def value_tensors(self):
"""Create value `Tensor`s for this object's attributes.
Does not require that the Python object has been created. Used for
restore-on-create when executing eagerly.
Returns:
A dictionary mapping from object attribute names to `Tensor`s.
"""
value_tensors = {}
for serialized_tensor in self.object_proto.attributes:
checkpoint_key = serialized_tensor.checkpoint_key
dtype = self._checkpoint.dtype_map[checkpoint_key]
base_type = dtype.base_dtype
with ops.init_scope():
with ops.device("/cpu:0"):
# Run the restore itself on the CPU.
value, = io_ops.restore_v2(
prefix=self._checkpoint.save_path_tensor,
tensor_names=[checkpoint_key],
shape_and_slices=[""],
dtypes=[base_type],
name="%s_checkpoint_read" % (serialized_tensor.name, ))
# Copy the value to the current device if necessary.
value_tensors[serialized_tensor.name] = array_ops.identity(
value)
return value_tensors
def value_tensors(self):
"""Create value `Tensor`s for this object's attributes.
Does not require that the Python object has been created. Used for
restore-on-create when executing eagerly.
Returns:
A dictionary mapping from object attribute names to `Tensor`s.
"""
value_tensors = {}
for serialized_tensor in self.object_proto.attributes:
checkpoint_key = serialized_tensor.checkpoint_key
dtype = self._checkpoint.dtype_map[checkpoint_key]
base_type = dtype.base_dtype
with ops.init_scope():
with ops.device("/cpu:0"):
# Run the restore itself on the CPU.
value, = io_ops.restore_v2(
prefix=self._checkpoint.save_path,
tensor_names=[checkpoint_key],
shape_and_slices=[""],
dtypes=[base_type],
name="%s_checkpoint_read" % (serialized_tensor.name,))
# Copy the value to the current device if necessary.
value_tensors[serialized_tensor.name] = array_ops.identity(value)
return value_tensors
def restore_ops(self):
"""Create restore ops for this object's attributes."""
restore_tensors = {}
for serialized_tensor in self.object_proto.attributes:
checkpoint_key = serialized_tensor.checkpoint_key
dtype = self._checkpoint.dtype_map[checkpoint_key]
base_type = dtype.base_dtype
with ops.init_scope():
restore, = io_ops.restore_v2(prefix=self._checkpoint.save_path,
tensor_names=[checkpoint_key],
shape_and_slices=[""],
dtypes=[base_type],
name="%s_checkpoint_read" %
(serialized_tensor.name, ))
restore_tensors[serialized_tensor.name] = restore
return restore_tensors
def value_tensors(self, shape_and_slices=None):
"""Create value `Tensor`s for this object's attributes.
Does not require that the Python object has been created. Used for
restore-on-create when executing eagerly.
Args:
shape_and_slices: A dict mapping from object attribute names to a shape
and slice string that will be passed to a RestoreV2 op. If the dict is
None or if an object attribute is not in the dict, the full tensor will
be restored.
Returns:
A dictionary mapping from object attribute names to `Tensor`s.
"""
value_tensors = {}
for serialized_tensor in self.object_proto.attributes:
checkpoint_key = serialized_tensor.checkpoint_key
dtype = self._checkpoint.dtype_map[checkpoint_key]
base_type = dtype.base_dtype
io_device = self._checkpoint.options.experimental_io_device or "cpu:0"
with ops.init_scope():
with ops.device(io_device):
# Run the restore itself on the io_device(CPU or specified).
if (shape_and_slices is not None
and serialized_tensor.name in shape_and_slices):
shape_and_slice = shape_and_slices[
serialized_tensor.name]
else:
shape_and_slice = ""
value, = io_ops.restore_v2(
prefix=self._checkpoint.save_path_tensor,
tensor_names=[checkpoint_key],
shape_and_slices=[shape_and_slice],
dtypes=[base_type],
name="%s_checkpoint_read" % (serialized_tensor.name, ))
# Copy the value to the current device if necessary.
value_tensors[serialized_tensor.name] = array_ops.identity(
value)
return value_tensors
def value_tensors(self):
"""Create value `Tensor`s for this object's attributes.
Does not require that the Python object has been created. Used for
restore-on-create when executing eagerly.
Returns:
A dictionary mapping from object attribute names to `Tensor`s.
"""
value_tensors = {}
for serialized_tensor in self.object_proto.attributes:
checkpoint_key = serialized_tensor.checkpoint_key
dtype = self._checkpoint.dtype_map[checkpoint_key]
base_type = dtype.base_dtype
with ops.init_scope():
value, = io_ops.restore_v2(
prefix=self._checkpoint.save_path,
tensor_names=[checkpoint_key],
shape_and_slices=[""],
dtypes=[base_type],
name="%s_checkpoint_read" % (serialized_tensor.name,))
value_tensors[serialized_tensor.name] = value
return value_tensors
def _call_restore_v2():
gen_io_ops.restore_v2(checkpoint_path, all_names,
[""] * len(all_names), all_dtypes)