def lstm_block_cell_eager_fallback(x, cs_prev, h_prev, w, wci, wcf, wco, b, forget_bias=1, cell_clip=3, use_peephole=False, name=None, ctx=None):
    'This is the slowpath function for Eager mode.\n  This is for function lstm_block_cell\n  '
    _ctx = (ctx if ctx else _context.context())
    if (forget_bias is None):
        forget_bias = 1
    forget_bias = _execute.make_float(forget_bias, 'forget_bias')
    if (cell_clip is None):
        cell_clip = 3
    cell_clip = _execute.make_float(cell_clip, 'cell_clip')
    if (use_peephole is None):
        use_peephole = False
    use_peephole = _execute.make_bool(use_peephole, 'use_peephole')
    (_attr_T, _inputs_T) = _execute.args_to_matching_eager([x, cs_prev, h_prev, w, wci, wcf, wco, b], _ctx)
    (x, cs_prev, h_prev, w, wci, wcf, wco, b) = _inputs_T
    _inputs_flat = [x, cs_prev, h_prev, w, wci, wcf, wco, b]
    _attrs = ('forget_bias', forget_bias, 'cell_clip', cell_clip, 'use_peephole', use_peephole, 'T', _attr_T)
    _result = _execute.execute(b'LSTMBlockCell', 7, inputs=_inputs_flat, attrs=_attrs, ctx=_ctx, name=name)
    _execute.record_gradient('LSTMBlockCell', _inputs_flat, _attrs, _result, name)
    _result = _LSTMBlockCellOutput._make(_result)
    return _result
This is the slowpath function for Eager mode.
This is for function lstm_block_cell
def lstm_block_cell_eager_fallback(x, cs_prev, h_prev, w, wci, wcf, wco, b, forget_bias=1, cell_clip=3, use_peephole=False, name=None, ctx=None):
    'This is the slowpath function for Eager mode.\n  This is for function lstm_block_cell\n  '
    _ctx = (ctx if ctx else _context.context())
    if (forget_bias is None):
        forget_bias = 1
    forget_bias = _execute.make_float(forget_bias, 'forget_bias')
    if (cell_clip is None):
        cell_clip = 3
    cell_clip = _execute.make_float(cell_clip, 'cell_clip')
    if (use_peephole is None):
        use_peephole = False
    use_peephole = _execute.make_bool(use_peephole, 'use_peephole')
    (_attr_T, _inputs_T) = _execute.args_to_matching_eager([x, cs_prev, h_prev, w, wci, wcf, wco, b], _ctx)
    (x, cs_prev, h_prev, w, wci, wcf, wco, b) = _inputs_T
    _inputs_flat = [x, cs_prev, h_prev, w, wci, wcf, wco, b]
    _attrs = ('forget_bias', forget_bias, 'cell_clip', cell_clip, 'use_peephole', use_peephole, 'T', _attr_T)
    _result = _execute.execute(b'LSTMBlockCell', 7, inputs=_inputs_flat, attrs=_attrs, ctx=_ctx, name=name)
    _execute.record_gradient('LSTMBlockCell', _inputs_flat, _attrs, _result, name)
    _result = _LSTMBlockCellOutput._make(_result)
    return _result