c2f59ba0593671c56da7830cf7e2a171a224d2e0,tfcoreml/_layers.py,,batchnorm,#,81

Before Change

    param_list = []
    for idx in range(1,5):
      if compat.as_str_any(op.inputs[idx].name) in context.consts:
        param_list.append(context.consts[compat.as_str_any(op.inputs[idx].name)])
      else:
        param_list.append(context.consts[compat.as_str_any(
            op.inputs[idx].op.inputs[0].name)])
    gamma, beta, mean, variance = param_list

After Change

  elif op.type == "FusedBatchNorm":
    param_list = []
    for idx in range(1,5):
        t = _get_const_tensor_value(context, op.inputs[idx].name, op.inputs[idx].op)
        if t is None:
            raise ValueError("Value not found for {}".format(op.inputs[idx].name))
        param_list.append(t)
    gamma, beta, mean, variance = param_list
    is_training = op.get_attr("is_training")
    if mean.shape == (0,) and variance.shape == (0,) and is_training:

Instances