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Diffstat (limited to 'tensorflow/docs_src/performance/index.md')
| -rw-r--r-- | tensorflow/docs_src/performance/index.md | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/tensorflow/docs_src/performance/index.md b/tensorflow/docs_src/performance/index.md index 131d28fa3e..a0f26a8c3a 100644 --- a/tensorflow/docs_src/performance/index.md +++ b/tensorflow/docs_src/performance/index.md @@ -7,18 +7,18 @@ details on the high level APIs to use along with best practices to build and train high performance models, and quantize models for the least latency and highest throughput for inference. - * @{$performance_guide$Performance Guide} contains a collection of best + * [Performance Guide](../performance/performance_guide.md) contains a collection of best practices for optimizing your TensorFlow code. - * @{$datasets_performance$Data input pipeline guide} describes the tf.data + * [Data input pipeline guide](../performance/datasets_performance.md) describes the tf.data API for building efficient data input pipelines for TensorFlow. - * @{$performance/benchmarks$Benchmarks} contains a collection of + * [Benchmarks](../performance/benchmarks.md) contains a collection of benchmark results for a variety of hardware configurations. * For improving inference efficiency on mobile and embedded hardware, see - @{$quantization$How to Quantize Neural Networks with TensorFlow}, which + [How to Quantize Neural Networks with TensorFlow](../performance/quantization.md), which explains how to use quantization to reduce model size, both in storage and at runtime. @@ -31,20 +31,20 @@ XLA (Accelerated Linear Algebra) is an experimental compiler for linear algebra that optimizes TensorFlow computations. The following guides explore XLA: - * @{$xla$XLA Overview}, which introduces XLA. - * @{$broadcasting$Broadcasting Semantics}, which describes XLA's + * [XLA Overview](../performance/xla/index.md), which introduces XLA. + * [Broadcasting Semantics](../performance/xla/broadcasting.md), which describes XLA's broadcasting semantics. - * @{$developing_new_backend$Developing a new back end for XLA}, which + * [Developing a new back end for XLA](../performance/xla/developing_new_backend.md), which explains how to re-target TensorFlow in order to optimize the performance of the computational graph for particular hardware. - * @{$jit$Using JIT Compilation}, which describes the XLA JIT compiler that + * [Using JIT Compilation](../performance/xla/jit.md), which describes the XLA JIT compiler that compiles and runs parts of TensorFlow graphs via XLA in order to optimize performance. - * @{$operation_semantics$Operation Semantics}, which is a reference manual + * [Operation Semantics](../performance/xla/operation_semantics.md), which is a reference manual describing the semantics of operations in the `ComputationBuilder` interface. - * @{$shapes$Shapes and Layout}, which details the `Shape` protocol buffer. - * @{$tfcompile$Using AOT compilation}, which explains `tfcompile`, a + * [Shapes and Layout](../performance/xla/shapes.md), which details the `Shape` protocol buffer. + * [Using AOT compilation](../performance/xla/tfcompile.md), which explains `tfcompile`, a standalone tool that compiles TensorFlow graphs into executable code in order to optimize performance. |