def tensor_list_gather(input_handle, indices, element_dtype, name=None): return gen_list_ops.tensor_list_gather( input_handle=input_handle, indices=indices, element_shape=-1, element_dtype=element_dtype, name=name)
def _TensorListScatterGrad(op, dlist): t, indices, _ = op.inputs return gen_list_ops.tensor_list_gather(dlist, indices, element_shape=array_ops.slice( array_ops.shape(t), [1], [-1]), element_dtype=t.dtype), None, None
def _TensorListScatterGrad(op, dlist): t, indices, _ = op.inputs return gen_list_ops.tensor_list_gather( dlist, indices, element_shape=array_ops.slice(array_ops.shape(t), [1], [-1]), element_dtype=t.dtype), None, None
def _TensorListScatterIntoExistingListGrad(op, dlist): """Gradient function for TensorListScatterIntoExistingList.""" _, tensor, indices = op.inputs dtensor = gen_list_ops.tensor_list_gather( dlist, indices, element_shape=array_ops.slice(array_ops.shape(tensor), [1], [-1]), element_dtype=tensor.dtype) zeros = array_ops.zeros_like(tensor) dlist = tensor_list_scatter(zeros, indices, indices, input_handle=dlist) return dlist, dtensor, None
def _TensorListScatterGrad(op, dlist): """Gradient function for TensorListScatter.""" tensor = op.inputs[0] indices = op.inputs[1] dtensor = gen_list_ops.tensor_list_gather( dlist, indices, element_shape=array_ops.slice(array_ops.shape(tensor), [1], [-1]), element_dtype=tensor.dtype) if op.type == "TensorListScatterV2": return dtensor, None, None, None else: return dtensor, None, None
def _TensorListScatterGrad(op, dlist): t, indices, _ = op.inputs return gen_list_ops.tensor_list_gather( dlist, indices, element_dtype=t.dtype), None
def _TensorListScatterGrad(op, dlist): t, indices, _ = op.inputs return gen_list_ops.tensor_list_gather(dlist, indices, element_dtype=t.dtype), None