLoad NameLoad Num CompareIn NameLoad TupleLoad Str Str Str body Raise Call NameLoad Call AttributeLoad Str attr NameLoad Assign TupleStore NameStore NameStore TupleLoad Num Num If CompareEq NameLoad Str body Assign TupleStore NameStore NameStore TupleLoad BinOpSub SubscriptLoad AttributeLoad NameLoad attr Index Num Num BinOpSub SubscriptLoad AttributeLoad NameLoad attr Index Num Num orelse If CompareEq NameLoad Str body Assign TupleStore NameStore NameStore TupleLoad BinOpFloorDiv SubscriptLoad AttributeLoad NameLoad attr Index Num Num BinOpFloorDiv SubscriptLoad AttributeLoad NameLoad attr Index Num Num orelse If Call NameLoad NameLoad NameLoad body Assign TupleStore NameStore NameStore Call NameLoad NameLoad AttributeLoad NameLoad attr If BoolOpOr CompareGt SubscriptLoad AttributeLoad NameLoad attr Index Num Num CompareGt SubscriptLoad AttributeLoad NameLoad attr Index Num Num body Assign NameStore TupleLoad SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad AttributeLoad NameLoad attr Index Num BinOpAdd BinOpSub BinOpAdd SubscriptLoad NameLoad Index Num BinOpMult Num NameLoad SubscriptLoad AttributeLoad NameLoad attr Index Num Num BinOpAdd BinOpSub BinOpAdd SubscriptLoad NameLoad Index Num BinOpMult Num NameLoad SubscriptLoad AttributeLoad NameLoad attr Index Num Num Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword AttributeLoad NameLoad attr Assign SubscriptStore NameLoad ExtSlice Slice Slice Slice SubscriptLoad AttributeLoad NameLoad attr Index Num Slice SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad Assign NameStore NameLoad Assign NameStore Call AttributeLoad NameLoad attr Num Num Num Num If AttributeLoad NameLoad attr body Assign NameStore SubscriptLoad NameLoad ExtSlice Slice Slice Slice Num Slice Num Assign NameStore Call AttributeLoad NameLoad attr NameLoad NameLoad keyword Str If AttributeLoad NameLoad attr body Assign NameStore SubscriptLoad NameLoad ExtSlice Slice Slice Slice Num Slice Num If BoolOpOr CompareGt NameLoad Num CompareGt NameLoad Num body Assign NameStore SubscriptLoad NameLoad ExtSlice Slice Slice Slice NameLoad BinOpSub SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad Slice NameLoad BinOpSub SubscriptLoad AttributeLoad NameLoad attr Index Num NameLoad Assign SubscriptStore NameLoad Index Num Call AttributeLoad AttributeLoad SubscriptLoad AttributeLoad NameLoad attr Index Num attr attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign TupleStore NameStore NameStore SubscriptLoad NameLoad Slice Num Assign TupleStore NameStore NameLoad Assign NameStore Call Call NameLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Slice Num Assign NameStore Call Call NameLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad NameLoad Assign NameStore Call NameLoad NameLoad AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Assign NameStore Call NameLoad NameLoad AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Assign NameStore TupleLoad Call Call AttributeLoad AttributeLoad NameLoad attr attr Return BinOpAdd TupleLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Return ListLoad ListLoad Num ListLoad Num ListLoad Num decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign NameStore SubscriptLoad NameLoad Index Num Assign NameStore SubscriptLoad NameLoad Index Num Assign NameStore IfExp CompareIsNot AttributeLoad NameLoad attr NameLoad SubscriptLoad AttributeLoad NameLoad attr Slice BinOpMult ListLoad NameLoad Num Assign NameStore ListLoad SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num SubscriptLoad SubscriptLoad AttributeLoad NameLoad attr Index Num Index Num SubscriptLoad SubscriptLoad AttributeLoad NameLoad attr Index Num Index Num Assign NameStore ListComp IfExp CompareIs SubscriptLoad NameLoad Index NameLoad NameLoad SubscriptLoad NameLoad Index NameLoad SubscriptLoad NameLoad Index NameLoad comprehension NameStore Call NameLoad Num Return ListLoad NameLoad decorator_list decorator_list
N/A N/A 
Abstract conv interface
 N/A logging N/A theano theano.tensor as_tensor_variable patternbroadcast theano.gof Apply Op six.moves xrange N/A numpy N/A N/A scipy.signal.signaltools _valfrommode _bvalfromboundary scipy.signal.sigtools _convolve2d N/A imported_scipy_signal True N/A N/A N/A ImportError N/A N/A imported_scipy_signal False N/A __docformat__ restructuredtext en N/A _logger N/A N/A logging getLogger theano.tensor.nnet.abstract_conv get_conv_output_shape N/A N/A image_shape kernel_shape border_mode subsample N/A N/A N/A 
    This function compute the output shape of convolution operation.

    Parameters
    ----------
    image_shape: tuple of int (symbolic or numeric) corresponding to the input
        image shape. Its four (or five) element must correspond respectively
        to: batch size, number of input channels, height and width (and
        possibly depth) of the image. None where undefined.
    kernel_shape: tuple of int (symbolic or numeric) corresponding to the
        kernel shape. Its four (or five) elements must correspond respectively
        to: number of output channels, number of input channels, height and
        width (and possibly depth) of the kernel. None where undefined.
    border_mode: string, int (symbolic or numeric) or tuple of int (symbolic
        or numeric). If it is a string, it must be 'valid', 'half' or 'full'.
        If it is a tuple, its two (or three) elements respectively correspond
        to the padding on height and width (and possibly depth) axis.
    subsample: tuple of int (symbolic or numeric). Its or three elements
        espectively correspond to the subsampling on height and width (and
        possibly depth) axis.

    Returns
    -------
    output_shape: tuple of int corresponding to the output image shape. Its
        four element must correspond respectively to: batch size, number of
        output channels, height and width of the image. None where undefined.

     N/A N/A bsize imshp N/A N/A image_shape N/A 0 N/A image_shape N/A 2 N/A N/A nkern kshp N/A N/A kernel_shape N/A 0 N/A kernel_shape N/A 2 N/A N/A isinstance border_mode tuple N/A N/A out_shp N/A tuple N/A N/A get_conv_shape_1axis N/A imshp N/A i N/A kshp N/A i N/A border_mode N/A i N/A subsample N/A i N/A i N/A range N/A len subsample N/A N/A out_shp N/A tuple N/A N/A get_conv_shape_1axis N/A imshp N/A i N/A kshp N/A i border_mode N/A subsample N/A i N/A i N/A range N/A len subsample N/A N/A N/A bsize nkern out_shp N/A get_conv_shape_1axis N/A N/A image_shape kernel_shape border_mode subsample N/A N/A N/A 
    This function compute the output shape of convolution operation.

    Parameters
    ----------
    image_shape: int or None. Corresponds to the input image shape on a
        given axis. None if undefined.
    kernel_shape: int or None. Corresponds to the kernel shape on a given
        axis. None if undefined.
    border_mode: string or int. If it is a string, it must be
        'valid', 'half' or 'full'. If it is an integer, it must correspond to
        the padding on the considered axis.
    subsample: int. It must correspond to the subsampling on the
        considered axis.

    Returns
    -------
    out_shp: int corresponding to the output image shape on the
        considered axis. None if undefined.

     N/A N/A None N/A image_shape kernel_shape border_mode subsample N/A N/A None N/A N/A border_mode half N/A N/A pad N/A kernel_shape 2 N/A N/A N/A border_mode full N/A N/A pad N/A kernel_shape 1 N/A N/A N/A border_mode valid N/A N/A pad 0 N/A N/A pad border_mode N/A N/A pad 0 N/A N/A N/A ValueError border_mode must be >= 0 N/A out_shp N/A N/A N/A N/A image_shape N/A 2 pad kernel_shape subsample 1 N/A out_shp N/A conv2d N/A N/A input filters input_shape filter_shape border_mode subsample filter_flip N/A None None valid N/A 1 1 True N/A N/A This function will build the symbolic graph for convolving a mini-batch of a
    stack of 2D inputs with a set of 2D filters. The implementation is modelled
    after Convolutional Neural Networks (CNN).

    Refer to :func:`nnet.conv2d <theano.tensor.nnet.conv2d>` for a more detailed documentation.
     N/A conv_op N/A AbstractConv2d imshp input_shape kshp filter_shape border_mode border_mode subsample subsample filter_flip filter_flip N/A N/A conv_op input filters N/A conv2d_grad_wrt_inputs N/A N/A output_grad filters output_grad_shape input_shape filter_shape border_mode subsample filter_flip N/A None None None valid N/A 1 1 True N/A N/A This function builds the symbolic graph for getting the
    gradient of the output of a convolution (namely output_grad)
    w.r.t the input of the convolution, given a set of 2D filters
    used by the convolution, such that the output_grad is upsampled
    to the input shape.

    Parameters
    ----------
    output_grad : symbolic 4D tensor
        mini-batch of feature map stacks, of shape (batch size, input
        channels, input rows, input columns).  This is the tensor that
        will be upsampled or the output gradient of the convolution
        whose gradient will be taken with respect to the input of the
        convolution.  See the optional parameter
        ``output_grad_shape``.
    filters : symbolic 4D tensor
        set of filters used in CNN layer of shape (output channels,
        input channels, filter rows, filter columns).  See the
        optional parameter ``filter_shape``.
    output_grad_shape : list of 4 symbolic or real ints
        The shape of the output_grad parameter.  Optional, possibly
        used to choose an optimal implementation.  You can give
        ``None`` for any element of the list to specify that this
        element is not known at compile time.
    input_shape : list of 2 symbolic or real ints
        The shape (row and column size) of the input (upsampled)
        parameter.  Not Optional, since given the output_grad_shape
        and the subsample values, multiple input_shape may be
        plausible.
    filter_shape : list of 4 symbolic or real ints
        The shape of the filters parameter.  Optional, possibly used
        to choose an optimal implementation.  You can give ``None``
        for any element of the list to specify that this element is
        not known at compile time.
    border_mode : str, int or tuple of two int
        Either of the following:

          ``'valid'``
            apply filter wherever it completely overlaps with the
            input. Generates output of shape: input shape - filter
            shape + 1

          ``'full'``
            apply filter wherever it partly overlaps with the input.
            Generates output of shape: input shape + filter shape - 1

          ``'half'``
            pad input with a symmetric border of ``filter rows // 2``
            rows and ``filter columns // 2`` columns, then perform a
            valid convolution. For filters with an odd number of rows
            and columns, this leads to the output shape being equal to
            the input shape.

          ``int``
            pad input with a symmetric border of zeros of the given
            width, then perform a valid convolution.

          ``(int1, int2)``
            pad input with a symmetric border of ``int1`` rows and
            ``int2`` columns, then perform a valid convolution.

    subsample : tuple of len 2
        The subsampling used in the forward pass.  Also called strides
        elsewhere.
    filter_flip : bool
        If ``True``, will flip the filter rows and columns before
        sliding them over the input. This operation is normally
        referred to as a convolution, and this is the default. If
        ``False``, the filters are not flipped and the operation is
        referred to as a cross-correlation.

    Returns
    -------
    symbolic 4D tensor
        set of feature maps generated by convolutional layer. Tensor
        is of shape (batch size, output channels, output rows, output
        columns)

    Notes
    -----

    :note: If CuDNN is available, it will be used on the
        GPU. Otherwise, it is the *CorrMM* convolution that will be used
        "caffe style convolution".

    :note: This is only supported in Theano 0.8 or the development
        version until it is released.

     N/A grad_input_op N/A AbstractConv2d_gradInputs imshp input_shape kshp filter_shape border_mode border_mode subsample subsample filter_flip filter_flip N/A N/A grad_input_op filters output_grad input_shape N/A conv2d_grad_wrt_weights N/A N/A input output_grad input_shape output_grad_shape filter_shape border_mode subsample filter_flip N/A None None None valid N/A 1 1 True N/A N/A This function will build the symbolic graph for getting the
    gradient of the output of a convolution (output_grad) w.r.t its wights.

    Parameters
    ----------
    input : symbolic 4D tensor
        mini-batch of feature map stacks, of shape (batch size, input
        channels, input rows, input columns).  This is the input of
        the convolution in the forward pass.
    output_grad : symbolic 4D tensor
        mini-batch of feature map stacks, of shape (batch size, input
        channels, input rows, input columns).  This is the gradient of
        the output of convolution.
    filters : symbolic 4D tensor.
        set of filters used in CNN layer of shape (output channels,
        input channels, filter rows, filter columns).  See the
        optional parameter ``filter_shape``.
    output_grad_shape : list of 4 ints or Constant variables
        The shape of the input parameter.  Optional, possibly used to
        choose an optimal implementation.  You can give ``None`` for
        any element of the list to specify that this element is not
        known at compile time.
    input_shape : list of 2 ints or Constant variables
        The shape of the input parameter.  This parameter indicates
        the row and column size of the input in the forward pass.
        Optional, possibly used to choose an optimal implementation.
        You can give ``None`` for any element of the list to specify
        that this element is not known at compile time.
    filter_shape : list of 4 ints or Constant variables
        The shape of the filters parameter.  Not Optional, since given
        the output_grad_shape and the input_shape, multiple
        filter_shape may be plausible.
    border_mode : str, int or tuple of two ints
        Either of the following:

          ``'valid'``
            apply filter wherever it completely overlaps with the
            input. Generates output of shape: input shape - filter
            shape + 1

          ``'full'``
            apply filter wherever it partly overlaps with the input.
            Generates output of shape: input shape + filter shape - 1

          ``'half'``
            pad input with a symmetric border of ``filter rows // 2``
            rows and ``filter columns // 2`` columns, then perform a
            valid convolution. For filters with an odd number of rows
            and columns, this leads to the output shape being equal to
            the input shape.

          ``int``
            pad input with a symmetric border of zeros of the given
            width, then perform a valid convolution.

          ``(int1, int2)``
            pad input with a symmetric border of ``int1`` rows and
            ``int2`` columns, then perform a valid convolution.

    subsample : tuple of len 2
        The subsampling used in the forward pass of the convolutional
        operation.  Also called strides elsewhere.
    filter_flip : bool
        If ``True``, will flip the filter rows and columns before
        sliding them over the input. This operation is normally
        referred to as a convolution, and this is the default. If
        ``False``, the filters are not flipped and the operation is
        referred to as a cross-correlation.

    Returns
    -------
    symbolic 4D tensor
        set of feature maps generated by convolutional layer. Tensor
        is of shape (batch size, output channels, output rows, output
        columns)

    Notes
    -----

    :note: If CuDNN is available, it will be used on the
        GPU. Otherwise, it is the *CorrMM* convolution that will be used
        "caffe style convolution".

    :note: This is only supported in Theano 0.8 or the development
        version until it is released.

     N/A gradWeight_op N/A AbstractConv2d_gradWeights imshp input_shape kshp filter_shape border_mode border_mode subsample subsample filter_flip filter_flip N/A N/A gradWeight_op input output_grad filter_shape N/A BaseAbstractConv2d N/A Op N/A N/A Base class for AbstractConv

    Define an abstract convolution op that will be replaced with the
    appropriate implementation

    Parameters
    ----------
     imshp: None, tuple/list of len 4 of int or Constant variable
        The shape of the input parameter.
        Optional, possibly used to choose an optimal implementation.
        You can give ``None`` for any element of the list to specify that this
        element is not known at compile time.
        imshp is defined w.r.t the forward conv.

     kshp: None, tuple/list of len 4 of int or Constant variable
        The shape of the filters parameter.
        Optional, possibly used to choose an optimal implementation.
        You can give ``None`` for any element of the list to specify that this
        element is not known at compile time.
        kshp is defined w.r.t the forward conv.

     border_mode: str, int or tuple of two int
        Either of the following:

        ``'valid'``: apply filter wherever it completely overlaps with the
            input. Generates output of shape: input shape - filter shape + 1
        ``'full'``: apply filter wherever it partly overlaps with the input.
            Generates output of shape: input shape + filter shape - 1
        ``'half'``: pad input with a symmetric border of ``filter rows // 2``
            rows and ``filter columns // 2`` columns, then perform a valid
            convolution. For filters with an odd number of rows and columns, this
            leads to the output shape being equal to the input shape.
        ``int``: pad input with a symmetric border of zeros of the given
            width, then perform a valid convolution.
        ``(int1, int2)``: pad input with a symmetric border of ``int1`` rows
            and ``int2`` columns, then perform a valid convolution.

    subsample: tuple of len 2
        Factor by which to subsample the output.
        Also called strides elsewhere.

    filter_flip: bool
        If ``True``, will flip the filter rows and columns
        before sliding them over the input. This operation is normally referred
        to as a convolution, and this is the default. If ``False``, the filters
        are not flipped and the operation is referred to as a
        cross-correlation.

     N/A check_broadcast False N/A __props__ N/A border_mode subsample filter_flip imshp kshp __init__ N/A N/A self imshp kshp border_mode subsample filter_flip N/A None None valid N/A 1 1 True N/A N/A N/A isinstance border_mode int N/A N/A border_mode N/A border_mode border_mode N/A N/A isinstance border_mode tuple N/A N/A N/A pad_h pad_w N/A map int border_mode N/A border_mode N/A pad_h pad_w N/A N/A border_mode N/A 0 0 N/A N/A border_mode valid N/A N/A N/A N/A N/A isinstance border_mode tuple N/A N/A min border_mode 0 N/A border_mode N/A valid full half N/A N/A N/A ValueError N/A N/A invalid border_mode {}, which must be either "valid", "full", "half", an integer or a pair of integers format border_mode N/A N/A self imshp N/A imshp N/A tuple imshp None N/A N/A self kshp N/A kshp N/A tuple kshp None N/A N/A self border_mode border_mode N/A N/A self filter_flip filter_flip N/A N/A N/A len subsample 2 N/A N/A N/A ValueError subsample must have two elements N/A N/A self subsample N/A tuple subsample N/A flops N/A N/A self inp outp N/A N/A N/A  Useful with the hack in profilemode to print the MFlops N/A N/A inputs filters inp N/A N/A outputs outp N/A N/A N/A inputs N/A 1 N/A filters N/A 1 N/A flops N/A N/A N/A filters N/A 2 N/A filters N/A 3 2 N/A flops N/A N/A outputs N/A 2 N/A outputs N/A 3 N/A flops N/A N/A N/A inputs N/A 1 N/A filters N/A 0 N/A inputs N/A 0 N/A flops N/A do_constant_folding N/A N/A self node N/A N/A N/A False N/A conv2d N/A N/A self img kern mode N/A valid N/A N/A 
        Basic slow python implementatation for DebugMode
         N/A N/A imported_scipy_signal N/A N/A N/A NotImplementedError AbstractConv perform requires the python package for scipy.signal to be installed. N/A N/A N/A mode N/A valid full N/A N/A N/A ValueError N/A N/A invalid mode {}, which must be either "valid" or "full" format mode N/A out_shape N/A get_conv_output_shape N/A img shape N/A kern shape mode N/A 1 1 N/A out N/A N/A numpy zeros out_shape dtype N/A img dtype N/A val N/A _valfrommode mode N/A bval N/A _bvalfromboundary fill N/A b N/A xrange N/A N/A img shape N/A 0 N/A N/A n N/A xrange N/A N/A kern shape N/A 0 N/A N/A im0 N/A xrange N/A N/A img shape N/A 1 N/A N/A N/A out N/A N/A b N/A n N/A N/A _convolve2d N/A img N/A N/A b N/A im0 N/A N/A kern N/A N/A n N/A im0 N/A 1 val bval 0 N/A out N/A N/A AbstractConv2d N/A BaseAbstractConv2d N/A N/A  Abstract Op for the forward convolution.
    Refer to :func:`BaseAbstractConv2d <theano.tensor.nnet.abstract_conv.BaseAbstractConv2d>`
    for a more detailed documentation.
     __init__ N/A N/A self imshp kshp border_mode subsample filter_flip N/A None None valid N/A 1 1 True N/A N/A N/A N/A N/A super AbstractConv2d self __init__ imshp kshp border_mode subsample filter_flip N/A make_node N/A N/A self img kern N/A N/A N/A ktype N/A N/A N/A img type clone dtype N/A kern dtype broadcastable N/A kern broadcastable N/A kern N/A N/A ktype filter_variable kern N/A N/A N/A N/A img type ndim 4 N/A N/A N/A TypeError img must be 4D tensor N/A N/A N/A N/A kern type ndim 4 N/A N/A N/A TypeError kern must be 4D tensor N/A broadcastable N/A N/A N/A img broadcastable N/A 0 N/A N/A kern broadcastable N/A 0 False False N/A output N/A N/A N/A N/A img type clone broadcastable broadcastable N/A N/A Apply self N/A img kern N/A output N/A perform N/A N/A self node inp out_ N/A N/A N/A N/A img kern inp N/A img N/A N/A numpy asarray img N/A kern N/A N/A numpy asarray kern N/A N/A o out_ N/A mode N/A self border_mode N/A N/A N/A N/A N/A isinstance mode tuple N/A N/A min mode 0 N/A mode N/A valid full half N/A N/A N/A ValueError N/A N/A invalid border_mode {}, which must be either "valid", "full", "half", an integer or a pair of integers format mode N/A N/A mode full N/A N/A mode N/A N/A N/A N/A kern shape N/A 2 1 N/A N/A N/A kern shape N/A 3 1 N/A N/A N/A mode half N/A N/A mode N/A N/A N/A N/A kern shape N/A 2 2 N/A N/A N/A kern shape N/A 3 2 N/A N/A isinstance mode tuple N/A N/A N/A pad_h pad_w N/A map int mode N/A mode valid N/A new_img N/A N/A numpy zeros N/A N/A N/A img shape N/A 0 N/A N/A img shape N/A 1 N/A N/A N/A img shape N/A 2 N/A 2 pad_h N/A N/A N/A img shape N/A 3 N/A 2 pad_w dtype N/A img dtype N/A N/A new_img N/A N/A N/A N/A pad_h N/A N/A N/A img shape N/A 2 pad_h N/A pad_w N/A N/A N/A img shape N/A 3 pad_w img N/A img new_img N/A N/A N/A self filter_flip N/A N/A kern N/A kern N/A N/A N/A N/A -1 N/A -1 N/A conv_out N/A N/A self conv2d img kern mode valid N/A conv_out N/A conv_out N/A N/A N/A N/A N/A N/A self subsample N/A 0 N/A N/A N/A self subsample N/A 1 N/A N/A o N/A 0 N/A N/A N/A N/A N/A node outputs N/A 0 type filter conv_out N/A R_op N/A N/A self inputs eval_points N/A N/A N/A rval None N/A N/A N/A eval_points N/A 0 None N/A N/A rval N/A N/A N/A N/A self make_node N/A eval_points N/A 0 N/A inputs N/A 1 outputs N/A 0 N/A N/A N/A eval_points N/A 1 None N/A N/A N/A rval None N/A N/A rval N/A N/A N/A N/A self make_node N/A inputs N/A 0 N/A eval_points N/A 1 outputs N/A 0 N/A N/A rval N/A N/A N/A N/A self make_node N/A inputs N/A 0 N/A eval_points N/A 1 outputs N/A 0 N/A N/A rval N/A grad N/A N/A self inp grads N/A N/A N/A N/A bottom weights inp N/A N/A top grads N/A d_bottom N/A N/A AbstractConv2d_gradInputs N/A self imshp N/A self kshp N/A self border_mode N/A self subsample N/A self filter_flip weights top N/A N/A bottom shape N/A -2 N/A d_weights N/A N/A AbstractConv2d_gradWeights N/A self imshp N/A self kshp N/A self border_mode N/A self subsample N/A self filter_flip bottom top N/A N/A weights shape N/A -2 N/A d_bottom N/A patternbroadcast d_bottom N/A bottom broadcastable N/A d_bottom N/A N/A N/A bottom type filter_variable d_bottom N/A d_weights N/A patternbroadcast d_weights N/A weights broadcastable N/A d_weights N/A N/A N/A weights type filter_variable d_weights N/A N/A d_bottom d_weights N/A infer_shape N/A N/A self node input_shapes N/A N/A N/A imshp N/A input_shapes N/A 0 N/A kshp N/A input_shapes N/A 1 N/A N/A N/A self imshp None N/A N/A imshp N/A N/A N/A N/A N/A self imshp N/A i None N/A imshp N/A i N/A N/A self imshp N/A i N/A i N/A range 4 N/A N/A N/A self kshp None N/A N/A kshp N/A N/A N/A N/A N/A self kshp N/A i None N/A kshp N/A i N/A N/A self kshp N/A i N/A i N/A range 4 N/A res N/A get_conv_output_shape imshp kshp N/A self border_mode N/A self subsample N/A N/A res N/A N/A AbstractConv2d_gradWeights N/A BaseAbstractConv2d N/A N/A Gradient wrt. filters for `AbstractConv2d`.
    Refer to :func:`BaseAbstractConv2d <theano.tensor.nnet.abstract_conv.BaseAbstractConv2d>`
    for a more detailed documentation.

    :note: You will not want to use this directly, but rely on
           Theano's automatic differentiation or graph optimization to
           use it as needed.

     __init__ N/A N/A self imshp kshp border_mode subsample filter_flip N/A None None valid N/A 1 1 True N/A N/A N/A N/A N/A super AbstractConv2d_gradWeights self __init__ imshp kshp border_mode subsample filter_flip N/A make_node N/A N/A self img topgrad shape N/A N/A N/A gtype N/A N/A N/A img type clone dtype N/A topgrad dtype broadcastable N/A topgrad broadcastable N/A topgrad N/A N/A gtype filter_variable topgrad N/A N/A N/A N/A img type ndim 4 N/A N/A N/A TypeError img must be 4D tensor N/A N/A N/A N/A topgrad type ndim 4 N/A N/A N/A TypeError topgrad must be 4D tensor N/A shape N/A as_tensor_variable shape N/A broadcastable N/A N/A N/A topgrad broadcastable N/A 1 N/A N/A img broadcastable N/A 1 False False N/A output N/A N/A N/A N/A img type clone broadcastable broadcastable N/A N/A Apply self N/A img topgrad shape N/A output N/A perform N/A N/A self node inp out_ N/A N/A N/A N/A img topgrad shape inp N/A img N/A N/A numpy asarray img N/A topgrad N/A N/A numpy asarray topgrad N/A N/A o out_ N/A mode N/A self border_mode N/A N/A N/A N/A N/A isinstance mode tuple N/A N/A min mode 0 N/A mode N/A valid full half N/A N/A N/A ValueError N/A N/A invalid border_mode {}, which must be either "valid", "full", "half", an integer or a pair of integers format mode N/A N/A mode full N/A N/A mode N/A N/A N/A shape N/A 0 1 N/A N/A shape N/A 1 1 N/A N/A N/A mode half N/A N/A mode N/A N/A N/A shape N/A 0 2 N/A N/A shape N/A 1 2 N/A N/A isinstance mode tuple N/A N/A N/A pad_h pad_w N/A map int mode N/A mode valid N/A new_img N/A N/A numpy zeros N/A N/A N/A img shape N/A 0 N/A N/A img shape N/A 1 N/A N/A N/A img shape N/A 2 N/A 2 pad_h N/A N/A N/A img shape N/A 3 N/A 2 pad_w dtype N/A img dtype N/A N/A new_img N/A N/A N/A N/A pad_h N/A N/A N/A img shape N/A 2 pad_h N/A pad_w N/A N/A N/A img shape N/A 3 pad_w img N/A img new_img N/A N/A N/A N/A N/A self subsample N/A 0 1 N/A N/A N/A self subsample N/A 1 1 N/A N/A new_shape N/A N/A N/A topgrad shape N/A 0 N/A N/A topgrad shape N/A 1 N/A N/A N/A N/A img shape N/A 2 N/A shape N/A 0 1 N/A N/A N/A N/A img shape N/A 3 N/A shape N/A 1 1 N/A new_topgrad N/A N/A numpy zeros new_shape dtype N/A topgrad dtype N/A N/A new_topgrad N/A N/A N/A N/A N/A N/A self subsample N/A 0 N/A N/A N/A self subsample N/A 1 topgrad N/A topgrad new_topgrad N/A topgrad N/A N/A N/A topgrad transpose 1 0 2 3 N/A N/A N/A N/A -1 N/A -1 N/A img N/A N/A img transpose 1 0 2 3 N/A kern N/A N/A self conv2d img topgrad mode valid N/A N/A self filter_flip N/A N/A kern N/A N/A N/A kern transpose 1 0 2 3 N/A N/A N/A N/A -1 N/A -1 N/A N/A kern N/A N/A kern transpose 1 0 2 3 N/A N/A o N/A 0 N/A N/A N/A N/A N/A node outputs N/A 0 type filter kern N/A grad N/A N/A self inp grads N/A N/A N/A N/A bottom top N/A inp N/A 2 N/A N/A weights grads N/A d_bottom N/A N/A AbstractConv2d_gradInputs N/A self imshp N/A self kshp N/A self border_mode N/A self subsample N/A self filter_flip weights top N/A N/A bottom shape N/A -2 N/A d_top N/A N/A AbstractConv2d N/A self imshp N/A self kshp N/A self border_mode N/A self subsample N/A self filter_flip bottom weights N/A d_bottom N/A patternbroadcast d_bottom N/A bottom broadcastable N/A d_bottom N/A N/A N/A bottom type filter_variable d_bottom N/A d_top N/A patternbroadcast d_top N/A top broadcastable N/A d_top N/A N/A N/A top type filter_variable d_top N/A d_height_width N/A N/A N/A N/A N/A theano gradient DisconnectedType N/A N/A N/A d_bottom d_top d_height_width N/A connection_pattern N/A N/A self node N/A N/A N/A N/A N/A 1 N/A 1 N/A 0 N/A infer_shape N/A N/A self node input_shapes N/A N/A N/A imshp N/A input_shapes N/A 0 N/A topshp N/A input_shapes N/A 1 N/A kshp N/A N/A N/A self kshp None N/A N/A self kshp N/A N/A N/A None 4 N/A fallback_kshp N/A N/A topshp N/A 1 N/A imshp N/A 1 N/A N/A N/A node inputs N/A 2 N/A 0 N/A N/A N/A node inputs N/A 2 N/A 1 N/A kshp N/A N/A N/A N/A kshp N/A i None N/A fallback_kshp N/A i N/A kshp N/A i N/A i N/A range 4 N/A N/A kshp N/A N/A AbstractConv2d_gradInputs N/A BaseAbstractConv2d N/A N/A Gradient wrt. inputs for `AbstractConv2d`.
    Refer to :func:`BaseAbstractConv2d <theano.tensor.nnet.abstract_conv.BaseAbstractConv2d>`
    for a more detailed documentation.

    :note: You will not want to use this directly, but rely on
           Theano's automatic differentiation or graph optimization to
           use it as needed.

     __init__ N/A N/A self imshp kshp border_mode subsample filter_flip N/A None None valid N/A 1 1 True N/A N/A N/A N/A N/A super AbstractConv2d_gradInputs self __init__ imshp kshp border_mode subsample filter_flip N/A make_node N/A N/A self kern topgrad shape N/A N/A N/A gtype N/A N/A N/A kern type clone dtype N/A topgrad dtype broadcastable N/A topgrad broadcastable N/A topgrad N/A N/A gtype filter_variable topgrad N/A N/A N/A N/A kern type ndim 4 N/A N/A N/A TypeError kern must be 4D tensor N/A N/A N/A N/A topgrad type ndim 4 N/A N/A N/A TypeError topgrad must be 4D tensor N/A shape N/A as_tensor_variable shape N/A broadcastable N/A N/A N/A N/A topgrad type broadcastable N/A 0 N/A N/A N/A kern type broadcastable N/A 1 False False N/A output N/A N/A N/A N/A kern type clone broadcastable broadcastable N/A N/A Apply self N/A kern topgrad shape N/A output N/A perform N/A N/A self node inp out_ N/A N/A N/A N/A kern topgrad shape inp N/A kern N/A N/A numpy asarray kern N/A topgrad N/A N/A numpy asarray topgrad N/A N/A o out_ N/A mode N/A self border_mode N/A N/A N/A N/A N/A isinstance mode tuple N/A N/A min mode 0 N/A mode N/A valid full half N/A N/A N/A ValueError N/A N/A invalid border_mode {}, which must be either "valid", "full", "half", an integer or a pair of integers format mode N/A N/A pad_h pad_w N/A 0 0 N/A N/A mode full N/A N/A N/A pad_h pad_w N/A N/A N/A N/A kern shape N/A 2 1 N/A N/A N/A kern shape N/A 3 1 N/A N/A N/A mode half N/A N/A N/A pad_h pad_w N/A N/A N/A N/A kern shape N/A 2 2 N/A N/A N/A kern shape N/A 3 2 N/A N/A N/A isinstance mode tuple N/A N/A N/A pad_h pad_w N/A map int N/A self border_mode N/A N/A N/A N/A N/A self subsample N/A 0 1 N/A N/A N/A self subsample N/A 1 1 N/A N/A new_shape N/A N/A N/A topgrad shape N/A 0 N/A N/A topgrad shape N/A 1 N/A N/A N/A N/A shape N/A 0 N/A 2 pad_h N/A N/A kern shape N/A 2 1 N/A N/A N/A N/A shape N/A 1 N/A 2 pad_w N/A N/A kern shape N/A 3 1 N/A new_topgrad N/A N/A numpy zeros new_shape dtype N/A topgrad dtype N/A N/A new_topgrad N/A N/A N/A N/A N/A N/A self subsample N/A 0 N/A N/A N/A self subsample N/A 1 topgrad N/A topgrad new_topgrad N/A kern N/A N/A kern transpose 1 0 2 3 N/A N/A self filter_flip N/A N/A topgrad N/A topgrad N/A N/A N/A N/A -1 N/A -1 N/A img N/A N/A self conv2d topgrad kern mode full N/A N/A self filter_flip N/A N/A img N/A img N/A N/A N/A N/A -1 N/A -1 N/A N/A N/A pad_h 0 N/A pad_w 0 N/A N/A img N/A img N/A N/A N/A N/A pad_h N/A N/A N/A img shape N/A 2 pad_h N/A pad_w N/A N/A N/A img shape N/A 3 pad_w N/A N/A o N/A 0 N/A N/A N/A N/A N/A node outputs N/A 0 type filter img N/A grad N/A N/A self inp grads N/A N/A N/A N/A weights top N/A inp N/A 2 N/A N/A bottom grads N/A d_weights N/A N/A AbstractConv2d_gradWeights N/A self imshp N/A self kshp N/A self border_mode N/A self subsample bottom top N/A N/A weights shape N/A -2 N/A d_top N/A N/A AbstractConv2d N/A self imshp N/A self kshp N/A self border_mode N/A self subsample bottom weights N/A d_weights N/A patternbroadcast d_weights N/A weights broadcastable N/A d_weights N/A N/A N/A weights type filter_variable d_weights N/A d_top N/A patternbroadcast d_top N/A top broadcastable N/A d_top N/A N/A N/A top type filter_variable d_top N/A d_height_width N/A N/A N/A N/A N/A theano gradient DisconnectedType N/A N/A N/A d_weights d_top d_height_width N/A connection_pattern N/A N/A self node N/A N/A N/A N/A N/A 1 N/A 1 N/A 0 N/A infer_shape N/A N/A self node input_shapes N/A N/A N/A kshp N/A input_shapes N/A 0 N/A topshp N/A input_shapes N/A 1 N/A imshp N/A N/A N/A self imshp None N/A N/A self imshp N/A N/A N/A None 4 N/A fallback_imshp N/A N/A topshp N/A 0 N/A kshp N/A 1 N/A N/A N/A node inputs N/A 2 N/A 0 N/A N/A N/A node inputs N/A 2 N/A 1 N/A imshp N/A N/A N/A N/A imshp N/A i None N/A fallback_imshp N/A i N/A imshp N/A i N/A i N/A range 4 N/A N/A imshp N/A N/A