1# Copyright 2015 The TensorFlow Authors. All Rights Reserved. 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15"""Shared utilities related to backprop.""" 16 17from tensorflow.core.framework import types_pb2 18from tensorflow.python.framework import dtypes 19from tensorflow.python.framework import ops 20from tensorflow.python.framework import tensor_util 21from tensorflow.python.ops import handle_data_util 22 23 24def _DTypeFromTensor(tensor): 25 """Extract either `tensor.dtype` or the unanimous sub-type of a variant.""" 26 dtype = tensor.dtype 27 if dtype.base_dtype == dtypes.variant: 28 # If we know statically that the data a variant points to is non-trainable 29 # then the variant itself is non-trainable. 30 if isinstance(tensor, ops.EagerTensor): 31 handle_data = tensor._handle_data # pylint: disable=protected-access 32 else: 33 handle_data = handle_data_util.get_resource_handle_data(tensor) 34 if (handle_data is not None 35 and handle_data.is_set 36 and handle_data.shape_and_type): 37 first_type = handle_data.shape_and_type[0].dtype 38 # Some variants have statically unknown dtypes; we can't make inferences 39 # about trainability, so we conservatively assume they're trainable 40 # (which may waste memory passing zeros around, but will be correct). 41 if (first_type != types_pb2.DT_INVALID 42 and all(shape_and_type.dtype == first_type 43 for shape_and_type in handle_data.shape_and_type)): 44 return first_type 45 return dtype 46 47 48def IsTrainable(tensor_or_dtype): 49 """Determines whether a tensor or dtype supports infinitesimal changes.""" 50 if tensor_util.is_tf_type(tensor_or_dtype): 51 dtype = _DTypeFromTensor(tensor_or_dtype) 52 else: 53 dtype = tensor_or_dtype 54 dtype = dtypes.as_dtype(dtype) 55 return dtype.base_dtype in (dtypes.float16, dtypes.float32, dtypes.float64, 56 dtypes.complex64, dtypes.complex128, 57 dtypes.resource, dtypes.variant, dtypes.bfloat16) 58