bcfb60d0a1
This is needed for invoking the MLIR tf2xla bridge from xla_compiler. This CL breaks apart items from xla_compiler into individual build targets, which are then depended on from the MLIR TF bridge. PiperOrigin-RevId: 323640340 Change-Id: I78b972503db9e7b5254014ca7e889005490d8339
54 lines
1.9 KiB
C++
54 lines
1.9 KiB
C++
/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/compiler/tf2xla/xla_argument.h"
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namespace tensorflow {
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bool XlaArgument::operator==(const XlaArgument& other) const {
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if (std::tie(kind, resource_kind, type, name, initialized, max_array_size,
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tensor_array_gradients) !=
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std::tie(other.kind, other.resource_kind, other.type, other.name,
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other.initialized, other.max_array_size,
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other.tensor_array_gradients)) {
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return false;
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}
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if (absl::holds_alternative<xla::Shape>(shape)) {
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if (!absl::holds_alternative<xla::Shape>(other.shape)) {
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return false;
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}
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if (!xla::Shape::Equal()(absl::get<xla::Shape>(shape),
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absl::get<xla::Shape>(other.shape))) {
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return false;
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}
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} else {
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if (!absl::holds_alternative<TensorShape>(other.shape)) {
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return false;
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}
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if (absl::get<TensorShape>(shape) != absl::get<TensorShape>(other.shape)) {
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return false;
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}
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}
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if (constant_value.shape() != other.constant_value.shape()) {
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return false;
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}
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if (is_same_data_across_replicas != other.is_same_data_across_replicas) {
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return false;
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}
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return constant_value.tensor_data() == other.constant_value.tensor_data();
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}
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} // end namespace tensorflow
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