def _PopBackGrad(op, dlist, delement):
if dlist is None:
dlist = empty_tensor_list(
element_dtype=delement.dtype,
element_shape=gen_list_ops.tensor_list_element_shape(
op.outputs[0], shape_type=dtypes.int32))
return gen_list_ops.tensor_list_push_back(dlist, delement), None
def _PopBackGrad(op, dlist, delement):
if dlist is None:
dlist = gen_list_ops.empty_tensor_list(
element_dtype=delement.dtype,
element_shape=gen_list_ops.tensor_list_element_shape(
op.outputs[0], shape_type=dtypes.int32))
return gen_list_ops.tensor_list_push_back(dlist, delement)
def _TensorListGatherGrad(op, dtensor):
"""Gradient function for TensorListGather."""
input_list, indices, _ = op.inputs
dlist = gen_list_ops.tensor_list_scatter_v2(
tensor=dtensor,
indices=indices,
element_shape=gen_list_ops.tensor_list_element_shape(
input_list, shape_type=dtypes.int32),
num_elements=gen_list_ops.tensor_list_length(input_list))
return dlist, None, None
def _TensorListGatherGrad(op, dtensor):
"""Gradient function for TensorListGather."""
input_list, indices, _ = op.inputs
element_shape = gen_list_ops.tensor_list_element_shape(
input_list, shape_type=dtypes.int32)
num_elements = gen_list_ops.tensor_list_length(input_list)
dlist = tensor_list_reserve(element_shape, num_elements, dtensor.dtype)
dlist = tensor_list_scatter(
tensor=dtensor, indices=indices, input_handle=dlist)
return dlist, None, None
def _TensorListGatherGrad(op, dtensor):
"""Gradient function for TensorListGather."""
input_list, indices, _ = op.inputs
dlist = gen_list_ops.tensor_list_scatter_v2(
tensor=dtensor,
indices=indices,
element_shape=gen_list_ops.tensor_list_element_shape(
input_list, shape_type=dtypes.int32),
num_elements=gen_list_ops.tensor_list_length(input_list))
return dlist, None, None
def _TensorListGatherGrad(op, dtensor):
"""Gradient function for TensorListGather."""
input_list, indices, _ = op.inputs
element_shape = gen_list_ops.tensor_list_element_shape(
input_list, shape_type=dtypes.int32)
num_elements = gen_list_ops.tensor_list_length(input_list)
dlist = tensor_list_reserve(element_shape, num_elements, dtensor.dtype)
dlist = tensor_list_scatter(
tensor=dtensor, indices=indices, input_handle=dlist)
return dlist, None, None
def _TensorListConcatGrad(op, dtensor, unused_dlengths):
"""Gradient function for TensorListConcat."""
dlist = tensor_list_split(
dtensor,
element_shape=gen_list_ops.tensor_list_element_shape(
op.inputs[0], shape_type=dtypes.int32),
lengths=op.outputs[1])
if op.type == "TensorListConcatV2":
return dlist, None, None
else:
return dlist
def _TensorListConcatGrad(op, dtensor, unused_dlengths):
"""Gradient function for TensorListConcat."""
dlist = tensor_list_split(
dtensor,
element_shape=gen_list_ops.tensor_list_element_shape(
op.inputs[0], shape_type=dtypes.int32),
lengths=op.outputs[1])
if op.type == "TensorListConcatV2":
return dlist, None, None
else:
return dlist
def _TensorListGetItemGrad(op, ditem):
"""Gradient for TensorListGetItem."""
list_size = gen_list_ops.tensor_list_length(op.inputs[0])
list_grad = gen_list_ops.tensor_list_set_item(
gen_list_ops.tensor_list_reserve(
gen_list_ops.tensor_list_element_shape(op.inputs[0],
shape_type=dtypes.int32),
list_size, element_dtype=ditem.dtype),
index=op.inputs[1],
item=ditem)
index_grad = None
return list_grad, index_grad
def _TensorListGetItemGrad(op, ditem):
"""Gradient for TensorListGetItem."""
list_size = gen_list_ops.tensor_list_length(op.inputs[0])
list_grad = gen_list_ops.tensor_list_set_item(
gen_list_ops.tensor_list_reserve(
gen_list_ops.tensor_list_element_shape(op.inputs[0],
shape_type=dtypes.int32),
list_size, element_dtype=ditem.dtype),
index=op.inputs[1],
item=ditem)
index_grad = None
return list_grad, index_grad
def _TensorListFromTensorGrad(op, dlist):
"""Gradient for TensorListFromTensor."""
if op.inputs[0].shape[0] is not None:
num_elements = op.inputs[0].shape[0]
else:
num_elements = None
if dlist is None:
dlist = gen_list_ops.empty_tensor_list(
element_dtype=op.inputs[0].dtype,
element_shape=gen_list_ops.tensor_list_element_shape(
op.outputs[0], shape_type=dtypes.int32))
return gen_list_ops.tensor_list_stack(dlist,
element_dtype=op.inputs[0].dtype,
num_elements=num_elements)
def _TensorListFromTensorGrad(op, dlist):
"""Gradient for TensorListFromTensor."""
if op.inputs[0].shape[0] is not None:
num_elements = op.inputs[0].shape[0]
else:
num_elements = None
if dlist is None:
dlist = gen_list_ops.empty_tensor_list(
element_dtype=op.inputs[0].dtype,
element_shape=gen_list_ops.tensor_list_element_shape(
op.outputs[0], shape_type=dtypes.int32))
return gen_list_ops.tensor_list_stack(
dlist, element_dtype=op.inputs[0].dtype,
num_elements=num_elements)
def _TensorListFromTensorGrad(op, dlist):
"""Gradient for TensorListFromTensor."""
if op.inputs[0].shape.dims and op.inputs[0].shape.dims[0].value is not None:
num_elements = op.inputs[0].shape.dims[0].value
else:
num_elements = None
if dlist is None:
dlist = empty_tensor_list(
element_dtype=op.inputs[0].dtype,
element_shape=gen_list_ops.tensor_list_element_shape(
op.outputs[0], shape_type=dtypes.int32))
tensor_grad = gen_list_ops.tensor_list_stack(
dlist, element_dtype=op.inputs[0].dtype, num_elements=num_elements)
shape_grad = None
return tensor_grad, shape_grad
def _TensorListFromTensorGrad(op, dlist):
"""Gradient for TensorListFromTensor."""
if op.inputs[0].shape.dims and op.inputs[0].shape.dims[0].value is not None:
num_elements = op.inputs[0].shape.dims[0].value
else:
num_elements = None
if dlist is None:
dlist = empty_tensor_list(
element_dtype=op.inputs[0].dtype,
element_shape=gen_list_ops.tensor_list_element_shape(
op.outputs[0], shape_type=dtypes.int32))
tensor_grad = gen_list_ops.tensor_list_stack(
dlist, element_dtype=op.inputs[0].dtype, num_elements=num_elements)
shape_grad = None
return tensor_grad, shape_grad
