def debug_numeric_summary_eager_fallback(input, device_name='', tensor_name='', debug_urls=[], lower_bound=float('-inf'), upper_bound=float('inf'), mute_if_healthy=False, gated_grpc=False, name=None):
    'This is the slowpath function for Eager mode.\n  This is for function debug_numeric_summary\n  '
    _ctx = _context.context()
    if (device_name is None):
        device_name = ''
    device_name = _execute.make_str(device_name, 'device_name')
    if (tensor_name is None):
        tensor_name = ''
    tensor_name = _execute.make_str(tensor_name, 'tensor_name')
    if (debug_urls is None):
        debug_urls = []
    if (not isinstance(debug_urls, (list, tuple))):
        raise TypeError(("Expected list for 'debug_urls' argument to 'debug_numeric_summary' Op, not %r." % debug_urls))
    debug_urls = [_execute.make_str(_s, 'debug_urls') for _s in debug_urls]
    if (lower_bound is None):
        lower_bound = float('-inf')
    lower_bound = _execute.make_float(lower_bound, 'lower_bound')
    if (upper_bound is None):
        upper_bound = float('inf')
    upper_bound = _execute.make_float(upper_bound, 'upper_bound')
    if (mute_if_healthy is None):
        mute_if_healthy = False
    mute_if_healthy = _execute.make_bool(mute_if_healthy, 'mute_if_healthy')
    if (gated_grpc is None):
        gated_grpc = False
    gated_grpc = _execute.make_bool(gated_grpc, 'gated_grpc')
    (_attr_T, (input,)) = _execute.args_to_matching_eager([input], _ctx)
    _inputs_flat = [input]
    _attrs = ('T', _attr_T, 'device_name', device_name, 'tensor_name', tensor_name, 'debug_urls', debug_urls, 'lower_bound', lower_bound, 'upper_bound', upper_bound, 'mute_if_healthy', mute_if_healthy, 'gated_grpc', gated_grpc)
    _result = _execute.execute(b'DebugNumericSummary', 1, inputs=_inputs_flat, attrs=_attrs, ctx=_ctx, name=name)
    _execute.record_gradient('DebugNumericSummary', _inputs_flat, _attrs, _result, name)
    (_result,) = _result
    return _result
This is the slowpath function for Eager mode.
This is for function debug_numeric_summary
def debug_numeric_summary_eager_fallback(input, device_name=, tensor_name=, debug_urls=[], lower_bound=float('-inf'), upper_bound=float('inf'), mute_if_healthy=False, gated_grpc=False, name=None):
    'This is the slowpath function for Eager mode.\n  This is for function debug_numeric_summary\n  '
    _ctx = _context.context()
    if (device_name is None):
        device_name = 
    device_name = _execute.make_str(device_name, 'device_name')
    if (tensor_name is None):
        tensor_name = 
    tensor_name = _execute.make_str(tensor_name, 'tensor_name')
    if (debug_urls is None):
        debug_urls = []
    if (not isinstance(debug_urls, (list, tuple))):
        raise TypeError(("Expected list for 'debug_urls' argument to 'debug_numeric_summary' Op, not %r." % debug_urls))
    debug_urls = [_execute.make_str(_s, 'debug_urls') for _s in debug_urls]
    if (lower_bound is None):
        lower_bound = float('-inf')
    lower_bound = _execute.make_float(lower_bound, 'lower_bound')
    if (upper_bound is None):
        upper_bound = float('inf')
    upper_bound = _execute.make_float(upper_bound, 'upper_bound')
    if (mute_if_healthy is None):
        mute_if_healthy = False
    mute_if_healthy = _execute.make_bool(mute_if_healthy, 'mute_if_healthy')
    if (gated_grpc is None):
        gated_grpc = False
    gated_grpc = _execute.make_bool(gated_grpc, 'gated_grpc')
    (_attr_T, (input,)) = _execute.args_to_matching_eager([input], _ctx)
    _inputs_flat = [input]
    _attrs = ('T', _attr_T, 'device_name', device_name, 'tensor_name', tensor_name, 'debug_urls', debug_urls, 'lower_bound', lower_bound, 'upper_bound', upper_bound, 'mute_if_healthy', mute_if_healthy, 'gated_grpc', gated_grpc)
    _result = _execute.execute(b'DebugNumericSummary', 1, inputs=_inputs_flat, attrs=_attrs, ctx=_ctx, name=name)
    _execute.record_gradient('DebugNumericSummary', _inputs_flat, _attrs, _result, name)
    (_result,) = _result
    return _result