diff options
Diffstat (limited to 'doc/operators.md')
| -rw-r--r-- | doc/operators.md | 62 |
1 files changed, 31 insertions, 31 deletions
diff --git a/doc/operators.md b/doc/operators.md index e08d20ca..2cca391b 100644 --- a/doc/operators.md +++ b/doc/operators.md @@ -25,7 +25,7 @@ Marian. The central component in the graph is the `Chainable<Tensor>` object. This object provides the abstract interface necessary to interact with elements in the computation graph. The details of this interface can be found in -[/src/graph/chainable.h](api/file_src_graph_chainable.h.html). Note that the +[/src/graph/chainable.h](file_src_graph_chainable.h). Note that the template parameter corresponds to the underlying data structure, which in Marian is the `Tensor`. Therefore, for convenience, the type `Expr` is defined: @@ -37,22 +37,22 @@ The implementation of the different operator components are divided across several files: - Expression Operator - - [/src/graph/expression_operators.h](api/file_src_graph_expression_operators.h.html) - - [/src/graph/expression_operators.cpp](api/file_src_graph_expression_operators.cpp.html) + - [/src/graph/expression_operators.h](file_src_graph_expression_operators.h) + - [/src/graph/expression_operators.cpp](file_src_graph_expression_operators.cpp) - Node Operator - - [/src/graph/node_operators_unary.h](api/file_src_graph_node_operators_unary.h.html) - - [/src/graph/node_operators_binary.h](api/file_src_graph_node_operators_binary.h.html) - - [/src/graph/node_operators_tuple.h](api/file_src_graph_node_operators_tuple.h.html) + - [/src/graph/node_operators_unary.h](file_src_graph_node_operators_unary.h) + - [/src/graph/node_operators_binary.h](file_src_graph_node_operators_binary.h) + - [/src/graph/node_operators_tuple.h](file_src_graph_node_operators_tuple.h) - Functional Operator - - [/src/functional/operators.h](api/file_src_functional_operators.h.html) + - [/src/functional/operators.h](file_src_functional_operators.h) - Tensor operation - - [/src/tensors/tensor_operators.h](api/file_src_tensors_tensor_operators.h.html) - - [/src/tensors/cpu/tensor_operators.cpp](api/file_src_tensors_cpu_tensor_operators.cpp.html) - - [/src/tensors/gpu/tensor_operators.cu](api/file_src_tensors_gpu_tensor_operators.cu.html) + - [/src/tensors/tensor_operators.h](file_src_tensors_tensor_operators.h) + - [/src/tensors/cpu/tensor_operators.cpp](file_src_tensors_cpu_tensor_operators.cpp) + - [/src/tensors/gpu/tensor_operators.cu](file_src_tensors_gpu_tensor_operators.cu) - Declared Specialization - - [/src/tensors/gpu/element.inc](api/program_listing_file_src_tensors_gpu_element.inc.html) - - [/src/tensors/gpu/add.inc](api/program_listing_file_src_tensors_gpu_add.inc.html) - - [/src/tensors/gpu/add_all.inc](api/program_listing_file_src_tensors_gpu_add_all.inc.html) + - [/src/tensors/gpu/element.inc](program_listing_file_src_tensors_gpu_element.inc) + - [/src/tensors/gpu/add.inc](program_listing_file_src_tensors_gpu_add.inc) + - [/src/tensors/gpu/add_all.inc](program_listing_file_src_tensors_gpu_add_all.inc) To understand how the different components are inter-linked, we'll look at each of them in turn. @@ -197,7 +197,7 @@ this example code, these are optional and, when omitted, calling `NaryNodeOp({a})` would result in a node with the same shape and type as `a`. The `type()` method returns the friendly name for the node. Note that the [ONNX](https://onnx.ai) -[interface](api/program_listing_file_src_onnx_expression_graph_onnx_serialization.cpp.html) +[interface](program_listing_file_src_onnx_expression_graph_onnx_serialization.cpp) maintains a mapping of these friendly names to their ONNX representation. In the absence of any member variables the `hash()` and `equal()` methods can be omitted, and defer to their `NaryNodeOp` definition. However, if such variables @@ -244,7 +244,7 @@ _1 = sin(_2) ``` The placeholders `_1`, `_2` are enabled by code in -[/src/functional](api/dir_src_functional.html) and interoperate with the +[/src/functional](dir_src_functional) and interoperate with the functional operators. In the call to `Element`, `val_` is assigned to `_1` and `child(0)->val()` to `_2`. Therefore, this has the action of setting the elements of this node to the result obtained by applying `sin` to the elements @@ -328,7 +328,7 @@ specialization required for each type. The current required types are: - half (see `cuda_fp16.h` in the CUDA Math API) Further details are available in -[/src/common/types.h](api/file_src_common_types.h.html). +[/src/common/types.h](file_src_common_types.h). Returning to the example of `sin(x)`, the specialization for `float` and `double` requires @@ -355,12 +355,12 @@ struct Ops<double> { ``` The remaining specializations can be seen in -[/src/functional/operators.h](api/file_src_functional_operators.h.html). Note +[/src/functional/operators.h](file_src_functional_operators.h). Note that the general template must produce a runtime abort. The final component of the functional operator is to call the macro that enables interoperability with the framework of -[/src/functional](api/dir_src_functional.html). For a unary operator, this is +[/src/functional](dir_src_functional). For a unary operator, this is the macro `UNARY`. ```cpp @@ -392,7 +392,7 @@ representation. Furthermore, the OpenMPI and OpenMP libraries are employed for parallelisation. While macros provided in -[/src/common/definitions.h](api/file_src_common_definitions.h.html) locally +[/src/common/definitions.h](file_src_common_definitions.h) locally enable faster floating-point math in supported compilers. ```cpp @@ -402,14 +402,14 @@ MARIAN_FFAST_MATH_END ``` The usual caveats apply when enabling `fast_math`, and can be found in -[/src/common/definitions.h](api/file_src_common_definitions.h.html) +[/src/common/definitions.h](file_src_common_definitions.h) Tensor operators are declared in -[/src/tensors/tensor_operators.h](api/file_src_tensors_tensor_operators.h.html), +[/src/tensors/tensor_operators.h](file_src_tensors_tensor_operators.h), these are device-agnostic function that call the relevant device-specific implementation. The CPU- and GPU-specific implementation are defined in `cpu` -namespace in [/src/tensors/cpu/](api/dir_src_tensors_cpu.html) and the `gpu` -namespace [/src/tensors/gpu/](api/dir_src_tensors_gpu.html). Therefore a typical +namespace in [/src/tensors/cpu/](dir_src_tensors_cpu) and the `gpu` +namespace [/src/tensors/gpu/](dir_src_tensors_gpu). Therefore a typical operator defers to an implementation in the device-specific namespace. ```cpp @@ -461,16 +461,16 @@ compilation: ``` To fix these undefined references, we must explicitly add the specialization to -the `.inc` files of [/src/tensors/gpu/](api/dir_src_tensors_gpu.html). Each +the `.inc` files of [/src/tensors/gpu/](dir_src_tensors_gpu). Each `.inc` file is included at the end of its corresponding `.cu` file, ensuring that the specialization is compiled. The undefined references should be added to the `.inc` file that corresponds to the header file in which contains the declaration of the missing functions. -The file [element.inc](api/file_src_tensors_gpu_element.inc.html) contains the +The file [element.inc](file_src_tensors_gpu_element.inc) contains the specializations of the function defined in -[element.h](api/file_src_tensors_gpu_element.h.html): +[element.h](file_src_tensors_gpu_element.h): ```cpp // src/tensors/gpu/element.h @@ -478,9 +478,9 @@ template <class Functor, class... Tensors> void Element(Functor functor, Tensor out, Tensors... tensors); ``` -Similarly, [add.inc](api/file_src_tensors_gpu_add.inc.html) contains the +Similarly, [add.inc](file_src_tensors_gpu_add.inc) contains the specializations for functions matching either of the two signatures in -[add.h](api/file_src_tensors_gpu_add.h.html): +[add.h](file_src_tensors_gpu_add.h): ```cpp // src/tensors/gpu/add.h @@ -491,8 +491,8 @@ template <class Functor, class AggFunctor, class... Tensors> void Aggregate(Functor functor, float initAgg, AggFunctor aggFunctor, float scale, marian::Tensor out, Tensors... tensors); ``` -Finally [add_all.inc](api/file_src_tensors_gpu_add_all.inc.html) contains the -specializations for [add_all.h](api/file_src_tensors_gpu_add_all.h.html), which +Finally [add_all.inc](file_src_tensors_gpu_add_all.inc) contains the +specializations for [add_all.h](file_src_tensors_gpu_add_all.h), which are several versions of: ```cpp @@ -507,7 +507,7 @@ void AggregateAll(Ptr<Allocator> allocator, const Tensor in1); ``` -However, for [add_all.h](api/file_src_tensors_gpu_add_all.h.html), there is an +However, for [add_all.h](file_src_tensors_gpu_add_all.h), there is an additional type dependence in the first template parameter, which requires two entries: |