def concat(self, name=None): """Return the values in the TensorArray as a concatenated `Tensor`.""" value, _ = gen_data_flow_ops._tensor_array_concat(handle=self._handle, flow_in=self._flow, dtype=self._dtype, name=name) return value
def concat(self, name=None): """Return the values in the TensorArray as a concatenated `Tensor`. All of the values must have been written, their ranks must match, and and their shapes must all match for all dimensions except the first. Args: name: A name for the operation (optional). Returns: All the tensors in the TensorArray concatenated into one tensor. """ if self._elem_shape and self._elem_shape[0].dims is not None: element_shape_except0 = tensor_shape.TensorShape( self._elem_shape[0].dims[1:]) else: element_shape_except0 = tensor_shape.TensorShape(None) with ops.colocate_with(self._handle): value, _ = gen_data_flow_ops._tensor_array_concat( handle=self._handle, flow_in=self._flow, dtype=self._dtype, name=name, element_shape_except0=element_shape_except0) if self._elem_shape and self._elem_shape[0].dims is not None: value.set_shape([None] + self._elem_shape[0].dims[1:]) return value
def concat(self, name=None): """Return the values in the TensorArray as a concatenated `Tensor`. All of the values must have been written, their ranks must match, and and their shapes must all match for all dimensions except the first. Args: name: A name for the operation (optional). Returns: All the tensors in the TensorArray concatenated into one tensor. """ if self._elem_shape and self._elem_shape[0].dims is not None: element_shape_except0 = tensor_shape.TensorShape(self._elem_shape[0].dims[ 1:]) else: element_shape_except0 = tensor_shape.TensorShape(None) with ops.colocate_with(self._handle): value, _ = gen_data_flow_ops._tensor_array_concat( handle=self._handle, flow_in=self._flow, dtype=self._dtype, name=name, element_shape_except0=element_shape_except0) if self._elem_shape and self._elem_shape[0].dims is not None: value.set_shape([None] + self._elem_shape[0].dims[1:]) return value
def concat(self, name=None): """Return the values in the TensorArray as a concatenated `Tensor`. All of the values must have been written, their ranks must match, and and their shapes must all match for all dimensions except the first. Args: name: A name for the operation (optional). Returns: All the tensors in the TensorArray concatenated into one tensor. """ with ops.colocate_with(self._handle): value, _ = gen_data_flow_ops._tensor_array_concat( handle=self._handle, flow_in=self._flow, dtype=self._dtype, name=name ) return value
def concat(self, name=None): """Return the values in the TensorArray as a concatenated `Tensor`. All of the values must have been written, their ranks must match, and and their shapes must all match for all dimensions except the first. Args: name: A name for the operation (optional). Returns: All the tensors in the TensorArray concatenated into one tensor. """ with ops.colocate_with(self._handle): value, _ = gen_data_flow_ops._tensor_array_concat( handle=self._handle, flow_in=self._flow, dtype=self._dtype, name=name) return value
def concat(self, name=None): """Return the values in the TensorArray as a concatenated `Tensor`.""" value, _ = gen_data_flow_ops._tensor_array_concat( handle=self._handle, flow_in=self._flow, dtype=self._dtype, name=name) return value